NZ711144B2 - Methods of disease activity profiling for personalized therapy management - Google Patents

Abstract

non-invasive method for selecting a therapy regimen to promote mucosal healing in an individual diagnosed with inflammatory bowel disease (IBD) comprises (a) measuring the levels of an array of mucosal healing markers in a sample obtained from the individual at time point t0 to generate a mucosal healing index at t0; (b) measuring the levels of an array of mucosal healing markers in a sample obtained from the individual at time point t1 to generate a mucosal healing index at t1; (c) comparing the change in the mucosal healing index from t0 to t1; and (d) selecting the therapy regimen for the individual to promote mucosal healing. healing index at t0; (b) measuring the levels of an array of mucosal healing markers in a sample obtained from the individual at time point t1 to generate a mucosal healing index at t1; (c) comparing the change in the mucosal healing index from t0 to t1; and (d) selecting the therapy regimen for the individual to promote mucosal healing.

Description

COMPLETE SPECIFICATION S OF DISEASE ACTIVITY PROFILING FOR ALIZED THERAPY MANAGEMENT I/We, Nestec S.A., a body corporate organised under the laws of Switzerland of Avenue Nestlé 55, 1800, Vevey, SWITZERLAND hereby declare the ion, for which I/we pray that a patent may be granted to me/us, and the method by which it is to be performed, to be particularly described in and by the following statement:- Total Fee Paid: NZ$250.00 – by Credit Card 505534048_1/6858 METHODS OF DISEASE ACTIVITY PROFILING FOR PERSONALIZED Y MANAGEMENT CROSS-REFERENCES TO RELATED APPLICATIONS The present application is a divisional application of New d application No. 617009, which is incorporated in its entirety herein by reference. [0001a] This application claims priority to U.S. Provisional Patent Application No. 61/484,607, filed May 10, 2011, U.S. Provisional Patent Application No. ,026, filed July 6, 2011, U.S.

Provisional Application No. 61/553,909, filed October 31, 2011, U.S. Provisional Application No. ,509, filed December 2, 2011, and U.S. Provisional Application No. 61/636,575, filed April , 2012, the disclosures of which are hereby incorporated by reference in their entirety for all purposes.

BACKGROUND OF THE ION [0001b] Any discussion of the prior art throughout the ication should in no way be considered as an admission that such prior art is widely known or forms part of common general knowledge in the field.

Inflammatory bowel disease (IBD) which includes Crohn’s disease (CD) and ulcerative colitis (UC) is a chronic thic inflammatory disorder affecting the gatrointestine tract.

Disease progression of CD and UC includes repeated episodes of inflammation and ulceration of the ine, leading to complications ing hospitalization, surgery and escalation of therapy n-Biroulet et al., Am. J. Gastroenterol,. 105: 289-297 (2010); Langholz E., Dan. Med. Bull., 46: 400-415 (1999)). Current treatments such as anti-tumor necrosis factor-alpha (TNF-α) biologics (e.g., infliximab (IFX), etanercept, adalimumab (ADL) and certolizumab pegol), thiopurine drugs (e.g., azathioprine (AZA), 6-mercaptopurin (6-MP)), anti-inflammatory drugs (e.g., mesalazine), and steroids (e.g., corticosteroids) have been shown to reduce disease activity.

In some clinical trials of CD, mucosal healing which is described as the absence of intestinal , was induced in patients on combination therapy of corticosteroids, IFX and ADL. rmore, MH was maintained in patients receiving IFX.

Other studies have shown that mucosal healing can be a hallmark of suppression of bowel mation and predict long-term disease remission (Froslie et al., Gastroenterology, 133: 412-422 (2007); Baert et al., Gastroenterology, ). Long-term mucosal healing has been associated with a sed risk of colectomy and colorectal cancer in UC ts, a decreased need for corticosteroid treatment in CD patients, and possibly a decreased need for hospitalization (Dave et al., Gastroenterology & Hepatology, 8(1): 29-38 (2012)).

The International Organization for the Study of Inflammatory Bowel Disease proposed defining mucosal healing in UC as the absence of friability, blood. ns an dulcers in all visualized ts of gut mucosa (D‘Haens ct al.. Gastroentcrology. 132: 763— 786 (2007)). MH in CD was proposed to be the absence of ulcers. The gold standard for measurement of Crohn‘s disease activity is the Crohn‘s e Endoscopic Index ofSeverity (CDEIS). This e index score is established from several variables such as superficial and deep ulceration. ulcerated and nonulcerated is. and surface area of ulcerated and disease segments. A simplified version ofthe index is the Simple Endoscopic Score for Crohn‘s e, which takes into account disease variables including ulcer size. ulcerated surface. affected surface and presence of narrowing. Both indices evaluate clinical symptoms of CD. yet fail to measure the underlying cause of disease (e.g.. inflammation) or resolution of disease (e.g.. mucosal healing). A measurement of mucosal healing can be perfowncd to assess disease induction as well as disease progression and resolution.

The process of l g begins with bleeding (cg. degradation ofthe endothelial layers of the blood vessels) and inflammation. then progresses to cell and tissue proliferation, and finally tissue remodeling. At the inflammation stage, inflammatmy markers and anti-inflammatory markers. such as. but not limited to, lL—l, lL-Z. lL-h. lL-l4.

IL- 1 7. TGFB. and TNFOL are expressed. During remodeling. tissue repair and remodeling growth factors. such as. but not limited to, AREG, EREG. HB-EGF, HGF, NRG l -4. BTC.

EGF. IGF, TGF-OL. VEGFs. FGFs, and TWEAK are expressed. Repair ofthe intestinal epithelium es multiple signal transduction pathways which are ary for cell survival. proliferation. and migration. We have identified novcl s ofmucosal healing that are predictive of the risk ofdiseasc relapse and disease remission. A measurement of mucosal healing can be used to periodically assess disease status in patients receiving a therapy regimen.

Mucosal healing is typically assessed by endoscopy. Although the ve ure is considered to be low-risk. its cost and patient discomfort and compliance remain obstacles to frequent. regular cndoseopies to assess mucosal healing. There is an unmet need in the art for non—invasive methods ofdetermining l healing in a patient.

There is a need in the art for methods of therapeutic management of diseases such as autoimmune disorders using an individualized ch to optimize therapy and monitor y. The methods need to include assessing disease course and al parameters such as phamacokinetics, disease activity indices, disease burden, and mucosal status. [0007a] It is an object of the present ion to overcome or ameliorate at least one of the disadvantages of the prior art, or to provide a useful ative. [0007b] Unless the context clearly requires otherwise, throughout the description and the claims, the words “comprise”, “comprising”, and the like are to be construed in an inclusive sense as opposed to an exclusive or exhaustive sense; that is to say, in the sense of “including, but not limited to”.

BRIEF SUMMARY OF THE INVENTION [0007c] According to a first aspect of the invention there is provided a non-invasive method for selecting a therapy n to promote mucosal healing in an dual diagnosed with inflammatory bowel disease (IBD), said method comprising: (a) ing the levels of an array of mucosal healing markers in a sample obtained from the individual at time point t0 to generate a mucosal healing index at t0; (b) measuring the levels of an array of mucosal healing markers in a sample obtained from the individual at time point t1 to generate a mucosal healing index at t1; (c) comparing the change in the mucosal healing index from t0 to t1; and (d) selecting the therapy regimen for the individual to e mucosal healing.

The present invention provides methods for personalized therapeutic management of a disease in order to optimize therapy and/or monitor therapeutic cy. In particular, the present invention comprises measuring an array of one or a plurality of mucosal healing biomarkers at one or a plurality of time points over the course of therapy with a eutic agent to ine a l healing index for selecting therapy, optimizing therapy, reducing toxicity, and/or monitoring the efficacy of therapeutic treatment. In some embodiments, the therapy is an anti-TNF therapy, an immunosuppressive agent, a corticosteroid, a drug that targets a different mechanism, a nutrition therapy and combinations thereof. In certain instances, the anti-TNF y is a TNF inhibitor (e.g., anti-TNF drug, NFα antibody) for the treatment of a TNFα-mediated disease or disorder.

TNFα has been implicated in inflammatory diseases, autoimmune es, viral, bacterial and parasitic infections, malignancies, and/or neurodegenerative diseases and is a useful target for specific biological therapy in diseases, such as rheumatoid arthritis and Crohn’s disease. TNF inhibitors such as anti-TNFα antibodies are an important class of therapeutics. In some embodiments, the methods of the present invention advantageously improve therapeutic management of patients with a TNFα-mediated disease or disorder by optimizing therapy and/or monitoring eutic efficacy to anti-TNF drugs such as anti-TNFα eutic antibodies.

As such, in a further aspect, the present invention provides a non-invasive method for measuring mucosal healing in an individual diagnosed with inflammatory bowel disease (IBD) receiving a therapy regimen, the method comprising: (a) measuring the levels of an array of l healing s in a sample from the individual; (b) comparing the levels of an array of mucosal healing s in the dual to that of a control to e the mucosal healing index of the individual, wherein the mucosal healing index comprises a representation of the extent of mucosal healing; and (c) determining whether the individual undergoing mucosal healing should maintain the therapy regimen.

As such. in one aspect‘ the present invention provides a method for monitoring therapeutic efficiency in an individual with IBD receiving therapy. the method sing: (a) measuring levels ofan may of mucosal healing markers in a sample from the individual at a plurality oftime points over the course oftherapy with a therapeutic antibody; (b) applying a statistical algorithm to the level of the one or more markers determined in step (a) to generate a mucosal healing index; (C) comparing the individual‘s mucosal healing index to that ofa control: and (d) ining whether the therapy is appropriate for the individual to promote mucosal healing.

In another aspect, the present invention provides a method for selecting a therapy regimen in an individual with IBD. the method comprising: (a) ing levels ofan array ofmueosal g markers in a sample from the individual at a plurality oftime points over the course oftherapy, the individual receiving a therapeutic antibody; (b) applying a statistical algorithm to the level ofthe one or more markers determined in step (a) to generate a mucosal healing index; (c) comparing the individual‘s mucosal healing index to that ofa control; and (d) selecting an riate therapy regimen for the individual n the y regimen es mucosal g As such. in another aspect, the present invention provides a method for reducing or minimizing the risk ofsurgery in an individual diagnosed with IBD being administered a therapy regimen. the method comprising: (a) measuring an array of mucosal healing markers at a ity oftime points over the course oftherapy with a therapeutic antibody; (1)) generating the individual’s mucosal healing index sing a representation ofthe presence and/or concentration levels of each of the markers over time; (c) comparing the individual’s mucosal healing index to that ofa control. and (d) selecting an appropriate therapy regimen for to reduce or ze the risk ot‘surgery.

As such. in another aspect, the present invention es a method for selecting a therapy regimen to promote l healing in an individual diagnosed with lBD, the method comprising: (a) measuring lcvcls ofa panel ofmucosal healing markers at time point to to generate a mucosal g index at to; (b) measuring levels ot‘a panel of mucosal healing markers at time point t1 to generate a mucosal healing index at t]; (c) comparing the change in the mucosal healing index from to to t.; and (d) selecting the therapy n for the individual to promote mucosal healing.

As such. in one aspect. the present invention provides a non-invasive method for measuring mucosal healing in an individual diagnosed with Crohn"s disease receiving an anti-TNF therapy regimen, the method comprising: (a) measuring the levels of an array ofmucosal g s in a sample from the individual; (b) ing the levels of an array ot‘mucosal healing markers in the dual to that ofa control to compute the mucosal g index ofthe individual, wherein the mucosal healing index comprises a representation ofthe extent of mucosal healing; and (c) determining whether the dual undergoing mucosal healing should maintain the anti-TNF therapy regimen.

As such. in another aspect. the present invention provides a method for monitoring therapeutic ncy in an individual with Crohn‘s disease receiving anti-TNF therapy. the method sing: (a) measuring levels of an array osal healing markers in a sample from the individual at a plurality oftime points over the course oftherapy with a therapeutic antibody; (1)) applying a statistical algorithm to the level ofthe one or more markers determined in step (a) to generate a mucosal healing index; (c) comparing the individual‘s mucosal healing index to that ofa control: and (d) determining whether the anti-TNF therapy is appropriate for the individual to promote mucosal healing.

As such, in another aspect. the present invention provides a method for selecting an anti-TNF therapy regimen in an individual with s disease. the method comprising: (a) measuring levels of an array ot‘mucosal healing s in a sample from the individual at a plurality oftime. points over the course oftherapy, the dual receiving a therapeutic antibody; (b) applying a statistical algorithm to the level ofthe one or more markers determined in step (a) to generate a mucosal healing index; (c) ing the individual‘s mucosal healing index to that ot‘a control: and (d) selecting an appropriate anti-TNF therapy regimen for the individual wherein the anti-TNF therapy promotes mucosal healing.

As such. in r aspect. the present invention provides a method for reducing or zing the risk of surgery in an individual diagnosed with Crohn‘s disease being administered an anti-TNF dy therapy n. the method comprising: (a) measuring an away of mucosal healing markers at a ity oftime points over the course oftherapy with a therapeutic antibody; (b) generating the individual’s l healing index comprising a representation ofthe ce and/or concentration levels of each of the markers over time; (C) comparing the individual‘s mucosal healing index to that ofa control. and (d) selecting an appropriate anti-TNF dy therapy regimen for to reduce or minimize the risk ofsurgety.

As such. in another aspect. the present invention provides a method for selecting an anti-TNF antibody therapy regimen to promote mucosal healing in an individual diagnosed with Crohn‘s disease. the method comprising: (a) measuring levels ofa panel of mucosal healing markers at time point to to generate a mucosal g index at to; (b) measuring levels ofa panel of mucosal healing markers at time point t] to generate a mucosal healing index at t1; (c) comparing the change in the mucosal healing index from to to ti: and (d) selecting the anti-TNF antibody therapy regimen for the dual to promote mucosal g. |0020l In some embodiments, the disease is a gastrointestinal disease or an autoimmune disease. In certain instances. the subject has Crohn‘s disease (CD) or rheumatoid arthritis (RA). In other embodiments. the therapeutic antibody is an anti—TNFu antibody. in some embodiments, the anti-TNFu antibody is a member selected from the group ting of DETM (infliximabx ENBRELTM (etanercept). HUMIRATM (adalimumab). ClMZIAK' (ceitolizumab . and combinations thereof. In preferred embodiments, the subject is a human.

In some embodiments. the away of markers comprises a mucosal healing marker. In some ments. the mucosal marker comprises AREG. EREG. HB~EGF. HGF. NRG l.

NRG2. NRG3. NRG4. BTC. EGF. IGF. TGF—a. VEGF-A. . . VEGF-D.

FGFl . FGFZ. FGF7. FGF9. TWEAK and combinations thereof.

On other embodiments. the away of markers r ses a member selected from the group consisting of an anti-TNFa antibody. an anti-drug antibody (ADA), an inflammatory . an anti-inflammatory . a tissue repair marker (eg, a growth factor). and combinations f. In certain instances. the anti-TNFa antibody is a member selected from the group consisting of REMIC‘ADETM (infliximab). ENBRELTM (etanerccpt).

HUMIRATM (adalimumab). CIMZIAE (ceitolizumab pegol). and combinations thereof. In certain other instances, the anti-drug antibody (ADA) is a member selected from the group consisting ofa human anti-chimeric antibody (HACA). a human anti-humanized antibody (HAHA). a human anti-mouse antibody (HAMA). and combinations thereof. In yet other instances. the inflammatory marker is a member selected from the group consisting of GM- CSF. IFN—y, IL-I B, IL-2. lL-6. lL-‘t. TNF-a. sTNF RH. and combinations thereof. In funhcr instances. the anti-inflammatory marker is a member selected from the group consisting of IL-l2p70. IL-IO. and combinations thereof.

In certain embodiments. the array comprises at least 2. 3.4. 5. 6. 7. 8. 9. I0. I I. I2. l3. 14. I5. l6. l7. l8. I9. 20. 2]. 22. 23. 24. 25. 30. 35. 40. 45. 50. or more markers. In some embodiments. the markers are measured in a biological sample selected from the group consisting of serum. plasma. whole blood. stool. peripheral blood mononuclear cells . polymorphonuclear (PMN’) cells. and a tissue biopsy (cg, from a site of mation such as a portion ofthe gastrointestinal tract or synovial tissue).

In n ments. the plurality oftime points comprises at least 2. 3. 4. 5. (. 7. 8. 9. IO. ll. l2. l3. I4. 15. 16. I7. 18. I9. 20. 25. 30. 35. 40. 45. 50. or more time points.

In some instances. the first time point in the plurality oftime points is prior to the course of therapy with the therapeutic antibody. In other instances. the first time point in the plurality oftime points is during the course oftherapy with the therapeutic antibody. As non-limiting examples. each of the markers can be measured prior to therapy with a therapeutic antibody and/or during the course of therapy at one or more (e.g., a plurality) ofthe following weeks: 1.2.3.4. 5.6. 7. 8.9. IO. ll. l2. l3. I4. 15. l6. l7. I8. 19. 20. 22. 24. 26. 28. 30. 32. 34, 36. 38. 40. 42. 44. 46. 48. 50.52. 54. 56. 58. 60. 62. 64. 66. 68. 70. 80. 90. IOO. etc.

In some embodiments. selecting an riate therapy comprises maintaining. increasing, or decreasing a subsequent dose ofthe course of therapy for the subject. in other embodiments. the method further comprises ining a different course of therapy for the subject. In certain instances, the different course of therapy comprises treatment with a different N Fa antibody. In other instances. the different course of therapy comprises the current course of therapy along with another therapeutic agent. such as. but not limited to an anti-TNF therapy. an immunosupprcssivc agent. a corticosteroid. a drug that targets a different mechanism. a nutrition therapy and other combination treatments.

In some ments, selecting an riate therapy comprises selecting an riate therapy for initial treatment. In some instances. the y ses an anti- TNFOt antibody therapy.

In certain embodiments. the methods disclosed herein can be used as confirmation that a proposed new drug or therapeutic is the same as or is sufficiently similar to an approved drug product. such that the proposed new drug can be used as a “biosimilar” therapeutic. For example. if the proposed new drug has only a slightly different disease activity profile compared to the branded drug product. this would be apparent using the methods disclosed herein. lfthe proposed new drug has a significantly different disease activity profile compared to the branded drug t. then the new drug would not be biosimilar. Advantageously. the methods sed herein can be used in clinical trials of proposed new drugs in order to assess the effective therapeutic efficacy or value of the dmg.

Accordingly. in some aspects. the methods ofthe invention provide infonnation useful for guiding ent decisions for patients receiving or about to receive NF drug therapy. cg, by selecting an riate anti-TNF therapy for initial treatment. by determining when or how to adjust or modify (cg. increase or decrease) the uent dose of an anti-TNF drug. by determining when or how to combine an anti-TNF drug (tag, at an l. increased. decreased. or same dose) with one or more immunosuppressivc agents such as methotrcxate (MTX) or azathioprinc (AZA). and/or by determining when or how to change the cun'cnt course apy (cg, switch to a different anti—TNF drug or to a drug that targets a different mechanism such as an lL-6 receptor—inhibiting monoclonal antibody. anti-integrin molecule (cg, Tysabri. Vedaluzamab). JAK-2 inhibitor. and tyrosine kinase inhibitor. or to a nutritition therapy (cg, special carbohydrate dict)).

In other embodiments. the s ofthe present invention can be used to predict responsiveness to a TNFu inhibitor. especially to an anti-TN Fa antibody in a subject having an autoimmune er (cg, rheumatoid arthritis. Crohn’s Disease. ulcerative colitis and the like.) In this method, by ng the subject for the correct or therapeutic dose of anti- TNFo. dy. Ila. the therapeutic concentration level. it is possible to predict whether the individual will be responsive to the therapy.

In another embodiment. the t invention provides methods for monitoring IBD (C.g.. C‘rohn‘s disease and ulcerative colitis) in a subject having the IBD disorder“ wherein the method comprises assaying the subject for the correct or therapeutic dose of anti-TNFa antibody, i.e.. the eutic concentration level. over time. In this manner. it is possible to predict whether the individual will be responsive to the therapy over the given time period.

Other objects. features, and advantages ofthe present invention will be nt to one of skill in the art from the following detailed description and figures.

BRIEF DESCRIPTION OF THE DRAWINGS Figure I shows a personalized IBD activity profile as described in Example I.

Figure 2A show various patient infliximab concentrations as a function oftreatment time. Figure 23 shows patient ranks over a course of treatment with events (infliximab falling below a threshold tration) noted.

Figure 3A show various patient HACA (ATI) concentrations as a function of treatment time. Figure 3B shows patient ranks over a course oftreatment with events (HACA detection or appearance) noted.

Figure 4A illustrates an association between the presence ofATl and the level of IFX in t samples. Samples with no able level of ATI had a icantly higher IFX median concentration‘ compared to sample with detectable ATI. Figure 48 illustrates that the presence of ATI correlates with higher CDAI. Figure 4C shows that comment immunosuppressant therapy (cg, MTX) is more likely to suppress the presence of ATI.

Figure 5A shows that ts with ATI are more likely to p a poor response to treatment. Figure SB illustrates that the inflammatory marker CRP is associated with increased levels of AT].

Figure 6 illustrates that the protein levels of an away of one or more inflammatory and tissue repair markers correlate to the formation of antibodies to IFX.

Figure 7A illustrates that an array ofinflammatory markers can be used to ish an inflammatory index what correlates with the presence of ATI and/or disease progression.

Figure 7B shows the relationship between the P11 and lFX concentrations in samples with AT] present. Figure 7C illustrates that an exemplary PRO Inflammatory Index correlates with levels oleX (p<0.0001 and R2 = -0.129) in patient samples of the COMMIT study.

Figure 8A illustrates the correlation between Crohn‘s Disease Activity Index (CDAI) score and the concentration of mab in serum in a number of patients in clinical study #1. Figure SB shows that the presence oleX in a sample ated with a higher CDAl.

Figure 9A illustrates the association between lFX concentration and the presence of antidrug dies to inflixamab in samples analyzed. Figure 93 illustrates that a high concentration ofATl can lead to neutralizing dies and undetectable levels oleX.

Figure 9C illustrates that an ATI ve sample determined at an early time point leads to a higher CDAI at a later time point. compared to the lower CDAI level from an ATI negative sample. “Vl” = Visit l; “V3” = Visit 3. Figure 9D illustrates that in clinical study #l. patients had lower odds ofdeveloping ATl ifreceiving a combination therapy of infliximab and an immunosuppressant agent (cg, MTX and AZA).

Figure 10A shows that correlation between IFX concentration and the presence of AT] in samples of clinical study #ZA. Figure 108 rates the relationship between ISA therapy and the ce of AT] in the study. Figure 10C illustrates the relationship between CRP concentrations and the presence of AT] (ATl and/or neutralizing ATl). Figure 10D illustrates the onship between loss of responsiveness to lFX therapy and the presence of AT] in the study.

Figure 1] rates that levels of AT] and neutralizing antibodies can be determined over time in a series of samples from various patients.

Figure 12A illustrates the comparison ofCRP levels to the presence of lFX.

Figure 128 illustrates the relationship between the presence of ATI and the infusion reaction.

Figure 12C illustrates the onship between IFX concentration and the presence of AT] in clinical study #28. Figure 12D illustrates the correlation between the presence ofATl and the withdrawal OFISA therapy at a specific. given date.

Figure 13A illustrates the relationship between ATI and the inflammatory marker CRP. Our analysis showed that the odds ofexperiencing a loss ofresponsc to lFX was higher in ts determined to be ATI positive at any time point. Figure 133 illustrates the correlation between the presence of AT] at any time point and responsiveness to lFX treatment. Figure 13C shows that loss of response can be related to an increase in C RP.

Figure 13D illustrates the association between the presence of IFX and CRP levels.

Figure 14A shows that lower lFX levels are associated with the presence of AT] in clinical study #ZC‘. Figure 143 shows that lower lFX levels are associated with the presence of ATI in clinical study #3. Figure 14C illustrates that the same correlation n lFX levels and AT! was also present in the study data. follow-up study and in the phannacokinetics study.

Figure [5A illustrates the relationship between ATl levels and lFX. It was determined that samples with high concentration AT] are neutralizing on [FX and thus. lFX concentration was determined to be 0 [lg/ml. Figure [SB illustrates an association between ADL concentration and the presence of ATA in patient samples.

Figure [6A describes the details of an exemplary PRO Inflammatory Index.

Figure [68 illustrates that there is no obvious relationship between the PH and the concentration of ADL in an array of samples with ADL alone or in combination with other drugs.

Figure 17 shows a plot ofthe PI] scores for patients receiving Humira and Humira in combination with other drug such as Remicade. C imzia. Asathioprinc and Methotrexate.

Figure 18 shows details of methods for ed patient management ofCD and/or Figure 19 shows the effect ofthe TN F-OL y and related pathways on different cell types, cellular mechanisms and disease (cg. s Disease (CD). rheumatoid atthritis (RA) and Psoriasis (Ps)).

Figure 20 illustrates an exemplary CEER multiplex growth factor array. s 21A-G illustrate multiplexed growth factor profiling of t samples using CEER growth factor arrays.

Figure 22 illustrates the ation between CRP levels and the growth factor index score in ining disease remission.

Figure 23 illustrates embodiments ofthe present invention to assist in developing personalized patient ent for an IBD patient with mild. moderate. or severe e activity.

Figure 24 illustrates a treatment paradigm to alize patient ent.

Monitoring ofdisease burden and mucosal healing can assist in determining treatment selection. dose selection. and initial drug response.

Figure 25 shows the ROC analysis of CRP and lFX trough thresholds.

Figure 26 shows the relationship of CRP. serum lFX concentration and ATI at tial time points. Figure 26A shows presence of lFX and ATI in the pair‘s first data point and CRP in the subsequent measurements. Figure 263 shows CRP levels, lFX serum concentration and ATI status at sequential time points for a . In this sample CRP levels are lowest when the patient is ATI- and has a serum lFX concentration higher than threshold.

Figure 27 shows that there was no association n lFX levels higher than threshold and CRP in ATl+ patients. Yet. in AT]- patients CRP levels were significantly higher in ts with lFX levels less than threshold (3 rig/ml).

DETAILED DESCRIPTION OF THE INVENTION Introduction The present invention provides methods for measuring mucosal healing in patients with lBD, CD and/0r UC. In particular, the present invention provides methods ofmeasuring mucosal healing markers wherein the markers are indicative of intestinal tissue repair. and disease resolution or remission.

The present invention is advantageous because it addresses and overcomes current limitations associated with monitoring l healing in patients with lBD (tag. Crohn‘s disease and ulcerative colitis). The present invention es non-invasive methods for monitoring mucosal healing patients receiving anti-TNF therapy. In addition, the present invention provides methods of ting therapeutic response. risk of relapse. and risk of surgery in patients with lBD (cg, Crohn‘s disease and tive colitis). In particular, the methods ofthe t invention find utility for selecting an appropriate anti-TNF therapy for initial ent. for determining when or how to adjust or modify (cg, increase or se) the subsequent dose of an anti-TNF drug to ze therapeutic efficacy and/or to reduce toxicity, for determining when or how to combine an anti-TNF drug (cg, at an initial, increased. decreased, or same dose) with one or more immunosuppressivc agents such as methotrexate ( MTX) or azathioprine (AZA). and/or for determining when or how to change the current course of therapy (eg, switch to a different anti-TNF drug or to a drug that targets a different mechanism). The t invention also provides methods for selecting an appropriate therapy for ts diagnosed with CD. wherein the therapy promotes mucosa] healing. ll. Definitions ] As used herein. the following terms have the meanings ascribed to them unless specified ise.

The phrase "mucosal healing index“ es an empirically derived index that is based upon an analysis ofa plurality of mucosal healing markers. In one aspect, the concentration of markers or their measured concentration values are ormed into an index by an algorithm resident on a computer. In certain aspects, the index is a synthetic or human derived output, score. or cut off valuc(s). which expresses the biological data in numerical terms. The index can be used to determine or make or aid in making a clinical decision. A mucosal g index can be measured multiple times over the course oftime.

In one aspect. the algorithm can be trained with known samples and thereafter validated with samples of known identity.

The phrase “mucosal healing index control“ includes a mueosal healing index derived from a healthy individual, or an individual who has progressed from a disease state to a healthy state. Alternatively, the control can be an index representing a time course ofa more diseased state to a less disease state or to a healthy state.

The phrase “detetmining the course oftherapy” and the like es the use of an empirically d index, score or is to select for example. selecting a dose of drug, selecting an appropriate dung, or a course or length of therapy, a therapy regimen, or maintenance of an existing drug or close. In certain aspects, a derived or measured index can be used to determine the course oftherapy.

The terms “TNF inhibitor”, "TNF-0t inhibitor” and “TNFU. inhibitor“ as used herein are ed to encompass agents including proteins, antibodies, antibody fragments, fusion proteins (cg. lg fusion proteins or Fe fusion proteins). multivalent binding proteins (cg.

DVD lg), small molecule TN F-a antagonists and similar naturally- or nonnaturally-occurring les. and/or recombinant and/or engineered forms f. that. directly or indirectly. inhibits TNF (1 activity, such as by inhibiting interaction ofTNF-o. with a cell surface or for TN F-(t. inhibiting TNF-0t protein production, inhibiting TNF-rt gene expression. inhibiting TNFo. secretion from cells, inhibiting TN F-u or signaling or any other means resulting in sed TN F-(t activity in a subject. The term “TN F0. inhibitor” ably includes agents which interfere with TN F-o. activity. Examples of TNF-o. inhibitors include etancrcept (EN . Amgen). infliximab (REMICADETM. .lohnson and Johnson). human NF monoclonal antibody umab (D2E7/HUMIRATM, Abbott Laboratories), CDP 57] (Celltech). and (DP 870 (Cellteeh). as well as other compounds which t TN F-a activity. such that when administered to a subject suffering from or at risk of suffering from a disorder in which TNF-(l activity is detrimental (c.g.. RA). the er is treated.

The term “predicting responsiveness to a TN Fa inhibitor”. as used herein. is intended to refer to an ability to assess the hood that treatment ofa subject with a TNF inhibitor will or will not be effective in (e.g., provide a measurable benefit to) the t. In particular. such an ability to assess the likelihood that treatment will or will not be effective lly is exercised after treatment has begun. and an indicator of ef‘ectivencss (eg. an indicator of measurable benefit) has been obsewed in the subject. Particularly preferred TNFa inhibitors are ic agents that have been approved by the FDA for use in humans in the treatment of rheumatoid arthritis. which agents include adalimumab (HUMIRATM'). infliximab (REMICADETM) and etanercept (ENBRELTM). most preferably adalimumab (HUMIRATM).

The term e of therapy” includes any therapeutic approach taken to relieve or prevent one or more symptoms associated with a TNaF-mediated disease or disorder. The term encompasses administering any nd. drug. procedure. and/or regimen useful for improving the health of an individual with a TNFa-mediated disease or disorder and includes any ofthe therapeutic agents described . One d in the art will appreciate that either the course of y or the dose of the current course of therapy can be changed (cg. increased or decreased) based upon the presence or concentration level ofTNF. anti-TNF drug. and/or anti-drug antibody using the methods of the present invention. |0068| The term “imnumosuppressive agent” includes any substance capable of producing an immunosuppressive effect. cg. the prevention or diminution of the immune response. as by irradiation or by administration of drugs such as anti-metabolites. anti-lymphocyte sera. antibodies. etc. es of suitable immunosuppressive agents include. without limitation. thiopurinc drugs such as azathioprine (AZA) and metabolites thereof; anti—metabolites such as methotrexate (MTX); sirolimus (rapamycin); temsirolimus; everolimus: taerolimus (FK- 506); FK-778; anti-lymphocyte globulin antibodies. anti-thymoeytc globulin antibodies. anti— CD3 antibodies. D4 antibodies. and antibody-toxin conjugates; cyclosporine; mycophcnolate; mizoribine monophosphate; scoparone: glatiramer acetate; metabolites f; phannaceutieally acceptable salts thereof; derivatives thereof; s thereof: and combinations thereof.

The term “thiopurine drug" includes azathioprine (AZA ). 6-mercaptopurinc (6-MP), or any metabolite thereofthat has therapeutic efficacy and includes, without limitation, 6- thioguanine (6—TG), 6—methylmercaptopurine riboside, 6~thioinosinc nucleotides (eg, 6— thioinosine monophosphate. inosine diphosphate, 6—thioinosine triphosphate). 6— thioguanine tides (cg. 6-thioguanosine monophosphate, 6-thioguanosinc diphosphate. 6-thioguanosine triphosphate), 6-thioxanthosine nucleotides (c.g., 6-thioxanthosine monophosphatc, 6-thioxanthosinc diphosphatc, xanthosinc triphosphate), derivatives thereof, analogues thcrco f, and combinations thereof.

The term “sample” as used herein includes any biological specimen obtained from a patient. Samples include, without limitation, whole blood, plasma, serum, red blood cells, white blood cells (e.g.. peripheral blood clear cells (PBMC). polymorphonuelcar (PMN) cells), ductal lavage fluid, nipple aspirate, lymph (€.g., disseminated tumor cells of the lymph node), bone matrow aspirate, saliva. urine, stool (116., feces), sputum, bronchial lavage fluid. tears. fine needle aspirate (c.g., ted by random periarcolar fine needle aspiration), any other bodily fluid, a tissue sample such as a biopsy ofa site ofinflammation tag. needle biopsy), and cellular extracts thereof. in some embodiments. the sample is whole blood or a fractional component thereof such as . serum. or a cell . in other embodiments, the sample is obtained by isolating PBMCs and/or PMN cells using any que known in the an. In yet other embodiments. the sample is a tissue biopsy. cg, from a site ofinflammation such as a portion ofthe gastrointestinal tract or al tissue. [007ll The term "Crohn‘s Disease Activity index” or "CDAI" includes a research tool used to quantify the symptoms of patients with Crohn’s disease (CD). The CDAl is generally used to define response or remission of CD. The CDAl ts of eight factors, each summed after adjustment with a weighting factor. The components of the CDAI and weighting s are the following: Weighting Clinical or laboratory variable. . . factor Number of liquid or soft stools each day for seven days x 2 Abdominal pain (graded from 0-3 on severity) each day for seven days x 5 General well being. subjectively assessed from 0 (well) to 4 (terrible) each day for seven days Presence of complications. x 20 Taking Lomitil or s for diarrhea x 30 Presence of an abdominal mass (0 as none, 2 as questionable, 5 as definite) x 10 Hematocrit of <0.47 in men and <0.42 in women Percentage deviation from standard weight One point each is added for each set of complications: . the presence ofjoint pains (arthralgia) or frank arthritis: inflammation ofthc iris or uveitis; presence oferythcma nodosum. pyoderma gangrenosum, or aphthous ulcers; anal fissures, fistulae or abscesses; other fistulae; and/or fever during the previous week.

Remission of s disease is lly defined as a fall in the CDAl of less than 150 points. Severe disease is lly defined as a value of greater than 450 points. In certain aspects, response to a particular medication in a Crohn‘s e t is defined as a fall ofthc CDAl of r than 70 points.

The terms “mucosal injury” or “mucosal " include the Formation of copically visible mucosal lesions in the intestines able during endoscopy, granuloma formation and disruption ofthc muscularis layer at the microscopic tissue level, epithelial apoptosis and infiltration of activated inflammatory and lymphocytic cells at the cellular level, increased epithelial permeability at a sub-cellular level, and gapjunction disruption at a lar level. In lBD such as Crohn’s disease, the intestinal epithelium is damaged by the inflammatory environment, which results in the formation ofrefractory ulcers and lesions. |0074l The term “mucosal healing” refers to restoration ofnormal mucosal appearance ofa previously inflamed region, and complete e of ulceration and inflammation at the endoscopic and microscopic levels. Mucosal healing includes repair and restoration ofthc mucosa and muscularis layers. It can also include neuronal and , submucosa. lymphangiogenie elements ofthc intestinal wall.

The term “nutrition-based therapy “ includes butyrate, probiotics (tag, VSL#3, E. coli Nissle 1917, bacterium bacillus rmenticus), vitamins, proteins, macromolecules, and/or chemicals that promote mucosal healing such as growth and turnover ofintcstinal mucosa.

Ill. Description of the Embodiments The present invention provides methods for personalized therapeutic management ofa disease in order to ze therapy and/or monitor therapeutic efficacy. In ular, the present invention comprises measuring an array of one or a plurality of mucosal healing biomarkers at one or a plurality oftime points over the course oftherapy with a therapeutic agent to determine a l healing index for selecting therapy. optimizing therapy. reducing toxicity, and/or monitoring the efficacy of therapeutic treatment in certain ces, the therapeutic agent is a TNFO. inhibitor for the treatment ofa TNFa-mediated disease or disorder. In some embodiments. the methods of the present invention advantageously improve eutic management of patients with a TNFtr-mediated e or disorder by optimizing therapy and/or monitoring therapeutic efficacy to NF drugs such as anti-TNFo. therapeutic antibodies.

As such. in one aspect, the t invention provides a method for personalized eutic management ofa disease in order to optimize therapy or monitor therapeutic efficacy in a subject, the method comprising: (a) measuring an array of mucosal healing markers at a plurality oftime points over the course ofthcrapy with a therapeutic antibody; (b) generating the subject‘s mucosal healing index comprising a representation of the presence and/or concentration levels ofeach of the markers over time; (c) ing the subject‘s mucosal healing index to that ofa control; and (d) selecting an riate therapy for the subject, to y achieve personalized therapeutic management ofthe disease in the subject.

As such, in another aspect, the present invention provides a method for personalized eutic management of a disease in order to select therapy in a subject, the method comprising: (a) measuring an may of mucosal healing markers; (b) generating the subject‘s mucosal healing index comprising a representation of the presence and/or concentration levels of each of the markers; (c) comparing the subject‘s mucosal healing index to that ofa control; and (d) selecting an appropriate therapy for the subject, to thereby achieve personalized therapeutic management of the disease in the subject.

As such. in one aspect, the present invention provides a method for zing y in a subject. the method comprising: (a) measuring an array ofmucosal healing markers at a plurality oftime points over the course apy with a therapeutic antibody; (b) applying a statistical algorithm to the level ofthe one or more markers determined in step (a) to generate a mucosal healing index; (c) ing the subject‘s mucosal healing index to that oFa control; and (d) ining a uence dose of the course of y for the subject or whether a different course of y should be stered to the subject based upon the mucosal healing index.

As such, in one aspect, the present invention provides a method for selecting therapy in a subject, the method comprising: (a) measuring an array ofmucosal healing markers at a plurality of time points over the course oftherapy with a therapeutic antibody; (b) applying a tical thm to the level ofthe one or more markers determined in step (a) to te a mucosal healing index; (e) comparing the subject‘s mucosal healing index to that oFa control; and (d) selecting an appropriate course of therapy for the subject based upon the mucosal healing index. [0081I As such. in another aspect, the present invention provides a method for reducing the risk of surgery in a subject diagnosed with lBD (eg, Crohn‘s disease) being administered a therapy regimen (cag, an anti-TNF antibody therapy regimen), the method comprising: (a) measuring an away ofmueosal healing markers at a plurality oftime points over the course ofthcrapy with a eutic antibody; (b) applying a statistical algorithm to the level ofthc one or more markers determined in step (a) to generate a mucosal healing index; (c) comparing the subject‘s mucosal healing index to that ofa control; and (d) determining r the therapy regimen is reducing the subject‘s risk of surgery.

As such. in one aspect. the present invention provides a method for monitoring therapeutic efficiency in a subject receiving therapy (ch anti-TNF therapy), the method comprising: (a) measuring an array ofmucosal healing markers at a plurality oftime points over the course oftherapy with a therapeutic antibody: (b) applying a statistical algorithm to the level ofthe one or more markers ined in step (a) to generate a mucosal healing index; (c) comparing the subject‘s mucosal healing index to that ofa control; and (d) determining whether the current course oftherapy is appropriate for the subject based upon the mucosal healing index.

In some embodiments. the disease is a gastrointestinal disease or an autoimmune disease. In certain instances, the subject has inflammatory bowel disease (IBD, c.g., Crohn‘s disease (CD) or ulcerative colitis (UC)). In other instances, the subject has rheumatoid arthritis ( RA). In preferred embodiments. the subject is a human.

In some embodiments, the therapy is selected from the group comprising an anti- TNF therapy, an imimmosuppressivc agent, a corticosteroid. a drug that targets a different ism, a nutrition therapy or combinations f. In n instances. the anti—TNF therapy is a TNF tor (cg, anti-TNF drug. NFa antibody).

In other embodiments, the anti-TNF therapy is an anti-TNFa antibody. In some ments, the anti-TNFrt antibody is a member selected from the group consisting of REMICADETM (infliximab), ENBRELTM (etanercept), I-IUMIRATM (adalimumab), C‘IMZIAR" (ceitolizumab pegol), and combinations f. In preferred embodiments. the subject is a human.

In some embodiments, the therapy is an immunosuppressive agent. Non-limiting examples of immunosuppressive agents include thiopurine drugs such as azathioprine (AZA), (3-mereaptopun'ne (6-MP), and/or any metabolite thereofthat has therapeutic efficacy and includes, t limitation, 6-thioguanine (6-TG), yImercaptopurine ribosidc. 6- thioinosine nucleotides (cg, 6-thioinosine monophosphate, 6-thioinosinc diphosphate, 6- osine triphosphate), 6-thioguanine nucleotides (tag. 6-thioguanosine monophosphate. 6—thioguanosine diphosphatc. 6-tliioguanosine triphosphate), 6-thioxanthosinc nucleotides (cg, 6-thioxanthosine monophosphate, 6-thioxanthosine diphosphate, 6-thioxanthosine triphosphate), derivatives thereof, analogues thereof, and combinations thereof; anti- lites such as methotrexate (MTX); mus (rapamycin); temsirolimus: everolimus; tacrolimus (FK-506'); FK-778; anti-lymphocyte globulin dies. anti-thymoeyte in antibodies. anti-CD3 antibodies. anti—CD4 antibodies. and antibody-toxin conjugates; cyclosporine; mycophenolate: mizoribine monophosphate; one; glatiramer acetate; metabolites thereof; pharmaceutically acceptable salts thereof; derivatives thereof; prodrugs thereof; and combinations thereof.

In other embodiments, the therapy is a corticosteroid. In yet other embodiments, the therapy is a drug that targets a ent mechanism (e.g., a mechanism that is not mediated by the TNFO. pathway). Non-limiting examples ofa drug that s a different mechanism include lL-6 receptor inhibiting monoclonal antibodies, anti-integrin molecules (cg. natalizumab (Tysabri), vedoluzamab). .lAK—Z inhibitors, tyrosine kinase inhibitors, and combinations thereof.

In other embodiments, the therapy is a nutrition therapy. In particular embodiments. the ion therapy is a special ydrate diet. Special carbohydrate dict (SCD) is a strict grain-free. lactose-free. and sucrose-free nutritional regimen that was designed to reduce the symptoms of IBD such as Crohn‘s disease and uleerative s. It has been shown that SCD can promote and/or maintain mucosal healing in patients with IBD (eg, Crohn’s disease or tive colitis). Typically. SCD restricts the use ofcomplex carbohydrates and eliminates refined sugar, grains and starch from the diet. It has been described that the microvilli of patients with IBD lack the ability to break down specific types of x carbohydrates, resulting in the overgrowth ofharmful bacteria and irritation of the gut mucosa. It has been recommended that SCD is a therapy for IBD (e.g., Crohn’s disease or ulcerative colitis) because it enables the gut to undergo mucosal healing.

In some embodiments, the array ofmarkers comprises a mucosal healing marker. In some embodiments, the mucosal marker comprises AREG‘ EREG, HB-EGF, HGF, NRG I, NRGZ. NRG3. NRG4. BTC. EGF, lGF, TGF-a, VEGF-A, VEGF-B. , VEGF-D.

FGFI. FGFZ, FGF7. FGFO. TWEAK and combinations f.

In other embodiments, the array ofmarkers further comprises a member ed from the group consisting of an anti-TNFo. antibody, an ing antibody (ADA), an inflammatory marker. an anti-inflammatory marker. a tissue repair marker (cg. a growth factor). and combinations f. In certain instances, the anti-TNFa antibody is a member selected from the group consisting of REMICADETM (infliximab), ENBRELTM ('etanercept).

HUMIRATM (adalimumab). CIMZIA‘R‘ (eertolizumab pegol), and combinations f. In certain other instances, the anti-drug antibody (ADA) is a member ed from the group consisting ofa human anti-chimeric antibody . a human anti-humanized antibody (HAHA), a human anti-mouse antibody (HAMA), and combinations thereof. In yet other instances, the inflammatory marker is a member selected from the group consisting of GM- CSF, IFN-y, IL-IB. IL-2, IL~6. ch8. TNF-a, sTNF RH, and combinations thereof. In r instances. the anti-inflammatory marker is a member selected from the group consisting of 70. IL-IO, and combinations thereof.

In certain embodiments, the array comprises at least 2, 3, 4. 5, 6, 7, 8, 9. 10, l l, 12. l3, I4, 15. 16, 17, 18, 19,20, 21, 22, 23, 24, 25, 30, 35.40.45, 50, or more markers. In some embodiments. the markers are measured in a biological sample selected from the group consisting of serum, plasma, whole blood, stool. peripheral blood clear cells (PBMC), polymorphonuclear (PMN) cells. and a tissue biopsy (cg. from a site of inflammation such as a portion ofthe gastrointestinal tract or synovial tissue).

In certain embodiments, the plurality oftime points comprises at least 2, 3, 4, 5, 6, 7, 8. 9. 10. ll. 12, l3. 14, 15, 16, 17, 18, 19.20, 25, 30, 35, 40, 45, 50. or more time points.

In some instances, the first time point in the plurality oftime points is prior to the course of therapy with the therapeutic dy. In other instances, the first time point in the plurality oftime points is during the course apy with the therapeutic antibody. As non-limiting examples, each ofthe markers can be measured prior to therapy with a therapeutic antibody and/or during the course oftherapy at one or more (cg, a plurality) ofthc following weeks: 1, 2, 3, 4, 5, 6. 7, ,11,12,13,14,15,16,17,l8,l9,20,22, 24, 26, 28, 30, '32, 34, 36. 38, 40, 42, 44, 46. 48, 50,52, 54, 56, 58, 60, 62, 64, 66, 68, 70, 80. 90, 100, etc.

In further embodiments, the method for assessing or measuring mucosal healing further ses comparing the determined level of the mucosal healing marker present in a sample to an index value or cutoff value or reference value or threshold value. wherein the level ofthe mucosal healing marker abovc or below that value is predictive or indicative of an sed or higher likelihood ofthe subject either undergoing mucosal healing or not undergoing mucosal healing. One skilled in the art will understand that the index value or cutoff value or reference value or threshold value is in units such as mg/ml, pig/ml, ng/ml, pg/ml, fg/ml, EU/ml, or U/ml depending on the marker rest that is being measured.

In some embodiments. the mucosal healing index includes an empirically derived index that is based upon an analysis ofa ity ofmueosal healing markers. In one aspect, the concentration of markers or their measured concentration values are transformed into an index by an algorithm resident on a computer. In certain aspects, the index is a synthetic or human derived output, score, or cut off valuc(s), which expresses the biological data in numerical terms. The index can be used to determine or make or aid in making a clinical decision. A mucosal healing index can be measured multiple times over the course oftimc.

In one aspect. the algorithm can be trained with known samples and thereafter validated with s of known identity.

In some embodiments. the mucosal healing index control is a mucosa! healing index derived from a healthy individual. or an individual who has progressed from a disease state to a healthy state. Alternatively. the control can be an index representing a time course ofa more diseased state or y to e.

In some embodiments. the methods of ining the course of therapy and the like include the use of an empirically derived index. score or analysis to select for example. selecting a dose of drug. selecting an appropriate drug. or a course or length oftherapy. a therapy regimen. or maintenance of an existing drug or dose. In certain aspects. a derived or measured index can be used to determine the course of therapy.

In some embodiments. mucosal healing can be assessed or monitored by endoscopy.

Non-limiting examples of endoscopy include video capsule endoscopy (capsule opy). disposable endoscopy. and 3D endoscopy. In other embodiment. the l healing index is monitored or ed by endoscopy.

In some embodiments. selecting an appropriate therapy comprises maintaining. increasing. or sing a subsequent dose of the course of therapy for the t. In other embodiments. the method further comprises ining a ent course oftherapy for the subject. In certain instances. the ent course of therapy comprises treatment with a different anti-TNFa antibody. In other instances. the different course oftherapy comprises the current course of therapy along with another therapeutic agent. such as. but not limited to. an immunosuppressive agent. a corticosteroid. a drug that targets a different mechanism. nutrition y. and combinations thereofl.

In some embodiments. ing an appropriate therapy comprises selecting an appropriate therapy for initial treatment. In some instances. the therapy comprises an anti- TNth antibody therapy.

In certain embodiments. the methods sed herein can be used as confirmation that a proposed new drug or therapeutic is the same as or is sufficiently similar to an approved drug product. such that the proposed new drug can be used as a “biosimilar” therapeutic. For example. ifthe proposed new drug has only a slightly different disease activity profile compared to the branded drug product. this would be apparent using the methods disclosed herein. Ifthe proposed new drug has a cantly different disease activity profile compared to the branded drug product, then the new drug would not be biosimilar. Advantageously. the s disclosed herein can be used in clinical trials of proposed new drugs in order to assess the effective therapeutic value of the drug.

Accordingly, in some aspects. the methods ofthe invention provide infonnation useful for guiding treatment ons for patients receiving or about to receive anti—TNF drug y. eg. by selecting an appropriate anti-TNF therapy for initial treatment. by determining when or how to adjust or modify (e.g.. increase or decrease) the subsequent dose ofan anti-TNF drug. by determining when or how to combine an anti-TNF drug (eg. at an initial, increased, decreased, or same dose) with one or more immunosuppressive agents such as methotrexate (MTX) or azathioprine (AZA ), and/or by determining when or how to change the cun'ent course oftherapy (cg. switch to a different anti-TNF drug or to a drug that targets a ent mechanism such as an lL-6 receptor-inhibiting monoclonal antibody, anti-integrin molecule (c.g., Tysabri. Vedaluzamab). JAK-Z inhibitor. and tyrosine kinase inhibitor, or to a ition therapy (cg. special carbohydrate dietl). [0l02] In other ments, the methods of the present invention can be used to predict responsiveness to a TN F0. inhibitor. especially to an anti-TN Fa antibody in a subject having an autoimmune disorder (cg, rheumatoid arthritis. Crohn‘s e. ulcerative colitis and the like). In this method. by assaying the subject for the correct or therapeutic dose of anti- TNFtt antibody. [.e., the therapeutic concentration level, it is possible to predict whether the individual will be responsive to the therapy.

In another embodiment. the t invention provides s for monitoring lBD (cg. Crohn‘s disease and ulcerative colitis) in a subject having the lBD disorder. wherein the method comprises assaying the subject for the correct or therapeutic dose of NFn antibody, 118.. the therapeutic concentration level, over time. In this manner. it is possible to predict whether the individual will be responsive to the therapy over the given time period.

In certain embodiments. step (a) comprises determining the presence and/or level of at least two. three. four. five. six. seven. eight. nine. ten. fifteen. twenty. thirty, forty. fifty. or more markers in the sample.

In other embodiments, the algorithm comprises a learning statistical fier system. In some instances, the learning tical classifier system is selected from the group consisting ofa random forest. classification and regression tree. boosted tree. neural network. support vector machine, general chi-squared automatic interaction detector model. interactive tree, daptive regression spline, machine learning fier, and ations thereof.

In n instances. the statistical algorithm comprises a single learning statistical classifier system. In certain other instances. the statistical algorithm comprises a combination of at least two learning tical fier systems. In some instances. the at least two leaming statistical classifier systems are applied in tandem. Non-limiting examples of statistical algorithms and analysis suitable for use in the invention are described in ational Application No. PCT/U820] 1/056777. filed r 18. 201 I. the disclosure of which is hereby incorporated by reference in its entirety for all purposes.

In other embodiments, step (b) further comprises ng a statistical thm to the presence and/or level ofone or more mucosal healing markers determined at an r time during the course oftherapy to generate an earlier mucosal healing index. In some instances. the earlier mucosal healing index is compared to the mucosal healing index generated in step (b) to determine a uent dose of the course of therapy or whether a different course oftherapy should be administered. In certain embodiments, the subsequent dose of the course of y is increased. decreased. or maintained based upon mucosal healing index generated in step (b). In some instances. the different course oftherapy comprises a different anti-TN Fa. antibody. In other instances. the different course apy comprises the t course of therapy along with an immunosuppressive agent.

In some embodiments. step (b) further comprises applying a statistical thm to the presence and/or level of one or more of the mucosal healing markers determined at an earlier time to generate an earlier disease activity/severity index. In certain instances. the mucosal healing index is compared to the mucosal g index generated in step (b) to predict the course of the TN F-mcdiatcd e or er.

In some embodiments. the method further comprises sending the results from the selection or determination ofstep (d) to a clinician. In other embodiments. step (d) comprises selecting an initial course oftherapy for the subject.

Once the diagnosis or prognosis ofa subject receiving anti-TNF drug therapy has been determined or the likelihood ofresponse to an anti-TNF drug has been predicted in a subject diagnosed with a disease and disorder in which TNF has been implicated in the pathophysiology, cg. but not d to. shock. sepsis. infections. autoimmune diseases. RA, Crohn‘s disease. transplant rejection and graft-versus-host disease. according to the methods bed herein. the present invention may further comprise recommending a course of therapy based upon the diagnosis. prognosis. or prediction. In certain instances. the present invention may r comprise administering to a subject a therapeutically effective amount ofan anti-TNFu drug useful for treating one or more symptoms associated with the TN F- mediated disease or disorder. For therapeutic applications. the NF drug can be administered alone or co-administered in combination with one or more additional anti~TNF drugs and/or one or more drugs that reduce the side-effects associated with the NF drug (cg, an immunosupprcssive agent). As such, the present invention advantageously enables a clinician to practice “personalized medicine” by guiding treatment decisions and ing y selection and optimization for anti-TNFa drugs such that the right drug is given to the right patient at the right time. [01 10] The present invention is advantageous because it ses and mes current limitations associated with the stration of anti-TNF drugs such as infliximab, in part, by providing information useful for guiding treatment decisions for those ts receiving or about to receive anti-TNF drug therapy. In particular. the s of the present invention find utility for selecting an appropriate anti—TNF therapy for initial treatment, for determining when or how to adjust or modify (cg, increase or se) the subsequent dose of an anti- TNF drug to optimize therapeutic efficacy and/or to reduce toxicity, for determining when or how to combine an NF drug (cg. at an initial. increased‘ decreased. or same dose) with one or more immunosuppressive agents such as methotrexate (MTX) or azathioprine (AZA). and/or for determining when or how to change the current course of therapy (6.0., switch to a different anti-TNF drug or to a drug that targets a ent mechanism).

] Accordingly, the present invention is particularly useful in the following methods of improving t management by guiding treatment decisions: 1. Crohn‘s disease prognostics: Treat patients most likely to benefit from therapy 2. Anti-therapeutic antibody monitoring (ATM) + Biomarker-based disease activity profiling ATM sub—stratification ATM with pharmacokinetic modeling Monitor response and predict risk of relapse: a. Avoid chronic maintenance therapy in patients with low risk of recurrence b. Markers of mucosal healing e. Therapy selection: Whether to combine or not to combine anti-TNF drug therapy with an immunosuppressive agent such as MTX or AZA t selection for biologics.

In some embodiments. the present invention provides a method for measuring an inflammatory index for Crolrn‘s Disease management for an individual to optinrizc therapy, and predict se to the anti—TNF therapeutic. the method comprising: (a) chromatographically measuring NF therapeutics and autoarrtibodies in a sample from the individual to determine their concentration levels; (b) chromatographically measuring anti- TNF therapeutics and autoantibodies in a sample From the individual to determine their concentration levels; (c) ing the measured values to an efficacy scale to optimize therapy. and predict response to the anti—TNF therapeutic. l3] In some embodiments. the present invention provides a method for predicting the likelihood the concentration of an anti-TNF therapeutic during the course oftreatment will fall below a threshold value. the method comprising: (a) measuring a panel ofmarkers selected from the group consisting of I) GM- CSF; 2) lL-Z; 3) TN F-u: 4) sTNFRll; and 5) the disease being situated in the small intestine; (b) predicting the likelihood the concentration of an anti-TNFrt therapeutic will fall below the threshold based upon the concentration ofthe markers. [0| 14] For the purpose of ration only. Example 5 shows an ary embodiment of the present invention In particular. a method of predicting the likelihood the concentration of an anti-TNF treatment will fall below a threshold value.

In some embodiments, the present invention es a method for predicting the likelihood the concentration of an anti-TNF eutic during the course of treatment will fall below a threshold value. the method sing: (a) measuring a panel of markers ed from the group consisting of l ) ; 2) lL-Z; 3) TNF—a: 4) sTNFRlI; and 5) the disease being situated in the small intestine; and (b) predicting the likelihood the concentration of an anti-TNF therapeutic will fall below the threshold based upon the concentration ofthe s.

In other embodiments. the present invention provides a method for predicting the likelihood that anti—drug antibodies will occur in an dual on anti-TNF therapy, the method sing: (a) measuring a panel ofmarkers selected from the group consisting oft EGF.

VEGF. lL—8. CRP and VCAM- l; and (b) ting the likelihood that anti-drug antibodies will occur in an individual on anti-TNF therapy based on the concentration of marker levels.

For the purpose ofillustration only. Example 4 is an exemplary embodiment of the present invention and demonstrates the detectin ofanti-drug antibodies to infliximab (ATl). [0| l8| In other embodiments, the present invention provides a method for monitoring an infliximab treatment regimen. the method comprising: (a) measuring infliximab and antidrug antibodies to infliximab (ATI ); (b) ing inflammatmy s CRP. SAA. lCAM. VCAM; (c) measuting tissue repair marker VEGF; and (d) correlating the measurements to therapeutic efficacy.

For the purpose of illustration only‘ e 5 is an exemplary embodiment of the present invention and shows a method of monitoring an IFX treatment regimen. |0120| In other embodiments. the present invention provides a method for detennining whether an individual is a ate for combination therapy wherein said individual is administered infliximab, the method comprising: (a) measuring for the presence or absence of AT] in said individual; and (b) administering an suppressant (cg. MTX) is the individual has significant levels of ATI. 21| In yet other ments. the method also includes measuring the concentration level ofCRP which is indicative ofthe ce of ATI. For the purpose ofillustration only, Examples 6 and 7 show that the presence and absence of AT] are predictive of responders and non-responders of Remicade therapy. Examples 6 and 7 are exemplary embodiments.

In yet other embodiments, the present invention provides a method for monitoring Crohn’s disease ty‘ the method comprising: (a) detennining an inflammatory index comprising the measurement ofa panel of markers comprising VEGF in pg/ml, CRP in ng/ml, SAA in ng/ml, [CAM in ng/ml and VCAM in ng/ml: and (b) comparing the index to an efficacy scale to monitor and mange disease. [0123I For the e ofillustration only. Example 9 is an ary embodiment and shows use of the inflammatory index. [01241 In particular ments, the present invention provides methods for determining the threshold of an anti—TNF drug such as IFX that can best discriminate disease activity as measured by C-reactive protein (CRP) levels. For the purpose of illustration only, Example 12 shows that IFX dichotomized at a threshold of3 rig/ml can be differentiated by CRP. In n instances. random IFX < 3 and IFX 2 3 rig/ml serum samples have higher CRP in IFX < 3 ug/ml at a 74 ”/6 rate (ROC AUC). Example 12 also shows that in ATI+ samples pairs, no significant difference in CRP between IFX groups (above and below 3 rig/ml) was observed.

In particular, CRP levels were generally higher in ATl+ sample pairs, and CRP levels were higher in IFX < 3 rig/ml for ATI- samples. Regression confirmed that CRP was positively related to AT! and negatively related to IFX. As such. the ction corresponds to a (RP- IFX relationship that differs between ATl+ and ATl—.

IV. Mucosal Healing Index The methods of the present invention comprise monitoring y se and predicting risk of relapse. in some embodiments. the methods include detecting. measuring and/or determining the presence and/or levels ofmarkers ofmucosal healing.

The gut mucosa plays a key role in barrier defense in on to nutrient digestion. absorption and metabolism. The dynamic ses ofintestinal epithelial cell proliferation, migration. and sis are highly affected by general nutritional status. route of feeding. and adequacy ofspeeific nutrients in the diet. However, with inflammatory diseases ofthe gut. mucosa] cell impairment can result in mucosal injury or damage. thereby resulting in enhanced bility to macromolecules. increased bacterial translocation from the lumen, and stimulation ofepithelial cell apoptosis. [0127l Mucosal injury is a multi-faceted physiological s spanning macroscopic to lar levels. Mucosal injury includes the formation of macroscopically visible ] lesions detectable during endoscopy. granuloma formation and disruption ofthe muscularis layer at the microscopic tissue level. epithelial apoptosis and infiltration of activated inflammatory and lymphocytic cells at the cellular level. increased epithelial bility at a sub-cellular level. and gap junction disruption at a molecular level. |0128l Mucosal injuty is likely initiated by a combination of endogenous and environmental s. At first stage. it is believed that food—derived compounds. viral and ial-derived factors. as well as host-derived factors. may cause epithelial cell destruction and activation ofinnate and adaptive immunity. Damaged mucosa is lly infiltrated by diverse inflammatory cells consisting of phils. eosinophils. mast cells. inflammatory monocytes, activated macrophages and dendritic cells. Specific adaptive immune ses toward the intestinal flora are generated leading to the later recruitment of activated B cells.

CD4+ and CD8+ T cells to the inflamed mucosa. Neutrophils secrete elastase which can result in extracellular matrix ation ofthe epithelium. Likewise, T cells. macrophages and intestinal fibroblasts express inflammatory factors such as lL-l. lL-2. lL-6, lL-l4, lL—l7, TGFB and TN F0. that lead to extracellular matrix degradation. epithelial damage, cndothelial activation. and/or fibrosis stricture formation. Non-limiting examples of markers of mucosal injury include matrix metalloproteases (MMPs) and markers of oxidative stress (cg, iNOS. reactive oxygen metabolites).

A. Array of Mucosal g Markers A y ofmucosal markers including growth factors are particularly useful in the methods of the present invention for personalized therapeutic management by selecting therapy. optimizing therapy. reducing toxicity. and/or monitoring the efficacy oftherapeutic treatment with one or more therapeutic agents such as biologics (cg. anti—TNF drugs). In particular embodiments. the s bed herein utilize the determination ofa mucosal healing index based upon one or more (a plurality of) mucosal healing s such as growth factors (€.f’., alone or in combination with biomarkers from other categories) to aid or assist in predicting disease course. selecting an appropriate anti-TNF drug therapy. optimizing anti-TNF drug therapy. ng ty associated with anti-TNF drug therapy. and/or monitoring the efficacy oftherapeutie treatment with an anti-TNF drug.

As such. in certain embodiments. the determination ofthe presence and/or level of one or more growth s in a sample is useful in the present invention. As used herein. the term “growth factor” includes any ofa variety ofpcptides. polypeptides. or proteins that are capable of stimulating ar proliferation and/or cellular differentiation.

In some embodiments. mucosal g markers include. but are not limited to. growth factors. inflammatory s. cellular adhesion markers. ncs. anti- inflammatory markers. matrix metalloprotcinases. oxidativc stress markers, and/or stress response markers.

In some embodiments. mucosal healing markers include growth factors. Non- limiting examples of growth factors include amphiregulin . epiregulin (EREG). heparin binding epidermal growth factor F). hepatocye growth factor (HGF). heregulin-Bl (HRG) and isofomis, neuregulins (NRG l, NRG2, NRG3. NRG4). betaeellulin (BTC). epidermal growth factor (EGF). insulin growth factor-l (lGF-l ). transforming growth factor (TGF). platelet-derived growth factor (PDGF). vascular endothelial growth factors (VEGF-A. VEGF-B. VEGF—C, VEGF-D), stem cell factor (SCF'). platelet derived growth factor (PDGF). soluble fms-like tyrosine kinase 1 (sFlt l ), ta growth factor (PIGF.

PLGF or PGF), fibroblast growth factors , FGFZ. FGF7. FGF9), and combinations thereof. In other embodiments. mucosal healing markers also include pigment epithelium- d factor (PEDF. also known as SERPINFl ). endothclin-l (ET-I ). keratinocyte growth factor (KGF; also known as FGF7). bone monphogenctic proteins (tag, BMPl-BMPIS). et-derived growth factor (PDGF), nerve growth factor (NGF). vc growth factor ([5— NGF). neurotrophic factors (tag. brain-derived neurotrophic factor (BDNF), neurotrophin 3 (NTS). neurotrophin 4 (NT4). etc. ), growth entiation -9 (GDF-9). granulocyte- colony stimulating factor (G-CSF). Uranuloeyte-macrophage colony stimulating factor (GM- CSF). myostatin (GDP-8). erythropoietin (EPO), thrombopoietin (TPO). and combinations thereof.

In other embodiments. mucosal healing markers also include cytokines. Non- limiting examples ofeytokines that can be used to establish a mucosa] healing index include bFGF. . lL-lO. lL-12(p70).lL-l[3. lL-Z. lL-6. GM-CSF. lL-l3. JPN-y. TGF-Bl. TOF- 2, TOP-[33, and combinations thereof. Non-limiting examples of ar adhesion markers include SAA. CRP. IC‘AM. VCAM. and combinations thereof. Non-limiting es of anti-inflammatory markers include lL-l2p70. lL-IO. and combinations thereof.

In some embodiments, mucosal healing markers include markers specific to the intestinal tract including inflammatory markers and serology markers as described herein. Non-limiting examples include antibodies to bacterial antigens such as. c.g.. OmpC. flagellins (cBir-l, Fla-A, Fla-X, eta), l2. and others , ASCA. ere. ); anti-neutrophil antibodies. anti-Succhumm}recs (-crevisiue dies. and anti-mierobiol antibodies.

The ination ers ofoxidative stress in a sample is also useful in the present invention. Non-limiting examples of markers ofoxidative stress include those that are protein-based or DNA-based, which can be detected by measuring protein oxidation and DNA fragmentation, respectively. Other examples of markers ofoxidative stress include organic compounds such as malondialdeliyde.

Oxidative stress represents an imbalance between the production and manifestation ofreactive oxygen species and a biological system‘s ability to readily detoxify the reactive ediates or to repair the resulting damage. Disturbances in the normal redox state of tissues can cause toxic effects through the production of peroxides and free radicals that damage all components of the cell. ing proteins, lipids, and DNA. Some reactive oxidative species can even act as messengers through a phenomenon called redox signaling.

In certain embodiments, derivatives ofreactive oxidative metabolites (DROMs). ratios ofoxidized to reduced glutathione (Eh GSH). and/or ratios of ed to reduced cysteine (Eh CySH) can be used to quantify oxidative stress. See, cg. Neuman er (1/.. Clin.

Che/11.. 53:1652-l657 (2007‘). Oxidative modifications ofhighly reactive cysteine residues in proteins such as tyrosine atases and thioredoxin-related ns can also be detected or measured using a technique such as. e.g.. mass spectrometry (MS). See. e.g., Naito el al., Ami-Aging ne. 7 (5):36-44 (2010). Other markers of oxidativc stress include proteinbound acrolein as described. e.g.. in Uchida e! al.. PNAS, 95 (9) 4882-4887 (1998), the free oxygen radical test (FORT). which reflects levels oforganie hydroperoxides, and the redox potential of the reduced glutathione/glutathione ide couple. (Eh) GSH/GSSG. See, e.g., Abramson er al.. A{/7crosc/ernsi.s', 178(1):] 15-21 (2005). [0138l In some embodiments, matrix metalloproteinases (MMPs) include members ofa family of Zn2 -dependent extracellular matrix (ECM) degrading endopeptidascs that are able to degrade all types of ECM proteins. Non-limiting es of MMPs include MMP-l, MMP-Z. MMP-3. MMP-7. MMP-R. MMP-9. MMP-I2, MMP-l3. MTl-MMP-l, and combinations thereof. It has been shown that MMP-3 and MMP-9 are associated with mucosal injury and fistulae in CD ts (Baugh ct ul.. Gustrucnrem/ogv, l 17: 814-822. (1999‘); Bailey at a/.. J. Clin. Pat/70].. 47: 1 13-] I6 (1994)). In some embodiments, stress response markers include markers of oxidative stress. such as reactive oxygen s (ROS). superoxide dismutase (SOD), catalase (CAT). and hione‘ and markers ofendoplasmic reticulum (ER) stress. Non-limiting examples of markers ofoxidative stress include those that are protein-based or DNA-based. which can be detected by measuring protein oxidation and DNA fragmentation, respectively. In other ments, mucosal healing s further include markers of oxidative DNA and/or protein damage. Non-limiting examples of ER stress markers include markers of unfolded protein response (e.g.. ATF6, HSPAS, PD1A4. XBPl, IRE]. PERK. E1F2A, GADD34. GRP-78. phosphoylatcdJNK.caspase-12, caspase-3‘ and combinations f).

The human egulin (AREG) polypeptide sequence is set forth in. «g, Genbank Accession Nos. NP_001648.1 and XP_001 125684. I. The human AREG mRNA (coding) sequence is set forth in, fig, Genbank Accession Nos. NM_001657.2 and XM_001 1256843. One d in the art will appreciate that AREG is also known as AR. colorectum cell-derived growth factor. CRDGF. SDGF. and AREGB.

The human ulin (EREG) polypeptide sequence is set forth in, cg. Genbank Accession No. NP_001423. l. The human EREG mRNA (coding) sequence is set forth in. cflg Genbank Accession No. NM_001432.2. One skilled in the art will appreciate that EREG is also known as EPR.

The human heparin—binding EGF-like growth factor (HB-EGF) polypeptide sequence is set forth in. c.g.. Genbank Accession No. NP_001936.1. The human HB-EGF mRNA (coding) sequence is set forth in. cg. Genbank Accession No. NM_001945.2. One skilled in the an will appreciate that HB-EGF is also known as diphtheria toxin receptor. DT- R. HBEGF. DTR. DTS. and HEGFL. |0142| The human hepatocyte growth factor (HGF) polypeptide ce is set forth in, e.g.. k Accession Nos. NP_000592.3. NP_00101093 l .1. NP_001010932.1. 010933.1. and NP_001010934.1. The human HGF mRNA (coding) sequence is set forth in, cg. Genbank Accession Nos. 60].4. NM-00]0]O931.1. NM»00]0]0932.].

NM_001010933.1 and NM_001010934.1. One skilled in the art will appreciate that HGF is also known as scatter factor. SF, HPTA and hepatopoietin-A. One of skill will also appreciate that HGF includes to all isoform variants.

The human neuregulin-l (NRGl) polypeptide sequence is set foflh in. e..,g Genbank Accession Nos..NP_00]153467.1. NP_001153471.1.NP_001153473.1. 153477.1.

NP_039250.2. NP_039251.2. NP_0392522, NP_039253.1, NP_039254.], NP_0392562. and NP_039258.1. The human NRG] mRNA (coding) sequence is set forth in. tag. Genbank Accession N0.NM_001159995.].NM_00]1599991. NM_001160001.1. NM_001160005.], NM_013956.3. NM_013957.3. NM_013958.3. NM_013959.3. 960.3.

NM_0139622, and NM_013964.3. One skilled in the art will appreciate that NRC] is also known as GGF. HGL. HRGA. NDF. SMDF. ARIA. acetyleholine receptor-inducing activity. breast cancer cell differentiation factor p45. glial growth factor, heregulin. HRG. neu differentiation factor, and y and motor neuron-derived factor. One of skill will also appreciate that NRG] includes to all isoform variants.

The human neurcgulin-Z (NRGZ) polypeptide sequence is set fonh in. mg. Genbank Accession Nos. NP_OOl 171864.1.NP_004874.1, 584.1, NP_053585.1 and NP_053586.1. The human NRG2 mRNA g) sequence is set forth in. e.g.. Genbank Accession Nos. NM_OOl 184935.1.NM_004883.2. NM_013981.3. NM_0139822 and 983.2. One skilled in the art will appreciate that NRG2 is also known as NTAK. - and thymus-derived activator for ERBB kinases. DON-l. and divergent of neuregulin-l. One of skill will also appreciate that NRGZ includes to all isofomt variants. [01451 The human neuregulin-3 (NRG3) polypeptide sequence is set forth in. ug.‘ Genbank Accession Nos. 01084X.2 and NP_OOl 159445.]. The human NRG3 mRNA (coding) sequence is set fonh in. cg. Genbank Accession Nos. NM_0010108483 and NM_OOl 1659731. One skilled in the art will appreciate that NRGZ includes to all isoform variants.

The human neuregulin-4 (NRG4) polypeptide sequence is set forth in. emg Genbank Accession No. NP_612640. 1. The human NRG4 mRNA (coding) sequence is set forth in. cg. Genbank Accession No. NM_138573.3. One d in the an will appreciate that NRG4 includes to all isoform variants. |0147| The human betacellulin (BTC) polypeptide sequence is set forth in. cg, Genbank Accession No. NP_001720.1. The human BTC mRNA (coding) sequence is set forth in. e.g..

Genbank Accession No. NM_001729.2. One d in the art will appreciate that BTC includes to all isoform variants. [01481 The human epidermal growth factor (EGF) polypeptide sequence is set forth in. eflg Genbank Accession Nos. NP_001954.2 and NP_001 171602. 1. The human EGF mRNA g) sequence is set forth in, erg, Genbank Accession Nos. NM_001963.4 and NM_OOl 1781311. One skilled in the art will appreciate that EGF is also known as beta- urogastrone. urogastrone. URG. and HOMG4.

The human insulin-like growth factor (IGF) polypeptide sequence is set fonh in. eg, Genbank Accession Nos. NP_000609.1 and NP_001 104755.]. The human lGF mRNA (coding) sequence is set fonh in, e.g.. Genbank Accession No. 618.3 and NM_OOl l 1 1285.1. One skilled in the art will appreciate that IGF includes to all isoform ts. One skilled in the art will also appreciate that lGF is also known as mechano growth factor. MGF and somatomedin-C.

The human transforming growth factor alpha x) polypeptide sequence is set forth in, cg, Genbank Accession Nos. 227.| and NP_00109316I.1. The human TGF-o. mRNA (coding) sequence is set forth in. c.g., Genbank Accession Nos.

NM_003236.3 and NM_001099691.2. One skilled in the art will appreciate that TGF-O. includes to all isoform variants. One skilled in the art will also appreciate that TGF-o. is also known as EGF-like TGF, ETGF, and TGF type 1.

The human vascular endothelial growth factor (VEGF-A) ptide sequence is set forth in. cg. Genbank Accession Nos. NP_001020537. 020538. NP_001020539.

NP_001020540. 020541. NP_001028928. and NP_003367. The human VEGF-A mRNA (coding) sequence is set fonh in, eg. Genbank Accession No. NM_001025366, NM_001025367. NM_001025368, NM_001025369, NM_001025370. NM_001033756. and NM_003376. One skilled in the art will appreciate that VEGF-A is also known as VPF.

VEGFA. VEGF, and 09. . One skilled in the art will appreciate that VEGF-A includes to all isoform variants.

The human vascular endothelial growth factor (VEGF-B) polypeptide sequence is set forth in. e.g., Genbank Accession Nos. NP_001230662, and NP_003368. The human VEGF-B mRNA (coding) sequence is set forth in, e.g.. Genbank Accession Nos.

NM_00l243733 and NM_003377. One skilled in the art will appreciate that VEGF-B is also known as VEGFB. VEGF-related factor. and VRF. One skilled in the art will appreciate that VEGF-B includes to all isoform variants.

The human vascular endothelial growth factor (VEGF-C) polypeptide sequence is set forth in. tag. Genbank Accession No. NP_005420. The human VEGF-C mRNA (coding) sequence is set forth in. Lag. Genbank Accession No. NM_005429. One skilled in the art will iate that VEGF-C is also known as Flt4 ligand. Flt4-L. VRP and vascular endothelial growth factor-realtcd protein. One skilled in the art will appreciate that VEGF-C‘ includes to all isoform variants.

The human fibroblast growth factor I (FGFl) polypeptide ce is set forth in, cg. Genbank ion Nos. NP_00079I. NP_00] 138364. NP_00l 138406.

NP_00| 138407. NP_00l l38407, l.'Z7, and NP_l49l28. The human FGFl mRNA (coding) ce is set forth in. c.g.. Genbank Accession Nos. 800.

NM_00l 144892. NM_00] 144934.NM_001144934. NM_001144935. NM_O33l36 and NM_O33l37. One skilled in the art will appreciate that FGFl is also known as FGFA. FGF- l, acidic fibroblast growth , aFGF. endothelial cell growth factor. ECGF. heparin- binding growth factor 1. and HB-EGFI. One skilled in the art will appreciate that FGFl includes to all isoform variants.

The human basic fibroblast growth factor (bFGF) polypeptide ce is set forth in. 6.31.. Genbank ion No. NP4001997.5. The human bFGF mRNA (coding) sequence is set forth in. cg. Genbank Accession No. NM_002006.4. One skilled in the art will appreciate that bFGF is also known as FGFZ. FGFB. and HBGF-Z.

The human fibroblast growth factor 7 (FGF7) polypeptide sequence is set forth in. c.g.. Gcnbank Accession No. 000. l. The human FGF7 mRNA (coding) sequence is set forth in. cg, Gcnbank Accession No. 009.3. One skilled in the art will appreciate that FGF7 is also known as FGF-7. HBGF—7 and keratinocyte growth factor. [01571 The human fibroblast growth factor 9 (FGF9) polypeptide sequence is set forth in. rag. Genbank ion No. NP_002001. l. The human FGF9 mRNA (coding) sequence is set forth in. e.g.. Genbank Accession No. NM_002010.2. One skilled in the art will appreciate that FGFQ is also known as FOP-9. CAP. and HBGF-Q.

The human TN F-related weak inducer of apoptosis (TWEAK) polypeptide sequence is set forth in. eg. Genbank Accession No. NP_003800.1. The human TWEAK mRNA (coding) sequence is set forth in. tag. Genbank Accession No. NM_003809.2. One skilled in the art will appreciate that TWEAK is also known as TNFIZ. APO3 ligand. APO3L. DR3LG. and UNQIRl/PR0207..

In certain instances. the presence or level ofa particular mucosa] healing marker such as a growth factor is detected at the level of mRNA sion with an assay such as. for example. a hybridization assay or an amplification-based assay. In n other instances. the presence or level of a particular growth factor is detected at the level of protein expression using. for example. an immunoassay (e.g., ELISA) or an immunohistochemical assay. In an exemplary ment, the ce or level ofa particular growth factor is detected using a multiplexed array. such as a Collaborative Enzyme Enhanced Reactive ImmunoAssay (CEER), also known as the Collaborative Proximity Immunoassay ). CEER is described in the following patent documents which are herein incorporated by reference in their entirety for all purposes: PCT Publication No. WO 2008/036802; PCT Publication No. ; PCT Publication No. WO 2009/108637; PCT Publication No. ; PCT Publication No. WO 201 1/008990; and PCT Application No. ZOIO/053386, filed October 20, 2010.

Suitable ELISA kits for determining the presence or level ofa growth factor in a serum. plasma, saliva. or urine sample are available from. c.g., Antigenix America Inc. (Huntington Station. NY), Promega (Madison. WI). R&D s. Inc. (Minneapolis. MN), Invitrogen (Camarillo. CA). CHEMICON International. Inc. (Temecula. CA). Neogen Corp. (Lexington.

KY), PeproTech (Rocky Hill. NJ). Alpco Diagnostics . NH), Pierce Biotechnology, Inc. ord. IL). and/or Abazymc (Needham. MA).

In particular embodiments. at least one or a plurality (cg. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11.12.13.14.15 . 16. 17, IX. 19. 20. or2]. such as. e.g.. a panel or an array)ofthe following growth factor markers can be detected (e.g., alone or in combination with biomarkers from other categories) to aid or assist in predicting disease course. and/or to improve the cy of selecting therapy. optimizing y. ng toxicity. and/or monitoring the efficacy of therapeutic treatment to anti-TNF drug therapy: AREG, EREG.

HB-EGF. HGF, NRGl. NRG2, NRG3. NRG4, BTC, EGF. lGF, TGF-Ot, VEGF-A. VEGF-B.

VEGF-C, . FGFI, FGF2, FGF7, FGF9, TWEAK and combinations thereof.

B. Mucosal g Index In certain aspects, the t invention es an algorithmic-based analysis of one or a plurality ofteg, 2, 3. 4, 5, 6, 7. 8, 9,10,11,12,13,|4,15,l6,l7,l8,l9, 20, 21, or more) mucosal healing markers to improve the accuracy of selecting y. optimizing therapy, reducing toxicity. and/or monitoring the efficacy apeutic ent to anti- TNFU. drug therapy.

A single statistical algorithm or a combination of two or more statistical algorithms described herein can then be applied to the presence or concentration level of the mucosal healing markers detected, measured. or determined in the sample to thereby select therapy, optimize therapy, reduce toxicity, or monitor the efficacy of therapeutic treatment with an anti-TN Fa ding. As such. the methods ofthe invention find utility in determining patient management by determining patient immune status.

In some embodiments, the statistical algorithm comprises a learning statistical classifier system. In some instances, the ng statistical classifier system is selected from the group consisting ofa random forest, classification and regression tree, boosted tree, neural network, t vector machine, general chi-squared tic interaction detector model, interactive tree. multiadaptive regression spline, machine learning classifier, and ations f. In certain instances, the statistical algorithm comprises a single learning statistical classifier system. In other embodiments, the statistical algorithm comprises a combination of at least two ng statistical classifier systems. In some instances, the at least two learning statistical classifier systems are applied in . Non- limiting examples of statistical algorithms and analysis suitable for use in the invention are described in International ation No. PCT/U820] l/056777, filed October 18, 20l l, the sure of which is hereby incorporated by reference in its entirety for all purposes.

Preferably, mucosa] healing index is an empirically derived experimentally prepared index of values. In some instances, the index of values is transformed from an array of control measurements that were experimentally determined. In one aspect. the concentration of markers or their measured concentration values are transformed into an index by an algorithm resident on a computer. In certain aspects. the index is a synthetic or human derived output, score, or cut off s_), which expresses the biological data in numerical terms. The index can be used to determine or make or aid in making a clinical decision. A mucosal healing index can be ed multiple times over the course oftime. In one aspect, the algorithm can be d with known samples and thereafter validated with samples of known identity.

In further embodiments. the method for ing or measuring mucosal healing further comprises comparing the ined level of the mucosal healing marker present in a sample to an index value or cutoff value or reference value or threshold value. wherein the level ofthe mucosal healing marker above or below that value is predictive or tive of an increased or higher likelihood ofthe subject either undergoing mucosal healing or not undergoing mucosal healing. One skilled in the art will understand that the index value or cutoffvalue or nce value or threshold value is in units such as mg/ml. [Lg/ml, ng/ml, pg/ml, fg/ml. EU/ml. or U/ml depending on the marker ofinterest that is being measured.

In some embodiments, the mucosal healing index l is a mucosal healing index derived from a healthy individual. or an individual who has progressed from a disease state to a y state. Alternatively, the control can be an index representing a time course ofa more diseased state or healthy to disease.

In some embodiments, the methods ofdetermining the course oftherapy and the like include the use of an empirically derived index, score or analysis to select for example. selecting a dose of drug. selecting an appropriate drug. or a course or length of therapy. a therapy regimen, or maintenance of an existing drug or dose. In certain aspects, a derived or measured index can be used to ine the course oftherapy.

Understanding the clinical course of disease will enable physicians to make better informed treatment decisions for their inflammatory disease patients (cg. IBD. Crohn‘s disease or ulcerative colitis) and may help to direct new drug development in the future. The ideal mucosal healing marker(s) for use in the mucosal healing index described herein should be able to identify individuals at risk for the e and should be disease-specific.

Moreover, mucosal g (s) should be able to detect disease activity and monitor the effect of treatment; and should have a predictive value towards relapse or recurrence of the disease. ting disease course. however. has now been expanded beyond just disease ence, but perhaps more importantly to include predictors of disease complications including surgery. The t invention is particularly advantageous because it provides indicators Ofmueosal healing and enables a prediction ofthe risk ofrelapse in those patients in remission. ln addition. the mucosal g markers and mucosal healing index of present invention have enonnous implications for patient management as well as therapeutic decision-making and would aid or assist in directing the appropriate therapy to those ts who would most likely benefit from it and avoid the expense and potential toxicity ofchronic maintenance therapy in those who have a low risk of recurrence. l. e Activity Profile As described herein. the e activity profile (DAP) ofthe present invention can advantageously be used in methods for personalized therapeutic management ot‘a disease in order to ze therapy and/or monitor therapeutic efficacy. In certain embodiments. the methods of the invention can improve the accuracy of selecting therapy. optimizing therapy. ng toxicity, and/or ring the efficacy oftlrerapeutic treatment to anti-TNF drug therapy. In particular embodiments, the DAP is determined by measuring an array of one or a ity of(c.g., 5. 6. 7. 8. 9, 10, ll, 12, l3, 14. 15. 16. I7. 18, l9, 20, 2i, 22,23. 24, 25, 30. 35. 40. 45, 50, or more) markers at a plurality oftime points over the course of therapy with a therapeutic antibody (Kg, anti—TNF drug) to determine a DAP. wherein the DAP comprises a representation ofthe concentration level ofeach marker over time. In certain embodiments, the DAP may comprise a representation ofthe presence or absence. concentration (e.g., expression) level, activation (e.g., phosphorylation) level, and/or velocity valuc (cg. change in slope ofthc level ot‘a particular marker) of each marker over time. As such. the s ofthe present invention find utility in determining patient management by deternrining patient immune status.

In certain instances, a single statistical algorithm or a combination oftwo or more tical algorithms can be applied to the concentration level of each marker over the course of therapy or to the DAP . tanding the clinical course of disease enables physicians to make better informed ent decisions for their inflammatory disease patients (cg. lBD (cg, Crohn‘s disease), rheumatoid arthritis (RA). others) and helps to direct new drug development. The ideal biomarker(s) for use in the disease activity profile described herein is able to identify individuals at risk for the disease and is e-specific. Moreover. the biomarkerts) are able to detect disease activity and monitor the effect of treatment; and have a predictive value towards relapse or recurrence of the disease. Predicting disease course. however. has now been expanded beyond just disease recurrence, but more importantly to include predictors of disease cations ing surgery. The present invention is particularly advantageous because it provides indicators of disease activity and/or severity and enables a prediction of the risk of relapse in those patients in remission. In addition. the biomarkers and disease activity profile of the present invention have enormous implications for patient ment. as well as eutic decision-making. and aid or assist in directing the appropriate therapy to patients who most likely will benefit from it and avoid the expense and potential toxicity of chronic maintenance therapy in those who have a low risk of recurrence.

As a non-limiting example, the disease activity profile (DAP‘) in one embodiment comprises detecting, measuring. or determining the presence, level ntration (6.g., total) and/or activation (e.g., phosphorylation», or genotype of one or more specific biomarkers in one or more ofthe ing categories of biomarkers: (1) Drug levels (tag, anti-TNF drug levels): (2) Anti-drug antibody (ADA) levels (Lugs level of autoantibody to an anti-TNF drug); (3) Inflammatory markers; (4) Anti-inflammatory markers; and/or (5) Tissue repair markers.

Non-limiting es of additional and/0r alternative markers in which the presence, level ntration (cg, total) and/or activation (cg, orylation», or genotype can be measured include: (6) gy (cg, immune markers); (7) Markers ofoxidativc ; (8) Cell surface receptors (Chg. CD64. others); (9) Signaling ys; (l0) kcl, or the elimination rate constant ofa drug such as a therapeutic antibody (6.0., infliximab); and/or ( l l ) Other markers (cg, genetic markers such as inflammatory pathway genes).

A. Anti-TNF Drug Levels & Anti-Drug Antibody (ADA) Levels In some ments, the disease activity profile (DAP) comprises determining the presence and/or level of anti-TNF drug (cg, level of free anti-TN Fa therapeutic antibody such as infliximab) and/or anti-drug antibody (ADA) (e.g., level of autoantibody to the anti- TNF drug such as HACA) in a patient sample (eg. a serum sample from a patient on anti— TNF drug therapy) at le time points. e.g.. before. during. and/or after the course of therapy.

In particular embodiments. the presence and/or level ofanti-TNF drug and/or ADA is determined with a homogeneous mobility shift assay using size exclusion chromatography.

This method. which is described in PCT Application No. PCT/USZOlO/054IZSt filed October 26, 20l0, the disclosure ofwhieh is hereby incorporated by reference in its entirety for all purposes, is particularly advantageous for measuring the presence or level ofTNFa. inhibitors as well as autoantibodies (cg. HACA. HAHA. etc.) that are generated against them.

In one embodiment. the method for detecting the presence of an anti-TNFa antibody in a sample comprises: (a) contacting d TNFu with a sample having or suspected of having an anti- TNth antibody to form a labeled complex with the anti-TNFo. antibody; (b) subjecting the labeled complex to size exclusion chromatography to separate the labeled complex; and (c) detecting the labeled complex, thereby detecting the anti-TNFa antibody.

In certain instances, the methods are ally useful for the ing anti-TNFa antibodies: REMICADETM ximab), ENBRELTM (etanerccpt), HUMIRATM (adalimumab), and CIMZIA": (certolizumab pegol).

Tumor necrosis factor a. (TNFa) is a eytokine involved in systemic inflammation and is a member ofa group of eytokines that stimulate the acute phase reaction. The primary role ofTNFa is in the regulation of immune cells. TNFa is also able to induce apoptotic cell death, to induce inflammation. and to inhibit tumorigencsis and viral replication. TNF is primarily produced as a 212-amino acid-long type II transmembranc protein ed in stable homotrimers.

The terms “TNF”, “TNFa,” and “TNF-a,” as used herein, are intended to include a human cytokine that exists as a 17 kDa secreted form and a 26 kDa membrane associated form. the biologically active form of which is ed ofa trimer ofnoncovalently bound 17 kDa molecules. The structure ofTN F-o. is described further in. for example, Jones, at al. (1989) Nature, -228. The term TNF-a is intended to include human, a recombinant human TNF-(L (rhTNF-u), or at least about 80% ty to the human TN Fa n. Human TNFa consists ofa 35 amino acid (aa) asmic domain, a 21 aa transmembrane segment. and a 177 aa extracellular domain (ECD) (Pennica, D. er al. (1984) Nature 3l22724). Within the ECD. human TNFU. shares 97% aa sequence identity with rhesus and 7100 92% with bovine, , cotton rat, equine, feline, mouse, porcine. and rat TNFa. TNFa can be prepared by standard recombinant expression s or purchased commercially (R & D Systems, Catalog No. , Minneapolis. Minn.) In certain instances, after the TNF 0, antibody is detected, the TNF a. antibody is ed using a standard curve.

In r embodiment, the method for detecting an autoantibody to an anti—TNFo. antibody in a sample comprises: (a) contacting labeled anti-TNFa antibody with the sample to form a labeled x with the autoantibody; (b) subjecting the labeled complex to size ion chromatography to separate the labeled complex: and (c) detecting the labeled complex, thereby detecting the autoantibody.

In certain instances. the autoantibodies include human anti-chimeric antibodies (HACA), human anti—humanized antibodies (HAHA), and human anti-mouse antibodies (HAMA). miting examples of other methods for ining the presence and/or level of anti-TNF drug and/or anti-drug antibodies (ADA) include -linked immunosorbcnt assays (ELlSAs) such as bridging ELlSAs. For e, the lnfliximab ELlSA from Matriks Biotek Laboratories detects free infliximab in serum and plasma samples, and the HACA ELISA from PeaceHealth Laboratories detects HACA in serum samples.

B. Inflammatory Markers Although disease course ofan inflammatory disease is typically measured in terms of inflammatory activity by noninvasive tests using white blood cell count, this method has a low specificity and shows limited correlation with disease activity.

As such. in certain embodiments, a variety ofinflammatory markers. including biochemical s, serological markers, protein markers, c markers. and/or other clinical or aphic characteristics. are particularly useful in the methods ofthe present invention for personalized therapeutic management by selecting therapy. optimizing therapy, reducing toxicity, and/or monitoring the efficacy oftherapeutic treatment with one or more therapeutic agents such as biologics (e.g.. anti-TNF drugs). In particular embodiments, the methods described herein utilize the determination ofa disease activity profile (DAP) based upon one or more (a plurality of) inflammatory markers (cg. alone or in combination with kers from other categories) to aid or assist in predicting disease course, selecting an riate anti-TNF drug therapy, optimizing anti-TNF drug therapy. ng toxicity associated with anti-TNF drug therapy, and/or monitoring the efficacy of therapeutic ent with an anti-TNF drug.

Non-limiting examples ammatory markers include cytokines, chemokines, acute phase proteins. cellular adhesion molecules, SlOO ns, and/or other inflammatory markers. In preferred ments. the inflammatory markers comprise at least I. 2. 3. 4. 5. 6. 7. 8, 9. 10. IS. 20. 25. or nrore cytokines. In one particular embodiment. the cytokines are at least I. 2. 3. 4. 5. 6. 7. or all 8 ofthe following: GM-CSF. lFN-y. lL-lB. lL-Z. lL-6. lL—b’.

TNF—a. and sTNF R11. 1. Cytokines and Chemokines The determination ofthe presence or level of at least one cytokine or chemokine in a sample is particularly useful in the present invention. As used herein. the term “cytokine” es any ofa variety of polypeptides or proteins secreted by immune cells that regulate a range ne system functions and encompasses small cytokines such as chemokines.

The term “cytokine” also includes adipocytokines. which se a group of cytokines secreted by adipocytcs that function. for example. in the regulation of body weight. hematopoiesis. angiogenesis. wound healing. insulin resistance. the immune response. and the atory response.

In certain embodiments. the presence or level of at least one cytokine including. but not limited to. granulocyte-macrophage colony-stimulating factor (GM—CSF). lFN-y. lL-lB. lL-Z. lL-6. lL-8. TNF-a. soluble tumor necrosis factor-a receptor 1] (sTNF Rll). lated weak inducer ofapoptosis (TWEAK). osteoprotegerin (OPG). lFN-a. lFN-B. lL-la. lL-l receptor antagonist (lL-lra). lL-4, lL-5. soluble lL-6 receptor (le-6R). lL-7. lL-9, lL-l2. IL- 13.1L-l5. lL-l7. lL-23. and lL-27 is determined in a sample.

In certain other embodiments. the ce or level of at least one chemokine such as. for example. /GROl/GROu. C‘XCLZ/GROZ. CXCL3/GRO3, CXCL4/PF-4.

CXCLS/ENA-78. CXCLb/GCP-Z. CXCL7/NAP-2. CXCL9/MIG. C‘XCL l O/IP- l 0.

CXCLl l/l—TAC. CXCLIZ/SDF—l, CXCLl3/BCA-l. CXCLM/BRAK. CXCLlS. CXCLl6.

CXCL l 7/DMC. CC‘Ll . CCLZ/MCP-l . IP- l 0.. CCL4/MlP-l [3. ANTES.

CCLo/CIO. CCL7/MCP-3. C‘P-2. CCL9/CCL10, CCLl l/Eotaxin. CCL l Z/MCP-S.

CCLl3/MCP-4. C(‘L l4/HCC-l. CCLlS/MIP-S. CCLl6/LEC. (‘CL l WYARC‘. CCLIS/MIP- 4. CCLl9/MlP-3B. CCLZO/MIP-3a. CCLZ l/SLC. /MDC. CCL23/MPIF1.

CCL24/Eotaxin—2. CCLZSfl'ECK, CCLZfi/Eotaxin-3. CCL27/CTACK. CCLZS/MEC. CL], CL2. and CX_:CLl is determined in a sample. In certain further embodiments. the presence or level of at least one adipocytokine ing. but not limited to. leptin, adiponeetin. resistin. active or total plasmirrogen activator inhibitor-1 (PAl-l ). visfatin. and retinol binding protein 4 (RBP4) is determined in a sample. Preferably. the presence or level of GM—CSF.

IFN-y, IL-IB. IL-Z. lL—6, IL-8, TNF-tt, sTNF RlI. and/or other cytokinCs or ehcmokines is determined. [0190[ In certain instances. the presence or level ofa particular cytokinc or chemokine is detected at the level of mRNA expression with an assay such as, for example. a hybridization assay or an amplification—based assay. In certain other instances, the presence or level ofa particular eytokine or chemokine is detected at the level ofprotein expression using. for example, an immunoassay (e.g., ELISA) or an immunohistochemical assay. Suitable ELISA kits for determining the ce or level ofa eytokine or chemokine of interest in a serum, , , or urine sample are available from, cg, R&D Systems, Inc. (Minneapolis, MN), Neogen Corp. (Lexington, KY), Alpeo Diagnostics (Salem, NH), Assay Designs, Inc.

(Ann Arbor. MI), BD Biosciences Pharmingen (San Diego, CA). lnvitrogen (Camarillo. CA), Calbiochem (San Diego, CA). CH EMICON International, Inc. (Temeeula. CA), Antigenix America Inc. (Huntington Station, NY), QIAGEN Inc. (Valencia, CA). d Laboratories, Inc. (Hercules, CA), and/or Bender MedSystems Inc. (Burlingame, CA). [0191[ The human lL-6 polypeptide sequence is set forth in. e.g., Genbank Accession No.

NP_00059I. The human IL-6 mRNA (coding) sequence is set forth in, rag, Genbank Accession No. NM_000600. One skilled in the art will appreciate that lL-6 is also known as eron beta 2 (IFNB2), HGF. HSF. and BSFZ. [0192[ The human lL-IB polypeptide sequence is set forth in. e.g.. k Accession No.

NP_000567. The human IL-IB mRNA (coding) sequence is set forth in. e.g.. k ion No. NM_000576. One skilled in the art will appreciate that IL-10 is also known as ILIFZ and IL-lbcta.

The human IL-8 polypeptide sequence is set forth in, e.g., Genbank Accession No.

NP_000575 (SEQ ID N011). The human IL-8 mRNA (coding) ce is set forth in. rag.

Genbank Accession No. NM_000584 (SEQ ID NO:2). One skilled in the art will appreciate that lL-8 is also known as CXCLS, K60, NAF, GCPI, LECT, LUCT, NAPI, 3-IOC, GCP-I.

LYNAP. MDNCF. MONAP. NAP-l, SCYBS. TSG—I. AMCF-l, and .

The human TWEAK polypeptide sequence is set forth in, e.g., Genbank Accession Nos. NP-003800 and AAC51923. The human TWEAK mRNA (coding) sequence is set forth in, e.g.. Genbank Accession Nos. NM_003809 and BC I 04420. One skilled in the art will appreciate that TWEAK is also known as tumor necrosis factor ligand superfamily member 12 (TNFSFIZ). APO3 ligand ), CD255. DR3 ligand, growth factor- inducible I4 (Fnl4) ligand, and UNQIXI/PROZOT 2. Acute Phase Proteins The determination ofthe presence or level of one or more acute—phase proteins in a sample is also useful in the present invention. Acute—phase proteins are a class of proteins whose plasma concentrations increase (positive acute-phase proteins) or decrease (negative acute-phase proteins) in response to inflammation. This response is called the acute-phase reaction (also called acute-phase response). Examples of positive acute-phase proteins include, but are not limited to. C-reactivc protein (CRP). D—dimcr protein. e-binding protein. alpha l-antitrypsin, alpha l-antichymonypsin, alpha 2-macroglobulin. fibrinogen. prothrombin. factor VIII. von Willebrand factor. plasminogen. complement factors. ferritin. serum amyloid P component. serum amyloid A (SAA). orosomucoid (alpha l—acid glycoprotein. AGP). ccruloplasmin. lobin. and combinations thereof. Non-limiting examples of ve acute-phase proteins e albumin. en‘in. transthyretin. transcortin. retinol-binding protein, and combinations thereof. Preferably, the presence or level ofCRP and/or SAA is determined.

In certain instances, the presence or level ofa particular acute-phase protein is detected at the level omeNA expression with an assay such as. for example. a hybridization assay or an amplification-based assay. In ceitain other instances. the ce or level ofa particular acute-phase protein is detected at the level of protein expression using. for example. an immunoassay (e.g., ELISA) or an immunohistochemical assay. For example, a sandwich colorimetric ELISA assay available from Alpco stics (Salem, NH) can be used to ine the level ofC‘RP in a serum. . urine, or stool sample. Similarly. an ELISA kit available from a Corporation (Foster City. CA) can be used to detect CRP levels in a sample. Other methods for ining CRP levels in a sample are bed in. e.g., US. Patent Nos. 6.838.250 and 6.406.862: and US. Patent Publication Nos. 20060024682 and l9410. Additional methods for determining CRP levels include, cg, immunoturbidimetry assays. rapid immunodiffusion , and visual agglutination assays. Suitable ELISA kits for determining the presence or level of SAA in a sample such as serum. plasma, saliva. urine. or stool are available from. e.g., Antigcnix America Inc.

(Huntington Station. NY), Abazyme (Needham. MA). USCN Life (Missouri City. TX). and/or U.S. Biological (Swampscott. MA).

C-reactive protein (CRP) is a protein found in the blood in se to inflammation (an acute-phase protein). CRP is typically produced by the liver and by fat cells (adipocytes).

It is a member ofthe pentraxin family of proteins. The human CRP polypeptide sequence is set forth in, e.g.. Genbank Accession No. NP_000558. The human CRP mRNA (coding) sequence is set forth in. cg. Genbank Accession No. NM_000567. One skilled in the art will appreciate that CRP is also known as PTX], MGC88244. and MGC I 49895.

Serum amyloid A (SAA) proteins are a fanrily of apolipoproteins associated with high-density lipoprotein (HDL) in plasma. Different isoforms of SAA are expressed constitutivcly (constitutive SAAs) at different levels or in response to inflammatory stimuli (acute phase SAAs). These ns are inantly ed by the liver. The conservation of these proteins throughout invertebrates and vertebrates ts SAAs play a highly essential role in all animals. Acute phase serum amyloid A proteins (A-SAAs) are secreted during the acute phase ofinflammation. The human SAA polypeptide sequence is set forth in, e.g.. k Accession No. NP_000322. The human SAA mRNA g) sequence is set forth in. e.g.. Genbank ion No. NM_00033 l. One skilled in the art will appreciate that SAA is also known as PlG4, TP53l4, MGCI l I216, and SAA l. 3. Cellular Adhesion Molecules (lgSF CAMs) The determination oftlre presence or level ofone or more immunoglobulin superfamily cellular adhesion molecules in a sample is also useful in the present invention.

As used herein, the term “immunoglobulin superfamily cellular adhesion molecule” (lgSF CAM) includes any ofa y of polypeptides or proteins located on the surface ofa cell that have one or more immunoglobulin-like fold domains, and which on in intereellular on and/or signal transduction. In many cases. lgSF CAMs are transmembrane proteins.

Non-limiting examples of lgSF CAMs include Neural Cell Adhesion Molecules (NCAMs: e.g.. NCAM-l20, NCAM-lZS. NCAM—l40, NCAM-l45. NCAM-IXO. NCAM-lb’S, eta). lntercellular Adhesion Molecules (lCAMs. tag, lCAM-l, lCAM-Z. lCAM-3, lCAM—4, and lCAM—S), Vascular Cell Adhesion Molecule-l ('VCAM—l ), Platelet-Endothelial Cell Adhesion Molecule-l (PECAM-l ). Ll Cell Adhesion Molecule (LlCAM), cell on molecule with homology to L l CAM (close homolog of Ll ) (CHL l ), sialic acid binding lg- like lectins Cs; e.g., SlGLEC-l. SlGLEC-Z. SlGLEC-B. SlGLEC-4. eta). Neetins (e.g.. Neetin—l, Neetin-2, Nectin-3. cm). and Nectin—like molecules (cg, Neel-l , Neel-2.

Neel-3. Neel-4. and Neel-5). Preferably. the presence or level oflCAM-l and/or VCAM-l is determined. lCAM-l is a transmembrane cellular adhesion n that is continuously present in low concentrations in the membranes of ytes and endothelial cells. Upon cytokine stimulation, the concentrations greatly increase. [CAM-l can be induced by lL-l and TNth and is expressed by the vascular endothelium. macrophages. and lymphocytes. In lBD, proinflammatory cytokines cause ation by upregulating expression of adhesion molecules such as ICAM-I and VCAM-l. The increased expression of adhesion molecules recruit more lymphocytes to the infected tissue. resulting in tissue inflammation (sec. Goke at u/.. ./., Gusrmenterul.. 322480 (1997'); and Rijcken er (1/.. Cut. 511529 (2002)). lCAM-l is encoded by the intercellular adhesion molecule I gene (ICAM 1'. Entrez GeneID:3383; Gcnbank Accession No. NM_00020 I) and is produced after processing ofthe intercellular adhesion molecule I precursor polypeptide (.Genbank Accession No. NP_000I92).

VCAM-l is a transmembrane cellular adhesion protein that es the adhesion oflymphocytes. monoeytes. phils. and basophils to vascular endothelium.

Upregulation of VCAM-l in endothelial cells by cytokincs occurs as a result eascd gene transcription (L’.g.. in response to Tumor necrosis factor-alpha (TNFa) and Interleukin-I (IL-1)). VCAM-I is encoded by the vascular cell on molecule I gene (VCAMI; Entrez GeneID:7412) and is ed after differential splicing ofthe transcript (Genbank Accession No. NM-001078 (variant 1 ) or NM_080682 (variant 2)). and processing ofthe precursor polypeptide splice m ('Genbank Accession No. NP_00 l 069 (isoform a) or NP_5424 l 3 (isoform b)). |0202| In certain instances. the presence or level ofan lgSF CAM is detected at the level of mRNA expression with an assay such as. for example. a hybridization assay or an amplification-based assay. In certain other instances. the presence or level of an lgSF CAM is detected at the level of protein expression using. for example. an assay (tags ELISA) or an immunohistochemical assay. Suitable antibodies and/or ELISA kits for determining the presence or level of ICAM-1 and/or VCAM-l in a sample such as a tissue sample. biopsy. serum. plasma. saliva. urine. or stool are available from. e.g.. Invitrogen (Camarillo. CA). Santa Cruz hnology. Inc. (Santa Cruz. CA). and/or Abcam Inc.

(Cambridge. MA). 4. 5100 ns The determination ofthe presence or level of at least one 8100 n in a sample is also useful in the present invention. As used herein, the term “Sl00 protein” includes any member ofa family of low lar mass acidic proteins terized by ccll-type-spceific expression and the presence of2 EF-hand calcium-binding s. There are at least 21 different types ofSlOO proteins in humans. The name is derived from the fact that S l 00 proteins are 100% soluble in ammonium sulfate at neutral pH. Most Sl00 proteins are homodimcric. consisting of two identical ptides held together by non-covalent bonds.

Although S [00 proteins are structurally similar to ulin, they differ in that they are cell- specific, expressed in particular cells at different levels depending on environmental factors.

S~l00 proteins are normally present in cells derived from the neural crest (cg, Schwann cells, melanoeytes. glial cells), chondrocytes, adipoeytes, myoepithelial cells, macrophages.

Langerhans cells, dcndritic cells, and keratinocytes. SlOO proteins have been implicated in a variety ofintracellular and extracellular functions such as the regulation of protein orylation, transcription factors. Caz' homeostasis, the dynamics of eytoskeleton constituents, enzyme activities, cell growth and differentiation, and the inflammatow response.

Calgranulin is an 8100 protein that is expressed in multiple cell types, including renal epithelial cells and neutrophils, and are abundant in infiltrating monocytes and granulocytes under conditions of chronic inflammation Examples of calgranulins include. t limitation, calgranulin A (also known as SIOOA8 or , calgranulin B (also known as SlOOA9 or MRP- l4), and calgranulin C (also known as Z).

In eeltain instances, the presence or level ofa particular SIOO protein is detected at the level of mRNA expression with an assay such as, for example, a ization assay or an amplification-based assay. In certain other instances, the presence or level of a particular SIOO protein is detected at the level ofprotein expression using, for e. an immunoassay (8.0., ELISA) or an immunohistochemieal assay. Suitable ELISA kits for detetmining the presence or level ofan SIOO protein such as nulin A (SlOOAtx’), nulin B Q), or nulin C (SIOOAIZ) in a serum. plasma, or urine sample are available from. e.g.. Peninsula Laboratories Inc. (San Carlos. CA) and Hycult biotechnology b.v. (Uden. The Netherlands).

Calprotectin, the complex ofSlOOA8 and SIOOA9. is a calcium- and zine-binding protein in the cytosol of neutrophils, monocytcs, and keratinoeytes. Calprotectin is a major protein in neutrophilic granulocytes and macrophages and accounts for as much as 60% of the total protein in the eytosol fraction in these cells. It is therefore a sun‘ogate marker of neutrophil turnover. Its concentration in stool con‘elates with the intensity ofneutrophil infiltration of the intestinal mucosa and with the severity of inflammation. In some instances, tcetin can be measured with an ELISA using small (50-100 mg) fecal s (see. e.g., Johne et ul., Scam/J GustmememL, 36291-296 (200I )).

. Other Inflammatory s The ination ofthe presence or level oflactoferrin in a sample is also useful in the present invention. In ceitain ces, the presence or level oflactofen'in is detected at the level omeNA expression with an assay such as. for example. a ization assay or an amplification-based assay. In certain other instances, the presence or level of lactofcrrin is detected at the level of protein expression using. for example. an immunoassay (cg, ELISA) or an immunohistoehemical assay. A lactoferrin ELISA kit available from Calbiochem (San Diego. CA) can be used to detect human laetoferrin in a plasma. urine, bronchoalveolar lavage, or cerebrospinal fluid sample. Similarly. an ELISA kit available from US. Biological (Swampseott. MA) can be used to determine the level oflaetofen'in in a plasma sample. US.

Patent Publication No. 20040137536 describes an ELISA assay for determining the presence ofclcvatcd lactoferrin levels in a stool sample. Likewise. US Patent Publication No. 20040033537 describes an ELISA assay for determining the concentration of endogenous lactofcrrin in a stool. mucus. or bile sample. In some embodiments, then presence or level of anti—Iactoferrin antibodies can be detected in a sample using. e.g., Iaetofeirin protein or a fragment thereof.

The determination ofthe presence or level of one or more pyruvate kinase es such as MI-PK and M2-PK in a sample is also useful in the present invention. In certain instances. the presence or level ofMI-PK and/or MZ-PK is detected at the level of mRNA expression with an assay such as. for e. a hybridization assay or an amplification- based assay. In certain other instances. the presence or level of M 1 -PK and/or M2-PK is detected at the level ofprotein expression using, for example. an immunoassay (c.g., ELISA) or an immunohistoehemical assay. Pyruvate kinase isozymes M I/MZ are also known as pyruvate kinase muscle isozyme (PKM). pyruvate kinase type K. cytosolie thyroid hormone- binding protein (CTHBP). thyroid hormone-binding protein I (THBPI ), or opal-interacting protein 3 (OIP3).

In further ments. the determination ofthe presence or level of one or more growth factors in a sample is also useful in the t invention. Non-limiting examples of growth s e transforming growth factors (TGF ) such as TGF-a. TGF-B. 2.

TOE-[33. etc, which are described in detail below. 6. Exemplary Set of Inflammatory Markers In ular embodiments. at least one or a plurality (cg, two. three. four. five. six. seven. or all eight, such as. 8.53., a panel or an array) ofthe following inflammatory markers can be ed (cg, alone or in combination with biomarkers from other categories) to aid or assist in predicting disease course. and/or to improve the cy ofselecting therapy. zing therapy. reducing toxicity. and/or monitoring the cy oftherapeutic treatment to anti—TNF drug therapy: (I ) GM~CSF; (2) lFN-y; (3) lL-IB: (4) lL—2; (5) lL-6; (6) lL—X; (7) TNF-a; and (8) sTNF RII.

C. Anti-Inflammatory Markers I0211| In certain embodiments. a y of anti-inflammatory markers are particularly useful in the methods of the t invention for personalized therapeutic management by selecting therapy. optimizing therapy. reducing toxicity. and/or monitoring the efficacy of therapeutic treatment with one or more therapeutic agents such as biologics (cg, anti—TNF drugs). In particular embodiments, the methods described herein utilize the determination of a disease activity profile (DAP) based upon one or more (a plurality of) nflammatory markers (e.g.. alone or in combination with biomarkcrs from other categories) to aid or assist in predicting disease course. selecting an appropriate anti-TNF drug therapy. optimizing anti- TNF drug therapy, reducing toxicity associated with anti—TNF drug therapy, and/or monitoring the efficacy oftherapeutic treatment with an anti-TNF drug.

Non—limiting examples -inflammatory markers include IL-l2p70 and lL-IO.

In preferred embodiments. the presence and/or concentration levels of both lL-l2p70 and IL- l0 are determined.

In certain instances. the presence or level ofa particular anti-inflammatory marker is detected at the level of mRNA expression with an assay such as. for example. a hybridization assay or an amplification-based assay. In certain other ces, the presence or level of a particular anti-inflammatory marker is detected at the level of protein sion using. for e. an immunoassay (cg. ELISA) or an immunohistochemieal assay.

The human lL-l2p70 polypeptide is a heterodimer made up of two subunits of IL- 12 proteins: one is 40kDa (IL-121340) and one is 35kDa (lL-l2p35). Suitable ELISA kits for determining the presence or level of lL-12p70 in a serum. plasma. saliva. or urine sample are available from. e.g., Gen-Probe Diaclonc SAS e). Abazyme (Necdham. MA). BD Biosciences Pharmingen (San Diego. CA). Cell Sciences (Canton. MA). eBioscience (San Diego. CA). lnvitrogcn (Camarillo. CA). R&D s. Inc. apolis. MN). and Thcmio Scientific Pierce Protein Research Products (Rockford. IL).

The human lL-lO polypeptide is an anti—inflammatoxy cytokine that is also known as human cytokine synthesis inhibitory factor (CSIF). Suitable ELISA kits for determining the presence or level oflL-l2p70 in a senim. plasma, saliva. or urine sample are available from. cg. Antigenix America Inc. (Huntington Station, NY). BD Bioscienccs Pharmingen (San Diego. CA), Cell Sciences (Canton. MA). ienee (San Diego. CA), Gen-Probe Diaelone SAS (France). lnvitrogen (Camarillo. CA). R&D Systems. lnc. (Minneapolis. MN), and Thcnno ific Pierce Protein ch Products (Rockford. IL).

D. Serology (Immune Markers) The ination ofserological or immune markers such as autoantibodics in a sample (cg, serum sample) is also useful in the present invention. Antibodies against anti— inf‘lammatory molecules such as lL-lO. TGF-B. and others might suppress the body‘s ability to control inflammation and the presence or level of‘these antibodies in the patient tes the use of powerful immunosuppressivc medications such as anti-TNF drugs. Mucosal healing might result in a decrease in the antibody titre of dies to bacterial antigens such as. eg. OmpC, tlagcllins (cBir-l. Fla-A, Fla-X, era), 12. and others , ASCA. eta).

As such. in n aspects. the methods bed herein utilize the determination ofa disease activity profile (DAP) based upon one or more (a plurality of) serological or immune markers (fig... alone or in combination with kers from other categories) to aid or assist in predicting e course. selecting an appropriate anti-TNF drug therapy. zing anti-TNF drug therapy. reducing toxicity associated with anti-TNF drug therapy. and/or monitoring the efficacy oftherapeutic treatment with an anti-TNF drug.

Non-limiting examples ofserological immune markers suitable for use in the present invention e anti-neutrophil antibodies, anti—Succhummyces cereirisiae antibodies. and/or other icrobial antibodies.

Anti-Neutrophil Antibodies The determination ofANCA levels and/or the presence or absence of pANCA in a sample is useful in the methods ot‘the present invention. As used herein. the term “anti- neutrophil cytoplasmic antibody“ or “ANCA” includes antibodies directed to cytoplasmic and/or nuclear components of neutrophils. ANCA activity can be divided into several broad categories based upon the ANCA staining pattern in neutrophils: (l) asmic neutrophil staining without pcrinuclear highlighting (CANCA); (2) pcrinuclear staining around the outside edge of the nucleus (pANCA); (3) pcrinuclear staining around the inside edge ofthe nucleus ; and (4) diffuse staining with speckling across the entire neutrophil (SA PPA). In certain instances. pANCA staining is sensitive to DNase treatment. The term ANCA encompasses all varieties of anti-neutrophil reactivity, including. but not limited to.

CANCA. pANCA. NSNA. and SAPPA. Similarly, the temi ANCA encompasses all globulin isotypes including. without limitation. immunoglobulin A and G.

ANCA levels in a sample from an individual can be determined, for example. using an immunoassay such as an enzyme-linked immunosorbent assay (ELISA) with alcohol-fixed neutrophils. The presence or absence ofa particular category of ANCA such as pANCA can be determined. for example. using an immunohistochemical assay such as an ct fluorescent antibody (lFA) assay. Preferably, the presence or absence of pANCA in a sample is determined using an fiuoreseence assay with DNase-treated. fixed phils. In addition to fixed neutrophils. antigens specific for ANCA that are le for determining ANCA levels include. without limitation. unpurified or partially purified phil extracts: d proteins. protein fragments, or synthetic peptides such as histone HI or ANCA— ve fragments thereof (see. e.g.. US. Patent No. 835): histone e antigens, porin antigens. Bacteroides antigens. or ANCA-reactive fragments thereof(sce, tag, US.

Patent No. 6.033.864); secretory vesicle antigens or ANCA-reaetive fragments thereof (see, eg, US. Patent Application No. 08/804,106); and anti-ANCA idiotypic antibodies. One skilled in the art will appreciate that the use of onal antigens specific for ANCA is within the scope ofthe present invention. 2. Anti-Saccharomyces cerevisiae Antibodies [OZZII The determination of ASCA (c.g.. ASCA-lgA and/or ASCA-lgG) levels in a sample is useful in the present invention. As used herein. the term Sacc:hamniyces cereiris-iae immunoglobulin A“ or “ASCA-lgA” includes dies ofthe immunoglobulin A isotype that react specifically with S. cerevisiae. Similarly. the term “antiSac-Charonches cerevisiue immunoglobulin G” or “ASCA-lgG” includes dies ofthe immunoglobulin G isotype that react specifically with S. c'ercvisiae.

The determination of whether a sample is positive for ASCA-lgA or ASCA-lgG is made using an antigen specific for ASCA. Such an antigen can be any antigen or mixture of antigens that is bound specifically by ASCA-lgA and/or ASCA-lgG. Although ASCA antibodies were initially characterized by their ability to bind S. cerevisiae, those of skill in the art will understand that an antigen that is bound specifically by ASCA can be obtained from S. cerevixz‘ac or from a variety of other sources so long as the antigen is capable of g specifically to ASCA antibodies. Accordingly. exemplary sources of an antigen c for ASCA, which can be used to determine the levels of ASCA-lgA and/or ASCA- IgG in a sample. include. without limitation. whole killed yeast cells such as Succhal‘mn)’(Jes or a cells; yeast cell wall mannan such as phosphopeptidomannan (PPM): oligosachharides such as oligomannosidcs; ncoglycolipids; anti-ASCA pic antibodies; and the like. Different species and strains of yeast. such as S. c-ercw'siae strain Sul. 8112. CBS 1315, or BM 156, or Candida ans strain VW32, are suitable for use as an antigen specific for gA and/or ASCA-lgG. Purified and synthetic antigens specific for ASCA are also suitable for use in determining the levels of ASCA-lgA and/or ASCA-lgG in a sample. Examples of purified antigens include, without limitation, purified oligosaccharidc antigens such as oligomannosides. Examples of synthetic ns include, without limitation, synthetic oligomannosides such as those described in US. Patent Publication No. 20030105060. e.g., D-Man [3(1-2) D-Man ) D-Man [3(1-2) D-Man-OR, D-Man (1(1-2) D-Man a( 1-2) D-Man (1(1-2) OR, and D-Man (1(1-3) D-Man (1(1-2) D-Man ) D- Man-OR, wherein R is a hydrogen atom, a Ct to C20 alkyl, or an optionally labeled connector group.

Preparations ofyeast cell wall mannans, e.g., PPM, can be used in determining the levels ofASC‘A-lgA and/or ASCA-lgG in a sample. Such water-soluble surface antigens can be prepared by any appropriate extraction technique known in the art, including, for example, by autoclaving, or can be obtained commercially (see, c.g.. Lindberg et ul.. Gut, 33:909-913 (1992)). The acid-stable fraction of PPM is also useful in the present invention (Sendid er al., C/in. Diag. Lab. lmmzmul., 3:219-226 (1996)). An exemplary PPM that is useful in determining ASCA levels in a sample is derived from S. uvarum strain ATCC #38926. d aceharide antigens such as oligomannosides can also be useful in determining the levels of ASCA-lgA and/or ASCA-lgG in a sample. The purified oligomannoside antigens are preferably converted into neoglycolipids as described in, for example, Faille el al., Eur. J. i1v'li'cml)i()/. ln/éct. 01's., 1 11438-446 (1992). One skilled in the art tands that the reactivity ofsuch an oligomannoside antigen with ASC‘A can be optimized by g the mannosyl chain length (Frosh er al., Prov Natl. Acad. Sci. USA, 82:1 194-1 198 (1985)); the anomeric configuration (Fukazawa at al., In “Immunology of Fungal Disease.” E. Kurstak (ed), Marcel Dekker Inc, New York, pp. 37-62 (1989); Nishikawa er a/., zl-Ii(:1'()[>i0/. liiiniunnl., 34:825-840 (1990); Poulain e1 (1]., Eur. J. C/i'n. ln'o/q 52 (1993); Shibata er a/., Arc/7. Biochem. Biophys, 243:338—348 (1985); Trincl at al.. . [III/11101., 603845-3851 (1992)); or the position ofthe linkage (Kikuchi er al., P/ama. 5-535 (1993)).

Suitable oligomannosides for use in the s ofthe present invention include, without limitation, an oligomannoside having the mannotetraose Man(l—3) Man(l-Z) Man( 1 - 2) Man. Such an oligomannoside can be purified from PPM as described in, cg, Faille 9111].. supra. An exemplary neoglycolipid ic for ASCA can be constructed by ing the oligomannosidc from its respective PPM and subsequently ng the released oligomannoside to 4—hexadeeylaniline or the like. 3. Anti—Microbial Antibodies The determination of anti-OmpC antibody levels in a sample is also useful in the present invention. As used herein, the term outer membrane protein C antibody“ or OmpC antibody” includes antibodies directed to a bacterial outer membrane porin as described in. e.g., PCT Patent Publication No. WO 01/8936]. The term “outer membrane protein C‘” or “OmpC” refers to a bacterial porin that is immunoreactive with an anti-OmpC antibody.

The level of anti-OmpC antibody present in a sample from an individual can be determined using an OmpC‘ protein or a fragment thereof such as an immunoreaetive fragment f. le OmpC antigens useful in determining anti-OmpC antibody levels in a sample include. without limitation, an OmpC‘ protein. an OmpC‘ ptide having substantially the same amino acid sequence as the OmpC protein. or a fragment f such as an immunoreactive nt thereof. As used herein. an OmpC polypeptide generally describes polypeptides having an amino acid sequence with greater than about 50% identity. preferably greater than about 60% identity. more preferably greater than about 70% identity. still more preferably greater than about 80%. 85%. 90%, 95%, 96%. 97%, 98%, or 99% amino acid ce identity with an OmpC protein. with the amino acid identity determined using a sequence ent program such as CLUSTALW. Such antigens can be prepared. for example. by purification from enterie bacteria such as E. cu/i. by inant expression ofa nucleic acid such as Genbank Accession No. K00541. by synthetic means such as solution or solid phase peptide synthesis, or by using phage display.

The determination of anti-[2 antibody levels in a sample is also useful in the t invention. As used herein. the term “anti-12 antibody” includes antibodies directed to a microbial antigen sharing homology to bacterial transcriptional tors as described in. c.g., US. Patent No. 6,309,643. The term “[2” refers to a microbial antigen that is immunoreactive with an anti-[2 antibody. The microbial [2 protein is a polypeptide of 100 amino acids sharing some similarity weak homology with the predicted protein 4 from C. pastel/Hamlin. Rv3557c from ii’I'lr‘('()/7U(‘Icl'l'lllll rulmzfu/nsix. and a transcriptional regulator from Aquifer «colic-us. The nucleic acid and protein sequences for the l2 protein are described in, cg, US. Patent No. 6,309,643.

The level of anti-12 antibody present in a sample from an individual can be ined using an 12 protein or a fragment thereof such as an immunoreactive nt thereof. Suitable l2 ns useful in determining anti—l2 antibody levels in a sample include, without limitation, an [2 protein, an l2 ptide having substantially the same amino acid sequence as the 12 protein, or a fragment thereof such as an immunoreaetive fragment thereof. Such 12 polypeptides exhibit greater sequence similarity to the I] protein than to the C. pastel/Human n 4 and include isotype variants and homologs f. As used herein, an [2 polypeptide generally describes polypeptides having an amino acid sequence with greater than about 50% identity, preferably greater than about 60% identity, more preferably greater than about 70% ty, still more preferably greater than about 80%, 85%, 90%, 95%, 96%, 97%, 98%, or 99% amino acid sequence identity with a naturally-occurring 12 protein, with the amino acid identity determined using a ce alignment program such as CL USTALW. Such l2 antigens can be prepared, for example, by purification from microbes, by recombinant expression ofa c acid encoding an [2 antigen, by synthetic means such as solution or solid phase peptide synthesis, or by using phage display.

The determination of anti-flagellin antibody levels in a sample is also useful in the present invention. As used herein, the temt “anti-flagellin dy" includes antibodies directed to a n component of bacterial flagella as described in, e.g., PCT Patent Publication No. W0 03/053220 and US. Patent Publication No. 2004004393 l. The term “flagellin” refers to a bacterial flagellum protein that is reaetive with an agellin antibody. Microbial flagellins are proteins found in bacterial um that arrange themselves in a hollow cylinder to form the filament. |023l| The level of anti-flagellin antibody present in a sample from an individual can be determined using a flagellin protein or a fragment thereof such as an immunoreaetive fragment thereof. Suitable flagellin antigens useful in determining anti-flagellin antibody levels in a sample include, t limitation, a flagellin protein such as Cbir-l flagellin, flagellin X. flagellin A, flagellin B. fragments thereof, and ations thereof, a flagellin polypeptide having substantially the same amino acid sequence as the flagellin protein, or a fragment thereof such as an immunoreaetive fragment thereof. As used herein. a lin polypeptide generally describes polypeptides having an amino acid sequence with greater than about 50% identity, preferably greater than about 60% identity, more preferably greater than about 70% identity, still more preferably greater than about 80%. 85%. 90%. 95%. 96%. 97%. 98%. or 99% amino acid ce identity with a naturally-occun'ing fiagellin protein, with the amino acid identity determined using a sequence alignment m such as CLUSTALW. Such flagellin antigens can be prepared. eg. by purification from bacterium such as /mctcr Bill‘s. Helico/mcrcr music/ac. Helicn/mcrer pylori. Burrrivibrir) jiln-is'ti/i-‘ens'. and bacterium found in the cecum. by recombinant expression of a nucleic acid encoding a flagellin antigen, by tic means such as solution or solid phase peptide synthesis. or by using phage display.

E. Cell Surface Receptors The determination of cell sulfaee receptors in a sample is also useful in the t invention. The half-life of anti-TNF drugs such as Remieade and Humira is significantly decreased in ts with a high level of mation. CD64, the high-affinity receptor for immunoglobulin (lg) GI and lgG3. is predominantly sed by mononuclear ytes.

Resting polymorphonuclear (PMN) cells scarcely express CD64. but the sion ofthis marker is upregulated by interferon and granulocyte-colony-stimulating factor acting on myeloid precursors in the bone man'ow. Crosslinking ofCD64 with lgG complexes exerts a number ofccllular responses. ing the internalization of immune complexes by endoeytosis. phagocytosis of opsonized particles, degranulation‘ activation ofthe oxidative burst. and the release of cytokines.

A; such. in certain aspects, the methods described herein utilize the determination ofa disease activity profile (DAP) based upon one or more (a plurality ofl cell surface receptors such as CD64 (cg, alone or in ation with biomarkers from other categories) to aid or assist in predicting disease course, selecting an appropriate anti-TNF drug therapy, optimizing anti-TNF drug therapy‘ reducing toxicity associated with anti-TNF drug therapy, and/or monitoring the efficacy ofthcrapeutic treatment with an anti-TNF drug.

F. Signaling Pathways l0234| The determination of signaling pathways in a sample is also useful in the present invention. Polymorphonuclear (PMN) cell activation, followed by infltration into the inal mucosa (synovium for RA) and migration across the crypt epithelium is regarded as a key feature of lBD. It has been estimated by fecal indium-l l l-labcled leukocyte excretion that migration of PMN cells from the circulation to the diseased section ofthe intestine is increased by lO-fold or more in lBD ts. Thus. measuring activation of PMN cells from blood or tissue inflammation by measuring ing pathways using an assay such as the gollaborative Enzyme Enhanced Reactive lmmunoAssay (CEER) described herein is an ideal way to understand inflammatmy disease.

As such. in certain aspects, the s bed herein utilize the determination ofa disease activity profile (DAP) based upon one or more (a plurality ofl signal transduction molecules in one or more signaling pathways (e.g.. alone or in combination with biomarkers from other categories) to aid or assist in predicting disease course. selecting an appropriate anti-TNF drug y, optimizing NF drug therapy. ng toxicity associated with NF drug therapy. and/or monitoring the efficacy oftherapeutic treatment with an anti— TNF drug. In preferred embodiments, the total (e.g., expression) level and/or activation (cg, phosphorylation) level of one or more signal transduction molecules in one or more ing pathways is measured.

The term “signal transduction molecule” or “signal transducer" includes proteins and other molecules that carry out the process by which a cell converts an extracellular signal or us into a response. typically involving ordered sequences ofbioehemieal reactions inside the cell. Examples ofsignal transduction molecules include. but are not limited to, receptor tyrosine kinascs such as EGFR (rag, EGFR/HERl/ErbBl, HERZ/Neu/ErbBZ.

HER3/ErbB3, HER4/ErbB4’), VEGFRl/FLTI. VEGFRB/FLKl/KDR, VEGFR3/FLT4.

FLT3/FLK2, PDGFR (eg, PDGFRA, PDGFRB). e-KlT/SCFR. INSR (insulin receptor). lGF-lR, lGF-llR‘ [RR (insulin receptor-related receptor). CSF-lR, FGFR 1-4. HGFR 1-2, CCK4, TRK A-C. c-MET, RON. EPHA 1-8, EPHB 1-6. AXL, MER. TYRO3. TIE 1-2.

TEK. RYK, DDR l-Z‘ RET. c—ROS, V-cadherin. LTK (leukocyte tyrosine kinase), ALK (anaplastic lymphoma kinase), ROR 1-2, MUSK, AATYK 1-3, and RTK 106; truncated forms of or tyrosine kinases such as truncated HERZ receptors with missing amino- terminal extracellular domains (cg, B2 (p95m). pl IO, p95c, p95n, era), truncated cMET receptors with missing amino—temtinal extracellular domains, and truncated HER3 ors with g amino-terminal ellular domains; receptor tyrosine kinase dimers (cg, p95HER2/HER3; p95HER2/HER2; truncated HER3 or with HER]. HERZ, HER3, or HER4; HERZ/HERZ; HER3/HER3: ER3; HERl/HERZ: HERl/HER3; HERZ/HER4; l-lER3/HER4; etc. ); non-receptor tyrosine s such as BCR-ABL. Src, Frk, Btk, Csk, Abl. Zap70. Fes/Fps. Fak, Jak, Aek‘ and LIMK; tyrosine kinase signaling cascade components such as AKT (e.g.. AKT] , AKTZ, AKT3), MEK (MAPZKI), ERK2 (MAPKl ), ERKl (MAPK3).P13K(c.g., PIKSCA (pl 10). PIK3R1 (p85)). PDKI. PDKZ. phosphatase and tensin homolog (PTEN), SGK3, 4E-BP], P7OS6K (e.g., p70 86 kinase splice variant alpha l). protein tyrosine phosphatases (e.g., PTPlB, PTPN13‘ BDPl. urea). RAF. PLA2.

MEKK. JNKK, JNK, p38. Shc (p66), Ras (cg, K—Ras‘ N-Ras, H—Ras). Rho. Racl. C‘dc42.

PLC, PKC. p53. eyelin Dl, STATl, STAT3, atidylinositol 4,5-bisphosphate (PIPZ), atidylinositol 3.4.5-trisphosphate (PlP3). mTOR, BAD. p2l‘ p27. ROCK. lP3. TSP~l.

NOS. GSK-3B, RSK 1-3~ JNK. c—Jun, Rb, CREB. Ki67, paxillin, NF-kB, and [KK; nuclear hormone receptors such as estrogen receptor (ER). terone receptor (PR). androgen receptor. glueocortieoid receptor. mineraloconicoid receptor, vitamin A receptor, vitamin D receptor, retinoid receptor. thyroid hormone receptor. and orphan receptors; r receptor coactivators and repressors such as amplified in breast cancer-l (AlBl ) and nuclear receptor corepressor l (NCOR'), respectively; and ations thereof.

The term "activation state” refers to whether a particular signal transduction molecule is activated. rly. the term “activation level” refers to what extent a panicular signal transduction molecule is activated. The activation state typically corresponds to the phosphorylation. ubiquitination, and/or complexation status ofone or more signal transduction molecules. miting examples of activation states (listed in parentheses) include: HERl/EGFR (EGFvall. phosphorylated (p-) EGFR‘ he, tinated (u-) EGFR, p-EGFvall): ErbBZ (p-ErbBB, 2 (truncated ErbBZ). D‘p95HER2fi ErbBZShc. ErbBZ:Pl3K, ErbBZ:EGFR. ErbBZ:ErbB3. ErbBlerbB4); ErbB3 (p-ErbB3, truncated ErbB3, ErbBB:Pl3K. p-ErbB3:Pl3K. ErbB3IShc): ErbB4 (p-ErbB4. ErbB4:Shc); e- MET (p-e-M ET, tmncated e-MET, c-MetzHGF complex); AKTl (p-AKTl ); AKT2 (p- AKTZ); AKT3 (p-AKT3); PTEN (p-PTEN); P7086K (p-P7086K); MEK (p-MEK); ERKl (p-ERKI); ERKZ Z): PDKl (p-PDKI); PDK2 (p-PDKZ); SGK3 (p-SGK3): 4E-BP1 (p-4E-BPl ); P|K3Rl (p-PIK3R1); c-KIT (p-c-KlT); ER (p-ER); lGF-lR (p-lGF-lR‘ lGF- lelRS. [RS:PI3K, p-lRS‘ lGF-l RzPl3K); INSR (p-INSR); FLT3 (p—FLT3); HGFRI (p- HGFRl ); HGFRZ (p-HGFRZ); RET (p-RET); PDGFRA (p-PDGFRA); PDGFRB (p- PDGFRB); VEGFRI (p—VEGFR]. VEGFR12PLCy, VEGFRlerc); VEGFRZ (p-VEGFRZ.

VEGFR2:PLCy. VEGFRZISrc, VEGFR2zheparin sulphate, VEGFRZNE-cadhcrin); VEGFR3(p-VEGFR3)LFGFR1 (p-FGFRl ); FGFR2 (p-FGFR2)‘. FGFR3 (p—FGFR3): FGFR4 (p-FGFR4); TlEl (p-TlEl); TlEZ (p-TlE2); EPHA (p-EPHA); EPHB B); GSK-BB (p-GSK-BB); NFckB (p-NF-kB, NF—kB-[kB alpha x and others). ”(8 (p-lkB, p-P65zlkB); lKK (phospho IKK); BAD (p-BAD, BAD: 143); mTOR (p—mTOR‘); Rsk-l (p- Rsk-l ); Jnk (p-Jnk); P38 (p-P3X); STAT] (p—STATI ); STAT3 T3); FAK (p-FAK); RB (p-RB); Ki67; p53 (p-p53); CREB (p—CREB); c-Jun un); e-Sre (p-c-Src); paxillin illin); GRBZ (p-GRBZ). She (p—She), Ras (p-Ras), GABl (p-GABI), SHP2 (p-SHPZ), GRBZ (p-GRBE), CRKL KL). PLCy (p-PLCy). PKC (e.g., p-PKCa. p-PKCB, p— PKCo), adducin (p-adduein). RB] (p—RBI ). and PYKZ (p—PYKZ).

The following tables provide additional examples of signal transduction molecules for which total levels and/or activation (rag. phosphorylation) levels can be determined in a sample (6.3;. alone or in combination with biomarkers From other categories) to aid or assist in predicting disease , selecting an appropriate anti—TNF drug therapy. optimizing anti- TNF drug therapy. reducing toxicity associated with anti-TNF drug therapy, or monitoring the y of therapeutic treatment with an anti-TNF drug. vat-still Total VEGFRZ Phospho Y951, 1212 Erk Total Erk Phorépho TZOIIYIDQ Akt Total Akt'Phospho T308, 5473 ME“ Tmat MEX Phospho $2 17 f22 1 MEX Total MEK Phospho $2 17122 1 P705“ Total P7OS6K Phospho 219} PTEN Total VEGFR1 {7) VEGFRi Phospho 1\'\'£1< wits? sizes swarm-no CRXL Total CRKL n V207 SRC rota! SRC Phospho Y :1 16, 527 FAK Total FAK Phospho Y397 828 Total BCR Phospho PBK activated 1113 K tomptexad P85 \‘688 4E 3P1 488M 331105th T70, 1’37; 746 PRASAO {HMS-m phospho T246 TtE- 2 Phospho vsyztsnlsi Mk 2 Total MK 2 Phospbo vaamnms STATS Tow! STAT S Phaspho “Sn/'69:? STATBTotat STAT 3 Phaspho Y705 56F?! total FGFR1 Phospho Y 55!, 166 $65132 total F6??? 2 P110593": V653 iGFRBtatal HEP} 3 Phospha FGfiRdtatJl FGFR -$ o Ax! low} Ax! Phospho 02 BAD total BAD ghaspho [$112) {$136) RSK taut RSK 9hospho g 1399/5353; PDK total PDKl Phospho {5241] MK 1 and 3 tom! MK 1 and 3 Pbospha TSCZ {oral TSC 2 phospho $666, $939 SGRPTGN} 56R? phosplaa 5235/1136 The Collaborative Enzyme Enhanced Reactive lmmunoAssay (CEER), also known as the Collaborative Proximity Immunoassay (COPIA). is described in the ing patent documents which are herein incorporated by reference in their entirety for all purposes: PCT Publication No. W0 20087036802; PCT Publication No. W0 2009/012140: PCT Publication No. W0 2009/108637; PCT ation No. ; PCT ation No. W0 ] 1/008990; and PCT ation No. PCT/USZOIO/053386, filed October 20, 2010.

G. Elimination Rate Constant In n embodiments, a marker for the disease activity profile (DAP) is kel. or the elimination rate constant of an antibody such as an anti-TNF antibody (e.g.. infliximab). The determination of an elimination rate constant such as kel is particularly useful in the methods ofthe invention for personalized therapeutic management by selecting therapy. Optimizing y. reducing toxicity. and/or monitoring the efficacy oftherapeutic ent with one or more therapeutic agents such as biologics (cg, anti-TNF dmgs).

In certain instances. a differential equation can be used to model drug elimination from the patient. ln certain instances, a mpartment PK model can be used. in this ce. the equation for the drug in the central companment following intravenous bolus administration is: kt'l .Xt A- 1 2 . X1 Ali . X 2 The kel - Xl term describes elimination of the drug from the central tment. while the kl2 - XI and k2l - X2 terms describe the distribution of drug between the central and peripheral compartments.

H. Genetic Markers The determination ofthe presence or e ofallelie variants (e.g,, SNPs) in one or more c markers in a sample (6.5;, alone or in ation with biomarkers from other categories) is also useful in the methods ofthe present invention to aid or assist in predicting disease course. selecting an appropriate anti-TNF drug therapy, optimizing anti- TNF drug therapy. reducing toxicity ated with NF drug therapy, or monitoring the efficacy ofthcrapeutie treatment with an anti-TNF drug.

Non—limiting examples of genetic markers include. but are not limited to, any oftlie inflammatory pathway genes and corresponding SN Ps that can be genotyped as set forth in Table 1 (eg, a NODZ/CARDIS gene, an lLlZ/IL23 pathway gene‘ are). Preferably, the presence or absence of at least one allelic variant. e.g., a single nucleotide polymmphism (SN P), in the NODZ/CARDIS gene and/or one or more genes in the lLl2/IL23 pathway is ined. Sec, e.g.. Barrett at al., Nat. Genet, 40:955-62 (2008) and Wang et (2]., Amer. J.

Hum. GeneL. 84:399-405 (2009).

Gene- SNP NOD: (13.702355 — SNPS- mlfiz‘ffil‘vS-H ISZD'O'SS-‘li ATG 1 ISLE {TSOEEAQ ILZSR {FL-431(3) 3‘31 13(89036 DLGS 132 165‘11-17’ P52066847 ssilfiéfiSfi4 {53329309 PTGERJ LRRKE. 33.11%" A) l I T‘ ‘1'? 3 BTN'LZ. SLC‘E *A3. TEA-DRE}.

HLA-DQAI P153 1 5:? . ("(17 SLCIZ.‘ ‘3.

ILIIRB.‘ I Maw-’3 15JH;-.'.C-_,., 333.48%- l'SGéC; i 5'35 (5)55 “7957334 111331 51133. 512 T ccrzs 31A K14 15225709} 1L13 3"31321-13‘JS JSWéS-S {97697855 IRGM 3&1336‘; E 89 11:3:th r‘xLFQFSS-‘U HRGNf R] 0'00] 3 5 1-! mix-v) 1 f-rg- 1"»458 75%: xezzvaainI"; stlSfiETD 331i5$43$3 TNFRSFéB ZNFRM ZN}: 365 CA 10: 3‘0 LRRKEA-‘iflf’ 1 Q IL-37 13313494339 1SLR: TLR. ‘1}? ‘ ‘[LENG'_! 1%49S6T9‘3 TLR‘Jr {T313913 1549367535} 11PM {356:}N) m4g;r37333 TLRQ TLR‘) !’ ' " .‘ ...' IC (BS-LC": ELI—$533.3 1X l)‘\'\1,:———\.-~‘ 1&1843643 2 1‘3“: 1 1'") "5';~-. -'.—.‘t._ 18696332966 IGNOSEE IFSCLELM IFNGELICG IL26 g—‘LRPC‘D 12.16.11. 19 K. H311. i9 ILZSR H.231).

I .ZSR ILZSR BIA-DRE x M13131 EviEPI PifSli} PCS 1 {3 1‘96 @3668;- RNFI S6 I'SSSOESSUS.\ DLDLAMB‘; CAPNLCLKIE‘IA 64 1i} ILLS-P.

IL23R 3 1285134!) ELI 23-1340 H. 1 33"}340 EL 1 ‘lfi' STATS JAR.“ NK. m U. l SRAP L “9‘,v \' .'_\'L ‘5.-.-”“9398~ TNFRSFCSB TNFRSFSB INFRSFdB PSMGI KB? I ya}. 5-373 77—1 ICOSLGI 137634.31 BTLNZ ATGS (I'ULZLREM (DEB-"ZDLS OE'QEDLS Additional SNPs useful in the present invention include. Lug 152188962. rs9286879, rsl l584383. 137746082, rsl456893, r5155l398, rsl7582416, r53764l47. rs1736l35. rs4807569, 57758080. and rs8098673. See, e.g., Ban'ett at al., Nat. Gena. -62 (2008). ln particular embodiments, the presence or absence of one or more mutations in one or more ofthe following genetic markers is determined: inflammatmy pathway genes‘ cg, the presence or absence of variant alleles (cg, SN Ps) in one or more inflammatory markers such as, e.g.. NOD2/C‘ARD15 (cg. SNP 8, SNP 12. and/or SNP 13 described in US Patent No. 7,592,437), ATGl6L1 (tag, the rs2241880 ) SNP described in Lakatos et ul..

Digesn've and Liver Disease, 40 (2008) 867-873). 1L23R (cg. the rsl 1209026 (R38 1 Q) SNP described in Lakatos er ul.), the human leukocyte antigen (HLA) genes and/or cytokine genes described in, cg. Gaschc el al. (Eur. J. Guslrncnrernlagv & Hepam/agv, (2003) 15:599— 606). and the DLGS and/or OCTN genes from the lBDS locus.

I. NOD2/CARD15 The determination ofthe presence or absence of allelic variants such as SNPs in the ARD15 gene is particularly useful in the present invention. As used herein. the term “NOD2/CAR015 variant” or “NOD2 variant" includes a nucleotide sequence of a NODZ gene containing one or more changes as compared to the ype NOD2 gene or an amino acid sequence ofa NOD2 polypeptide containing one or more s as compared to the wild-type NOD2 polypeptide sequence. NOD2, also known as CARDIS, has been localized to the lBDl locus on chromosome 16 and identified by onal-cloning (Hugot er (1]..

Nature. 41 1:599-603 (2001)) as well as a positional candidate gene strategy (Ogura at al., Nature. 411:603—606 (2001'); Hampc et a/., Lancet, 357: 1925-1928 (2001)). The lBDl locus has a high multipoint linkage score (MLS) for inflammatoxy bowel disease ('MLS=5.7 at marker D16S411 in l6q12). See. Lag. Cho ct a/H Iii/lanmz. Bowel Disn. 3:186-190 (1997); Akolkar er al.. Am. J. Gastroentern/.. 96:1 127-1 132 (2001 ); Ohmen e! (1].. Hum. Mol. Genet., :1679-1683 (1996); Parkes el al., Lancet, 34821588 (1996); Cavanaugh el al., Ann. Hum.

Conch, 62:291-8 (1998); Brant at u/.. Gastmenlel'olngjr, 1 6—1061 (1998): Curran e! (1]..

Gastmemel‘nlogv, l 15:1066—1071 (1998); Hampc er al.. Am. J. Hum. Genet. 64:808-816 ; and Annese et al.. Eur. J. Hum. Gena. 7:567-573 (1999).

The mRNA g) and polypeptide sequences ofhuman NOD2 are set fonh in. mg, Genbank ion Nos. NM_022162 and 445, tively. In addition, the complete sequence of human chromosome 16 clone RP] 1-327F22. which includes NOD?" is set forth in, cg, Genbank ion No. AC007728. Furthermore the sequence ofNODI-Z from other s can be found in the GenBank database.

The NOD2 protein ns amino—terminal e recruitment s (CA RDs), which can activate NF-kappa B (NF-kB), and several carboxy-terminal leucinc—rich rcpcat domains (Ogura et al., J. Biol. Che/21.. 12-4818 (2001)). NOD2 has structural homology with the apOptosis regulator Apaf-l/CED—4 and a class of plant disease ant gene ts (Ogura e1 (1]., supra). Similar to plant disease resistant gene ts. NOD2 has an amino—terminal effector domain, a nucleotide-binding domain and leucine rich s (LRRs). ype NOD2 activates nuclear factor NF-kappa B, making it responsive to bacterial lipopolysaccharidcs (LPS; Ogura et ul., supra; lnohara crul.. J. Biol. Chem. 276:255l-2554 (200l ). NOD2 can Function as an intercellular or for LPS, with the leucine rich repeats required for responsiveness.

Variations at three single nucleotide polymorphisms in the coding region ofNODZ have been previously described. These three SNPs, designated R702W (“SNP 8”), G908R (“SNP l2”), and 1007fs (“SNP 13”), are located in the carboxy-terminal region of the NOD2 gene (Hugot et ((1., supra). A further ption of SNP 8, SNP 12, and SNP 13, as well as additional SNPs in the NOD2 gene suitable for use in the invention, can be found in, c.g., US. Patent Nos. 6,835,815; 6,858,391; and 7,592,437; and US. Patent ation Nos. 20030190639, 20050054021, and 20070072180.

In some ments, a NOD2 variant is located in a coding region ofthe NOD2 locus, for e, within a region encoding several leucine-rich repeats in the carboxy- terminal portion ofthe NOD2 polypeptide. Such NOD2 variants located in the leucine-rich repeat region ofNODZ include, without limitation, R702W (“SNP 8“) and GQOXR (“SNP 12“). A NOD2 variant useful in the invention can also encode a NOD2 polypeptide with reduced ability to activate NF-kappa B as compared to NF-kappa B activation by a wild-type NODZ polypeptide. As a non-limiting example, the NOD2 variant 1007fs (“SNP 13”) s: in a truncated NOD2 polypeptide which has reduced ability to induce NF-kappa B in response to LPS stimulation (Ogura er al., Nature, 41 12603-606 (2001)).

A NOD2 variant useful in the invention can be. for example, R702W, G908R, or l007fs. R702W, G9OXR. and 1007fs are located within the coding region of NOD2. In one embodiment, a method ofthe invention is practiced with the R702W NOD2 variant. As used herein, the temi “R702W” includes a single nucleotide polymorphism within exon 4 ofthe NOD2 gene, which occurs within a triplet encoding amino acid 702 ofthe NOD2 protein.

The wild—type NOD2 allele contains a cytosine (c) residue at position 138.991 ofthc AC007728 sequence, which occurs within a triplet encoding an arginine at amino acid702.

The R702W NOD2 variant contains a thymine (t) residue at position 138,991 ot‘thc AC007728 sequence. resulting in an arginine (R) to tiyptophan (W) substitution at amino acid 702 ofthe NOD2 protein. Accordingly, this NOD2 t is denoted ” or “702W” and can also be denoted “R675W” based on the earlier numbering system of Hugot er (1]., supra. In addition. the R702W variant is also known as the "SNP 8” allele or a “2” allele at SNP X. The NCBI SNP ID number for R702W or SNP 8 is 132066844. The presence of the R702W NOD2 variant and other NOD2 variants can be conveniently detected, for example. by allelic discrimination assays or sequence analysis.

A method of the invention can also be practiced with the G9OXR NOD2 variant. As used herein, the term “G908R” includes a single nucleotide polymorphism within exon 8 of the NOD2 gene. which occurs within a triplet encoding amino acid 908 ofthe N002 protein.

Amino acid 908 is located within the leucinc rich repeat region ofthe NOD2 gene. The wild- type N002 allele contains a guanine (g) residue at position 128,377 of the AC007728 sequence. which occurs within a triplet encoding e at amino acid 908. The G908R NOD2 variant contains a cytosine (c) residue at position 128,377 ofthe AC007728 sequence. resulting in a glycine (G) to arginine (R) substitution at amino acid 908 ofthe NOD2 protein.

Accordingly. this NOD2 variant is d ” or “908R” and can also be denoted “(1881 R“ based on the earlier numbering system of Hugot et a/.. supra. In addition. the G908R variant is also known as the "SNP 12” allele or a “2” allele at SNP 12. The NCBI SNP ID number for G908R SNP 12 is rs2066845.

A method of the ion can also be practiced with the 1007fs NOD2 variant.

This variant is an ion ofa single nucleotide that results in a frame shift in the tenth leucinc-rich repeat ofthe NOD2 protein and is followed by a premature stop codon. The resulting truncation of the NOD2 protein appears to prevent activation ofNF-kappaB in response to bacterial lysaccharides (Ogura er al., . As used herein, the tcnn s” includes a single nucleotide polymmphism within exon I 1 of the NOD2 gene, which occurs in a triplet encoding amino acid 1007 ofthe NOD2 protein. The 1007fs variant contains a cytosine which has been added at position 121.139 ofthe 28 sequence. resulting in a frame shift mutation at amino acid 1007. Accordingly, this NOD2 t is denoted s” and can also be denoted “3020insC” or “980fs” based on the earlier numbering system of Hugot et (1].. supra. In addition. the 1007fs NOD2 variant is also known as the “SNP 13" allele or a “2” allele at SNP 13. The NCBl SNP ID number for 1007fs or SNP 13 is rs2066847. [02551 One skilled in the art recognizes that a particular NOD2 variant allele or other polymorphic allele can be conveniently defined. for example, in comparison to a Centre d‘Etude du Polymoiphismc Humain (CEPH) reference individual such as the individual designated 2 (Dib e! al.. Nature, 380: 1 52-154 (1996)), using commercially available reference DNA obtained. for example. from PE Biosystems (Foster City, CA). 1n on. specific information on SNPs can be obtained from the dbSNP ofthe National Center for Biotechnology 1nformation (NCBl). [02561 A NODZ variant can also be d in a non-coding region ofthe NOD22 locus.

Non-coding regions include, for example, intron sequences as well as 5‘ and 3’ untranslated sequences. A non-limiting example ofa NODZ variant allele located in a ding region ofthe NOD2 gene is the JWl variant. which is described in Sugimura et ul.. Am. J. Hum.

Genet, 72:509-518 (2003) and US. Patent Publication No. 20070072180. Examples of NOD2 variant alleles located in the 3‘ untranslated region ofthe NODZ gene e. without limitation, the .lWlS and JW|6 variant alleles, which are described in US. Patent Publication No. 20070072180. Examples ofNODZ t alleles located in the 5’ untranslated region (cg. promoter ) ofthe NOD32 gene include, without limitation. the .1W17 and JW18 variant alleles, which are described in US. Patent Publication No. 20070072180.

As used herein. the term “JWI variant ” es a genetic variation at nucleotide 158 of intervening sequence 8 (intron 8) ofthe NOD2 gene. In relation to the AC007728 sequence, the JWl variant allele is located at position 128,143. The genetic variation at tide 158 of intron 8 can be, but is not limited to, a single nucleotide substitution, multiple tide substitutions. or a deletion or insertion of one or more nucleotides. The wild-type ce ofintron 8 has a cytosine at position 158. As non- limiting examples, a JWl variant allele can have a cytosine (c) to adenine (a). cytosine (c) to guanine (g). or cytosine (c) to thymine (t) substitution at nucleotide 158 ofintron 8. In one embodiment, the JWl variant allele is a change from a cytosine (c) to a thymine (t) at nucleotide 158 of NOD2 intron 8.

The term “JW 1 5 variant allele” includes a genetic variation in the 3' untranslated region ofNOD2 at nucleotide position 1 18,790 of the 28 sequence. The genetic variation at nucleotide 1 18,790 can be. but is not limited to, a single nucleotide substitution, le nucleotide substitutions, or a deletion or ion of one or more nucleotides. The wild-type sequence has an adenine (a) at position 1 18,790. As non-limiting examples, a JWIS variant allele can have an adenine (a) to cytosine (c), adenine (a) to guanine (g), or adenine (a) to thymine (t) tution at nucleotide 1 18.790. in one embodiment, the JW15 variant allele is a change from an adenine (a) to a cytosine (e) at nucleotide 1 18.790.

As used herein, the term “JW16 variant allele” es a genetic variation in the 3' untranslated region ofNODZ at nucleotide position 1 18,031 ofthe AC007728 ce. The genetic variation at nucleotide I 18.03] can be, but is not limited to, a single nucleotide substitution, multiple nucleotide tutions. or a deletion or insertion of one or more nucleotides. The wild-type sequence has a guanine (g) at position 1 18,03 1. As non—limiting examples, a .lW l 6 variant allele can have a guanine (g) to cytosine (c), guanine (g) to adenine (a), or guanine (g) to thymine (t) substitution at nucleotide l l8,03l. In one embodiment, the .lWl6 variant allele is a change from a guanine (g) to an adenine (a) at nucleotide l l8,03 l.

The term “JW17 variant allele" includes a genetic variation in the 5' slated region ofNOD2 at nucleotide position 154,688 ofthc AC007728 sequence. The genetic variation at tide 154,688 can be, but is not d to, a single nucleotide substitution, multiple nucleotide substitutions, or a deletion or insertion ofonc or more nucleotides. The ype sequence has a cytosine (c) at position |54,688. As non-limiting examples, a JW17 variant allele can have a cytosine (c) to guanine (g), cytosine (c) to adenine (a), or cytosine (c) to thymine (t) substitution at nucleotide l54,688. In one ment, the .lWl7 variant allele is a change from a cytosine (e) to a thymine (t) at nucleotide [54,688.

As used herein, the term “JW18 variant allele” includes a genetic variation in the 5’ untranslated region ot‘NODZ at nucleotide position 1 ofthe AC007728 sequence. The genetic variation at nucleotide 154,47] can be, but is not limited to, a single nucleotide tution, multiple nucleotide substitutions, or a deletion or insertion ot‘one or more nucleotides. The wild—type sequence has a cytosine (c) at position [54.47 I. As non-limiting examples, a JW I 8 variant allele can have a cytosine (c) to guanine (g). cytosine (c) to adenine (a), or cytosine (c) to thymine (t) substitution at nucleotide l54,47l. In one embodiment, the JW18 t allele is a change from a ne (c) to a thymine (t) at nucleotide 154,471.

It is understood that the methods ofthe invention can be practiced with these or other NODZ variant alleles located in a coding region or ding region (cg, intron or promoter region) ofthe NODZ locus. It is further understood that the methods ofthe ion can involve determining the presence ot‘one. two. three, Four, or more NODZ variants, including, but not limited to, the SNP 8, SNP 12. and SNP l3 alleles, and other coding as well as non-coding region variants. ll. tical is In some aspects. the present invention provides methods for selecting anti~TNF drug therapy, optimizing anti—TNF drug therapy, reducing toxicity associated with anti-TNF drug therapy. and/or monitoring the efficacy of anti-TNF drug treatment by applying a statistical algorithm to one or more (cg, a combination oftwo, three. four, five, six, seven, or more) biochemical markers, gical markers. and/or genetic markers to generate a disease activity profile (DAP). in particular ments, quantile analysis is applied to the presence. level, and/or genotype of one or more s to guide treatment ons for patients receiving anti-TNF drug therapy. In other embodiments, one or a combination of two of more learning tical classifier systems are d to the presence, level, and/or genotype of one or more markers to guide treatment decisions for patients receiving anti-TNF drug y. The tical analyses ofthc methods of the present invention advantageously provide improved sensitivity, specificity. negative predictive value, positive predictive value, and/or overall accuracy for selecting an initial anti-TNF drug therapy and for determining when or how to adjust or modify (c.g, increase or decrease) the subsequent dose of an anti- TNF drug, to combine an NF drug (cg, at an increased, decreased. or same dose) with one or more immunosuppressive agents such as methotrexate (MTX) or oprine (AZA), and/or to change the current course oftherapy (cg, switch to a different anti-TNF drug).

The term "statistical analysis" or “statistical algorithm” or “statistical process” includes any ofa variety of statistical s and models used to determine relationships between variables. In the present invention, the variables are the presence. level, or genotype of at least one marker ofinterest. Any number of markers can be analyzed using a statistical analysis described herein. For example, the presence or level of l. 2. 3. 4. 5, 6, 7. 8, 9, 10, ll. l2, l3, 14. 15, l6, l7. l8, 19, 20, 25, 30, 35, 40. 45, 50, 55, 60, or more markers can be included in a statistical analysis. In one embodiment. logistic regression is used. In another embodiment, linear regression is used. In yet another ment. ordinary least squares regression or unconditional logistic sion is used. In certain preferred embodiments, the statistical analyses of the present invention comprise a quantile measurement of one or more markers, c.g.. within a given population, as a variable. Quantilcs are a set of“cut points” that divide a sample of data into groups containing (as far as possible) equal numbers of observations. For example, quaitilcs are values that divide a sample of data into four groups containing (as far as possible) equal numbers of observations. The lower quartile is the data value a quarter way up through the ordered data set; the upper quartile is the data value a quarter way down through the ordered data set. Quintiles are values that divide a sample of data into five groups containing (as far as le) equal numbers of observations. The present ion can also include the use of percentile ranges of marker levels (cg, textiles, quartile, quintilcs, cit: ), or their cumulative indiccs (cg, quartile sums of marker levels to obtain quartile sum scores (QSS). etc.) as variables in the statistical analyses (just as with continuous variables).

In certain embodiments. the present invention involves detecting or determining the presence. level (cg. magnitude). and/or genotype of one or more markers of interest using quartile analysis. In this type of statistical analysis, the level ofa marker ofinterest is defined as being in the first quartile (<25%). second quartile (25-5000). third quartile (5 I ‘%,-<75°/i)). or fourth quartile (75-I00%) in relation to a reference database of samples. These quartiles may be assigned a quartile score of I. 2. 3. and 4. respectively. In certain instances. a marker that is not detected in a sample is assigned a quartile score ofO or I. while a marker that is detected (cg. present) in a sample (eg, sample is positive for the marker) is assigned a quartile score of4. In some embodiments, quartile 1 represents samples with the lowest marker levels. while le 4 represent samples with the highest marker levels. In other embodiments. le 1 represents samples with a particular marker genotype (cg, wild- type allele). while quartile 4 ent samples with another ular marker pe (cg, allelic variant). The reference se of samples can include a large spectrum of patients with a TNFa-mediated disease or disorder such as. e.g.. IBD. From such a database. quartile cut-offs can be established. A miting example ofquartile analysis suitable for use in the present invention is described in. cg. Mow .. Gus(I'()enre/-u/()g).r. 126:4l4-24 (2004).

In some embodiments. the statistical analyses of the present invention comprise one or more leaming statistical classifier systems. As used herein, the term "learning statistical classifier system“ includes a machine learning algorithmic technique capable of ng to complex data sets (6g, panel of markers of interest) and making decisions based upon such data sets. In some embodiments. a single learning statistical classifier system such as a decision/classification tree (cg. random forest (RF) or classification and regression tree (C&RT)) is used. In other embodiments. a combination of 2. 3. 4. 5. 6. 7. 8. 9. 10. or more learning statistical fier systems are used. preferably in tandem. Examples of ng statistical classifier systems include. but are not limited to. those using inductive learning (cg. decision/classification trees such as random forests. classification and sion trees (C&RT). boosted trees. etc). Probably imately Correct (PAC) ng. connectionist learning (c.g., neural networks (NN). artificial neural networks (ANN). neuro fuzzy networks (NFN). network structures. the Cox Proportional-Hazards Model (CPHM). trons such as multi-layer pereeptrorrs. layer feed—forward networks. applications of neural ks. Bayesian learning in belief networks. etc. ). reinforcement learning ( e. (1.. passive learning in a known environment such as naive learning. ve dynamic learning. and temporal difference leaming. passive leaming in an unknown nment. active learning in an unknown environment, learning action-value functions. applications ofrcinforcemcnt learning. 61(1). and genetic algorithms and evolutionary programming. Other leaming statistical classifier systems e support vector machines (cg. Kernel methods), multivariate adaptive regression s (MARS), Levenberg~Marquardt algorithms. Gauss- Ncwton algorithms, mixtures ofGaussians. gradient descent algorithms, and learning vector quantization (LVQ').

Random forests are learning statistical classifier s that are constructed using an algorithm developed by Leo Breiman and Adele Cutler. Random s use a large number of individual decision trees and decide the class by choosing the mode (Ila. most frequently ing) of the classes as determined by the individual trees. Random forest analysis can be med. e.g.. using the RandomForests software available from Salford Systems (San Diego. CA). See, e.g., Breiman. il/lachine Learning. 45:5-32 ; and http://stat-www.berkeley.edu/users/breiman/RandomForests/ccjtome.htm. for a description of random s.

Classification and regression trees represent a computer intensive alternative to fitting cal regression models and are typically used to ine the best possible model for a categorical or continuous response of interest based upon one or more predictors.

Classification and regression tree analysis can be med, e.g.. using the C&RT software available from Salford Systems or the Statistica data analysis software available from StatSoft. Inc. . OK). A description of classification and regression trees is found. c.g., in Breiman cl (1/. “Classification and Regression Trees,” Chapman and Hall. New York (1984); and Steinberg et al.. “CART: Tree-Structured Non-Parametric Data Analysis.“ Salford Systems. San Diego. (1995).

Neural networks are interconnected groups of artificial s that use a mathematical or computational model for infomtation processing based on a connectionist approach to computation. Typically, neural networks are adaptive systems that change their structure based on external or intemal information that flows through the network. Specific examples of neural networks include feed-forward neural networks such as perceptrons. single-layer perceptrons. layer perceptions. backpropagation networks, ADALlNE networks. MADALI’NE networks. Learnmatrix networks. radial basis function (RBF) networks. and self—organizing maps or Kohonen self-organizing ks: ent neural ks such as simple recurrent networks and Hopfield networks; stochastic neural networks such as Boltzmann machines; modular neural networks such as committee of machines and associative neural ks: and other types of networks such as instantaneously d neural networks, g neural networks, dynamic neural networks, and cascading neural networks. Neural network is can be performed, Lag. using the Statistica data analysis software available from StatSoft, Inc. See, cg, Freeman er (1]., In “Neural Networks: Algorithms, Applications and Programming ques,” Addison- Wesley Publishing Company (_ I991); Zadch, ation and Control, 8:338-353 (1965); Zadch, “IEEE Trans. on Systems. Man and Cybernetics,” 3:28-44 (I973); Gersho cl (1]., In “Vector Quantization and Signal Compression," Kluywcr Academic Publishers, . cht, London (1992); and Hassoun, "Fundamentals of Artificial Neural Networks,” MIT Press, Cambridge, husetts, London (1995), for a description of neural networks.

Support vector machines are a set of related supewised lcaming techniques used for classification and regression and are described, e.g., in Cristianini e! [1]., “An uction to Support Vector Machines and Other Kcmel-Bascd Learning Methods,” Cambridge University Press (2000). Suppoxt vector machine analysis can be performed, eg, using the SVM/ig'h' software developed by Thorsten Joachims (Cornell University) or using the LIBSVM software developed by Chili-Chung Chang and Chili-Jen Lin (National Taiwan University).

The various statistical methods and models described herein can be trained and tested using a cohort ofsamples (cg, serological and/or genomic samples) from healthy individuals and ts with a TN Fat-mediated e or disorder such as, u.g., lBD (cg.

CD and/or UC). For example, samples from patients diagnosed by a physician, preferably by a gastroenterologist, as having lBD or a clinical subtype thereof using a biopsy, colonoscopy, or an immunoassay as described in, cug US. Patent No. 6,218,l29, are suitable for use in training and testing the statistical methods and models ofthe t invention. Samples from patients diagnosed with lBD can also be stratified into Crohn‘s disease or ulcerative colitis using an immunoassay as described in, c.g., US. Patent Nos. 355 and 5,830,675.

Samples from healthy duals can include those that were not identified as lBD samples.

One d in the aft will know of additional qucs and diagnostic criteria for obtaining a cohort of patient samples that can be used in training and testing the statistical methods and models ot‘the present invention.

As used herein, the term “sensitivity" includes the probability that a method ofthe present invention for selecting anti-TNF drug therapy, optimizing anti-TNF dmg therapy, reducing ty associated with anti-TNF drug therapy. and/0r monitoring the efficacy of anti-TNF drug treatment gives a positive result when the sample is positive, cg, having the predicted therapeutic response to anti-TNF drug therapy or toxicity associated with anti-TNF drug therapy. Sensitivity is calculated as the number oftruc positive results divided by the sum ofthe true positives and false negatives. Sensitivity essentially is a measure of how well the present invention correctly identifies those who have the predicted therapeutic response to anti-TNF drug therapy or toxicity associated with NF drug therapy from those who do not have the ted therapeutic response or toxicity. The statistical methods and models can be ed such that the sensitivity is at least about 60%, and can be. e.g., at least about 65%, 70%, 75%. 76%, 77%. 78%, 79%. 80%. 81%. 8.2%, 83%, 84%, 85%, 86%, 87%. 88%. 89%, 90%, 91%, 92W . 93%, 94%, 95%, 96%, 97%, 98%, or 99%.

The term “specificity“ includes the probability that a method ofthe present invention for selecting anti-TNF drug therapy. optimizing NF dmg therapy, reducing toxicity associated with anti-TNF drug therapy, and/or monitoring the efficacy ofanti-TNF drug treatment gives a negative result when the sample is not positive, cg. not having the ted eutic se to anti-TNF drug therapy or toxicity associated with anti-TNF drug therapy. Specificity is calculated as the number of true negative results divided by the sum of the true negatives and false positives. Specificity essentially is a measure of how well the t invention excludes those who do not have the predicted therapeutic response to anti-TNF drug therapy or toxicity associated with anti-TNF drug therapy from those who do have the predicted therapeutic response or toxicity. The statistical methods and models can be selected such that the specificity is at least about 60%. and can be. cg, at least about 65%, 70%, 75"/, 76%, 77%, 78%, 79%, 80%, 81%. 82%, 83%, 84"/, 85%. 86%. 87%, 88%. 89%. 90%, 91%, 92%. 93%, 94%. 95%, 96%, 97%, 98%, or 99%. |0274| The term “negative predictive value" or “NPV” includes the probability that an individual fied as not having the ted therapeutic response to anti-TNF drug therapy or toxicity associated with anti-TNF drug therapy actually does not have the predicted therapeutic response or toxicity. Negative predictive value can be calculated as the number oftrue negatives d by the sum ofthc true negatives and false negatives. ve predictive value is detemiined by the characteristics of the methods of the present invention as well as the Prevalence of the disease in the population analyzed. The statistical methods and models can be selected such that the negative predictive value in a tion having a disease prevalence is in the range of about 70% to about 99% and can be, for example, at least about 70%. 75%, 76%, 77%, 78%, 79%. 80%, 81%, 82%, 83%, 84%, 85%. 86%, 87%, 88%, 89%. 90%, 91%, 92%, 93%. 94%, 95%, 96%, 97%. 98%, or 99%.

The term “positive predictive value” or “PPV” es the probability that an dual identified as having the predicted therapeutic response to anti-TNF drug therapy or toxicity associated with anti—TNF drug therapy actually has the predicted therapeutic response or toxicity. Positive predictive value can be calculated as the number oftruc positives divided by the sum of the true positives and false positives. Positive predictive value is ined by the characteristics ofthc methods ofthe present invention as well as the prevalence ofthe disease in the population analyzed. The statistical methods and models can be selected such that the positive predictive value in a population having a disease prevalence is in the range of about 70% to about 99% and can be, for example, at least about 70%, 75%, 76%, 77%, 78%, 79%. 80W, 81%, 82%, 83%, 84%, 85%, 86%, 87%. 88%, 89%. 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99%. tive values, including ve and positive predictive , are influenced by the prevalence of the disease in the tion analyzed. In the present invention, the statistical methods and models can be selected to produce a desired clinical parameter for a al population with a ular prevalence for a TNFa-mediated disease or disorder such as, tag, lBD. As a non-limiting example, statistical methods and models can be selected for an lBD prevalence of up to about 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, %, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, or 70%, which can be seen, e.g.. in a clinician‘s office such as a gastroenterologist‘s office or a l practitioner‘s office.

As used herein, the term “overall agreement“ or “overall accuracy” includes the accuracy with which a method ofthe present ion selects anti-TNF drug therapy, optimizes anti-TNF drug therapy, reduces toxicity associated with anti-TNF drug therapy, and/0r monitors the efficacy ofanti-TNF drug treatment. Overall accuracy is calculated as the sum of the true ves and true negatives divided by the total number of sample results and is affected by the prevalence ofthe disease in the population analyzed. For example, the statistical methods and models can be selected such that the overall accuracy in a patient tion having a disease prevalence is at least about 40%, and can be, tag, at least about 40%, 41%, 42%, 43%, 44%, 45%, 46%, 47%. 48%, 49%, 50%, 51%. 52%, 53%, 54%. 55%, 56%, 57%, 58%, 59%, 60%, 61%, 62%, 63%, 64%, 65%, 66%, 67%, 68%, 69%, 70%, 71%, 72%, 73%. 74%, 75%, 76%, 77%, 78%, 79%, 80%, 81%, 82%. 83%, 84%. 85%. 86%, 87%, 88%, 89%, 90%, 91%, 920/ , 93%, 94%, 95%, 96W, 97%, 98%, or 99%.

Ill. Examples The present invention will be described in r detail by way of specific examples. The following examples are offered for illustrative purposes. and are not intended to limit the invention in any manner. Those of skill in the art will y recognize a variety of noncritical parameters which can be changed or modified to yield essentially the same results. l0279| The Examples set forth in US. Provisional ation No. 6 ”444,097, filed ry l7. 201 l. and PCT Application No. PCT/USZOlO/054l25. filed October 26, 2010. are hereby incorporated by reference in their entirety for all purposes.

Example 1. Disease Activity Profiling for Identifying Responders and Non-Responders t0 anti-TNFa Biologics.

This example describes methods for personalized therapeutic management ofa TN Fri-mediated disease in order to optimize therapy or monitor therapeutic efficacy in a subject using the disease activity profiling ofthc present invention to identify subjects as responders or non-responders to anti-TNF drug therapy. [0281l Figure 1 rates an exemplary lBD wound response e in which wound progression is divided into inflammatory. proliferative, and remodeling phases. As nonlimiting examples‘ inflammatory response phase markers tested include: anti-TNF drugs such as dc (infliximab); anti-drug antibodies (ADA) such as HACA; inflammatory markers such as GM-CSF. lFN-y. lL-l B, lL-2. lL-6, lL-8, TN F—a. and sTNF RH; and anti- inflammatory s such as lL-l2p70 and lL- l 0. Non-limiting examples of proliferation se phase markers tested include tissue repair/remodeling factors (also referred to as mucosal healing markers) such as AREG. EREG. HB-EGF. HGF. NRGl. NRGZ. NRG3‘ NRG4, BTC, EGF, lGF. TGF-Ot, VEGF-A, VEGF-B, VEGF-C, VEGF-D, FGFl. FGFZ.

FGF7. FGF‘), and TWEAK. |0282l A COMMIT (Combination Of Maintenance Mcthotrexate—lnfliximab Trial) study was performed to evaluate the safety and efficacy of Remicade (infliximab) in combination with rexatc for the long-term treatment of s disease (CD). Treatment success was defined by the proportion of subjects in clinical remission (Ila, te discontinuation of prednisone therapy and a Crohn‘s Disease ty Index (CDAI) score of<150) at week 14. and maintenance of clinical ion between study weeks 14 and 50. In particular. clinical assessment with CDAl was performed at week 0, 46. 50. and 66. Subjects with CDAI > 150 were identified as non-responders. Additional information on the COMMIT study is provided at htt :.:’r\vww.clinicaltrials. xov/etlt’showTNC'TOOl33899. the disclosure of which is incorporated by reference in its ty for all purposes.

Disease activity profiling was performed on a number of subjects in the COMMIT study. In particular, the Following away of markers were measured at various time points during treatment with Remicade (infliximab') only or a combination of Remicade (infliximab) with methotrexate: (I _) Remieade (infliximab) and HACA; (2) inflammatory s GM— CSF, IFN-y. IL-IB, lL-2. IL-6. IL-8. TNF-a. and sTNF RII; (3) anti-inflammatory markers IL—12p70 and lL—IO; and (4) tissue repair markers EGF, bFGF, PIGF, sFltI, and VEGF. The disease activity profile (DAP) for 7 ofthese subjects. which es a comparison between responder and non-responder profiles. is illustrated herein. These patient examples show that markers for inflammation and tissue repair correlated with infliximab and HACA levels in select active CD patients. certain markers may predict the disease activity profile. and disease activity profiling, will r guide patient y and identify mucosal healing markers. In addition. these patient examples show that whenever anti-inflammatory cytokines such as IL- l2p70 and IL-IO are elevated. the patient responds, indicating that they may be markers of mucosal healing. and that tissue repair markers (TRM) go up in non-responders.

Table of Personalized e Activity ng: Levels of IFX, HACA. Inflammatory s. Anti-Inflammatory Markers. and Mucosal Healing Markers Patient Treatment CDAI Clinical Inflammatory Anti- Mucosal Regimen Definition Markers inflammatory Healing Markers s IFX + MTX t=0, CDAI was HIGH LOW MEDIUM 202. responder t=wk 26, CDAI was 183 t=wk 66, CDAI=152.

IFX t=0, CDAI was Responder LOW HIGH HIGH 262. t=wk 46, CDAI was 85.

IFX t=O, CDAI was Responder MEDIUM HIGH HIGH 251. t=wk 46, CDAI was 109.

IFX + MTX t=O, CDAI was Responder HIGH HIGH 217. t=wk 46, CDAI was 68.

IFX t=0, CDAI was Non- Very Low MEDIUM LOW HIGH 272. responder at trough t=wk 46, CDAI (wk 14) was 145. t=wk 66, CDAI=195. 11601 lFX + MTX t=O, CDAI was Responder High at HACA+. HIGH HIGH MEDIUM 207. LOW t=wk 46, CDAI was 0. lFX=infliximab. MTX=methotrexate. ND = no detectable level ofHACA.

Patient 12209: lnfliximab + Methotrexate MTX Treated.

CDAI at time 0 was 202. At week 46, CDAI was [83 (“Delta l9” or =l83).

At week 66, C‘DAl was 15?. (“Delta 50” or 202-50=152). Clinically defined as non-responder.

Disease activity profile (DAP) accurately identified this patient. In particular, DAP showed that this t had low infliximab (IFX) levels at trough (“T“; Week 14). the presence ofa detectable concentration level of HACA (“HACA +“). high inflammatory marker levels, low anti-inflammatory marker levels, and medium tissue repair marker (TRM) levels. Suggested ative treatment options may e, for example, increasing the dose oleX, switching to therapy with adalimumab (HUMIRATM), treating with a different immunosuppressive drug such as azathioprine (AZA), and/or ing to therapy with a drug that targets a different mechanism (tag, an anti-lNFy antibody such as fontolizumab).

Patient llOlO: Infliximab Treated.

CDAl at week 0 was 262. At week 46. CDAI was 85 ("Delta 177“ or 262-l77=85).

Clinical responder. Disease activity profile (DAP) tely identified this patient. In particular, DAP showed that this patient had high infliximab (IFX) levels at trough ("'T"; Week 14), no detectable level of HACA (“HACA --”), low inflammatory marker levels, high nflammatory marker levels, and high tissue repair marker (TRM) levels. For e. anti-inflammatory cytokines lL-12p70 and IL-10 were high. As shown with the patients in this example, whenever anti-inflammatory cytokines were high, the patient responded most probably with mucosa! healing. In addition, bFGF concentration levels were low at all time points, although other TRM levels were high, ting that tissue growth was muted. such that tissue repair had already occurred.

Patient l0l l8: lnfliximab Treated.

CDAl at week 0 was 251. At week 46, CDAI was 109 (“Delta 142” or 251- l42=109). al responder. Disease activity profile (DAP) accurately identified this patient. In particular, DAP showed that this patient had high infliximab (lFX) levels at trough (“T”; Week 14), no detectable level of HACA (“HACA -—"). medium inflammatory marker levels, high anti-inflammatory marker levels. and high tissue repair marker (TRM) levels. For example, anti-inflammatmy nes lL-12p70 and lL-10 were high. Again. as shown with the patients in this example, whenever anti—inflammatory cytokines were high. the patient ded most probably with mucosal healing. In addition, bFGF tration levels were low at all time points and remained flat over the course oftherapy. although other TRM levels were higher, indicating that tissue growth was muted. such that tissue repair had y occurred.

Patient 1 I602: liifliximab + Methotrexate MTX Treated.

CDAl at week 0 was 217. At week 46. CDAl was 68 ("Delta 149“ or 217-149=68).

Clinical responder. Disease activity profile (DAP) tely identified this t. In particular, DAP showed that this patient had high infliximab (lFX) levels at trough (“T"z Week 14), no detectable level of HACA (“HACA --”), low inflammatory marker levels, high anti-inflammatory marker levels, and high tissue repair marker (TRM) levels. For example. anti-inflammatory eytokines 1L-12p70 and 1L-10 were high. Again. as shown with the patients in this e, whenever anti-inflammatory nes were high. the patient responded most probably with mucosal g. In addition. bFGF concentration levels were lower at all time points compared to the other TRM levels. indicating that tissue growth was muted. such that tissue repair had already occurred.

Patient 1 1505: liifliximab Treated.

CDAl at time 0 was 272. At week 46. CDAl was 145 (“Delta 127” or 272-127 = 145). At week 66. C‘DAI was 195. Clinically defined as non-responder. Disease activity profile (DAP) accurately identified this patient. In particular. DAP showed that this patient had very low infliximab(1FX) levels at trough ("‘T“; Week 14), a high concentration level of HACA (“HACA ++”). medium inflammatory marker levels. low anti—inflammatory marker levels. and high tissue repair marker (TRM) levels. In non-responders. the levels ofTRM such as bFGF go up. while in responders they either go down or do not change. Suggested altemativc treatment options may include. for example. increasing the dose oleX. switching to y with adalimumab (HUMJRATM), treating with an immunosuppressive drug such as MTX or azathioprine (AZA). and/or ing to therapy with a drug that targets a different mechanism (cg. an anti-lNFy antibody such as fontolizumab).

Patient 11601: ltifliximab + Methotrexate MTX Treated.

CDAl at week 0 was 207. At week 46. CDAI was 0 a 207” or 207~207=0).

The patient was clinically defined as responder. . Disease activity profile (DAP) accurately identified this patient. In particular. DAP showed that this patient had high infliximab (IFX) levels at trough (“T”: Week 14), low HACA levels (“HACA +”). high inflammatory marker levels. high nflammatory marker levels. and medium tissue repair marker (TRM) levels.

For example, anti-inflammatory cytokines 1L-12p70 and 1L- 1 0 were high. Again. as shown with the patients in this example. whenever anti-inflammatory cytokines were high. the patient responded most probably with mucosal healing. clearly ting that anti- inflammatory markers are very important. The presence ofhigh inflammation may be due to complication.

Patient 101 13: lnfliximab Treated.

CDAl at time 0 was 150. At week 46. CDAI was 96 (“Delta 54” or ISO-54:96). At visit 10 (“V10“), CDAl was 154, and at visit 11 ), (‘DAl was l69. As such, CDAl d at 150 and stayed around 150. The patient was clinically defined as non-responder.

Disease activity profile (DAP) accurately identified this patient. In particular. DAP showed that this patient had low mab (lFX) levels at trough (“T”; Week 14). a detectable concentration level of HACA (“HACA +”). medium inflammatory marker levels, low anti- inflammatory marker levels, and medium tissue repair marker (TRM) levels. Again. TRM levels go up in non-responders. while in responders they either go down or do not change.

Suggested alternative treatment options may e. for example. increasing the dose of lFX, switching to therapy with adalimumab (HUMIRATM). treating with an immunosuppressive drug such as MTX or azathioprine. and/or switching to therapy with a drug that targets a different ism (eg, an anti-1N Fy antibody such as fontolizumab).

Example 2. Disease Activity ng Modeling.

An exemplary 3-dimensional graph rendering of the disease activity profile (DAP) of the present invention includes each ofthe different markers present in the array of markers on the , normalized marker levels on the y-axis. and time on the z-axis (e.g.. time points n samples are taken and marker levels measured). An exemplary topographic map of the DAP of the present invention (also referred to herein as a personalized disease ) includes each ofthe different markers present in the array of markers the y-axis, time on the x-axis (cg. time points wherein samples are taken and marker levels measured). and relative marker levels in grayscale.

The 3D models described herein represent a novel paradigm for treatment because they are individualized and titratable such that dose adjustments are made in a personalized . For example. marker panels including markers such as inflammatory, proliferative. and remodeling markers enable a ination in real-time of the best course of treatment fora patient on therapy such as anti-TNF drug therapy. cg. for treating CD or RA. As a result. both the time course and the concentration levels ofmarkers in the panel or array of markers are important for therapy adjustment and monitoring to alize and dualizc therapy and determine optimal doses or dose adjustments. In n instances, the change in one or more marker levels over time is an ant consideration for therapy adjustment and monitoring. In particular embodiments, the desired therapeutic zone for the set or a subset of the markers in the array or panel is within a defined range in the 3D graph or topographic map.

Example 3. lnfliximab Non-Detection This example represents a model for to—event.“ In other words. this example uses the Cox tional-Hazards Model (CPHM) to model the time it takes for “an event“ to occur and the risk of such an event happening. The model is a regression analysis with “time-to-event” on the Y axis. which is a response variable. and “predictor variables” on the X axis. In this example, the non-detection ofinfliximab (i.e.. the concentration of imab falling below a detection threshold) is the event. with the potential predictors of such an event being biomarkers: e.g., CRPr lL-2. VEGF, and the like and or clinical ation such as age‘ MTX treatment, gender. and the like. |0294| In this example. the “Hazard" is the risk of infliximab not being detected (cg. non- detection) by an analytical assay such as a mobility shift assay. For example. Figure l 1 shows infliximab concentration levels for various patients during their course Oftreatment.

An event occurs in this e when the concentration of infliximab falls below a predetermined detection threshold. In certain instances. the CPHM is being used to predict the risk ofthe event occurring (infliximab non-detection). The example also identifies biomarkers indicative of such a risk occurring.

Using the CPHM. time is modeled until infliximab is not detectable by a mobility shift assay. In the model, the predetermined old is 0.67 ug/m L. which is the lower bound ofthe reference range. If the infliximab concentration level is less than the threshold at time “t” then the event has occurred at time ‘t.“ In Figure l2. patients were ranked by their time to the event. The event occurred for various patients at different points during treatment and is denoted with a bullet point.

In the initial model. there were various markers and clinical information used to predict the hazard or the risk ofinfliximab non-detection by the mobility shift assay. These markers ed the following markers in the Table: 1L—IB VCAM-l lL—Z AGE lL-6 Months since dia 'r‘nosis 1L-8 e (a; colon TN F-a Disease (an small |0297| From the initial marker list. the following list was derived as being the preferred markers indicative of the event: GM-CSF sRNFRll Disease (24., small intestine ICA-M — The following Table lists the significant predictors ofinfliximab non-detection risk or the hazard: Predictor coef ex a (coe se(coei) GM-CSF -1.92E-01 0.826 94813-02 4.34E-02 1L-2 1.42E-01 1.153 1.92E-02 1.63E-13 TNF-a 2.33E-02 1.024 7.57E-03 2.1 lE—O3 sTNFRll 3.57E-01 1.429 5.76E-02 5.67E- 10 SAA 6.13E-06 1.000 1.9OE-06 1.25E—03 Months since -3.20E-03 0.997 03 02 Disease ((1.. l.lOE+00 2.995 4.46E—01 1.39E—02 small intestine Success 01 [J A L) 3.13E-01 4.72E-03 The results in the above Table indicate the following are predictors of the hazard i.e., risk ofthe non—detection ofinfliximab: GM—CSF: holding all other variables constant, an extra ng/ul of GM—CSF reduces the weekly hazard ofinfliximab non-detection by a factor of 0.826. or l7.4 %. lL-Z: An onal l llg/ui of lL-Z increases the hazard by a factor of l.153, or .3 %.

TNF-a: A l ng/ul of TNF-o. increases the hazard by a factor of l .024 / 2.4 %. sTNFRll: A l ng/til of sTNFRll increases the hazard by a factor of L429 / 42.9 "o.

SAA: A l ng/ul ofSAA increases the hazard by a factor of [.000006/ 0.0006 %, which is very small] but still a detectable effect (small SE).

Months since diagnosis: Each additional month since sis decreases the hazard by a factor of0.997. or 0.3 "/0.

Disease site at the small intestine (categorical variable): lfthe disease is located at the small intestine. the hazard is increased by a factor of 2.995, or nearly 200 ”o. s (categorical le): Also a predictive ofhazard; in non-successful patients the hazard is increased by a factor of2.421 or [42 %.

In summary. the following markers appear to be good predictors of infliximab “clearance" /or non-detection: l)GM-CSF; 2) lL-2; 3) TNF—a; 4) sTNFRll; and 5) the disease being situated in the small intestine.

As such. in one embodiment. the present invention provides: A method for predicting the likelihood the concentration ofan anti-TNF therapeutic or antibody during the course oftrcatment will fall below a threshold value, the method comprising: measuring a panel of markers selected from the group consisting of l) GM—CSF; 2) lL-2; 3) : 4) sTNFRll; and 5) the disease being situated in the small intestine; and ting the likelihood the tration of an anti—TNF therapeutic or antibody will fall below the threshold based upon the concentration of the markers.

Example 4. Detection of Antidrug Antibody to lnfliximab (“ATP’ or “HACA“) This example uses the Cox Proportional-Hazards Model (CPHM) to model the time that it takes for an event to occur. This is a similar is to Example 3 above, but with the appearance ofthc anti—drug antibody also known as ATl or HACA as the event and risk of AT] formation (detection) as the hazard. Figure 13 shows the concentration of ATl (HACA) in various patients during the course oftreatment. In Figure 14, patients were ranked by their time to the event. The event occurred for s patients at different points during treatment and is denoted with a bullet point. The risk of ATl detection is the . Significant predictors of the hazard include: 78215-03 _—_Im_8.64E-04 1.06E-02 18313-02 3.25E-03 68113-03 ——Im_—3.00E-03 1.87510 The data in the above table indicates that EGF, VEGF, lL-8, CRP and VCAM-l all have very small. but significant effects on the hazard.

GM-CSF: Holding all other variables constant, an extra ng/ttl SF reduces the weekly hazard of ATl detection by a factor of 0.762. or 27.4 "o. lL-2: A l ng/ul increase of lL-2 increases the hazard by a factor of 1.85. or 85 "o. [0314[ TNF-a: A l ng/ul increase ofTNF-o. increases hazard by a factor of 1.024, or 2.4 00. [0315 In summaiy, the tors of AT] detection hazard are GM-CSF, lL-Z and TNF-a.

As such. in one embodiment, the present invention provides a method for predicting the likelihood that rug antibodies will occur in an individual on anti-TNF therapy or antibodies, said method comprising: measuring a panel ofmarkers selected from the group consisting of 130 F. VEGF. lL-b’, CRP and VC‘AM‘l; and predicting the likelihood that anti-drug dies will occur in an individual on anti-TNF therapy based on the tration of marker levels. e 5. Disease ty Profiling for Crohn’s Disease Prognosis Using COMMIT Study Samples. [03l7] This e illustrates s for personalized therapeutic management ofa TNFa-mediated disease in order to optimize therapy or monitor therapeutic efficacy in a subject using the disease activity profiling ofthe present ion. This examples illustrates disease activity profiling which comprises ing. measuring. or ining the presence. level and or activation of one or more specific biomarkers (e.g.. drug levels. rug antibody levels. inflammatory markers. anti-inflammatory markers. and tissue repair markers).

This example describes disease activity profiling on a number of samples from the COMMIT study. As described in Example I, the COMMIT (Combination of Maintenance Methotrexatc-Inflixamab Trial) study was performed to evaluate the safety and efficacy of Remicade xamab) in combination with methotrexate (MTX) for the long-term treatment of Crohn’s Disease (CD). In particular. the following array of markers was measured at various time points during treatment with Remicade (infliximab; IFX) only or a treatment of Remicade with MTX: (l) Remicade (inflixamab) and antidrug dies to infliximab (ATI): (2) inflammatory markers CRP. SAA. ICAM. VCAM; and (3) tissue repair marker VEGF. This example shows that the markers ofinflammation and tissue repair correlated with IFX and ATI levels in select patients ofTNF-Ot mediated disease (cg. Crohn’s Disease and Ulcerative Colitis). In some instances, arrays ofmarkers may t a disease activity index (6g. Crohn‘s Disease Activity Index). Analysis ofthe COMMIT study is illustrated herein.

The relationship between the presence of ATI and serum levels of IFX concentration was igated. For the evaluation. total ATI levels below the level of quantitation (BLOQ) were 3. I 3 U/ml. and were set to 0. IFX concentrations below the level of detection (BLOD) were set to 0. Per the sample comparison. only trough samples were used and a total of 2l9 were used in the evaluation. 24 samples were detemiined to be ATI positive (ATI+). It was determined that the median level ofIFX was 0 rig/ml in ATl+ samples, while the median level of IFX was 8.373 ug/ml in ATI ve (ATl-) samples (p=3.7l x l0'9 by Mann Whitney U test). Figure 4A illustrates an association between the presence of ATI and the level of IFX in patient samples. Patient samples with no detectable level of ATI had a significantly higher IFX median concentration. compared to ATI+ samples.

The relationship between CDAl and the presence ofATl was evaluated. In the analysis ATI of}. I 3 U/ml was set as the cut-off; only trough samples were evaluated and ATI BLOQ was set as 0. 195 samples were ATl-, while 24 s from a total of4 patients were ATI+. The results showed that the median CDAl for ATl+ s was l21.5 while the median C‘DAI for ATl- samples was 82 (p=0.0132 by Mann Whitney U test). Figure 48 illustrates that the presence of ATI correlates with higher CDAl. The results show that ATl+ samples have significantly higher CDAl than ATl- samples.

] The relationship between the presence of AT] and combination therapy of lFX and suppressant agent (e.g., MTX) was investigated. ATI+ samples at any trough time point were analyzed. The results showed that there was no significant difference in odds of having ATI between lFX therapy alone and IFX+MTX combination therapy. The high odds ratio (e.g., 2.851) indicates that MTX can t a patient from developing an immune response to eutic ics. Figure 4C shows that rent immunosuppressant therapy (cg, MTX) is more likely to suppress the presence ofATl.

The onship between ATI and clinical outcome at follow-up was also investigated. AT|+ samples at any trough time point were analyzed. Clinical outcome as described from the clinical data received from the study was parsed as either “success” or “non-success”. No significant difference in odds of being ATI+ was seen regardless of treatment regimen. The low odds ratio (eg, 0.1855. p=0. 1459) indicates that ATl+ patients tend to have poor clinical outcomes. Figure 5A shows that patients with ATI are more likely to develop a poor response to ent.

This example also illustrates an association of an exemplary PRO Inflammatory Index and serum levels ofinfliximab (lFX) or the presence of antibodies to lFX (ATI) in a patient sample. Figure SB illustrates that the inflammatory marker CRP is associated with increased levels of AT]. The data shows that the median CRP level was 8.] l ug/ml in ATl+ samples and 1.73 lag/ml in ATI- samples (p = 2.67 x 10'6 by Mann Whitney U Test). Other inflammatory and tissue repair markers were evaluated. Figure 6 illustrates that the protein levels of an array of one or more atory and tissue repair markers correlate to the formation of antibodies to lFX. The data shows that ofa combination of five markers (cg, CRP. SAA. lCAM. VCAM. VEGF and including at least one inflammatory marker) was sed in 23 out of 24 ATI positive samples (Figure 7A. grey box). The inflammatory marker SAA was found to be positive in 19 ofthe 24 AT] positive samples that were also clinically described as having “high inflammation". The results also show that VEGF and CRP are the most erlapping markers in the analysis.

This example further shows an ary PRO atory Index (PII). The inflammatory index score is created by logarithmic transformation ofa combination of values enting ined expression levels ofa plurality of markers (cg, PII = Iog((‘RP + SAA + IC‘AM + VC‘AM + VEGF)). Figure 78 illustrates that an exemplary PRO atory Index (PII) correlates with levels ofIFX (p<0.0001 and R2 = -0.I29) in patient samples ofthe COMMIT study. The results show that ATI positive samples have a significantly higher inflammatory index score compared to ATI negative samples ('P = 6.4xl0'3; see Figure 7C).

As such, in one embodiment. the present invention provides a method for monitoring an infliximab treatment regimen. said method comprising: a) measuring infliximab and antidrug antibodies to infliximab (AT1); b) measuring inflammatory markers CRP. SAA, ICAM, VCAM; c) measuring tissue repair marker VEGF; and d) correlating the measurements to eutic y.

Example 6. Disease Activity Profiling For TN F-(x Mediated Disease Prognosis Using Clinical Study #1 Samples.

This example describes methods for monitoring therapeutic efficacy in a subject using the disease activity profiling ofthc present invention to identify subjects as responders or non-responders to anti-TNF drug therapy. This e rates the use ofdiseasc activity profiling with a number of patient samples from a Crohn‘s Disease clinical trial #1.

In particular, an array of markers was measured at various time points during treatment with Remicade (infliximab; IFX) only or a treatment of Remicade with MTX: Remicade (inflixamab). antibodies to infliximab (ATI'), and neutralizing antibodies to IFX.

This example shows that a disease activity profile can show the relationship among ATI, IFX and lizing antibodies. is of clinical study #I is illustrated herein.

Figure 8A-B rates the correlation between Crohn’s Disease Activity Index (CDAI) score and the concentration ofinfliximab in serum in a number of patients in clinical study #1. In brief, 894 samples were analyzed. An IFX concentration 3 0.1 pig/ml at the limit of detection (LOD) was defined to be “present”. The s showed that IFX negative (lFX-) samples also have cantly higher CDAl (p: 0.0254. calculated by Mann- Whitney U test), compared to IFX positive samples (lFX+I).

Further analysis revealed that the presence ofATl correlates with lower lFX concentrations. It was assumed that total ATl below the level of tation (BLOQ) of3.l3 Ll/ml was set as 0 and lFX concentration below the level ofdctcction (BLOD) was set at 0. It was ined that 24% of the patients (62/258) in the study were ATl+. as defined as positive total ATl levels at one of three time points. The analysis of 894 samples showed a correlation between lFX concentration and ATI levels. In particular, the median lFX was 0 ug/ml for ATl+ samples and 7.95 ug/ml for ATl- samples (p <2.2 x IO'N’ by Mann—Whitney U test). Figure 9A illustrates the association between lFX concentration and the presence of antidrug antibodies to mab in s analyzed.

Analysis shows that a high concentration ot‘ATl in samples correlates with the presence of neutralizing antibodies that target TNF—Ot biologics. ln some embodiments. assays can be used to detect lizing antibodies. Neutralizing antibodies were detected in t samples with the highest concentrations of ATl. Figure QB illustrates that a high concentration of ATl can lead to the presence ofneutralizing antibodies and undetectable levels oleX.

Longitudinal analysis ofthe relationship oFCDAl and the presence ot‘ATl was evaluated in samples collected at clinic visit #I and #3 from 283 patients, A correlation between the presence of AT] at visit #I (Vl ) was established with CDAl at visit #3 (V3).

The median CDAl was 109 at V] in ATl+ samples. while the median CDAI was 78 in ATl- samples (p=0.027 by Mann Whitney U test). The s indicate a causal relationship between ATl positivity and CDAl. Figure 9C illustrates that AleL s determined at an early time point were more likely to have a higher CDAI at a later time. The results indicate that disease activity profiling at an early time point can predict C‘DAl at a later time point.

Figure 9D illustrates that in Clinical Study #1. patients had lower odds of developing AT] if ing a combination therapy ofinf'liximab (lFX) and an immunosuppressant agent (e.g., MTX and AZA). The odds ratio was 0.320 (p = 0.0009 by ’s Exact test). In this analysis, ATl positivity (ATl+) was defined as total ATl _>_ 3.13U/ml. e 7. e Activity Profiling For TNF-oc Mediated Disease Prognosis Using Clinical Study #2 Samples.

A. Clinical Study #2A This example rates the use ofa method For monitoring therapeutic efficacy in patients receiving Remicade (inflixamab) alone or in combination with an immtmosuppressant agent (cg. methotrexate. azathioprine and/or conicosteroids). This example bes using methods ofthe prevent ion to determine the disease activity profiles of samples from a series ofclinical trials.

In the analysis. we investigated the relationship between antidrug antibodies to inflixamab (ATI) and IFX concentrations in the cohort. It was determined that 90.6% ofthe ts were ATI+ (58/64). when ATI+ samples were defined to be those with total ATI > 3. I3 U/ml at at least one time point. The median concentration ofIFX in ATI positive samples was 0 pig/ml and 3.74 [lg/ml in ATI negative samples (P<2.2 IO-K' by Mann Whitney U Test). The concentration ofneutralizing antibodies was 0 in ATI+ samples. The results suggest that the presence ofATI reduces IFX concentration in a patient on IFX therapy. The range of IFX concentration for ATI- samples was 00-6728 ug/ml. In AT|+ samples the lFX tration was 0.0-26.I5 [lg/ml. In ATI+ samples with neutralizing dies (Nab) the IFX concentration ranged from 0-1.07 ug/ml. Figure IOA shows that correlation between IFX concentration and the presence of ATI in samples of clinical study #2A. The results also demonstrated that the odds g ATI positive versus ATI negative are significantly less for samples treated with an immunosuppressant agent (ISA. e.g.. methotrexate. azathioprine. corticosteroids. and ations thereof). In this analysis 814 samples were evaluated. The odds of being ATI+ was significantly less for ISA-treated samples than of being ATI- (odd ratio = 0.564; p < 0.00001 by Fisher‘s Exact Test). In on. fewer ISA treated samples expressed neutralizing ATIs. Ot‘the 34 ATI+ samples with neutralizing antibodies analyzed. 9 ofthc 34 samples were ISA-treated and 25 samples were non-ISA treated samples. This indicates that ISA therapy can reduce the progression to ATI. and even neutralizing antibodies to lFX. Figure IOB illustrates the relationship between ISA therapy and the presence of ATI in the study.

Next, we investigated the relationship between ATI and inflammatory s. As described herein. total ATI BLOQ was set at 0. CRP concentration was determined by methods such as a CEER assay. The results show that the median concentration of CRP was lowest (5.0 ug/ml) in ATI- samples and higher (10.0 ) in ATI+ samples. Sample expressing neutralizing ATl had a yet higher median concentration of CRP (10.0 ug/ml). All pair—wise comparisons between CRP trations and ATI status should that the values were cantly different (p < 0.000] by Mann Whitney U . Figure 10C illustrates the relationship between C‘RP concentrations and the presence of AT! (ATI and/or neutralizing AT”.

We also investigated the relationship between ATI and loss of response to therapy.

In the cohort. samples were marked as having a “response". “loss ofresponse“ and “no information” regarding lFX therapy. The samples were further rized as being "True” if having a loss ofresponse or "False" ifnot having a loss of response. In total 777 samples were analyzed. The results showed that in samples marked as “True”. there was a significantly higher odds ratio of also being AT] positive (odds ratio = 2.354. p<0.0001 by Fisher’s Exact Test). Surprisingly. more samples that were positive for neutralizing antibodies to lFX were determined to be sive to lFX, as compared to being no longer responsive. Of 34 neutralizing ATI+ samples. 21 were marked as nse“ and 8 were marked as “loss of se”. Figure 10D illustrates the relationship between loss of responsiveness to lFX therapy and the presence of AT] in the study. Figure l 1 illustrates that levels of AT] and neutralizing antibodies can be determined over time in a series of samples from various patients We ed the concentration oleX to the presence ofthe inflammatory marker CRP. We defined “lFX presence” per sample as “True” ileX was >: 0.1 ug/ml which is the LOD of the assay. The results suggest that the median CRP concentration was not different between samples with lFX present or without lFX present. The median CRP level was 7.40 1.1le in samples with lFX. while median CRP = 7.55 ug/ml in samples with IFX absent (p = 0.591 by Mann Whitney U Test). Figure 12A illustrates the comparison of CRP levels to the presence of lFX. [03371 We also compared the relationship between infusion reaction to the presence of ATI. The is included a total of 797 samples; 30 samples were categorized as having infusion reaction (“Yes”) and 767 samples were categorized as having no infusion on (“No”). 29 samples that had an infusion reaction were also ATI+ (odds ratio = 35.54. p<0.000l by Fisher‘s Exact Test). Figure 128 illustrates the relationship between the presence of ATI and the infusion reaction. Patients sing ATl were more likely to have had an infusion reaction. Yet. for the 27 samples with neutralizing ATI. no infusion reaction was observed in 22 samples. The remaining 5 samples with lizing ATl had infusion B. Clinical Study #28 [0338| In this analysis of clinical study #28. we investigated the relationships between the presence of AT], IFX concentration. administration of ISA. the expression of inflammatory markers (cg. CRP), and loss of response to IFX treatment. We ined that the median IFX tration was higher in samples expressing ATl compared to those not expressing the antidrug antibodies. 15.2%ofthe patients (16 out of 105) were ATI+ with a total ATl >3. 1 3 U/ml at at least one time point. Of the 489 samples analyzed. the median lFX concentrations were 0.59 jig/ml in ATl+ samples and 7.78 pig/ml in ATl- samples (p <4“: x "“ by Mann Whitney U Test). Figure 12C illustrates the onship between lFX concentration and the presence of AT] in the cohort. The analysis showed that there are high odds of developing antibodies to IFX when immunosuppressants have been withdrawn (odds ratio = 0.4l2, p = 00367 by Fisher‘s Exact Test). Figure l2D illustrates the correlation between the presence of AT] and the awal oflSA therapy at a specific. given date. We determined that ATl positive samples have a higher median concentration ofC‘RP (9.6 pig/ml. p 2 L5 x 10"2 by Mann Whitney U Test). ed to ATI negative samples (median CRP = l.5 ttg/ml). Figure l3A illustrates the relationship between ATI and the inflammatory marker CRP. Our analysis showed that the odds of experiencing a loss of response to IFX was higher in patients determined to be ATI positive at any time point. (odds ratio = 3.967. p = 0.0374 for Fisher’s Exact Test). Figure 133 rates the correlation between the presence ot‘ATl at any time point and siveness to lFX treatment. Loss of response to IFX was also correlated to a higher median concentration of the inflammatory marker CRP. In the analysis there were 14 samples with loss ofresponsc at follow-up and 91 samples from responders. The median CRP levels were i 1.767 ug/ml for those with loss of response and 2.585 pg/ml for those with response. ts who had lost response to IFX had a significantly higher mean CRP (p = 7.45 x 10'5 by Mann Whitney U Test). Figure 13C shows that loss onse can be related to an increase in CRP. CRP was also significantly higher in samples lacking detectable IFX 2. Samples were determined to have lFX (“IFX present”) ifthe level of IFX was >= to 01 ug/ml per sample (e.g., LOD ofthe assay). The median CRP was L6 ug/ml in lFX present samples and 13 ug/ml in IFX absent samples (p = 3.69.3(10’5 by Mann y U Test). Figure 13D illustrates the association between the presence of IFX and CRP levels. In this study “ATH” was defined as a sample with total ATl >3.l3 U/ml at at least one time point.

C. Clinical Study #ZC In this analysis ofelinical study #ZC. we investigated the relationship between IFX levels and the presence of ATI. It was determined that ATI+ have a significantly lower median IFX of0.43 [lg/ml as compared to ATI- samples which have a median IFX of3.28 tig/ml (p = 1.95xl0'4 by Mann Whitney U test). Figure 14A shows that lower IFX levels are associated with the presence of ATI.

As such. in one embodiment. the present invention provides a method for determining whether an individual is a candidate for combination therapy wherein said individual is administered infliximab, the method comprisinguncasuring for the presence or absence ofATI in said individual; and stering an immunosupprcssant (cg, MTX) is the individual has cant levels ofATl. In certain aspects. the concentration level of CRP is indicative ofthc presence ofATI.

Example 8. Disease ty Profiling For TNF-ot Mediated e Prognosis Using Patient Samples from Clinical Study #3.

This example illustrates using s ofthe present invention to monitor the eutic y of anti—TNF drug therapy. In particular. pooled data including study data, phannacokinetics data, follow-up study data of clinical study #3 were analyzed. The s showed that the median IFX concentration of 0.0 [lg/ml was lower in ATI positive samples compared to an IFX concentration of 12.21 ug/ml ATI negative samples (P < 2.2 x lO-I6 by Mann Whitney U test). Figure 148 shows that lower IFX levels are associated with the ce of ATI in these clinical samples. Figure 14C illustrates that the same correlation n IFX levels and ATI was also present in the study data. follow-up study and in the pharmacokinetics study (p< 0.05 by Mann Whitney U tests). We also used methods ofthc t invention to determine that a high concentration ofATI in a sample have a neutralizing effect on IFX. In particular. high trations of ATI act as neutralizing antibodies to inflixamab. Samples with a high concentration of ATI had an IFX lcvel ofO rig/ml. Figure ISA illustrates the relationship between ATI levels including neutralizing ATI and IFX.

Example 9. Methods of Disease Activity Profiling Including the PRC Inflammatory Index in Patients Receiving Humira.

This example illustrates methods ofthe present invention including determining the level ofTNF—O. biologic (cg. adalimumab (Humira); ADL‘) and the presence of anti-drug antibodies to the TN F-Ot ic (cg. ATA) in a patient sample. In this analysis. one sample represents one patient and a total of 98 CD samples were evaluated. 2.04% (2 out of 98 CD patients) ofthe samples were pOsitive for ATA., when ATA positivity was set as total ATA> O. Surprisingly, the two ATA positive samples also had the highest concentrations of ADL, Figure [58 illustrates an association between ADL concentration and the presence of ATA in patient samples. [0343l This example describes an ary PRO Inflammatory Index (Pll). The example also illustrates the use ofthe Pll in patient s receiving Humira (adalimumab) and different drug combinations. Figure 16A describes the details of an exemplary PRO matory Index. The Pll can represent a single per-sample score describing inflammation levels based on five biomarkers. The score is obtained from the logarithmic transformation of the sum of the five biomarkers. In some embodiments. the biomarkers include VEGF in pg/ml. CRP in ng/ml. SAA in ng/ml, ICAM in ng/ml and VCAM in ng/ml.

Figure I6B illustrates that there is no obvious relationship between the Pll and the concentration of ADL in an array of samples with ADL alone or in combination with other drugs. This could be due to the ance ofhigh ADL trough serum concentration in the sample cohoit. These is a significant negative ation between Pll and ADL concentration (p=l.6t’wxl0‘5 and Spearman‘s Rho =-0.459). A similar ve correlation relationship was found n lFX and PI].

We also compared the relationship between the PH and the presence of therapeutic agents used to treat TN F-O. mediated diseases. ADL positive samples were defined as samples with an ADL concentration of greater than 0 ug/ml. The results showed that a higher Pll was detected in patients on Humira compared to patients on dc and Humira. Figure l7 shows a plot ofthe Pll scores for patients receiving Humira and Humira in combination with other drug such as de, Cimzia. Asathioprine and Methotrexate.

As such. in one ment. the t invention provides a method for monitoring Crohn‘s disease activity, the method comprising: determining an inflammatory index comprising the measurement ofa panel of markers comprising VEGF in pg/ml. CRP in ng/ml. SAA in ng/ml. lC‘AM in ng/ml and VCAM in ng/ml; comparing the index to an efficacy scale or index to monitor and manage the disease.

Example 10. Methods for Improved Patient Management.

This example describes methods for improved patient management to assist in ping personalized patient treatment.

In some embodiments patients with active CD and UC can be analyzed using a mobility shift assay (see, eg, PCT Publication No. W0 20] 1/056590. the disclosure of which is hereby orated by reference in its ty for all pulposes) in conjunction with disease activity profiling. Figure I8 shows details ofthc methods ofthe present invention for improving the management of patients with CD and/0r UC. In some embodiments, the methods of disease activity profiling comprise pharmacokinetics, and determining the presence and/or levels ofdisease activity profile markers and/or mucosal healing markers. [03481 In some embodiments. disease activity profiling comprises methods of ing, measuring, and determining the ce and/or levels of biomarkers. nes, and/or growth factors. Non-limiting examples of cytokines that can be used in e activity profiling include bFGF. TNF-a. IL-IO, lL-l2p70, lL-IB, lL-Z‘ lL-6, GM-CSF‘ IL-l3. IFN-y, TG F-Bl. TGF-BZ. TOP-[33. and combinations thereof. Non-limiting examples of inflammatory markers include SAA. CRP. ICAM, VCAM. and combinations thereof. Non- limiting examples of anti-inflammatory markers include TGF-B. IL-lO, and combinations thereof. Non-limiting examples of growth factors include amphiregulin (AREG), ulin (EREG). n binding epidermal growth factor (HB-EGF). hepatocye growth factor (HGF), heregulin-Bl (HRG) and isoforms, neuregulins (NRGI. NRGZ, NRG3, NRG4), betacellulin (BTC), epidermal growth factor (EGF), insulin growth factor -1 (lGF-l ), transforming growth factor (TGF). platelet-derived growth factor (PDGF ). vascular endothelial growth factor (VEGF), stem cell factor (SCF), platelet derived growth factor (PDGF), soluble fms-like tyrosine kinase I (sFltl ), placenta growth factor (PIGF), fibroblast growth factors (FGFs). and combinations thereof. |0349| In other embodiments, disease activity profiling ses detecting. measuring and determining pharmacokinctics and mucosal healing. In some aspects. mucosal healing can be assessed by the presence and/or level of selected kcrs and/or endoscopy. In some instances, mucosal healing can be defined as the absence of friability. blood. erosions and ulcers in all visualized segments ofgut mucosa. In some embodiments. kers of mucosal healing. include, but are not limited to, AREG, EREG, HG-EGF. HGFr NRGI.

NRGZ. NRG3, NRG4. BTC. EGF, IGF-I, HRG, FGFI, FGFZ . FGF7. FGF9. SCF, PDGF. TWEAK. F. TNF—(l, lL-12p70. lL-IB, [1-2. IL—(x IL-lO, IL—l3, lFN-y. TGF-Ot.

TGF-[31. TGF-B2, TGF-B3, SAA, CRP. lCAM. VCAM. and combinations thereof. In some embodiments. a growth factor index can be established using statistical es ofthe detected levels of biomarkcrs of mucosal healing. In some ces, the growth factor index can be associated with other markers of e activity, and utilized in methods of the present invention to alize patient treatment.

Figure 19 shows the effect of the TNF-Ot y and related pathways on different cell types, cellular mechanisms and disease (tag. Crohn‘s Disease (CD), rheumatoid arthritis (RA) and Psoriasis (Ps1). Figure 20 rates a schematic ofan exemplary CEER multiplex growth factor array. In particular embodiments, the methods of the present invention can employ this array. As non-limiting examples, Figure 21A-F illustrate multiplexed growth factor profiling of patient samples using this array. In particular. longitudinal analysis of growth factors, such as AREG, EREG, HB—EGF. HGF, HRG. BTC, EGF, IGF, TGFa. and VEGF, was performed on a tion of t samples. Figures 21 B and E illustrate the ination ofthc level ofserologieal and immune markers. such as ASCA-a, ASCA-g, Cbirl and OmpC, in samples from Patient 10109, Patient 101 18 and Patient 10308. Figure 21G shows the ary growth factor arrays performed on samples from healthy controls, patients with lBS-C. and patients with lBS-D.

A series ofmultiplexcd CEER growth factor and CRP arrays was performed on patient samples. Tables A—D (below) highlight longitudinal analysis of mucosal healing in patient samples. The following Table (A) shows that CRP and growth factors can be predictive ofmucosal healing: Collection TGF TGF Date CRP bFGF VEGF Tweak beta 1 beta 2 IIIIIIIIII IIIIIIIflIII'lIIIIIIIHIlIII IE"IIIIIIMIIII 6768 III IIIIIIIIIIIEIIEIIIIIIIE 73.85 III IIIIIIIIIIIII63.79 IIIIIIHIIIMIHIIIIIII 57.93 IIIIIIIIII71.43 IIIIIIIIIIIlIIIIIIIEI 68.69 IIIIIIIII98.94 flIIIIIflIIIIIIIIIIIII IIIIIIIIIIIIIIII IIIIflIIIIflIflIIflflfl IIIIIIIIIII “IIIIIIIIIIIIIHIII IIIIIIIIIIIII IIIIIIIIflIIflIlIIIfl Collection 1 . . . . . 1120.06 IIIIIIIIflIlIlIIlIIlIIflIIl IIIIIIIIIIIIIIII IIIIIlIIlIIlIIIIIIIIIflIEIflN IIIIIIIIIIlIIlIIlIIIllIIIIN IIIIIIIIIIIIIIII IIIIIIIIlIIIIIIIIIIlI ”III-IIIIIIIIII IIIIIIIIIIIIIIIIIIII IIIIIIIIIIII IIIIIIIflIflIIIflIIflIlII “N” and “P” denote a negative or ve onship between pairs ol'obsewalions for each marker. respectively per subject. Underlined data are number pairs above upper limit oliquantitation and are assumed to have a positive relationship.

[0352] The following Table B lists CRP and growth factors predictive of mucosal healing: Subject Collection TGF ID Date CRP BTC alpha IIIIIIIIIIIIEIII IIIIIIIIIIIflIEIIIIEEI IIEIIIIIIIIIIIMIEI IIIIIIIflflIIIlflIMI@II IIIIIIIIIIMIII IIIIIIMIM IIIIIIEIIII IIIIIIIIIIIIIIIIIIIIII IIIIWIIIEIIIEII III-MINIM- IIIIIIIIIEIIIMIIEI IIIIIIIIIIIIIIIIIIIEIIII IIIIIIIIIIIEIII IIIIIIIIEIIIIEIIIIIMIEI IIIIIIEIIIIEIIIII IIIIIIIIflmflflflflflfl EIIIEIIIII IIIIIIIIIIIEIIEIIMIIIIIIIII IIIIIIIIEIIIIMIIIEMII IIIIIIIIIIIMIIIIEIIIIIII IIIIIIIIEEIIIIIMIIIIIIIII IIIIIEIIIIIIMIIEEIII IMIIIIEIIEIIEIIMI II‘IEIIIIII ’21ndP denote a negative 01 positive relationship between p211irs ol observations for each . respeetnely pe1 subject. Underlined data are. number pairs 11bo\e upper limit ol qu11nt1t11t1on and are assumed to MW 21 positive relationship.

[0353] The following Table C shows that CRP and growth factors can be tive of mucosal healing: WII IIIIDate CRP VEGF Tweak betal IIIII 624.03 IIIII III—II 509.73 III-In 1046.04 191.49 IIII 48725 N 23791 P 633 Ill 1117.85 1267.74III 3713 . P 633.56 957.18 m-_n 5301 32.19 5301 p 217.02 389.33 2.88 30.89 7757ICollection 1 838.39 11.24 7.90 43.35 7757 Collectionz 138.56 p 705.18 N 5.33 7966 Collection 1 120.82 326.72 5.59 38.67 7966 Collection 2 31.04 P 1089.52 691.29 6.81 P 48.68 8075 968.25 zlv 840.06 8.10 58.65 8075 p 620.97 876.55 6.27 N 51.36 8127 323.51 310.67 5.54 41.13 8127 N 318.02 N 284.46 6.87 P 51.87 8431 Collectionl 1829.91 214.78 2.18 52.82 N 301.14 HIP 8431 Collectlon 2 3O 51 P 816.10 3.47 P 58.41 3831 Collection 1 32.95 804.87il491.46 6.83 36.16 3831 Collection 2 N 491.17 912.29 '-U 7.31 P 23.62 3852 Collection 1 68.59 494.06 252.18 6.10 32.76 3352 N 291-49 N 122.66 6.56 P 39.22 3852_m 375.97 100.53 134 N 22.83 5477 550.58 76 7.51 36.73 5477III_ 7-55I“ 7456II_I-II_I 7456III-“um“N “N" and “P" denote a negative or positive onship between pairs ()l‘obserxv'alions for each marker. respectively per subject. Underlined data are number pairs above upper limit ol‘quantitalion and are d to have a positive relationship.

The following Table D shows that CRP and growth factors can be predictive of mucosal g: t Collection TGF ID Date CRP BTC alpha 6-88 2433 105-46 IIIIII 1-31 IIIIII 7.76 III-IE!- E" NO 107.22 IIIIIIIEJI 5301 Collectionl 7.62 ---_-- 5301 CollectionZ 36.61 ----_---HIHIEIH 4-49 IIIIIIIIEIIII‘EIII IIIIIIIIIIIIIIMIIEII‘EIIII IIIIIIIIIIIIEIIIII IIIIIIIIIIEIIIIEIIIIIIEIIIIIII IIIIIIIIIIIIIEIIIEII II_I-HWIIIIIIEIIIIIEIIEIIIEEII IIIIIIIIIIIIIIII IIIIIIIEIEZMIEIIIIIEIIEIIEIII IIIIIIIIIIEIIIIEIIIEII IIIIIIIIIIIIIIIIIIMIIII Collection 1 3831 3852 3852 N 3852 _-El 5477 5477 N 7456 “N" and “P" denote a negative or positive relationship between pairs ol'obscwations for each marker. respectively per subject. Underlined data are number pairs above upper limit ol‘quantitation and are assumed to have a positive relationship.

Tables A. B. C and D show marker values and relationships n pairs of observations in CRP and growth factor data. Using a criterion ofa = 0. l. we identified an association between three growth factors and CRP. The following Table (E) shows a two-by- two contingency table that highlights that an se or decrease in AREG. HRG and TGF was found to be significantly associated with an increase or decrease of CRP: ARE(i* TGF-al ha*** * s ** s *** denotes p = 0.034. p = 0.026. p = 0.07. 0356 Fi lure 22 illustrates the association between CRP levels and the5 EIrowth factor index score in determining disease remission.

Further studies for fying predictive markers of l g may e s from several clinical studies. As one non-limiting example. al Study A may include 4 l 3 samples (paired samples with 1-5 samples per patient). Clinical data may detail patient age. sex. weight. date of diagnosis. disease location. sample collection dates. dose. scopy. improvement of mucosa. presence of mucosal healing. and/or concomitant medication useagc. In Clinical Study A. colonoscopy may be performed prior to first drug infusion. As another non-limiting example. in Clinical Study B. 21?. UC samples may be analyzed (1 10 samples were diagnosed for CD at follow-up and l02 samples were diagnosed for UC based on mucosal healing). Clinical data may detail patient age. sex, weight. date of diagnosis. disease location. sample collection dates. lFX dose. colonoscopy results (endoscopic activity score). albumin level. CRP levcl. and/or Mayo score. In Clinical Studies A and B. three infusions may occur at week 0. 2 and 6 during induction. 6 additional drug ons may be performed during the maintenance phase at week 14. 22. 30. 38. 46 and 52.

A second colonoscopy may be performed during the maintenance phase. A third colonseopy may be performed during follow-up and patients may continue treatment if responsive to drug.

The methods of the present ion can be used to create alized therapeutic management ofa TNFa-mediated disease. A personalized therapeutic regimen for a patient diagnosed with IBD can be selected based on predictors of disease status and/or long-term outcome as described herein. including. but not limited to, a Crohn‘s prognostic test (see, e.g., PCT Publication No. . the disclosure of which is hereby incorporated by reference in its entirety for all purposes), a disease activity profile (cg. disease burden), a mucosal status index, and/or a PRO Inflammatory Index as described in Example 5. Using the methods of the present invention, it can be determined that a t has mild disease activity and the clinician can recommend, prescribe, and/or administer a nutrition-based therapy (Figure 23A). Yet, ifit is ined that a patient has mild disease activity with an sive phenotype, a nutrition-based therapy in addition to thiopurines can be ended. prescribed, and/or administered. A similar therapy can be recommended, prescribed. and/or administered ifit is determined that the patient has moderate e activity (Figure 238). lfit is determined that a patient has moderate e activity with an sive ype, either a combination ofthiopurines and nutrition therapy (Nx) or an appropriate anti-TNF drug can be ended, prescribed, and/or administered. In some instances, an anti-TNF monitoring test (see, rag, PCT ation No. W0 20] 90, the disclosure of which is hereby incorporated by nce in its entirety for all es) can be used to determine if the patient is likely to respond to the therapy. In the case when severe disease activity is determined, an appropriate anti-TNF drug administered at an optimized dose can be recommended and/or prescribed (Figure 23C). In such instances. an anti-TNF monitoring test (see, cg, PCT Publication No. W0 30] 90, the disclosure of which is hereby incorporated by reference in its entirety for all purposes) can be used to predict if the t is likely to be responsive to drug. [it other instances, it can be recommended and/or prescribed that a patient having severe disease activity also receive nutrition-based therapy.

In some embodiments, the methods ofthe present invention can be used in a treatment paradigm to personalize patient treatment (Figure 24). First, treatment can be selected based on the expression of mucosal status markers. Next. drug dose can be selected based on disease burden (e.g.. disease activity index). After the therapeutic drug is administered, the initial response can be determined from the expression of markers of mucosal healing. ATM monitioring can be used to identify patient who are responsive or non—responsive to therapy. sponsive patients can then be prescribed an appropriate anti-TNF drug.

Example ll. Novel lnl'liximab (lFX) and Antibody-to—lnfliximab (ATI) Assays are Predictive of Disease Activity in Patients with Crohn’s disease (CD).

Previous studies te that patients with CD who have a higher trough concentration of lFX during maintenance dosing are more likely to benefit from treatment.

However, development of ATls can result in increased drug clearance and loss ofrcsponse.

Therapeutic drug monitoring may allow clinicians to maintain effective drug concentrations.

Although previous AT] assays have been limited by the inability to measure ATls in the presence of drug. fluid-phase lFX and ATI assays have overcome this problem (see, e.g..

PCT Publication No. W0 20] 1/056590. the disclosure ofwhich is hereby incorporated by reference in its entirety for all purposes). We used these assays to evaluate the relationship between serum IFX concentration, ATls and disease activity. s: 202l serum samples from 532 participants in 4 prospective CD RCTs or cohort studies (COMMIT, Leuven dose optimization study, Canadian Multieenter and I) that evaluated the maintenance phase of lFX ent were used, and data were combined for analysis. IFX and ATI serum levels were measured using a ased fluid phase assay. CRP, measured by ELISA, was used to assess disease activity. ROC analysis determined the lFX threshold that best discriminated disease activity, as measured by CRP.

We examined pairs of samples taken over sequential time points and evaluated the relationship between lFX and ATI presence in the pair‘s first data point and CRP in the subsequent measurement. There were 1205 such observations. We identified four distinct patient groups, namely lFX 2 threshold and ATl-. IFX < old and ATl-, lFX 2 threshold and ATl+, and IFX < threshold and ATI+. Regression analyses assessed the potential interaction between IFX and ATI as predictors ofCRP.

Results: CRP can best differentiate lFX status with an IFX concentration threshold of3 ug/ml (ROC AUC = 74 "0). Using paired sequential samples both ATI and lFX were associated with median CRP (Table 2). Although ATI+ ts had higher CRP levels overall, within this group there was no association between lFX higher than threshold and uent CRP. ln ATI- patients, CRP was significantly higher in patients with lFX levels <3 ug/ml. In the regression is ATl positivity, lFX 2 3 ug/ml and the interaction term were all icant predictors of CRP. CRP was 3] ”0 higher in ATI positive patients than those who were ATl negative and 62 00 lower in patients with lFX levels 2 3 ttg/ml compared to those with lFX < 3 ug/ml.

Conclusions: We have shown that AT] positivity is tive ofincreased e activity. while an lFX concentration above the threshold value of3 ug/ml is tive of significantly lower disease ty. In ATI+ patients, lFX concentrations above 3ttg/ml had no effect on CRP, indicating that the benefits of lFX are diminished in the presence of AT] despite the presence of optimal dwg concentration. These findings support the concept that therapeutic drug monitoring is an important tool in zing lFX therapy. Using paired tial samples and regression is, both AT] and lFX were associated with median CRP as shown in the following table: -—_interquartile range) Significance Median CRP concentrations and interquartile ranges (in parentheses) in ng/ml. Asterisks denote significance levels oftwo-samplc Mann-Whitney U tests (***, p < 0.00]; **, p < 0.0]; *, p < 0.05; NS, not significant).

Example 12. Novel Infliximab (lFX) and Antibody-to-lnfliximab (AT1) Assays are Predictive of Disease Activity in Patients with Crohn‘s disease (CD).

This example illustrates the use ofinfliximab (lFX) and antibody-to-infliximab (AT1) assay in predicting disease activity in patients with Crohn‘s disease (CD). This example also illustrates a method of determining the threshold of lFX that can best discriminate disease activity as measured by C-reaetive protein (CRP) levels. This example also illustrates the association of both ATI and lFX to CD and CRP levels, which can some as a measure of disease activity.

Previous s have indicated that patients with CD who have a higher trough tration oleX during maintenance dosing are more likely to benefit from treatment.

However, development of ATls can result in increased drug nce and loss of response.

Therapeutic drug monitoring may allow clinicians to maintain effective drug concentrations.

Although previous ATl assays have been limited by the inability to measure ATls in the presence of drug. the fluid-phase lFX and ATI assays bed in PCT Publication No. W0 ] 1/056590 (the sure of which is hereby incorporated by reference in its entirety for all putposes) have overcome this problem.

In this study we used fluid—phase IFX and ATI assays to evaluate the relationship between serum lFX concentration, ATls and disease activity, as measured by CRP. We analyzed 3.021 serum samples from 532 participants in 4 prospective C‘D randomized lled trials (’RCTs) or cohort s. including COMMIT‘ Lcuven dose optimization study. Canadian Multicenter and lMEDEXl. The combined analysis was restricted to samples during maintenance of lFX treatment. There was evidence of non-heterogeneity among pooled CRP.

IFX and ATI serum levels were measured using a HPLC-based fluid phase assay.

CRP was measured by ELISA and used to assess disease activity. Receiver-operator curve (ROC) analysis was performed to determine the IFX trough threshold (cg, amount or concentration) that can best discriminate disease activity (c.g.. n high and low CRP values). Figure 25 shows the ROC analysis. CRP and nine IFX trough thresholds were analyzed and the ROC area under receiver-operator characteristic curve (AUC) are. as follows: ROC AUC 0.733 0.7 r 7 0.699 The ROC analysis showed that CRP can best differentiate IFX status with an IFX concentration threshold 0f3 rig/ml (ROC AUC = 74 %). For example, at an IFX through concentration threshold of 3.0 rig/ml. a randomly chosen sample with a “low” lFX serum concentration will have a higher CRP level than a randomly chosen sample with a “high” IFX serum concentration 74.3% ofthc time. In the IFX, ATI and CRP association analysis. a serum IFX trough threshold of 3.0 rig/ml was used.

To determine the association m IFX concentration, ATI, and (‘RP levels over time. we examined pairs ofsamples taken over tial time points. A l00—day time gap limit was imposed for the time points. We ted the onship between the presence of IFX and ATI in the pair‘s first data point and CRP in the uent measurements (Figure 26A). Figure 268 shows CRP levels, IFX serum concentration and ATI status at sequential time points for a sample. In total, 1.205 observations were examined.

Regression analysis (e.g., ordinary least squares regression) was performed to assess the potential interaction between prior IFX and prior ATI as predictors of e (i.e.. CRP levels). In particular. CRP was log transformed at the second time point observation. Prior IFX is the first time point with IFX tration above or below the calculated trough threshold of3 ug/ml. Prior AT] is the first time point AT] is above or below 3. l 3 U/ml which is the limit ofdetection (LOD). Using paired sequential samples and regression analysis. both ATI and IFX were associated with median CRP as shown in the ing table: Median CRP Concentration (ng/ml; interquartile range) Significance ———— Median CRP concentrations and interquartile ranges (in parentheses) in ng/ml. Asterisks denote significance levels oftwo-sample Mann-Whitney U tests (***, p < 0.00l; **t p < 0.01; *. p < 0.05; NS, not significant).

The results shows that the factors and interactions between the factors are cant. The regression coefficients were calculated to be 0.272 for ATl+ samples and -0.979 for IFX Z 3 ug/ml.

We identified four distinct patient groups: (I) IFX 2 threshold and ATl-, (2) lFX < threshold and ATl-, (3') IFX 2 threshold and ATl+. and (4) IFX < threshold and ATl+. Ofthe 1,205 ations used in the analysis. 605 were IFX 2 old and ATl-; 196 were IFX < threshold and ATl-; 41 were IFX 2 threshold and ATl+; and 363 were lFX < threshold and ATl+.

Although ATl+ patients had higher CRP levels overall. within this group there was no association between IFX levels higher than threshold and CRP (Figure 27). In ATl- patients. CRP levels were significantly higher in patients with IFX levels less than threshold (Figure 27).

In the sion analysis. ATl positivity, IFX 2 3 ug/ml and their interaction were all significant predictors of CRP levels. CRP was 31 % higher in AT] + patients than those who were ATl-. and 62 ‘Vn lower in ts with IFX levels 2 3 ttg/ml compared to those with IFX < 3 ug/ml. The relationship n IFX concentration and CRP levels differs n ATl+ and ATl- patient groups.

In this study we showed that AT] positivity is predictive ofincreased disease activity, as measured by CRP. We also showed that IFX concentration above the threshold value of3 ug/ml is predictive ofsignificantly lower disease activity. In ATl+ patients. IFX concentrations above 3 ug/ml had no effect on CRP levels. suggesting that the benefits of IFX are diminished in the presence of AT] even e the presence of optimal drug concentration.

We showed that disease activity, as measured by CRP, is strongly linked to both IFX and ATI in a large combined dataset. Thus. patients with active ’s disease can benefit from knowledge of both IFX and ATI levels at trough. Based on the experimental derivation ofthese relationships, the following treatment paradigms were created. For instance. a symptomatic patient with Crohn‘s disease with lFX< threshold at trough and ATI- can benefit from an increased dose of IFX therapy. A patient with lFX 3 threshold and ATI— can benefit from receiving endoscopy or switching y. A symptomatic patient with lFX< threshold at trough and ATI+ can t from switching therapy if ATl is high or optimizing therapy dose ifATl is low. A patient with IFX 3 threshold and ATl+ can benefit from ing y ifdiseasc activity (e.g.. CRP level) is high. Alternatively, if e activity (e.g., CRP level) is low in that patient. further monitoring is recommended. The treatment paradigms are described in the following table: Switch therapy (high ATl) IFX < threshold Increase dose Optimize dose ("low ATl) Cheek endoscopy Switch therapy (high activity) IFX 3 threshold or or Switch therapy Monitor (low activity) |0377| These findings demonstrate that therapeutic dmg monitoring using methods of the present invention are important tools in optimizing IFX therapy.

Although the foregoing invention has been described in some detail by way of illustration and e for purposes of clarity of understanding. one of skill in the art will appreciate that certain changes and modifications may be ced within the scope ofthe appended claims. In addition. each reference provided herein is incorporated by nce in its entirety to the same extent as if each reference was individually incorporated by reference.

Claims (10)

1. A non-invasive method for ing a therapy regimen to promote mucosal healing in an individual diagnosed with inflammatory bowel e (IBD), said method comprising: (a) measuring the levels of an array of l healing markers in a sample obtained from the individual at time point t0 to generate a mucosal healing index at t0; (b) measuring the levels of an array of mucosal healing markers in a sample obtained from the individual at time point t1 to te a mucosal healing index at t1; (c) comparing the change in the mucosal healing index from t0 to t1; and (d) selecting the therapy regimen for the dual to promote mucosal healing.

2. The method of claim 1, wherein the mucosal healing marker is a member selected from the group consisting of AREG, EREG, HB-EGF, HGF, NRG1, NRG2, NRG3, NRG4, BTC, EGF, IGF, TGF-, VEGF-A, VEGF-B, VEGF-C, VEGF-D, FGF1, FGF2, FGF7, FGF9, TWEAK and combinations f.

3. The method of claim 1 or claim 2, wherein the mucosal healing index is determined using a statistical algorithm.

4. The method of any one of claims 1 to 3, wherein the therapy regimen comprises an anti-TNF antibody.

5. The method of claim 4, wherein the anti-TNF antibody is a member selected from the group consisting of infliximab, etanercept, adalimumab, izumab pegol, and combinations thereof.

6. The method of any one of claims 1 to 5, wherein the markers are measured in a sample selected from the group consisting of serum, plasma, whole blood, stool, peripheral blood mononuclear cells (PBMC), rphonuclear (PMN) cells, and a tissue biopsy.

7. The method of any one of claims 1 to 6, wherein the levels of an array of mucosal healing markers are measured at 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 30, 35, 40, 45, 50, or more additional time points.

8. The method of any one of claims 1 to 7, n the IBD ses Crohn’s disease or ulcerative colitis.

9. The method of any one of claims 1-8, wherein: (i) the marker is a cytokine selected from the group consisting of GM-CSF, IFN-γ, IL- 1β, IL-2, IL-6, IL-8, TNF-α, soluble tumor is factor-α receptor II (sTNF RII), TNF- related weak inducer of apoptosis (TWEAK), osteoprotegerin (OPG), IFN-α, IFN-β, IL-1α, IL- 1 receptor antagonist (IL-1ra), IL-4, IL-5, soluble IL-6 receptor (sIL-6R), IL-7, IL-9, IL-12, IL- 13, IL-15, IL-17, IL-23, and IL-27; or (ii) the marker is ed from the group consisting of MMP-1, MMP-2, MMP-3, MMP-7, MMP-8, MMP-9, MMP-12, MMP-13, MT1-MMP-1, and ations thereof; or (iii) the marker is selected from the group consisting of C-reactive protein (CRP), D- dimer protein, mannose-binding protein, alpha 1-antitrypsin, alpha chymotrypsin, alpha 2- lobulin, fibrinogen, prothrombin, factor VIII, von Willebrand factor, plasminogen, complement factors, ferritin, serum amyloid P component, serum amyloid A (SAA), orosomucoid (alpha 1-acid glycoprotein (AGP)), ceruloplasmin, haptoglobin, and combinations f; or (iv) the marker is selected from the group consisting of TGF-α, TGF-β, TGF-β2, and TGF-β3; or (v) the marker selected from the group consisting of AREG, EREG, , HGF, HRG, NRG1, NRG2, NRG3, NRG4, BTC, EGF, IGF-1, TGF, VEGF-A, VEGF-B, VEGF-C, VEGF-D, FGF1, FGF2, FGF7, FGF9, and TWEAK; or (vi) the marker selected from the group consisting of IL-10, SCF, ICAM, VCAM, IL- 12p40, and VEGFA.

10. A non-invasive method for selecting a therapy regimen to promote mucosal healing in an individual diagnosed with inflammatory bowel disease (IBD), according to any one of claims 1 to 9, substantially as herein described with reference to any one or more of the examples but excluding comparative examples.