# Patent

## Title
Methods of predicting the need for surgery in crohn's disease

## Abstract

The present invention relates to methods of predicting susceptibility to a severe form of Crohn's disease in an individual by determining the presence or absence of one or more risk variants. In one embodiment, the risk variants comprise a combination of genetic risk variants and clinical risk factors. In another embodiment, the genetic risk variants are at the IL12B genetic locus. In another embodiment, the severe form of Crohn's disease is characterized by a rapid progression to a condition requiring surgery for treatment.

## Background
CROSS-REFERENCE TO RELATED APPLICATIONS
This application makes a claim of priority to U.S. provisional patent application No. 61/442,045, filed on Feb. 11, 2011, the contents of which are hereby incorporated by reference in their entirety.


STATEMENT REGARDING FEDERALLY-SPONSORED RESEARCH
This invention was made with Government support under Grant No. DK066248 awarded by the National Institutes of Health. The Government has certain rights in the invention.


BACKGROUND
The following description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.
Crohn's disease (CD) is a disease of diverse clinical phenotypes and patients with complicated disease phenotypes such as those with stricturing and/or internal penetrating disease behaviors often require surgical intervention. Over a 10 year period, approximately 80% of patients can expect to develop a complication and close to 50% of CD patients will progress to surgery (1, 2). This is in contrast to the small percentage of patients presenting with a complication, and requiring surgery at time of diagnosis. One of the biggest challenges facing clinicians today is predicting which patients will progress to complication resulting in intestinal resection. The identification of these “rapidly progressive” patients early in the course of their disease may assist in the decision regarding the early introduction of effective intervention strategies and customizing therapies based on risk of underlying disease. Those at highest risk of disease complication may well benefit most from early use of immunomodulators and/or biologic therapies. Despite major advances in genome discovery, there have only been a few studies that have considered the role of genetics in determining disease behavior. Variation in NOD2/CARD15 has been shown to be associated with stricturing CD, need for surgery as well as surgical recurrence (13-18). Serological immune markers have been shown to predict more aggressive disease. Recent genome-wide association (GWA) studies have identified multiple IBD susceptibility loci although their phenotypic consequences remain unknown. The ability to identify patients with Crohn's disease (CD) who are at highest risk for rapid progression to surgery would be invaluable in guiding initial therapeutic choices.
SUMMARY OF THE INVENTION
Various embodiments include a method of diagnosing susceptibility to a severe form of Crohn's disease in an individual, comprising obtaining a sample from the individual, assaying the sample to determine the presence or absence of one or more risk variants at the IL12B genetic locus, and diagnosing susceptibility to a severe form of Crohn's disease in the individual based on the presence of one or more risk variants at the IL12B genetic locus. In another embodiment, the severe form of Crohn's disease is characterized by a rapid progression to a condition requiring surgery for treatment. In another embodiment, the method further comprises determining the presence of one or more clinical, serologic and genetic risk factors. In another embodiment, the method further comprises determining the presence of anti-ASCA, pANCA, anti-Cbirl, anti-OmpC and/or anti-I2. In another embodiment, the method further comprises determining the presence of one or more risk variants at the NDFIP1, C13orf31, SMAD3, 21q21, IBD5, CACNA2D1, ZNRF1, and LDHD genetic loci. In another embodiment, the one or more risk variants comprise SEQ ID NO: 1. In another embodiment, the one or more risk variants comprise SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5, SEQ ID NO: 6, SEQ ID NO: 7, and SEQ ID NO: 8.
Other embodiments include a method of prognosing Crohn's disease in an individual, comprising determining the presence of a risk variant at the IL12B genetic locus and one or more risk factors in the individual comprising a diagnosis of Crohn's disease in the small bowel location, age of diagnosis, and/or risk serological factors, and prognosing a severe form of Crohn's disease characterized by a rapid progression to conditions associated with requiring surgery for treatment in the individual based on the presence of a risk variant at the IL12B genetic locus and one or more risk factors in the individual. In another embodiment, the method further comprises determining the presence of one or more risk variants at the genetic loci of NDFIP1, C13orf31, SMAD3, 21q21, IBD5, CACNA2D1, ZNRF1, and/or LDHD. In another embodiment, the risk serological factors comprise anti-ASCA, pANCA, anti-Cbirl, anti-OmpC and/or anti-I2. In another embodiment, the one or more risk variants comprise SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5, SEQ ID NO: 6, SEQ ID NO: 7, and SEQ ID NO: 8.
Other embodiments include a method of treating Crohn's disease in an individual, comprising diagnosing susceptibility to a severe form of Crohn's disease in the individual based on the presence of one or more risk variants at the IL12B genetic locus, and treating the individual. In another embodiment, the severe form of Crohn's disease is characterized by a rapid progression to a condition requiring surgery for treatment. In another embodiment, diagnosing susceptibility to a severe form of Crohn's disease further comprises determining the presence of one or more clinical, serologic and genetic risk factors. In another embodiment, diagnosing susceptibility to a severe form of Crohn's disease further comprises determining the presence of anti-ASCA, pANCA, anti-Cbirl, anti-OmpC and/or anti-I2. In another embodiment, diagnosing susceptibility to a severe form of Crohn's disease further comprises determining the presence of one or more risk variants at the NDFIP1, C13orf31, SMAD3, 21q21, IBD5, CACNA2D1, ZNRF1, and LDHD genetic loci. In another embodiment, the one or more risk variants comprise SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5, SEQ ID NO: 6, SEQ ID NO: 7, and SEQ ID NO: 8.
Other features and advantages of the invention will become apparent from the following detailed description, taken in conjunction with the accompanying drawings, which illustrate, by way of example, various embodiments of the invention.



BRIEF DESCRIPTION OF THE FIGURES
Exemplary embodiments are illustrated in the referenced figures. It is intended that the embodiments and figures disclosed herein are to be considered illustrative rather than restrictive.
FIG. 1A illustrates, in accordance with an embodiment of the invention, survival curves for three risk strata in the inventive model.
FIG. 1B illustrates, in accordance with an embodiment of the invention, survival curves for the three strata for model IV (clinical+genetics).
FIG. 1C illustrates, in accordance with an embodiment of the invention, survival curves for the three strata for model V (genetics+NOD2+clinical+serologies).



DESCRIPTION OF THE INVENTION
All references cited herein are incorporated by reference in their entirety as though fully set forth. Unless defined otherwise, technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Singleton et al., Dictionary of Microbiology and Molecular Biology 3rd ed., J. Wiley & Sons (New York, N.Y. 2001); March, Advanced Organic Chemistry Reactions, Mechanisms and Structure 5th ed., J. Wiley & Sons (New York, N.Y. 2001); and Sambrook and Russel, Molecular Cloning: A Laboratory Manual 3rd ed., Cold Spring Harbor Laboratory Press (Cold Spring Harbor, N.Y. 2001), provide one skilled in the art with a general guide to many of the terms used in the present application.
One skilled in the art will recognize many methods and materials similar or equivalent to those described herein, which could be used in the practice of the present invention. Indeed, the present invention is in no way limited to the methods and materials described.
“Haplotype” as used herein refers to a set of single nucleotide polymorphisms (SNPs) on a gene or chromatid that are statistically associated.
“GWAS” as used herein means Genome-Wide Association Study.
“Risk” as used herein refers to an increase in susceptibility to IBD, including but not limited to CD and UC.
“Protective” and “protection” as used herein refer to a decrease in susceptibility to IBD, including but not limited to CD and UC.
“CD” and “UC” as used herein refer to Crohn's Disease and Ulcerative colitis, respectively.
As apparent to one of skill in the art, there are many examples of the various single nucleotide polymorphisms (SNPs) and genetic variants referenced herein. Examples of genetic variants rs6556412, rs11167764, rs3764147, rs16950687, rs1736148, rs12521868, rs11978472, and rs7195303 are provided herein as SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5, SEQ ID NO: 6, SEQ ID NO: 7 AND SEQ ID NO: 8, respectively, although the genetic variants are in no way limited to those specific sequences disclosed.
As used herein, the term “biological sample” means any biological material from which nucleic acid molecules can be prepared. As non-limiting examples, the term material encompasses whole blood, plasma, saliva, cheek swab, or other bodily fluid or tissue that contains nucleic acid.
The inventors performed a genome-wide association study testing autosomal single nucleotide polymorphisms (SNPs) on the Illumina HumanHap300 Genotyping BeadChip. Based on these studies, the inventors found single nucleotide polymorphisms (SNPs) and haplotypes that are associated with increased or decreased risk for inflammatory bowel disease, including but not limited to CD. These SNPs and haplotypes are suitable for genetic testing to identify at risk individuals and those with increased risk for complications associated with serum expression of Anti-Saccharomyces cerevisiae antibody, and antibodies to 12, OmpC, and Cbir. The detection of protective and risk SNPs and/or haplotypes may be used to identify at risk individuals predict disease course and suggest the right therapy for individual patients. Additionally, the inventors have found both protective and risk allelic variants for Crohn's Disease and Ulcerative Colitis.
Based on these findings, embodiments of the present invention provide for methods of diagnosing and/or predicting susceptibility for or protection against inflammatory bowel disease including but not limited to Crohn's Disease and ulcerative colitis. Other embodiments provide for methods of prognosing inflammatory bowel disease including but not limited to Crohn's Disease and ulcerative colitis. Other embodiments provide for methods of treating inflammatory bowel disease including but not limited to Crohn's Disease and ulcerative colitis.
The methods may include the steps of obtaining a biological sample containing nucleic acid from the individual and determining the presence or absence of a SNP and/or a haplotype in the biological sample. The methods may further include correlating the presence or absence of the SNP and/or the haplotype to a genetic risk, a susceptibility for inflammatory bowel disease including but not limited to Crohn's Disease and ulcerative colitis, as described herein. The methods may also further include recording whether a genetic risk, susceptibility for inflammatory bowel disease including but not limited to Crohn's Disease and ulcerative colitis exists in the individual. The methods may also further include a prognosis of inflammatory bowel disease based upon the presence or absence of the SNP and/or haplotype. The methods may also further include a treatment of inflammatory bowel disease based upon the presence or absence of the SNP and/or haplotype.
In one embodiment, a method of the invention is practiced with whole blood, which can be obtained readily by non-invasive means and used to prepare genomic DNA, for example, for enzymatic amplification or automated sequencing. In another embodiment, a method of the invention is practiced with tissue obtained from an individual such as tissue obtained during surgery or biopsy procedures.
As disclosed herein, the inventors identified genetic and phenotypic associations with need for surgery and time to surgery within 5 years of diagnosis, and built a predictive model for need for surgery. The ability to identify patients with Crohn's disease (CD) who are at highest risk for rapid progression to surgery is invaluable in guiding initial therapeutic choices.
As further disclosed herein, the need for surgery was defined as intestinal resection within 5 years of diagnosis. Genotyping was performed on 1103 subjects using Illumina-based Genome-wide technology. Univariate and multivariate analyses tested genetic associations with need for surgery. Time to surgery was analyzed using Cox-proportional hazard. All analyses were performed by testing known IBD susceptibility loci (n=74) and also by performing a GWA study. Clinical and serologic immune phenotypes as measured by antibody sum were included in the logistic regression analyses and used to build a predictive model of need for surgery.
As further disclosed herein, the inventors found that surgery occurred within 5 years of diagnosis in 39% of total subjects. The median time to surgery was 6 months. In the univariate analyses, four known CD susceptibility loci (Table 2 herein) were associated with need for surgery within 5 years (p<0.05). The HLA region was the only known susceptibility loci associated with time to surgery (p=0.02). GWA revealed 16 putative loci associated with need for surgery and 51 with time to surgery at a level of nominal association at the genome-wide level (p<5×10−5). GWA identified SNPs at chromosome (chr.) 4q31 and at chr. 7p21 (containing the glucocorticoid induced transcript 1 gene) showed the most significant association with need for surgery within 5 years (Odds ratio [OR]=1.8; p=1.4×10−7) and time to surgery (Hazard Ratio [HR]=1.7; p=1.0×10−7), respectively. Two loci: rs6556412 (IL-12B, chr. 5q33) (OR=0.74; p<0.001) and the chr. 4q31 region (OR=1.51; p=0.003) remained independently associated with surgery in the logistic regression analyses. Small bowel location (OR=3.2; p<0.0001), age at diagnosis (OR=2.88; p<0.0001) and antibody sum (OR=1.64; p<0.0001) were also associated with need for surgery. A predictive model for surgery incorporating all 5 variables had an area under the curve of 0.770. Thus, the inventors found IL12B is associated with need for surgery in CD. The identification of genetic, clinical and immune risk factors that can predict need for surgery can help clinicians and patients choose appropriate treatments based on an individual's risk of early surgery.
Furthermore, the inventors performed additional studies with the objective to identify associations between known and novel CD loci with resective CD surgery, and develop predictive models for surgery using a combination of phenotypic, serologic and genetic variables. As further disclosed herein, the inventors found surgery occurred within 5 years in 21% of subjects at a median time of 12 months. Four susceptibility loci were associated with surgery (IL12B, C13orf31, 21q21, IBD5). GWA identified novel putative loci associated with surgery, 7q21 (CACNA2D1) and 16q23 (ZNRF1, LDHD). The most predictive model for surgery which included clinical, serologic and genetic factors had an AUC of 0.78. Forty percent of patients in the highest risk group progressed to surgery within 60 months in the best predictive model. In conclusion, the inventors found that progression to surgery is faster in CD patients with both genetic and clinical risk factors, and that IL12B is independently associated with need and time to surgery in CD patients.
In one embodiment, the present invention provides a method of predicting a susceptibility to a severe form of Crohn's disease in an individual by determining the presence or absence of one or more risk variants at the NDFIP1, C13orf31, IL12B, SMAD3, 21q21, IBD5, CACNA2D1, ZNRF1, and LDHD genetic loci, where the presence of one or more risk variants at the NDFIP1, C13orf31, IL12B, SMAD3, 21q21, IBD5, CACNA2D1, ZNRF1, and LDHD genetic loci is indicative of susceptibility to the severe form of Crohn's disease. In another embodiment, the one or more risk variants are listed in Tables 1, 2(a) and/or 2(b) herein. In another embodiment, the one or more risk variants are listed in Tables 4 and/or 5 herein. In another embodiment, the risk variants comprise genetic risk loci, clinical risk factors, serological risk markers, and combinations thereof. In another embodiment, the severe form of Crohn's disease is characterized by a rapid progression to a condition requiring surgery for treatment. In another embodiment, the individual has been diagnosed with Crohn's disease. In another embodiment, the condition requiring surgery for treatment occurs within a year of an initial diagnosis of Crohn's disease. In another embodiment, the condition requiring surgery for treatment occurs within 6 months of an initial diagnosis of Crohn's disease.
In another embodiment, the present invention provides a method of diagnosing a severe form of Crohn's disease in an individual by determining the presence or absence of one or more risk variants, and diagnosing the severe form of Crohn's disease in the individual based on the presence of one or more risk variants. In another embodiment, the risk variants comprise genetic risk loci, clinical risk factors, serological risk markers, and combinations thereof. In another embodiment, the severe form of Crohn's disease is characterized by a rapid progression to a condition requiring surgery for treatment.
In another embodiment, the present invention provides a method of treating a severe form of Crohn's disease in an individual by diagnosing a severe form of Crohn's disease and treating the individual.
A variety of methods can be used to determine the presence or absence of a variant allele or haplotype. As an example, enzymatic amplification of nucleic acid from an individual may be used to obtain nucleic acid for subsequent analysis. The presence or absence of a variant allele or haplotype may also be determined directly from the individual's nucleic acid without enzymatic amplification.
Analysis of the nucleic acid from an individual, whether amplified or not, may be performed using any of various techniques. Useful techniques include, without limitation, polymerase chain reaction based analysis, sequence analysis and electrophoretic analysis. As used herein, the term “nucleic acid” means a polynucleotide such as a single or double-stranded DNA or RNA molecule including, for example, genomic DNA, cDNA and mRNA. The term nucleic acid encompasses nucleic acid molecules of both natural and synthetic origin as well as molecules of linear, circular or branched configuration representing either the sense or antisense strand, or both, of a native nucleic acid molecule.
The presence or absence of a variant allele or haplotype may involve amplification of an individual's nucleic acid by the polymerase chain reaction. Use of the polymerase chain reaction for the amplification of nucleic acids is well known in the art (see, for example, Mullis et al. (Eds.), The Polymerase Chain Reaction, Birkhauser, Boston, (1994)).
A TaqmanB allelic discrimination assay available from Applied Biosystems may be useful for determining the presence or absence of a variant allele. In a TaqmanB allelic discrimination assay, a specific, fluorescent, dye-labeled probe for each allele is constructed. The probes contain different fluorescent reporter dyes such as FAM and VICTM to differentiate the amplification of each allele. In addition, each probe has a quencher dye at one end which quenches fluorescence by fluorescence resonant energy transfer (FRET). During PCR, each probe anneals specifically to complementary sequences in the nucleic acid from the individual. The 5′ nuclease activity of Taq polymerase is used to cleave only probe that hybridize to the allele. Cleavage separates the reporter dye from the quencher dye, resulting in increased fluorescence by the reporter dye. Thus, the fluorescence signal generated by PCR amplification indicates which alleles are present in the sample. Mismatches between a probe and allele reduce the efficiency of both probe hybridization and cleavage by Taq polymerase, resulting in little to no fluorescent signal. Improved specificity in allelic discrimination assays can be achieved by conjugating a DNA minor grove binder (MGB) group to a DNA probe as described, for example, in Kutyavin et al., “3′-minor groove binder-DNA probes increase sequence specificity at PCR extension temperature, “Nucleic Acids Research 28:655-661 (2000)). Minor grove binders include, but are not limited to, compounds such as dihydrocyclopyrroloindole tripeptide (DPI,).
Sequence analysis also may also be useful for determining the presence or absence of a variant allele or haplotype.
Restriction fragment length polymorphism (RFLP) analysis may also be useful for determining the presence or absence of a particular allele (Jarcho et al. in Dracopoli et al., Current Protocols in Human Genetics pages 2.7.1-2.7.5, John Wiley & Sons, New York; Innis et al., (Ed.), PCR Protocols, San Diego: Academic Press, Inc. (1990)). As used herein, restriction fragment length polymorphism analysis is any method for distinguishing genetic polymorphisms using a restriction enzyme, which is an endonuclease that catalyzes the degradation of nucleic acid and recognizes a specific base sequence, generally a palindrome or inverted repeat. One skilled in the art understands that the use of RFLP analysis depends upon an enzyme that can differentiate two alleles at a polymorphic site.
Allele-specific oligonucleotide hybridization may also be used to detect a disease-predisposing allele. Allele-specific oligonucleotide hybridization is based on the use of a labeled oligonucleotide probe having a sequence perfectly complementary, for example, to the sequence encompassing a disease-predisposing allele. Under appropriate conditions, the allele-specific probe hybridizes to a nucleic acid containing the disease-predisposing allele but does not hybridize to the one or more other alleles, which have one or more nucleotide mismatches as compared to the probe. If desired, a second allele-specific oligonucleotide probe that matches an alternate allele also can be used. Similarly, the technique of allele-specific oligonucleotide amplification can be used to selectively amplify, for example, a disease-predisposing allele by using an allele-specific oligonucleotide primer that is perfectly complementary to the nucleotide sequence of the disease-predisposing allele but which has one or more mismatches as compared to other alleles (Mullis et al., supra, (1994)). One skilled in the art understands that the one or more nucleotide mismatches that distinguish between the disease-predisposing allele and one or more other alleles are preferably located in the center of an allele-specific oligonucleotide primer to be used in allele-specific oligonucleotide hybridization. In contrast, an allele-specific oligonucleotide primer to be used in PCR amplification preferably contains the one or more nucleotide mismatches that distinguish between the disease-associated and other alleles at the 3′ end of the primer.
A heteroduplex mobility assay (HMA) is another well known assay that may be used to detect a SNP or a haplotype. HMA is useful for detecting the presence of a polymorphic sequence since a DNA duplex carrying a mismatch has reduced mobility in a polyacrylamide gel compared to the mobility of a perfectly base-paired duplex (Delwart et al., Science 262:1257-1261 (1993); White et al., Genomics 12:301-306 (1992)).
The technique of single strand conformational, polymorphism (SSCP) also may be used to detect the presence or absence of a SNP and/or a haplotype (see Hayashi, K., Methods Applic. 1:34-38 (1991)). This technique can be used to detect mutations based on differences in the secondary structure of single-strand DNA that produce an altered electrophoretic mobility upon non-denaturing gel electrophoresis. Polymorphic fragments are detected by comparison of the electrophoretic pattern of the test fragment to corresponding standard fragments containing known alleles.
Denaturing gradient gel electrophoresis (DGGE) also may be used to detect a SNP and/or a haplotype. In DGGE, double-stranded DNA is electrophoresed in a gel containing an increasing concentration of denaturant; double-stranded fragments made up of mismatched alleles have segments that melt more rapidly, causing such fragments to migrate differently as compared to perfectly complementary sequences (Sheffield et al., “Identifying DNA Polymorphisms by Denaturing Gradient Gel Electrophoresis” in Innis et al., supra, 1990).
Other molecular methods useful for determining the presence or absence of a SNP and/or a haplotype are known in the art and useful in the methods of the invention. Other well-known approaches for determining the presence or absence of a SNP and/or a haplotype include automated sequencing and RNAase mismatch techniques (Winter et al., Proc. Natl. Acad. Sci. 82:7575-7579 (1985)). Furthermore, one skilled in the art understands that, where the presence or absence of multiple alleles or haplotype(s) is to be determined, individual alleles can be detected by any combination of molecular methods. See, in general, Birren et al. (Eds.) Genome Analysis: A Laboratory Manual Volume 1 (Analyzing DNA) New York, Cold Spring Harbor Laboratory Press (1997). In addition, one skilled in the art understands that multiple alleles can be detected in individual reactions or in a single reaction (a “multiplex” assay). In view of the above, one skilled in the art realizes that the methods of the present invention for diagnosing or predicting susceptibility to or protection against CD in an individual may be practiced using one or any combination of the well-known assays described above or another art-recognized genetic assay.
EXAMPLES
The following examples are provided to better illustrate the claimed invention and are not to be interpreted as limiting the scope of the invention. To the extent that specific materials are mentioned, it is merely for purposes of illustration and is not intended to limit the invention. One skilled in the art may develop equivalent means or reactants without the exercise of inventive capacity and without departing from the scope of the invention.
Example 1







TABLE 1







Table 1: Univariate GWAS association (0-60 gwas sign SNPs n = 16)















CHR
SNP
BP
A1
TEST
NMISS
OR
STAT
P


















4
rs361147
153110013
C
ADD
1022
1.762
5.266
1.40E−07


8
rs1365032
75715655
A
ADD
1043
0.668
−4.404
1.07E−05


9
rs7029403
85897708
A
ADD
1043
0.6088
−4.387
1.15E−05


8
rs1365031
75718745
A
ADD
1043
0.6718
−4.323
1.54E−05


20
rs10460623
56638627
A
ADD
1042
1.614
4.294
1.76E−05


8
rs2016354
75722054
A
ADD
1043
0.6747
−4.283
1.84E−05


3
rs83615
172794423
G
ADD
1041
1.708
4.246
2.18E−05


13
rs17087682
70395009
C
ADD
1026
0.5474
−4.191
2.78E−05


4
rs7670729
84465114
A
ADD
1043
0.6516
−4.161
3.17E−05


2
rs10197959
230078358
A
ADD
1042
1.471
4.126
3.69E−05


14
rs7150586
68913992
A
ADD
1042
1.448
4.122
3.75E−05


1
rs1050492
224887123
A
ADD
1038
0.6549
−4.12
3.79E−05


14
rs10138313
68952145
G
ADD
1043
0.6915
−4.119
3.81E−05


12
rs1861872
14074193
G
ADD
1042
0.5062
−4.095
4.22E−05


21
rs2838735
45159710
G
ADD
1042
0.6882
−4.085
4.41E−05


5
rs34566
106628114
G
ADD
1042
0.6933
−4.08
4.51E−05


7
rs17152065
127861094
A
ADD
1043
0.5974
−4.073
4.65E−05


2
rs4364055
52907433
A
ADD
1042
0.5997
−4.07
4.71E−05


8
rs1581542
69376583
A
ADD
1043
0.6884
−4.056
5.00E−05









Example 2







TABLE 2





Univariate analysis chi square (0-60 top hits n = 74)







(a):















CHR
SNP
BP
A1
TEST
NMISS
OR
STAT
Pvalue





5
rs11167764
141459249
A
ADD
1043
0.6976
−2.975
0.002933


13
rs3764147
43355925
G
ADD
1043
1.277
2.449
0.01434


5
rs6556412
158719963
A
ADD
1043
1.212
2.079
0.03763


15
rs16950687
65251067
G
ADD
1043
1.229
2.063
0.03908










(b):













SNP
Chromosome
P value
OR
Gene of Interest






rs11167764
5
0.003
0.7
NDFIP1



rs3764147
13
0.01
1.3
C13orf31



rs6556412
5
0.04
1.2
IL12B



rs16950687
15
0.04
1.2
SMAD3









Example 3
Combination of Genetic, Clinical and Immune Markers Predict Surgery
The inventors identified genetic and phenotypic associations with need for surgery and time to surgery within 5 years of diagnosis, and built a predictive model for need for surgery. The ability to identify patients with Crohn's disease (CD) who are at highest risk for rapid progression to surgery is invaluable in guiding initial therapeutic choices.
The need for surgery was defined as intestinal resection within 5 years of diagnosis. Genotyping was performed on 1103 subjects using Illumina-based Genome-wide technology. Univariate and multivariate analyses tested genetic associations with need for surgery. Time to surgery was analyzed using Cox-proportional hazard. All analyses were performed by testing known IBD susceptibility loci (n=74) and also by performing a GWA study. Clinical and serologic immune phenotypes as measured by antibody sum were included in the logistic regression analyses and used to build a predictive model of need for surgery.
The inventors found that surgery occurred within 5 years of diagnosis in 39% of total subjects. The median time to surgery was 6 months. In the univariate analyses, four known CD susceptibility loci (Table 2 herein) were associated with need for surgery within 5 years (p<0.05). The HLA region was the only known susceptibility loci associated with time to surgery (p=0.02). GWA revealed 16 putative loci associated with need for surgery and 51 with time to surgery at a level of nominal association at the genome-wide level (p<5×10−5). GWA identified SNPs at chromosome (chr.) 4q31 and at chr. 7p21 (containing the glucocorticoid induced transcript 1 gene) showed the most significant association with need for surgery within 5 years (Odds ratio [OR]=1.8; p=1.4×10−7) and time to surgery (Hazard Ratio [HR]=1.7; p=1.0×10−7), respectively. Two loci: rs6556412 (IL-12B, chr. 5q33) (OR=0.74; p<0.001) and the chr. 4q31 region (OR=1.51; p=0.003) remained independently associated with surgery in the logistic regression analyses. Small bowel location (OR=3.2; p<0.0001), age at diagnosis (OR=2.88; p<0.0001) and antibody sum (OR=1.64; p<0.0001) were also associated with need for surgery. A predictive model for surgery incorporating all 5 variables had an area under the curve of 0.770. Thus, the inventors found IL12B is associated with need for surgery in CD. The identification of genetic, clinical and immune risk factors that can predict need for surgery can help clinicians and patients choose appropriate treatments based on an individual's risk of early surgery.
Example 4
The ability to identify patients with Crohn's disease (CD) at highest risk of surgery would be invaluable in guiding therapy. Genome-wide association (GWA) studies have identified multiple IBD loci with unknown phenotypic consequences. Methods: Surgery was defined as intestinal resection within 5 years of diagnosis. Genotyping was performed on 1115 subjects using Illumina-based Genome-wide technology. Univariate and multivariate analyses tested genetic associations with need for surgery. Time to surgery was analyzed using Cox-proportional hazard. Analyses were performed by testing known CD loci (n=71) and by performing a GWA study. Clinical and serologic variables were included to build predictive models for surgery. Results: Surgery occurred within 5 years in 21% of subjects at a median time of 12 months. Four susceptibility loci were associated with surgery (IL12B, C13orf31, 21q21, IBD5). GWA identified novel putative loci associated with surgery, 7q21 (CACNA2D1) and 16q23 (ZNRF1, LDHD). The most predictive model for surgery which included clinical, serologic and genetic factors had an AUC of 0.78. Forty percent of patients in the highest risk group progressed to surgery within 60 months in the best predictive model. Conclusion: Progression to surgery is faster in CD patients with both genetic and clinical risk factors. IL12B is independently associated with need and time to surgery in CD patients.
Example 5
Patient Population
A total of 1115 well characterized CD patients from both the Adult and Pediatric IBD Centers at CSMC, The Western Regional Research Alliance for Pediatric IBD and Wisconsin were included in this study. Surgery was defined as intestinal resection only for penetrating or stricturing CD. Perianal surgery and stricturoplasty were excluded. This study was approved by the IRB at all participating sites.
Example 6
Phenotyping
All data was collected by chart review and stored in a secured database. For the purpose of this study, phenotype was defined as all variables that were not genetic.
Clinical Phenotype:
These included demographic and clinical variables: age, gender, disease duration, age at diagnosis, date of diagnosis, disease location, type of disease complication (stricturing and/or internal penetrating disease), date of disease complication, type of CD surgery, time from diagnosis to CD surgery or time from diagnosis to last follow up in those patients who have not required surgery.
Immune Phenotype:
Serum was collected on all patients and analyzed at CSMC. Serum immune responses: anti-Saccharomyces Cereviciae antibodies (ASCA IgG and IgA), perinuclear anti-nuclear cytoplasmic antibody (pANCA), anti-flagellin (anti-CBir1), anti-outer membrane porin C (anti-OmpC) and anti-Pseudomonas fluorescens-associated sequence 12 (anti-12) were analyzed blinded to therapeutic responsiveness by ELISA as previously described (5, 25). Antibody sum score was calculated for each patient based on how many positive antibodies an individual patient had. Scores range from 0 to 5 ((ASCA IgA and IgG, anti-CBir1, anti-OMPc and anti-12), and for the purpose of analysis scores were then grouped into a score of 0 or 1, 2 or 3, and 4 or 5 positive. ANCA was analyzed separately given that ANCA has been shown to be negatively associated with CD resective surgery (26)
Example 7
Genotype
Genotyping was performed at the Medical Genetics Institute at CSMC using the Illumina Human610 platform (n=887) and Children's Hospital of Philadelphia (CHOP) using the Illumina Human550 platform (n=228) (27). Genotyping for the 3 common CD associated NOD2 SNPs (SNPs 8, 12 and 13) was performed using TaqMan MGB platform (28). For the purpose of quality control, SNPs with a minor allele frequency (MAF)<0.05, genotype failure rate>0.10, HWE p-value<10−5 and missing rate of >0.1 were excluded from the analysis. Following quality control, 486,926 SNPs were available in all data sets for analysis. Principal components (PC) analysis (using EIGENSTRAT) was conducted to examine population stratification (29). As the inventors examined the first 10 PCs with the default options provided by EIGENSTRAT, we observed that 66 patients were identified as outliers and the direction of the first 2 PCs shown in multidimensional scatter plot were separate. Thus, the inventors excluded the 66 patients identified as outliers, and corrected for population stratification by adding the first 2 PCs as covariates in the model of association analysis.
Example 8
Statistical Analysis
A. Need for Surgery within 60 Months
Genome-Wide Association Studies
The inventors' primary outcome was resective surgery within 60 months. In order to identify genetic factors that influence the need for surgery, they performed genome-wide single SNP association. For each SNP, an additive model was assumed. With a logistic regression model having 2 PCs and a SNP, PLINK was used to evaluate the association between the need for surgery and each single SNP. Genomic inflation factor λ of 1.00422 reveals no significant population stratification. The SNPs with a p-value<10−5 from the GWAS were considered as significant for this outcome and carried forward to additional analyses. For the 71 CD susceptibility loci (referred below as “top hits” that were reported in the latest published CD meta-analysis, the SNPs that had a p-value<0.05 in the analyses above were considered “significant” for association with need for surgery (20). NOD2, (SNP 8, 12 and 13) because of multiple disease predisposition alleles and prior literature, was tested separately using the chi-square test. Odds Ratio (OR) and 95% Confidence intervals (95% CI) were calculated by comparing the odds of surgery in the patients with a specific genotype versus those without the genotype.
Predictive Models of Need for Surgery
Models to predict need for surgery were built using multiple logistic regression, combining the following variables: A: Genetics; Top Hits p<0.05, Genome-wide SNPs p<10−5, and NOD2 status (any NOD2 SNP with a p≦0.05 was considered positive), B: Serologies; Antibody Sum Score 0, 1 or 2, 3 or 4, 5, and ANCA status (positive or negative) C: Clinical: age at diagnosis (<16 vs.>16 yrs), disease duration, gender, small bowel location. Using these variables, 5 model strategies were constructed:
I. Genetics only (excluding NOD 2 status)
II. Clinical variables only
III. Clinical+Serology
IV. Genetics+Clinical
V. Genetics (including NOD2 status)+Clinical+Serology
The final predictive model of the need for surgery for each strategic model was determined by using stepwise model selection method. The area under the Receiver Operating Characteristic curve (AUC) was used as a measure of the predictive performance of the final model. The likelihood based pseudo-R squared from the logistic regression model was used to measure the strength of association as well as the proportion of variance of the outcome accounted by the model's independent variables (30). The data analyses were generated using SAS/STAT software, Version 9.2 of the SAS System for Windows.
B. Time to Surgery
Survival Genome-Wide Association Analysis:
In order to determine influential genetic factors to time to surgery, survival genome-wide single SNP association was performed by assuming an additive genetic model for each SNP. The survival GWAS employed Cox regression modeling, utilizing 2PCs and SNPs as independent variables, and was performed by R package ‘survival’ (31). The SNPs with a p-value<10−5 from the GWAS were considered as “significant” for this outcome and carried forward for additional analyses. All hazard rations (HR) were expressed as a point estimate with 95% confidence interval. For the known 71 CD ‘SNPs’, association with time to surgery was considered significant if the p-value was ≦0.05. The AUCs for each of the models were compared to determine if there was statistical evidence of differing utilities between the models (32).
Predictive Models of Time to Surgery
Predictive models of time to surgery were built from the 5 strategic models described above. Patients who had surgery at diagnosis or within 3 months of diagnosis were excluded from this particular analysis. The final predictive model of time to surgery for each strategic model was determined by stepwise model selection method. In order to identify if disease progression is important for stratifying patients into more effective treatment paradigms, the patients were divided into 3 subgroups based on 25% and 75% quartiles of the risk score, which is the sum of variables in the final predictive model. Survival curves for each subgroup were plotted by Kaplan-Meier estimator of survival probability and were tested by the log-rank test to test whether the survival curves were significantly different among subgroups of patients.
Example 9
Patient Demographics
Table 3 illustrates the key demographic data for all patients. The mean age at diagnosis for this cohort was 15 years of age and more than 50% of the patients were diagnosed at 16 years of age or younger. Approximately 75% of patients had small bowel involvement and just over 50% had complicated disease behaviors as of last follow up or at time of surgery. Four hundred and forty-four of the 1115 (40%) had undergone resective surgery in our cohort with a median (range) time to surgery of 45.5 (0-516.8) months. A total of 219 or 21% of patients underwent surgery between diagnosis and 60 months of follow up with a median (range) of 12 (0-60) months. NOD2 ‘positivity’ (carrier for at least 1 of the 3 common CD associated NOD2 risk alleles) was found in 33% of CD patients consistent with previously published data (13-18). ANCA status was negative in 79% of patients, and Antibody Sum groups 0, 1, 2, 3 and 4, 5 were observed in 48%, 36% and 16%, respectively







TABLE 3





Patient Demographics

















Clinical Variable




Total Cohort N
1115



Gender: Males N (%)
597
(53)


Median disease duration at last follow up
38.1
[0-541.7]


(months [range])




Median age at diagnosis (years [range])
15
[1-77]


Diagnosis ≦16 years of age N (%)
632
(57)


Small bowel involvement N (%)
843
(76)


Stricturing and/or Internal Penetrating disease N (%)
454
(51)


Antibody Sum groups N (%)




0, 1
535
(48%)


2, 3
402
(36%)


4, 5
178
(16%)


NOD2 positive N (%)
321
(33%)









Example 10
Need for Respective Surgery within 60 Months
Single SNP Genome Wide Associations
From the targeted analysis of the 71 known CD susceptibility loci, 6 were found to be associated (p≦0.05) with need for surgery (Table 4). Table 5 lists the results of the single SNP associations (with a p value<5×10−5 identified in the genome-wide approach. The association with the need for surgery at the IL12B locus is observed in both the known susceptibility loci and genome-wide analyses, and remains significant when corrected for multiple tests in the known susceptibility loci (pc=0.001). No association was seen between any of the NOD2 SNPs and need for surgery.







TABLE 4







Known CD susceptibility loci: SNPs associated


with need for surgery (P < 0.05)
















Positional








Candidate







Risk
Gene (s)


P


SNP
Loci
Allele*
of Interest
OR
95% CI
value





rs6556412
5q33
A
IL12B
1.6
1.3-2.0
1.478 × 10−5


(SEQ. ID.








NO.: 1)








rs3936503
10p11
G
CREM
0.7
0.6-0.9
0.0066


rs359457
5q35
A
CPEB4
0.8
0.6-1.0
0.0155


rs3764147
13q14
G
C13orf31
1.3
1.0-1.6
0.0219


rs1736148
21q21
G
—
1.3
1.0-1.6
0.0357


rs4788084
16p11
G
IL27,
0.8
0.6-1.0
0.0366





SH2B1,








EIF3C,








LAT, CD19





— No gene of interest identified


*Risk allele as defined as risk for CD













TABLE 5







Genome-wide analysis:: SNPs associated with need for surgery (p < 5.0 × 10−5)
















Positional








candidate







Risk
Gene(s)


P


SNP
Loci
Allele
of Interest
OR
95% CI
value





rs11978472
7q21
A
CACNA2D1
0.6
0.4-0.7
8.418 × 10−7


rs2253755
10q26
A
PLEKHA1,
0.5
0.4-0.7
 7.13 × 10−6





HTRA1,








ARMS2





rs11863071
16q24
G
—
1.8
1.4-2.3
8.713 × 10−6


rs6556412
5q33
A
IL12B *
1.6
1.3-2.0
1.478 × 10−5


rs12520590
5q33
C
GALNT1,
1.7
1.3-2.1
1.724 × 10−5





SAP30L





rs13403289
2q31
A
ZNF385B,
0.6
0.4-0.8
1.924 × 10−5





SESTD1





rs2226674
21q21
G
—
0.6
0.4-0.7
2.208 × 10−5


rs11235508
11q13
G
CLPB, PDE2A
1.9
1.4-2.6
2.518 × 10−5


rs11647106
16q24
G
—
1.8
1.3-2.3
2.769 × 10−5


rs2295655
14q32
A
miRNA **
1.6
1.3-2.0
4.016 × 10−5


rs4709724
6q26
G
QK1
0.6
0.5-0.8
4.086 × 10−5


rs10955078
8q22
G
SDC2, PGCP
1.6
1.3-2.0
4.217 × 10−5


rs1528934
7q21
A
ZNF804B
1.6
1.3-2.0
4.406 × 10−5


rs2765122
13q12
G
MIPEP, PCOTH,
0.5
0.4-0.7
 4.8 × 10−5





SPATA13,








C1QTNF9B





rs550619
2p24
G
APOB
1.8
1.4-2.5
4.919 × 10−5





* Known IBD susceptibility locus


** miRNA—micro-RNA cluster.






Predictive Models of Need for Surgery

Five different predictive models on the need for surgery were developed using logistic multiple regression. Model I (Genetics only but excluding NOD2) (Table 6) examined the significance of known CD susceptibility loci (p≦0.05) (table 2) together with the genome-wide identified loci (p<10−5) (Table 5). IL12B remained independently associated with need for surgery (p=0.0002).
Model II (clinical only) examined the associations of demographics and clinical variables together (age at diagnosis, gender and small bowel disease location) with need for surgery within 60 months of diagnosis. Older age at diagnosis (OR [95% CI]=1.9 [1.4-2.5] p=7.83e-05) and small bowel disease (OR [95% CI]=4.4 [2.6-7.4] p=2.6e-08) were associated with need for surgery. In MODEL III (clinical+serologies); older age at diagnosis (OR [95% CI]=1.8 [1.3-2.5] p=0.0002), small bowel disease (OR [95% CI]=3.5 [2.0-5.9] p=5.41e-06) were associated with need for surgery. Low antibody sum score of 0, 1 was protective against surgery (OR [95% CI]=0.6 [0.4-0.8] p=0.001). In Model IV (genetics+clinical), all loci from Model 1, with the exception of the 16p11, (IL27) locus, remained significantly associated with need for surgery as was age at diagnosis and small bowel disease location, with odds ratios similar to those seen in models I and II. Table 7 illustrates the logistic regression for Model V (Genetics+NOD2 status+clinical+serologies). NOD2 status was not associated with need for surgery. Low antibody sum was protective against surgery. IL12B remained a significant predictor of surgery throughout all models. Table 8 compares the AUC and pseudo R2 for the 5 predictive models. The inventors did also look at the AUC and pseudo R2 for a model that included disease complication (internal penetrating and or stricturing disease behavior) as part of the clinical variables in addition to genetics and serologies. As expected, given the known association between disease complication and surgery, the AUC (95% CI) was the highest for this additional model at 0.83 (0.81-0.86) and pseudo R2 of 0.23.
They then compared the AUCs for each of the models to see if there was statistical evidence of differing utilities between the models: Model 1 (genetics only) vs. Model 2 (clinical only); p=0.03, Model 1 (genetics only) vs. Model 4 (genetics+clinical); p=0.04, Model 2 vs. 4; p=1.5×10−5 and Model 3 (clinical+serologies) vs. 4; p=0.002. In contrast, there was no difference between Models 1 or 2 vs. 3 or between Models 4 and 5 (genetics+NOD2+clinical+serologies). This suggests that a model that includes both genetics and clinical is more predictive than genetics alone or clinical alone Serologies or NOD2 status did not add significantly to the prediction of the model.







TABLE 6







Model I: Genetics Only Logistic Regression













Top Hit







SNP (TH)







or
Gene






GWAS
of





SNP
SNP (GW)
Interest
OR
95% CI
P value















rs6556412
TH
IL12B
1.5
1.2-1.9
0.0002


(SEQ. ID.







NO.: 1)







rs359457
TH
CPEB4
0.7
0.6-0.9
0.004


rs11978472
GW
CACNA2D1
0.5
0.4-0.7
1.1135 × 10−6


rs3936503
TH
CREM
0.7
0.6-0.9
0.0144


rs2253755
GW
PLEKHA1
0.5
0.4-0.7
 5.711 × 10−5


rs3764147
TH
C13orf31
1.3
1.0-1.6
0.0402


rs4788084
TH
IL27
0.8
0.6-1.0
0.0577


rs11863071
GW
—
1.8
1.4-2.3
3.7863 × 10−5





— No gene of interest identified













TABLE 7







Model V (genetics + NOD2 status + clinical + serologies)


Logistic Regression












Independent Variable
OR
95% CI
P value






Genetics*






SNP (gene of interest)






rs6556412 (IL12B)
1.6
1.2-2.0
0.0007



rs359457 (CPEB4)
0.6
0.5-0.9
0.0016



rs11978472 (CACNA2D1)
0.6
0.4-0.7
1.3364 × 10−5



rs3936503 (CREM)
0.7
0.5-0.9
0.0205



rs2253755 (PLEKHA1)
0.5
0.3-0.6
1.6205 × 10−6



rs11863071(16q24)
1.6
1.2-2.2
0.0025



rs1736148 (21q21)
1.4
1.1-1.9
0.0072



Clinical






Age at diagnosis
2.1
1.4-3.1
5.5603 × 10−5



Small bowel disease
3.3
1.8-6.0
7.9579 × 10−5



Serology






AB sum 0, 1
0.5
0.4-0.8
0.0019





*See Table 4 for Top Hits vs. GWAS origin of SNP













TABLE 8







AUC and pseudo R2 for the 5 models










Logistic Regression Model
AUC
95% CI
Pseudo R2














I.
Known CD susceptibility loci and
0.71
0.67-0.75
0.0963



genome-wide identified loci





II.
Clinical only: SB, gender, Age
0.66
0.62-0.69
0.0586



at Diagnosis,





III.
Clinical + Serologies
0.69
0.65-0.72
0.0721


IV.
Genetics + Clinical
0.76
0.73-0.80
0.1465


V.
Genetics + NOD2 status +
0.78
0.74-0.81
0.1610



Clinical + Serologies









Example 11
Time to Respective Surgery
Single SNP Genome Wide Associations
The total number of patients included in the time to surgery analyses was 983 after principal component analysis and after exclusion of patients who underwent surgery at or within 3 months of diagnosis. The known CD susceptibility loci and novel SNPs from the genome-wide analyses associated with time to surgery are shown in Tables 9 and 10.







TABLE 9







Known CD susceptibility loci: SNPs associated


with time to surgery (P < 0.05)
















Gene (s)







Risk
of
Hazard

P


SNP
Loci
Allele
interest
Ratio
95% CI
value





rs6556412
5q33
A
IL12B
1.5
1.2-1.9
0.0006


rs12521868
5q31
A
SLC22A4,
1.3
1.0-1.6
0.0442





SLC22A5,








IRF1, IL3





rs1736148
21q21
G
—
1.3
1.0-1.6
0.0495


rs3764147
13q14
G
C13orf31
1.3
1.0-1.6
0.0503
















TABLE 10







Genome-wide analysis: SNPs associated with time to surgery (p < 5.0 × 10−5)
















Gene (s)







Risk
of
Hazard

P


SNP
Loci
Allele
Interest
Ratio
95% CI
value





rs7195303
16q23
G
ZNRF1, LDHD,
2.1
1.5-2.8
 9.06 × 10−6





ZFP1, BCAR1,








CTRB1/2





rs471073
15q25
A
AKAP13, KLHL25,
1.8
1.4-2.3
1.6973 × 10−5





MIR1276





rs9346964
6q26
A
QK1
1.7
1.3-2.1
1.8184 × 10−5


rs6469010
8q23
G
ZFPM2
1.8
1.4-2.4
1.9105 × 10−5


rs4901140
14q21
G
C14orf25, TTC6
1.7
1.4-2.3
1.9378 × 10−5


rs11583755
1p36
A
THAP3, TAS1R1,
0.6
0.4-0.7
2.2889 × 10−5





PLEKHG5





rs11235508
11q13
G
CLPB, PDE2A
1.9
1.4-2.5
2.5083 × 10−5


rs1998828
13q21
A
—
1.6
1.3-2.0
2.7091 × 10−5


rs2894207
6p21
G
HLA**
1.6
1.3-2.1
2.8892 × 10−5


rs9548517
13q13
A
FREM2, STOML3
1.8
1.4-2.4
3.0068 × 10−5


rs2765122
13q12
G
PCOTH, SPATA13,
0.5
0.3-0.7
3. 8064 × 10−5 





C1QTNF9B,








MIPEP





rs13403289
2q31
A
ZNF385B, SESTD1
0.6
0.5-0.8
4.0984 × 10−5


rs12531232
7q21
A
ZNF804B
1.6
1.3-2.0
4.3313 × 10−5


rs823559
12q23
A
SLC5A8, ANO4
2.0
1.4-2.8
4.8477 × 10−5


rs6957717
7
A
SKAP2, C7orf71
0.6
0.4-0.7
4.9161 × 10−5





**Known CD susceptibility locus






Predictive Models of Need for Surgery

Predictive models of time to surgery were developed using the same 5 model strategies outlined earlier for predicting the need for surgery. The goal of these analyses were to first determine using Cox Hazard Regression modeling the variables that were independently associated with progression to surgery and then to use log rank testing to compare the survival curves for different risk strata within each model in order to determine which patients progressed to surgery faster. The 3 risk strata were derived based on the sum of the variables in the final predictive models: strata 1=≦the 25% quartile of the sum of variables, strata 2=between 25% and 75% quartiles of the sum of variables and strata 3=≧75% quartile of the sum of variables. Each clinical and serology variable gets a score of 1 or 0 and an additive genetic model was adopted. Table 9 shows the hazard ratios for the genetics only model (Model I) and FIG. 1A illustrates the survival curves for the 3 risk strata in this model. The proportion of patients in the lowest strata score that progressed to surgery within 60 months was significantly less (15%) than the medium (22%) and highest strata (36%) (log rank test: p=1.6×10−10). As compared to the predictors of need for surgery for model II (clinical only), only small bowel predicted time to surgery (HR [95% CI] 3.3 [1.9-5.6] p=1.28×10−5) and age at diagnosis did not. For model IV (genetics+clinical) all 4 SNPs from the genetics only model along with small bowel disease location and age at diagnosis were associated with time to surgery (HR [95% CI]=1.5 [1.1-2.0] p=0.02 and 3.2 [1.9-5.4], p=2.22×105, respectively). Table 10 shows the hazard ratios for model V (genetics+NOD2+clinical+serologies). Antibody sum score 2, 3, NOD2, 3 other loci (including IL12B) in addition to small bowel disease location and age at diagnosis were all associated with time to surgery. FIGS. 1B and 1C illustrate the survival curves for the 3 strata for model IV (clinical+genetics) and model V (genetics+NOD2+clinical+serologies). In all 3 models, patients in the highest risk group progressed to surgery faster (p<0.0001). For all 3 models depicted in figure form, there is a greater than 20% difference in frequency of progression to surgery between the lowest risk and highest risk strata.







TABLE 11







Model I: Genetics only; Cox proportional Regression













Top Hit







SNP (TH)







or







GWAS
Gene (s) of





SNP
SNP (GW)
Interest
HR
95% CI
P value





rs6556412
TH
IL12B
1.5
1.0-1.6
0.0006


rs12521868
TH
IBD5 SLC22A4,
1.3
1.2-1.9
0.0318




SLC22A5





rs7195303
GW
ZNRF1, LDHD
2.1
1.5-2.9
10 × 10−5


rs1736148
TH
21q21
1.3
1.0-1.6
0.0310
















TABLE 12







Model V: Genetics + NOD2 + clinical + serologies;


Cox proportional regression










Independent Variable
HR
95% CI
P value





Genetics





SNP and gene of interest





rs6556412 (IL12B)
1.5
1.2-2.9
0.0006


rs7195303 (ZNRF1, LDHD)
2.2
1.5-3.1
3.0456 × 10−5


rs1736148 (21q21)
1.4
1.1-1.8
0.0042


NOD2 positive
1.5
1.1-2.2
0.0150


Clinical





Age at Diagnosis
1.5
1.1-2.2
0.0135


Small bowel location
2.4
1.4-4.3
0.0019


Serologies





AB Sum 2, 3
1.5
1.1-2.1
0.0226









While the description above refers to particular embodiments of the present invention, it should be readily apparent to people of ordinary skill in the art that a number of modifications may be made without departing from the spirit thereof. The presently disclosed embodiments are, therefore, to be considered in all respects as illustrative and not restrictive.
The various methods and techniques described above provide a number of ways to carry out the invention. Of course, it is to be understood that not necessarily all objectives or advantages described may be achieved in accordance with any particular embodiment described herein. Thus, for example, those skilled in the art will recognize that the methods can be performed in a manner that achieves or optimizes one advantage or group of advantages as taught herein without necessarily achieving other objectives or advantages as may be taught or suggested herein. A variety of advantageous and disadvantageous alternatives are mentioned herein. It is to be understood that some preferred embodiments specifically include one, another, or several advantageous features, while others specifically exclude one, another, or several disadvantageous features, while still others specifically mitigate a present disadvantageous feature by inclusion of one, another, or several advantageous features.
Furthermore, the skilled artisan will recognize the applicability of various features from different embodiments. Similarly, the various elements, features and steps discussed above, as well as other known equivalents for each such element, feature or step, can be mixed and matched by one of ordinary skill in this art to perform methods in accordance with principles described herein. Among the various elements, features, and steps some will be specifically included and others specifically excluded in diverse embodiments.
Although the invention has been disclosed in the context of certain embodiments and examples, it will be understood by those skilled in the art that the embodiments of the invention extend beyond the specifically disclosed embodiments to other alternative embodiments and/or uses and modifications and equivalents thereof.
Many variations and alternative elements have been disclosed in embodiments of the present invention. Still further variations and alternate elements will be apparent to one of skill in the art. Among these variations, without limitation, are the selection of constituent modules for the inventive compositions, and the diseases and other clinical conditions that may be diagnosed, prognosed or treated therewith. Various embodiments of the invention can specifically include or exclude any of these variations or elements.
In some embodiments, the numbers expressing quantities of ingredients, properties such as concentration, reaction conditions, and so forth, used to describe and claim certain embodiments of the invention are to be understood as being modified in some instances by the term “about.” Accordingly, in some embodiments, the numerical parameters set forth in the written description and attached claims are approximations that can vary depending upon the desired properties sought to be obtained by a particular embodiment. In some embodiments, the numerical parameters should be construed in light of the number of reported significant digits and by applying ordinary rounding techniques. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of some embodiments of the invention are approximations, the numerical values set forth in the specific examples are reported as precisely as practicable. The numerical values presented in some embodiments of the invention may contain certain errors necessarily resulting from the standard deviation found in their respective testing measurements.
In some embodiments, the terms “a” and “an” and “the” and similar references used in the context of describing a particular embodiment of the invention (especially in the context of certain of the following claims) can be construed to cover both the singular and the plural. The recitation of ranges of values herein is merely intended to serve as a shorthand method of referring individually to each separate value falling within the range. Unless otherwise indicated herein, each individual value is incorporated into the specification as if it were individually recited herein. All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples, or exemplary language (e.g. “such as”) provided with respect to certain embodiments herein is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention otherwise claimed. No language in the specification should be construed as indicating any non-claimed element essential to the practice of the invention.
Groupings of alternative elements or embodiments of the invention disclosed herein are not to be construed as limitations. Each group member can be referred to and claimed individually or in any combination with other members of the group or other elements found herein. One or more members of a group can be included in, or deleted from, a group for reasons of convenience and/or patentability. When any such inclusion or deletion occurs, the specification is herein deemed to contain the group as modified thus fulfilling the written description of all Markush groups used in the appended claims.
Preferred embodiments of this invention are described herein, including the best mode known to the inventors for carrying out the invention. Variations on those preferred embodiments will become apparent to those of ordinary skill in the art upon reading the foregoing description. It is contemplated that skilled artisans can employ such variations as appropriate, and the invention can be practiced otherwise than specifically described herein. Accordingly, many embodiments of this invention include all modifications and equivalents of the subject matter recited in the claims appended hereto as permitted by applicable law. Moreover, any combination of the above-described elements in all possible variations thereof is encompassed by the invention unless otherwise indicated herein or otherwise clearly contradicted by context.
Furthermore, numerous references have been made to patents and printed publications throughout this specification. Each of the above cited references and printed publications are herein individually incorporated by reference in their entirety.
In closing, it is to be understood that the embodiments of the invention disclosed herein are illustrative of the principles of the present invention. Other modifications that can be employed can be within the scope of the invention. Thus, by way of example, but not of limitation, alternative configurations of the present invention can be utilized in accordance with the teachings herein. Accordingly, embodiments of the present invention are not limited to that precisely as shown and described.
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## Claims

1. A method, comprising:
providing a sample from a human with Crohn's Disease;
utilizing an allelic discrimination assay or an oligonucleotide hybridization assay to analyze the sample for an “A” allele at position 513 of SEQ ID NO: 1;
detecting the “A” allele at position 513 of SEQ ID NO: 1 in the sample;
determining a need for surgical intervention in the human having the “A” allele at position 513 of SEQ ID NO: 1 in the sample; and
treating the human by performing on the human determined to need surgical intervention a surgical intervention comprising intestinal resection.

2. The method of claim 1, further comprising determining the presence of two or more factors selected from the group consisting of clinical factors, serologic factors, genetic risk factors and combinations thereof.

3. The method of claim 1, further comprising determining the presence of anti-ASCA, pANCA, anti-Cbirl, anti-OmpC and/or anti-12.

4. The method of claim 1, further comprising detecting an “A” allele at position 251 of SEQ ID NO: 7.

5. The method of claim 1, further comprising detecting the presence of the “A” allele at position 201 of SEQ ID NO: 2, the “G” allele at position 301 of SEQ ID NO: 3, the “G” allele at position 251 of SEQ ID NO: 4, the “G” allele at position 401 of SEQ ID NO: 5, the “A” allele at position 501 of SEQ ID NO: 6, the “A” allele at position 251 of SEQ ID NO: 7, and the “G” allele at position 2156 of SEQ ID NO: 8.

6. The method of claim 1, further comprising detecting the “A” allele at position 201 of SEQ ID NO: 2.

7. The method of claim 1, further comprising detecting the “G” allele at position 301 of SEQ ID NO: 3.

8. The method of claim 1, further comprising detecting the “G” allele at position 251 of SEQ ID NO: 4.

9. The method of claim 1, further comprising detecting the “G” allele at position 401 of SEQ ID NO: 5.

10. The method of claim 1, further comprising detecting the “A” allele at position 501 of SEQ ID NO: 6.

11. The method of claim 1, further comprising detecting the “G” allele at position 2156 of SEQ ID NO: 8.

12. A method, comprising:
utilizing an allelic discrimination assay or an oligonucleotide hybridization assay to detect in a sample from a human with Crohn's disease, an “A” allele at position 513 of SEQ ID NO: 1;
identifying one or more risk factors selected from the group consisting of a diagnosis of Crohn's disease in the small bowel location, age of diagnosis, and risk serological factors;
prognosticating Crohn's disease with requiring surgery for treatment in the human having the “A” allele at position 513 of SEQ ID NO: 1 and the identified one or more risk factors; and
treating the human by performing surgery on the human prognosed with Crohn's disease requiring surgery for treatment, wherein the surgery comprises intestinal resection.

13. The method of claim 12, further comprising detecting one or more alleles selected from the group consisting of the “A” allele at position 201 of SEQ ID NO: 2, the “G” allele at position 301 of SEQ ID NO: 3, the “G” allele at position 251 of SEQ ID NO: 4, the “G” allele at position 401 of SEQ ID NO: 5, the “A” allele at position 501 of SEQ ID NO: 6, the “A” allele at position 251 of SEQ ID NO: 7, and the “G” allele at position 2156 of SEQ ID NO: 8.

14. The method of claim 12, wherein the risk serological factors are selected from the group consisting of anti-ASCA, pANCA, anti-Cbirl, anti-OmpC and anti-12.

15. The method of claim 12, further comprising detecting the presence of the “A” allele at position 201 of SEQ ID NO: 2, the “G” allele at position 301 of SEQ ID NO: 3, the “G” allele at position 251 of SEQ ID NO: 4, the “G” allele at position 401 of SEQ ID NO: 5, the “A” allele at position 501 of SEQ ID NO: 6, the “A” allele at position 251 of SEQ ID NO: 7, and the “G” allele at position 2156 of SEQ ID NO: 8.

16. The method of claim 12, further comprising detecting the “A” allele at position 251 of SEQ ID NO: 7.