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Gene–gene and gene–environment interactions in ulcerative colitis

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Abstract

Genome-wide association studies (GWAS) have identified at least 133 ulcerative colitis (UC) associated loci. The role of genetic factors in clinical practice is not clearly defined. The relevance of genetic variants to disease pathogenesis is still uncertain because of not characterized gene–gene and gene–environment interactions. We examined the predictive value of combining the 133 UC risk loci with genetic interactions in an ongoing inflammatory bowel disease (IBD) GWAS. The Wellcome Trust Case–Control Consortium (WTCCC) IBD GWAS was used as a replication cohort. We applied logic regression (LR), a novel adaptive regression methodology, to search for high-order interactions. Exploratory genotype correlations with UC sub-phenotypes [extent of disease, need of surgery, age of onset, extra-intestinal manifestations and primary sclerosing cholangitis (PSC)] were conducted. The combination of 133 UC loci yielded good UC risk predictability [area under the curve (AUC) of 0.86]. A higher cumulative allele score predicted higher UC risk. Through LR, several lines of evidence for genetic interactions were identified and successfully replicated in the WTCCC cohort. The genetic interactions combined with the gene-smoking interaction significantly improved predictability in the model (AUC, from 0.86 to 0.89, P = 3.26E−05). Explained UC variance increased from 37 to 42 % after adding the interaction terms. A within case analysis found suggested genetic association with PSC. Our study demonstrates that the LR methodology allows the identification and replication of high-order genetic interactions in UC GWAS datasets. UC risk can be predicted by a 133 loci and improved by adding gene–gene and gene–environment interactions.

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Acknowledgments

We thank the patients and the controls for participating in this study. We acknowledge the Feinstein Institute for Medical Research of the North Shore-Long Island Jewish Health System for Illumina Genotyping BeadChip processing. This study makes use of data generated by the Wellcome Trust Case Control Consortium. A full list of the investigators who contributed to the generation of the data is available from http://www.wtccc.org.uk. Funding for the project was provided by the Wellcome Trust under award 076113.

Funding

T32 DK083251, NIH—National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) (M-H W, CF); DK068112 (J-PA), DK062420 (RHD) and DK076025 (RHD); AG030653 (MIK); a Crohn’s and Colitis Foundation of America Senior Research Award (RHD); and funds generously provided by Kenneth and Jennifer Rainin, the Wesley Roj and Douglas Durham Roj Endowed Fund, and Gerald and Nancy Goldberg.

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Correspondence to Jean-Paul Achkar.

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439_2013_1395_MOESM1_ESM.tif

Supplementary Figure 2A Tree1 and its genetic interactions illustrated by further pairwise stratified analyses (TIFF 89 kb)

Supplementary Figure 2B Tree2 and its genetic interactions illustrated by further stratified analyses (TIFF 91 kb)

439_2013_1395_MOESM3_ESM.tif

Supplementary Figure 2C Tree3 and its genetic interactions illustrated by further pairwise stratified analyses (TIFF 91 kb)

Supplementary Figure 2D Tree4 and its genetic interactions illustrated by further stratified analyses (TIFF 150 kb)

439_2013_1395_MOESM5_ESM.tif

Supplementary Figure 2E Tree5 and its gene–gene and gene-smoking interactions illustrated by further stratified analyses (TIFF 77 kb)

Supplementary material 6 (DOC 207 kb)

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Wang, MH., Fiocchi, C., Zhu, X. et al. Gene–gene and gene–environment interactions in ulcerative colitis. Hum Genet 133, 547–558 (2014). https://doi.org/10.1007/s00439-013-1395-z

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