Paper Chase is a research database designed to offer abstracts of research articles published in journals that have a highly rated impact factor as determined by ISI Impact Factor and PageRank. Abstracts are organized by date, with the most recently published papers listed first.
Home/Research/Paper Chase/Deep resequencing of GWAS loci identifies independent rare variants associated with inflammatory bowel disease.
Deep resequencing of GWAS loci identifies independent rare variants associated with inflammatory bowel disease.
Nat. Genet..10 09, 2011;43(11):1066-73.
Rivas MA, Beaudoin M, Gardet A, Stevens C, Sharma Y, Zhang CK, Boucher G, Ripke S, Ellinghaus D, Burtt N, Fennell T, Kirby A, Latiano A, Goyette P, Green T, Halfvarson J, Haritunians T, Korn JM, Kuruvilla F, Lagacé C, Neale B, Lo KS, Schumm P, Törkvist L, Dubinsky MC, Brant SR, Silverberg MS, Duerr RH, Altshuler D, Gabriel S, Lettre G, Franke A, D'Amato M, McGovern DP, Cho JH, Rioux JD, Xavier RJ, Daly MJ.
Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, USA. firstname.lastname@example.org
More than 1,000 susceptibility loci have been identified through genome-wide association studies (GWAS) of common variants; however, the specific genes and full allelic spectrum of causal variants underlying these findings have not yet been defined. Here we used pooled next-generation sequencing to study 56 genes from regions associated with Crohn's disease in 350 cases and 350 controls. Through follow-up genotyping of 70 rare and low-frequency protein-altering variants in nine independent case-control series (16,054 Crohn's disease cases, 12,153 ulcerative colitis cases and 17,575 healthy controls), we identified four additional independent risk factors in NOD2, two additional protective variants in IL23R, a highly significant association with a protective splice variant in CARD9 (P < 1 × 10(-16), odds ratio ≈ 0.29) and additional associations with coding variants in IL18RAP, CUL2, C1orf106, PTPN22 and MUC19. We extend the results of successful GWAS by identifying new, rare and probably functional variants that could aid functional experiments and predictive models.