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Sökning: WFRF:(Van Steen Kristel) > Örebro universitet

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1.
  • Goyette, Philippe, et al. (författare)
  • High-density mapping of the MHC identifies a shared role for HLA-DRB1*01 : 03 in inflammatory bowel diseases and heterozygous advantage in ulcerative colitis
  • 2015
  • Ingår i: Nature Genetics. - New York, USA : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 47:2, s. 172-179
  • Tidskriftsartikel (refereegranskat)abstract
    • Genome-wide association studies of the related chronic inflammatory bowel diseases (IBD) known as Crohn's disease and ulcerative colitis have shown strong evidence of association to the major histocompatibility complex (MHC). This region encodes a large number of immunological candidates, including the antigen-presenting classical human leukocyte antigen (HLA) molecules. Studies in IBD have indicated that multiple independent associations exist at HLA and non-HLA genes, but they have lacked the statistical power to define the architecture of association and causal alleles. To address this, we performed high-density SNP typing of the MHC in >32,000 individuals with IBD, implicating multiple HLA alleles, with a primary role for HLA-DRB1*01:03 in both Crohn's disease and ulcerative colitis. Noteworthy differences were observed between these diseases, including a predominant role for class II HLA variants and heterozygous advantage observed in ulcerative colitis, suggesting an important role of the adaptive immune response in the colonic environment in the pathogenesis of IBD.
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2.
  • Wei, Zhi, et al. (författare)
  • Large sample size, wide variant spectrum, and advanced machine-learning technique boost risk prediction for inflammatory bowel disease
  • 2013
  • Ingår i: American Journal of Human Genetics. - : University of Chicago Press. - 0002-9297 .- 1537-6605. ; 92:6, s. 1008-12
  • Tidskriftsartikel (refereegranskat)abstract
    • We performed risk assessment for Crohn's disease (CD) and ulcerative colitis (UC), the two common forms of inflammatory bowel disease (IBD), by using data from the International IBD Genetics Consortium's Immunochip project. This data set contains ~17,000 CD cases, ~13,000 UC cases, and ~22,000 controls from 15 European countries typed on the Immunochip. This custom chip provides a more comprehensive catalog of the most promising candidate variants by picking up the remaining common variants and certain rare variants that were missed in the first generation of GWAS. Given this unprecedented large sample size and wide variant spectrum, we employed the most recent machine-learning techniques to build optimal predictive models. Our final predictive models achieved areas under the curve (AUCs) of 0.86 and 0.83 for CD and UC, respectively, in an independent evaluation. To our knowledge, this is the best prediction performance ever reported for CD and UC to date.
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