Publikation
Genome-wide comparative analysis of atopic dermatitis and psoriasis gives insight into opposing genetic mechanisms
Wissenschaftlicher Artikel/Review - 08.01.2015
Baurecht Hansjörg, Mrowietz Ulrich, Nair Rajan, Nöthen Markus M, Novak Natalija, O'Regan Grainne M, Schreiber Stefan, Smith Catherine, Strauch Konstantin, Stuart Philip E, Trembath Richard, Tsoi Lam C, Weichenthal Michael, Barker Jonathan, Elder James T, Weidinger Stephan, Cordell Heather J, Morris Derek W, McLean W H Irwin, Marenholz Ingo, Hotze Melanie, Brand Stephan, Büning Carsten, Cormican Paul, Corvin Aiden, Ellinghaus David, Ellinghaus Eva, Esparza-Gordillo Jorge, Fölster-Holst Regina, Franke Andre, Gieger Christian, Hübner Norbert, Illig Thomas, Irvine Alan D, Kabesch Michael, Lee Young A E, Lieb Wolfgang, Brown Sara J
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Kurzbeschreibung/Zielsetzung
Atopic dermatitis and psoriasis are the two most common immune-mediated inflammatory disorders affecting the skin. Genome-wide studies demonstrate a high degree of genetic overlap, but these diseases have mutually exclusive clinical phenotypes and opposing immune mechanisms. Despite their prevalence, atopic dermatitis and psoriasis very rarely co-occur within one individual. By utilizing genome-wide association study and ImmunoChip data from >19,000 individuals and methodologies developed from meta-analysis, we have identified opposing risk alleles at shared loci as well as independent disease-specific loci within the epidermal differentiation complex (chromosome 1q21.3), the Th2 locus control region (chromosome 5q31.1), and the major histocompatibility complex (chromosome 6p21-22). We further identified previously unreported pleiotropic alleles with opposing effects on atopic dermatitis and psoriasis risk in PRKRA and ANXA6/TNIP1. In contrast, there was no evidence for shared loci with effects operating in the same direction on both diseases. Our results show that atopic dermatitis and psoriasis have distinct genetic mechanisms with opposing effects in shared pathways influencing epidermal differentiation and immune response. The statistical analysis methods developed in the conduct of this study have produced additional insight from previously published data sets. The approach is likely to be applicable to the investigation of the genetic basis of other complex traits with overlapping and distinct clinical features.