Details

Autor(en) / Beteiligte

• STAHL, Eli A
• WEGMANN, Daniel
• GENETICS REPLICATION, Diabetes
• CONSORTIUM, Meta-Analysis
• INFARCTION GENETICS CONSORTIUM, Myocardial
• KATHIRESAN, Sekar
• WIJMENGA, Cisca
• GREGERSEN, Peter K
• ALFREDSSON, Lars
• SIMINOVITCH, Katherine A
• WORTHINGTON, Jane
• DE BAKKER, Paul I. W
• TRYNKA, Gosia
• RAYCHAUDHURI, Soumya
• PLENGE, Robert M
• GUTIERREZ-ACHURY, Javier
• DO, Ron
• VOIGHT, Benjamin F
• KRAFT, Peter
• CHEN, Robert
• KALLBERG, Henrik J
• KURREEMAN, Fina A. S

Titel

Bayesian inference analyses of the polygenic architecture of rheumatoid arthritis

Ist Teil von

• Nature genetics, 2012-05, Vol.44 (5), p.483-489

Ort / Verlag

New York, NY: Nature Publishing Group

Erscheinungsjahr

2012

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• The genetic architectures of common, complex diseases are largely uncharacterized. We modeled the genetic architecture underlying genome-wide association study (GWAS) data for rheumatoid arthritis and developed a new method using polygenic risk-score analyses to infer the total liability-scale variance explained by associated GWAS SNPs. Using this method, we estimated that, together, thousands of SNPs from rheumatoid arthritis GWAS explain an additional 20% of disease risk (excluding known associated loci). We further tested this method on datasets for three additional diseases and obtained comparable estimates for celiac disease (43% excluding the major histocompatibility complex), myocardial infarction and coronary artery disease (48%) and type 2 diabetes (49%). Our results are consistent with simulated genetic models in which hundreds of associated loci harbor common causal variants and a smaller number of loci harbor multiple rare causal variants. These analyses suggest that GWAS will continue to be highly productive for the discovery of additional susceptibility loci for common diseases.