Bayesian inference analyses of the polygenic architecture of rheumatoid arthritis  

Oleh:

Stahl, Eli A ; Wegmann, Daniel ; Trynka, Gosia

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Nature Genetics vol. 44 no. 05 (May 2012), page 483–489.

Ketersediaan

Perpustakaan FK Nomor Panggil: N12.K.2012.01 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

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.

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