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The contribution of coding variants to psoriasis much smaller than thought
Date:11/10/2013

November 10, 2013, Shenzhen, China - Coding variants in immune disease-related genes play only a small part in the overall genetic risk for psoriasis, according to a new study led by Anhui Medical University and BGI. This conclusion is strongly supported by their investigation on the contribution of functional coding variants to psoriasis in 21,309 Chinese individuals. In such a large-scale investigation, researchers only discovered two independent low-frequency variants with moderate effect on disease risk. The latest study was published online in Nature Genetics.

Psoriasis is a complex, chronic, lifelong skin disease. It typically first strikes people between the ages of 15 to 35, but can affect anyone at any age, including children. This terrible disease is the results of the interaction of multiple factors, such as environment, genetics, and immunology. The rapid and cost-effective sequencing technologies have enabled researchers to dig out numerous risk-associated variants in psoriasis, but the functional coding variants, particularly low-frequency and rare variants, have not been systematically investigated.

In this study, researchers took two-phase to identify coding variants. In the discovery stage, they conducted exome sequencing on 781 patients with psoriasis and 676 people without psoriasis as control. The efforts yielded 518,308 single-nucleotide variants (SNVs). Of these variants, 20.62% were nonsynonymous, and 68.13% were rare.

Considering the limitation of sample size and techniques in the discovery stage, researchers performed 2 independent studies in a large sample of 9,946 patients with psoriasis and 9,906 controls using targeted sequencing. A total of 3.2 Mb of coding DNA surrounding the targeted regions of 1,326 genes (covering 133 SNVs, 622 immune diseaserelated genes, and some top genes) was captured. They totally identified 82,387 nonsynonymous SNVs, of which 97.07% were rare.

Through further a
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Contact: Jia Liu
liujia@genomics.cn
BGI Shenzhen
Source:Eurekalert

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