Genome-wide association studies (GWAS) have successfully identified approximately 36 psoriasis susceptibility loci. However, the causal variants at these loci remain largely unknown, and it is very likely that a large number of additional loci remain to be identified. In this proposal, we pursue a comprehensive strategy to identify both common and rare causal variants in psoriasis, and then perform targeted functional studies of these variants. In the first aim, we focus on the identification of common causal variants, the majority of which are expected to be regulatory. We improve statistical power by performing a meta-analysis of 5 European ancestry psoriasis GWAS totaling 4,832 cases and 10,103 controls, and further refine causal regions by comparison with 2 Asian ancestry psoriasis GWAS totaling 1,588 cases and 3,566 controls. From within causal regions, putative causal variants are identified using a novel bioinformatics approach that takes advantage of the recent release of a genome-wide map of human regulatory elements. Causal variants are further validated by follow-up genotyping in an independent sample of 11,141 cases and 11,020 controls. In the second aim, we focus on the identification of rare, coding variants. To increase our statistical power to detect rare variant associations, we perform exome sequencing of 500 severe-phenotype psoriasis cases and then impute the identified rare variants onto a GWAS cohort of 4,832 cases and 10,103 controls. Putative causal variants are again validated in independent cohorts. In the third aim, we create a psoriasis regulatory roadmap that defines how non-coding variants impact cell lineage specific gene expression, and further test coding variants for functional impact using cellular assays. Overall, the expected outcome of the proposed work will be first, a high quality list of putative causal SNPs at established psoriasis loci; second, the discovery of common and rare causal variants at novel loci; and third, the establishment of a roadmap by which we can understand the impact of these variants in specific cell types relevant to psoriasis. These advances will establish an important and necessary foundation that will guide future mechanistic studies of psoriasis and will identify new biological targets for therapy.
Psoriasis is a debilitating, inflammatory skin disease that affects over 7 million Americans. Although genetic studies of psoriasis have thus far identified a number of gene variants linked to psoriasis, identifying the precise gene variants that cause psoriasis has remained elusive. In this proposal, we use large genetic datasets, novel bioinformatics methods, and the cutting-edge technologies to identify and characterize psoriasis causal variants, which may lead to new psoriasis therapies.
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