Systematic functional regulatory assessment of disease-associated variants
Author(s) -
Konrad J. Karczewski,
Joel T. Dudley,
Kimberly R. Kukurba,
Rong Chen,
Atul J. Butte,
Stephen B. Montgomery,
M Snyder
Publication year - 2013
Publication title -
proceedings of the national academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.1219099110
Subject(s) - biology , genome wide association study , single nucleotide polymorphism , genetics , disease , expression quantitative trait loci , allele , gene , genetic association , genetic variation , dna binding site , transcription factor , genome , computational biology , genotype , gene expression , promoter , medicine , pathology
Genome-wide association studies have discovered many genetic loci associated with disease traits, but the functional molecular basis of these associations is often unresolved. Genome-wide regulatory and gene expression profiles measured across individuals and diseases reflect downstream effects of genetic variation and may allow for functional assessment of disease-associated loci. Here, we present a unique approach for systematic integration of genetic disease associations, transcription factor binding among individuals, and gene expression data to assess the functional consequences of variants associated with hundreds of human diseases. In an analysis of genome-wide binding profiles of NFκB, we find that disease-associated SNPs are enriched in NFκB binding regions overall, and specifically for inflammatory-mediated diseases, such as asthma, rheumatoid arthritis, and coronary artery disease. Using genome-wide variation in transcription factor-binding data, we find that NFκB binding is often correlated with disease-associated variants in a genotype-specific and allele-specific manner. Furthermore, we show that this binding variation is often related to expression of nearby genes, which are also found to have altered expression in independent profiling of the variant-associated disease condition. Thus, using this integrative approach, we provide a unique means to assign putative function to many disease-associated SNPs.
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