Protein Interaction-Based Genome-Wide Analysis of Incident Coronary Heart Disease
Jensen, Majken K.
Pers, Tune H.
Girman, Cynthia J.
Rimm, Eric Bruce::0ab2926c8242f35e5a982e3cf59f4987::600
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CitationJensen, Majken K., Tune H. Pers, Piotr Dworzynski, Cynthia J. Girman, Søren Brunak, and Eric B. Rimm. 2011. “Protein Interaction-Based Genome-Wide Analysis of Incident Coronary Heart Disease.” Circulation: Cardiovascular Genetics 4 (5): 549–56. https://doi.org/10.1161/circgenetics.111.960393.
AbstractBackground-Network-based approaches may leverage genome-wide association (GWA) analysis by testing for the aggregate association across several pathway members. We aimed to examine if networks of genes that represent experimentally determined protein-protein interactions (PPIs) are enriched in genes associated with risk of coronary heart disease (CHD).Methods and Results-Genome-wide association analyses of approximately approximate to 700 000 single-nucleotide polymorphisms in 899 incident CHD cases and 1823 age-and sex-matched controls within the Nurses' Health and the Health Professionals Follow-up Studies were used to assign genewise P values. A large database of PPIs was used to assemble 8351 unbiased protein complexes and corresponding gene sets. Superimposed genewise P values were used to rank gene sets based on their enrichment in genes associated with CHD. After correcting for the number of complexes tested, 1 gene set was overrepresented in CHD-associated genes (P = 0.002). Centered on the beta 1-adrenergic receptor gene (ADRB1), this complex included 18 protein interaction partners that have not been identified as candidate loci for CHD. Of the 19 genes in the top complex, 5 are involved in abnormal cardiovascular system physiological features based on knockout mice (4-fold enrichment; Fisher exact test, P = 0.006). Ingenuity pathway analysis revealed that canonical pathways, especially related to blood pressure regulation, were significantly enriched in the genes from the top complex.Conclusions-The integration of a GWA study with PPI data successfully identifies a set of candidate susceptibility genes for incident CHD that would have been missed in single-marker GWA analysis. (Circ Cardiovasc Genet. 2011; 4:549-556.)
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