Scientific article
English

Meta-analysis identifies common and rare variants influencing blood pressure and overlapping with metabolic trait loci

ContributorsLiu, Chunyu; Kraja, Aldi T; Smith, Jennifer A; Brody, Jennifer A; Franceschini, Nora; Ehret, Georg Benedikt; Newton-Cheh, Christopher; Levy, Daniel; Chasman, Daniel I; CHD Exome+ Consortium; ExomeBP Consortium; GoT2DGenes Consortium; T2D-GENES Consortium; Myocardial Infarction Genetics and CARDIoGRAM Exome Consortia
Published inNature Genetics, vol. 48, no. 10, p. 1162-1170
Publication date2016
Abstract

Meta-analyses of association results for blood pressure using exome-centric single-variant and gene-based tests identified 31 new loci in a discovery stage among 146,562 individuals, with follow-up and meta-analysis in 180,726 additional individuals (total n = 327,288). These blood pressure-associated loci are enriched for known variants for cardiometabolic traits. Associations were also observed for the aggregation of rare and low-frequency missense variants in three genes, NPR1, DBH, and PTPMT1. In addition, blood pressure associations at 39 previously reported loci were confirmed. The identified variants implicate biological pathways related to cardiometabolic traits, vascular function, and development. Several new variants are inferred to have roles in transcription or as hubs in protein-protein interaction networks. Genetic risk scores constructed from the identified variants were strongly associated with coronary disease and myocardial infarction. This large collection of blood pressure-associated loci suggests new therapeutic strategies for hypertension, emphasizing a link with cardiometabolic risk.

Keywords
  • Blood Pressure/genetics
  • Exome
  • Genetic Variation
  • Genome
  • Human
  • Genome-Wide Association Study
  • Genotype
  • Humans
  • Hypertension/genetics
  • Oligonucleotide Array Sequence Analysis
  • Polymorphism
  • Single Nucleotide
Citation (ISO format)
LIU, Chunyu et al. Meta-analysis identifies common and rare variants influencing blood pressure and overlapping with metabolic trait loci. In: Nature Genetics, 2016, vol. 48, n° 10, p. 1162–1170. doi: 10.1038/ng.3660
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ISSN of the journal1061-4036
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