Functionally oriented analysis of cardiometabolic traits in a trans-ethnic sample

Lauren E. Petty, Heather M. Highland, Eric R. Gamazon, Hao Hu, Mandar Karhade, Hung Hsin Chen, Paul S. De Vries, Megan L. Grove, David Aguilar, Graeme I. Bell, Chad D. Huff, Craig L. Hanis, Harshavardhan Doddapaneni, Donna M. Munzy, Richard A. Gibbs, Jianzhong Ma, Esteban J. Parra, Miguel Cruz, Adan Valladares-Salgado, Dan E. ArkingAlvaro Barbeira, Hae Kyung Im, Alanna C. Morrison, Eric Boerwinkle, Jennifer E. Below

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


Interpretation of genetic association results is difficult because signals often lack biological context. To generate hypotheses of the functional genetic etiology of complex cardiometabolic traits, we estimated the genetically determined component of gene expression from common variants using PrediXcan (1) and determined genes with differential predicted expression by trait. PrediXcan imputes tissue-specific expression levels from genetic variation using variant-level effect on gene expression in transcriptome data. To explore the value of imputed genetically regulated gene expression (GReX) models across different ancestral populations, we evaluated imputed expression levels for predictive accuracy genome-wide in RNA sequence data in samples drawn from European-Ancestry and African-Ancestry populations and identified substantial predictive power using European-derived models in a non-European target population.We then tested the association of GReX on 15 cardiometabolic traits including blood lipid levels, body mass index, height, blood pressure, fasting glucose and insulin, RR interval, fibrinogen level, factor VII level and white blood cell and platelet counts in 15 755 individuals across three ancestry groups, resulting in 20 novel gene-phenotype associations reaching experiment-wide significance across ancestries. In addition, we identified 18 significant novel gene-phenotype associations in our ancestry-specific analyses. Top associations were assessed for additional support via query of S-PrediXcan (2) results derived from publicly available genome-wide association studies summary data. Collectively, these findings illustrate the utility of transcriptome-based imputation models for discovery of cardiometabolic effect genes in a diverse dataset.

Original languageEnglish
Pages (from-to)1212-1224
Number of pages13
JournalHuman Molecular Genetics
Issue number7
StatePublished - Apr 1 2019

Bibliographical note

Publisher Copyright:
© The Author(s) 2019.

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics
  • Genetics(clinical)


Dive into the research topics of 'Functionally oriented analysis of cardiometabolic traits in a trans-ethnic sample'. Together they form a unique fingerprint.

Cite this