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

Area of Science:

• Genetics
• Bioinformatics
• Cardiovascular Research

Background:

• Interpreting genetic association results for complex traits is challenging due to a lack of biological context.
• Identifying the functional genetic basis of cardiometabolic diseases remains a significant hurdle in precision medicine.

Purpose of the Study:

• To generate hypotheses for the functional genetic etiology of complex cardiometabolic traits.
• To evaluate the predictive accuracy and utility of genetically regulated gene expression (GReX) models across diverse ancestral populations.
• To discover novel gene-phenotype associations for cardiometabolic traits using transcriptome-wide imputation.

Main Methods:

• Utilized PrediXcan to estimate the genetically determined component of gene expression from common variants.
• Assessed the predictive accuracy of imputed gene expression levels genome-wide in European-ancestry and African-ancestry populations.
• Tested associations between GReX and 15 cardiometabolic traits in 15,755 individuals across three ancestry groups.

Main Results:

• Demonstrated substantial predictive power of European-derived GReX models in non-European populations.
• Identified 20 novel gene-phenotype associations reaching experiment-wide significance across ancestries.
• Discovered 18 additional significant novel gene-phenotype associations in ancestry-specific analyses.

Conclusions:

• Transcriptome-based imputation models, like GReX, are valuable tools for discovering cardiometabolic effect genes.
• Findings support the utility of GReX for genetic studies in diverse ancestral groups.
• The study provides a foundation for further functional investigation of identified gene-phenotype associations.