Cross-ancestry analyses of Chinese and European populations reveal insights into the genetic architecture and disease implication of metabolites.
Summary
Large cross-ancestry metabolite GWAS identified 15 associations in Han Chinese (8 replicated) and 228 more via meta-analysis with UK Biobank Europeans, improving fine-mapping. Mendelian randomization linked higher HDL-triglyceride levels to increased coronary artery disease risk and higher glycine to reduced heart failure risk across ancestries.
Key Findings
- GWAS of 171 metabolites in 10,792 Han Chinese identified 15 variant–metabolite associations; 8 replicated in an independent Chinese cohort (n=4,480).
- Cross-ancestry meta-analysis with 213,397 Europeans found 228 additional associations and improved fine-mapping resolution.
- Mendelian randomization implicated HDL-triglycerides in higher coronary artery disease risk and glycine in lower heart failure risk across ancestries.
Clinical Implications
Findings support using metabolite-informed genetics for cardiovascular risk prediction and prioritizing pathways (e.g., HDL-triglycerides, glycine) for therapeutic development and precision prevention.
Why It Matters
Provides cross-ancestry genetic architecture of circulating metabolites with causal links to major cardiovascular diseases, enabling hypothesis-driven target discovery and risk stratification.
Limitations
- Metabolites measured by a single NMR platform may limit biochemical coverage and quantitation granularity
- Ancestry representation focused on Han Chinese and Europeans; limited generalizability to other populations
- MR assumptions (e.g., no horizontal pleiotropy) may not hold for all instruments
Future Directions
Extend to additional ancestries, integrate multi-omics and longitudinal phenotypes, and functionally validate prioritized loci and pathways to enable translation into biomarkers and therapeutics.
Study Information
- Study Type
- Cohort
- Research Domain
- Pathophysiology
- Evidence Level
- II - Large-scale observational genetic association with replication and MR analyses
- Study Design
- OTHER