Multi-omics Integration Identifies Genes Influencing Traits Associated with Cardiovascular Risks: The Long Life...

Area of Science:

• Genetics and Genomics
• Cardiovascular Disease Research
• Multi-omics Integration

Background:

• The Long Life Family Study (LLFS) comprises individuals with exceptional longevity, offering a unique cohort for genetic studies of cardiovascular risk.
• Understanding genetic mechanisms underlying cardiovascular risks is crucial for public health and personalized medicine.

Approach:

• Developed and applied a novel multi-omics integration pipeline to analyze 11 cardiovascular risk traits in the LLFS cohort.
• Aggregated gene-level statistics from rare-variant analysis, genome-wide association studies (GWAS), and gene expression data using Correlated Meta-Analysis (CMA).
• Validated findings through replication in the Framingham Heart Study (FHS) cohort and analysis of protein-protein interaction (PPI) networks.

Key Points:

• Identified 64 significant genes associated with cardiovascular risk traits, with 29 replicating in the FHS cohort. Twenty of these replicated genes lack prior GWAS associations.
• Discovered 13 enriched modules in PPI networks, with three replicating in the FHS cohort, implicating biological processes like sterol transport and immune regulation.
• Highlighted potential roles for genes such as FCER1A, MS4A2, GATA2, HDC, HRH4 in atherosclerosis, ATG2A in obesity, and ENPP3 in triglyceride-induced inflammation.

Conclusions:

• The developed multi-omics pipeline effectively identifies novel genetic associations with cardiovascular risk traits.
• Findings provide new insights into the genetic architecture of longevity and cardiovascular health, suggesting specific genes and pathways for further investigation.
• The freely available pipeline facilitates broader application in genetic and omics research.