Connecting intermediate phenotypes to disease using multi-omics in heart failure.

Area of Science:

• Genetics and Cardiovascular Disease Research
• Multi-omics Integration in Human Health

Background:

• Heart failure (HF) affects 1-3% of the global population, necessitating advanced understanding of its complex etiology.
• Magnetic Resonance Imaging (MRI) provides key metrics for tracking HF progression, including left ventricular (LV) ejection fraction and volumes.
• Genome-wide association studies (GWAS) identify HF risk variants but lack tissue-specific and mechanistic details.

Purpose of the Study:

• To integrate transcriptome-wide association studies (TWAS) and proteome-wide association studies (PWAS) with MRI-derived cardiac measures and HF data.
• To identify genetically regulated gene expression and protein abundance linked to HF precursors and established HF.
• To elucidate novel biological pathways and mechanisms underlying HF development.

Main Methods:

• Performed TWAS and PWAS incorporating MRI-derived LV measures (ejection fraction, end-diastolic volume, end-systolic volume) and all-cause HF data.
• Utilized gene-set enrichment analysis to identify implicated biological pathways.
• Employed protein-protein interaction networks to explore functional relationships of identified genes and proteins.

Main Results:

• Identified significant overlaps in genes and proteins associated with LV ejection fraction and LV end-systolic volume.
• Observed shared genetic and proteomic factors between MRI-derived cardiac measures and all-cause HF.
• Implicated several putative HF-relevant pathways through multi-omics analyses.

Conclusions:

• Demonstrated the value of multi-omics approaches for understanding the genetic architecture of HF.
• Provided novel insights into the relationship between cardiac structural/functional changes and HF pathogenesis.
• Highlighted potential therapeutic targets by linking genetic factors to HF mechanisms.