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Published on: September 20, 2024
Connecting intermediate phenotypes to disease using multi-omics in heart failure
Anni Moore1, Rasika Venkatesh1, Michael G Levin2
1Genomics and Computational Biology, University of Pennsylvania Perelman School of Medicine, 3700 Hamilton Walk Philadelphia, PA, 19104, USA.
Insights
This study integrates multi-omics data with cardiac MRI to uncover genetic links to heart failure (HF). Findings reveal shared genetic factors between cardiac structure changes and HF risk, offering new insights into disease mechanisms.
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.
Abstract:
Heart failure (HF) is one of the most common, complex, heterogeneous diseases in the world, with over 1-3% of the global population living with the condition. Progression of HF can be tracked via MRI measures of structural and functional changes to the heart, namely left ventricle (LV), including ejection fraction, mass, end-diastolic volume, and LV end-systolic volume. Moreover, while genome-wide association studies (GWAS) have been a useful tool to identify candidate variants involved in HF risk, they lack crucial tissue-specific and mechanistic information which can be gained from incorporating additional data modalities. This study addresses this gap by incorporating transcriptome-wide and proteome-wide association studies (TWAS and PWAS) to gain insights into genetically-regulated changes in gene expression and protein abundance in precursors to HF measured using MRI-derived cardiac measures as well as full-stage all-cause HF. We identified several gene and protein overlaps between LV ejection fraction and end-systolic volume measures. Many of the overlaps identified in MRI-derived measurements through TWAS and PWAS appear to be shared with all-cause HF. We implicate many putative pathways relevant in HF associated with these genes and proteins via gene-set enrichment and protein-protein interaction network approaches. The results of this study (1) highlight the benefit of using multi-omics to better understand genetics and (2) provide novel insights as to how changes in heart structure and function may relate to HF.
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