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Multi-omics analysis of genetic drivers linking aortic stenosis and left ventricular diastolic dysfunction in heart failure
Journal article   Open access   Peer reviewed

Multi-omics analysis of genetic drivers linking aortic stenosis and left ventricular diastolic dysfunction in heart failure

Zeeshan Ahmed, Prithvi Govindareddy, Jayden Mathew, Naveena V. Yanamala and Partho Sengupta
BioData mining, Vol.19(1)
06/11/2026
PMID: 42277826

Abstract

Aortic stenosis Diastolic dysfunction Left ventricular Heart Failure Genetic Markers
Aortic stenosis (AS) and left ventricular diastolic dysfunction (LVDD) often coexist in heart failure (HF), but the mechanisms linking them remain unclear. While AS increases afterload and promotes myocardial stiffening, emerging AI-based evidence suggests LVDD can precede the development of AS or progress simultaneously, indicating shared upstream mechanobiological and inflammatory drivers. This study explores the genetic contributors connecting AS and LVDD to identify early molecular markers and convergent pathways in HF. We analyzed Whole Genome Sequence (WGS) and RNA-seq data of the HF patients, generated using their Peripheral Blood Mononuclear Cells (PBMCs) samples. Overall bioinformatics analysis was divided into two modules, 1) gene variant and annotation analysis, and 2) gene expression and enrichment analysis. We utilized our peer review published and open source WGS and RNA-seq pipelines to process Next-Generation Sequence (NGS) data. Furthermore, we performed bioinformatics and statistical analysis to identify genetic variations, expressions, regulation, enrichments, and disease annotations. We identified genetic markers uniquely associated with AS, LVDD, and shared between them. Furthermore, we report genes with significant expression, and functional variations, and discuss their relationship with other cardiovascular diseases (e.g. Vascular and Cardiac Stiffness, Aortic Dissection, Left Atrial Enlargement, Left Ventricular Hypertrophy, Outflow Tract Obstructive Defects, Non-Compaction Coronary Artery Disease, Arrhythmia, Congestive Heart Failure, and Hypertrophic, Dilated, and Ischemic Cardiomyopathy) and non-cardiovascular diseases (non-CVDs) (e.g. Type 1 Diabetes, Diabetic Nephropathy, Skeletal Anomalies, Rheumatoid Arthritis, Atypical Femoral Fractures, Chronic Kidney Disease, Dehydrated Hereditary Stomatocytosis, Schizophrenia, Varicose Veins, High-Altitude Pulmonary Edema, Periodontitis, and Respiratory Disorder) including multiple cancer types (e.g. Breast, Lung, Colorectal, Pancreatic, Hypopharyngeal, Acute Lymphoblastic, and Oral Squamous Cell Carcinomas) and rare genetic disorders (e.g. Hypophosphatasia, Multiple Sclerosis, Campomelic Dysplasia, Lymphatic Malformation). We validated our results through state of science literature, gene-disease annotation databases, and electronic health records. AS and LVDD share both clinical and genomic associations, with overlapping genetic drivers that are enriched in pathways related to inflammation, extracellular matrix remodeling, and vascular stress responses. This work supports the potential of blood-based multi-omics profiling to uncover early, systemic molecular signals of cardiac dysfunction and lays the groundwork for future tissue-specific studies to guide precision diagnosis, risk stratification, and targeted therapeutics in HF.
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Version of Record (VoR) BioData Mining Open CC BY-NC-ND V4.0
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