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

Zeeshan Ahmed1,2, Prithvi Govindareddy3, Jayden Mathew3

  • 1Division of Cardiovascular Diseases and Hypertension, Department of Medicine, Robert Wood Johnson Medical School, Rutgers Health, 125 Paterson St, New Brunswick, NJ, 08901, USA. zahmed@ifh.rutgers.edu.

Biodata Mining
|June 12, 2026
PubMed

Insights

Aortic stenosis and left ventricular diastolic dysfunction share genetic links in heart failure patients. Blood multi-omics can reveal early molecular signals for better diagnosis and treatment.

Area of Science:

  • Genomics
  • Cardiovascular Medicine
  • Bioinformatics

Background:

  • Aortic stenosis (AS) and left ventricular diastolic dysfunction (LVDD) frequently coexist in heart failure (HF), with unclear underlying mechanisms.
  • While AS increases afterload, evidence suggests LVDD may precede or coincide with AS, pointing to shared inflammatory and mechanobiological drivers.
  • This study investigates the genetic connections between AS and LVDD to identify early molecular markers and convergent pathways in HF.

Purpose of the Study:

  • To explore genetic contributors linking aortic stenosis and left ventricular diastolic dysfunction in heart failure.
  • To identify early molecular markers and convergent biological pathways shared by AS and LVDD.
  • To investigate the genomic basis of co-occurring cardiovascular conditions.

Main Methods:

  • Analysis of Whole Genome Sequence (WGS) and RNA-seq data from Peripheral Blood Mononuclear Cells (PBMCs) of heart failure patients.
  • Utilized peer-reviewed, open-source pipelines for processing Next-Generation Sequence (NGS) data, including gene variant annotation and gene expression analysis.
  • Performed bioinformatics and statistical analyses to identify genetic variations, expression patterns, regulation, enrichments, and disease associations.

Main Results:

  • Identified unique and shared genetic markers associated with AS and LVDD.
  • Reported genes with significant expression and functional variations, linking them to various cardiovascular and non-cardiovascular diseases, including cancers and rare genetic disorders.
  • Validated findings using literature, gene-disease databases, and electronic health records.

Conclusions:

  • AS and LVDD exhibit shared clinical and genomic associations, driven by overlapping genetic factors in inflammation, extracellular matrix remodeling, and vascular stress pathways.
  • Blood-based multi-omics profiling shows promise for detecting early systemic molecular signals of cardiac dysfunction.
  • This research provides a foundation for future tissue-specific studies to enhance precision diagnosis, risk stratification, and targeted therapies for HF.
Abstract

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