Related Experiment Video

Updated: Jul 14, 2025

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
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Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation

Published on: January 16, 2019

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Functional mutation, splice, distribution, and divergence analysis of impactful genes associated with heart failure

Ishani Mhatre1, Habiba Abdelhalim1, William Degroat1

  • 1Institute for Health, Health Care Policy and Aging Research, Rutgers University, 112 Paterson Street, New Brunswick, NJ, 08901, USA.

Scientific Reports
|October 5, 2023
PubMed

Insights

This study identifies key genes like FLNA and HBA1 associated with cardiovascular diseases (CVD) and heart failure (HF). Genetic analysis reveals common mutations and their functional impact, aiding in early diagnosis and personalized CVD treatment.

Area of Science:

  • Genomics
  • Cardiovascular Medicine
  • Human Genetics

Background:

  • Cardiovascular disease (CVD) encompasses complex, heritable conditions with high mortality, particularly heart failure (HF).
  • Identifying genetic susceptibility factors is crucial for early diagnosis and personalized treatment strategies in CVD patients.

Purpose of the Study:

  • To investigate genes associated with heart failure and other cardiovascular diseases.
  • To analyze whole genome sequence data for identifying genetic variants and their functional impact on CVD.

Main Methods:

  • Whole genome sequencing (WGS) of serum samples from thirty-five consented patients.
  • Performed functional mutation, splice, variant distribution, and divergence analyses.
  • Variant and prevalence analysis to identify enriched pathways and significant genes.

Main Results:

  • FLNA, CST3, LGALS3, and HBA1 were linked to numerous enrichment pathways.
  • ACE, MME, LGALS3, NR3C2, PIK3C2A, CALD1, TEK, and TRPV1 were identified as potentially significant genes.
  • Intron, 5' UTR, 3' UTR, and 3' Flank mutations were most common; missense mutations had greater functional impact.

Conclusions:

  • Genetic variants in genes such as FLNA, HBA1, and LGALS3 play a significant role in cardiovascular diseases.
  • Understanding mutation types and their prevalence offers insights into CVD pathogenesis.
  • This research contributes to the foundation for precision medicine approaches in managing cardiovascular conditions.

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