Genetic and non-genetic determinants of clinical phenotypes in cardiomyopathy

Seitaro Nomura1

  • 1Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.

Journal of Cardiology
|December 12, 2018
PubMed

Insights

Dilated cardiomyopathy (DCM) involves genetic and non-genetic factors, with titin and lamin A/C mutations causing distinct patient phenotypes. Multi-omics data integration offers new avenues for understanding DCM and developing precision cardiology treatments.

Area of Science:

  • Cardiology
  • Genomics
  • Molecular Biology

Background:

  • Cardiomyopathy is a significant global health issue, characterized by diverse causes and presentations.
  • Dilated cardiomyopathy (DCM) is frequently linked to titin truncating and lamin A/C mutations, which influence patient outcomes and treatment responses.
  • Understanding the molecular underpinnings of DCM is crucial for advancing patient care.

Purpose of the Study:

  • To explore the multi-omics landscape of dilated cardiomyopathy (DCM).
  • To identify key genetic determinants and molecular signatures associated with DCM.
  • To investigate the potential for omics-based patient stratification and precision medicine in cardiology.

Main Methods:

  • Analysis of genomic, transcriptomic, epigenomic, proteomic, and metabolomic data from DCM patients.
  • Integration of multi-omics datasets to uncover inter-omics associations.
  • Comparison of molecular profiles between different DCM genotypes and healthy controls.

Main Results:

  • Identified titin truncating mutations and lamin A/C mutations as major genomic drivers of DCM with distinct phenotypic consequences.
  • Revealed transcriptomic and epigenomic alterations including DNA damage response activation, metabolic reprogramming, and dedifferentiation in DCM.
  • Characterized proteomic and metabolomic signatures of the DCM heart and blood, highlighting fatty acid dependency, stress response, immune activation, and microbiota links.
  • Demonstrated the utility of multi-omics data integration for patient stratification.

Conclusions:

  • Multi-omics data integration provides a comprehensive understanding of DCM etiology and pathogenesis.
  • Distinct molecular profiles associated with specific genotypes offer opportunities for personalized treatment strategies.
  • Omics-based patient stratification holds promise for advancing precision medicine in cardiology for cardiomyopathy patients.

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