Regression of Established Cardiac Fibrosis in Hypertensive Heart Disease

Karl T Weber1, Yao Sun1, Ivan C Gerling2

  • 1Division of Cardiovascular Diseases, University of Tennessee Health Science Center, Memphis, Tennessee, USA.

Insights

Regression of established cardiac fibrosis (ECF) in hypertensive heart disease is a critical unmet need. This review explores the feasibility, cellular mechanisms, and knowledge gaps for reversing ECF and improving heart failure symptoms.

Area of Science:

  • Cardiology
  • Hypertension Research
  • Fibrosis Studies

Background:

  • Established cardiac fibrosis (ECF) is prevalent in patients with heart failure with preserved ejection fraction (HFpEF) and hypertension.
  • ECF contributes to myocardial stiffness and symptomatic heart failure, representing a significant clinical challenge.
  • Current therapeutic strategies for ECF regression in this population are limited.

Purpose of the Study:

  • To review the feasibility of regressing ECF in hypertensive heart disease.
  • To investigate the cellular and molecular signaling pathways involved in ECF regression.
  • To identify knowledge gaps crucial for advancing therapeutic interventions.

Main Methods:

  • This is a review article, synthesizing existing research on cardiac fibrosis and hypertension.
  • Literature search focused on studies investigating ECF regression, myocardial stiffness, and HFpEF.
  • Analysis of cellular and molecular mechanisms implicated in fibrotic remodeling.

Main Results:

  • The review suggests that ECF regression in hypertensive heart disease is potentially feasible.
  • Key signaling pathways involved in fibrosis and its potential reversal are discussed.
  • Significant knowledge gaps remain regarding effective therapeutic strategies.

Conclusions:

  • Reversing ECF in hypertensive heart disease could improve myocardial stiffness and HFpEF symptoms.
  • Further research into specific cellular/molecular targets is necessary.
  • Translational studies are needed to develop effective treatments for ECF regression.