Investigation of Novel Biomarkers and Treatment Targets for Pediatric Heart Failure

Abstract

Human hearts are unable to self-repair due to their very limited endogenous regenerative capacity. Thus, mortality rates of heart failure are extremely high. Pediatric heart failure (PHF) is the leading non-trauma-related cause of death for an infant, child, or adolescent in the United States. Many children with PHF are treated by inserting a pump known as a Left Ventricular Assist Device (LVAD) into the heart to assist blood circulation. However, most patients dont respond to LVAD treatment and require heart transplantation. Unfortunately, transplantation is severely limited by the scarcity of donor hearts. Hence, an unmet clinical need is to accurately predict whether PHF patients respond to LVAD treatment. This would ease the decision of physicians on whether heart transplantation is needed. Accordingly, identification of biomarkers in PHF patient blood samples would provide a novel non-invasive method to determine whether heart function improves upon LVAD treatment. Hence, our study is aimed at developing gene expression signature-based methods that predict whether PHF patients respond favorably to LVAD treatment. Our studies are also aimed at stimulating endogenous cardiac regeneration with the goal of significantly improving PHF survival rates. As such, we will employ cutting-edge techniques to determine the molecular mechanisms that govern cardiac regeneration in order to develop novel PHF therapy approaches.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2021
Accession Number
AD1158146

Entities

People

  • James F. Martin

Organizations

  • Baylor College of Medicine

Tags

DTIC Thesaurus Topics

  • Biomedical Research
  • Cardiovascular Physiological Phenomena
  • Cell Physiological Processes
  • Cells
  • Chemistry
  • Computational Science
  • Data Sets
  • Gene Expression
  • Gene Therapy
  • Genetics
  • Health Services
  • Heart Diseases
  • Heart Failure
  • Medical Personnel
  • Neural Networks
  • Regenerative Medicine
  • Stem Cells

Fields of Study

  • Medicine

Readers

  • Battery Technology and Engineering
  • Cardiovascular Physiology
  • Oncology

Technology Areas

  • Biotechnology