Sex Differences in Circulating Biomarkers of Heart Failure

Roopa A Rao1, Anju Bhardwaj2, Mrudula Munagala3

  • 1Division of Cardiovascular Medicine, Indiana University School of Medicine, 1801, N Senate Blvd, Indianapolis, IN, 46202, USA. rrao@iuhealth.org.

PubMed

Insights

Sex differences in heart failure biomarkers are evident, but their clinical impact remains unclear. Further research is needed to understand these variations for better diagnosis and treatment in men and women.

Area of Science:

  • Cardiology
  • Biomarker Research
  • Sex Differences in Medicine

Background:

  • Growing evidence highlights sex-based disparities in heart failure.
  • The clinical significance of sex-specific thresholds for cardiac biomarkers is not well-defined.
  • Understanding these differences is crucial for personalized medicine in cardiovascular disease.

Purpose of the Study:

  • To review current understanding of sex differences in cardiac biomarkers in heart failure.
  • To explore the clinical relevance of these sex-specific biomarker thresholds.
  • To identify knowledge gaps and emerging research areas in sex-specific heart failure biomarker studies.

Main Methods:

  • Review of recent scientific literature on sex differences in heart failure biomarkers.
  • Analysis of studies investigating differential biomarker thresholds in males and females.
  • Exploration of novel biomarkers and technologies, including proteomics and microRNAs.

Main Results:

  • Females exhibit distinct thresholds for certain biomarkers, such as lower troponin and higher NT-proBNP levels.
  • Clinical relevance of ST-2, Galectin 3, and other biomarkers in a sex-specific context remains ambiguous.
  • Despite observed sex-related differences in biomarker expression, translation into clinical practice for diagnosis and prognostication is limited.

Conclusions:

  • Sex-specific differences in heart failure biomarkers exist but require further investigation for clinical application.
  • Novel biomarkers and advanced technologies like machine learning are being explored to bridge knowledge gaps.
  • Personalized approaches considering sex-based variations are essential for improving heart failure management.
Abstract

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