Growth Differentiation Factor 15 Predicts All-Cause Morbidity and Mortality in Stable Coronary Heart Disease

Emil Hagström1,2, Claes Held3,2, Ralph A H Stewart4

  • 1Department of Medical Sciences, Cardiology, Uppsala University, Uppsala, Sweden; emil.hagstrom@ucr.uu.se.

Clinical Chemistry
|November 5, 2016
PubMed

Insights

Elevated growth differentiation factor 15 (GDF-15) levels predict cardiovascular and non-cardiovascular mortality in stable coronary heart disease patients. GDF-15 offers valuable risk assessment information for these individuals.

Area of Science:

  • Cardiology
  • Biomarker Research

Background:

  • Higher growth differentiation factor 15 (GDF-15) concentrations are linked to increased cardiovascular (CV) and non-CV morbidity and mortality.
  • Limited data exists on GDF-15's association with specific CV and non-CV events in stable coronary heart disease (CHD) patients.

Purpose of the Study:

  • To investigate the association between GDF-15 levels and the risk of various adverse CV and non-CV events in patients with stable CHD.
  • To determine if GDF-15 provides independent prognostic information beyond other established biomarkers.

Main Methods:

  • Analysis of 14,577 stable CHD patients from the STABILITY trial.
  • Measurement of GDF-15 and other prognostic biomarkers (NT-proBNP, hsTnT, cystatin C, hs-CRP).
  • Utilized adjusted Cox regression models to assess associations between GDF-15 and composite CV endpoint, other CV, and non-CV events.

Main Results:

  • Higher GDF-15 quartiles were associated with increased risk for composite CV endpoint, CV death, sudden death, heart failure death, cancer death, and hospitalization for heart failure.
  • GDF-15 remained significantly associated with all assessed fatal and nonfatal outcomes after adjustment for other biomarkers, except for myocardial infarction (MI).

Conclusions:

  • GDF-15 is an independent predictor of CV, non-CV, and cancer mortality, as well as MI and stroke in stable CHD patients.
  • GDF-15 provides prognostic information for adverse outcomes, even after adjusting for other biomarkers, highlighting its clinical utility in risk stratification.
Abstract

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