A systematic review of fetal genes as biomarkers of cardiac hypertrophy in rodent models of diabetes

PLoS One. 2014 Mar 24;9(3):e92903. doi: 10.1371/journal.pone.0092903. eCollection 2014.

Abstract

Pathological cardiac hypertrophy activates a suite of genes called the fetal gene program (FGP). Pathological hypertrophy occurs in diabetic cardiomyopathy (DCM); therefore, the FGP is widely used as a biomarker of DCM in animal studies. However, it is unknown whether the FGP is a consistent marker of hypertrophy in rodent models of diabetes. Therefore, we analyzed this relationship in 94 systematically selected studies. Results showed that diabetes induced with cytotoxic glucose analogs such as streptozotocin was associated with decreased cardiac weight, but genetic or diet-induced models of diabetes were significantly more likely to show cardiac hypertrophy (P<0.05). Animal strain, sex, age, and duration of diabetes did not moderate this effect. There were no correlations between the heart weight:body weight index and mRNA or protein levels of the fetal genes α-myosin heavy chain (α-MHC) or β-MHC, sarco/endoplasmic reticulum Ca2+-ATPase, atrial natriuretic peptide (ANP), or brain natriuretic peptide. The only correlates of non-indexed heart weight were the protein levels of α-MHC (Spearman's ρ = 1, P<0.05) and ANP (ρ = -0.73, P<0.05). These results indicate that most commonly measured genes in the FGP are confounded by diabetogenic methods, and are not associated with cardiac hypertrophy in rodent models of diabetes.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.
  • Review
  • Systematic Review

MeSH terms

  • Animals
  • Biomarkers / metabolism
  • Cardiomegaly* / genetics
  • Cardiomegaly* / metabolism
  • Diabetes Mellitus, Experimental* / genetics
  • Diabetes Mellitus, Experimental* / metabolism
  • Diabetic Cardiomyopathies* / genetics
  • Diabetic Cardiomyopathies* / metabolism
  • Humans
  • Mice
  • Rats

Substances

  • Biomarkers