Objectives: To investigate the biologic relevance of cross-platform concordant changes in gene expression in intact human failing/hypertrophied ventricular myocardium undergoing reverse remodeling.
Background: Information is lacking on genes and networks involved in remodeled human LVs, and in the associated investigative best practices.
Methods: We measured mRNA expression in ventricular septal endomyocardial biopsies from 47 idiopathic dilated cardiomyopathy patients, at baseline and after 3-12 months of β-blocker treatment to effect left ventricular (LV) reverse remodeling as measured by ejection fraction (LVEF). Cross-platform gene expression change concordance was investigated in reverse remodeling Responders (R) and Nonresponders (NR) using 3 platforms (RT-qPCR, microarray, and RNA-Seq) and two cohorts (All 47 subjects (A-S) and a 12 patient "Super-Responder" (S-R) subset of A-S).
Results: For 50 prespecified candidate genes, in A-S mRNA expression 2 platform concordance (CcpT), but not single platform change, was directly related to reverse remodeling, indicating CcpT has biologic significance. Candidate genes yielded a CcpT (PCR/microarray) of 62% for Responder vs. Nonresponder (R/NR) change from baseline analysis in A-S, and ranged from 38% to 100% in S-R for PCR/microarray/RNA-Seq 2 platform comparisons. Global gene CcpT measured by microarray/RNA-Seq was less than for candidate genes, in S-R R/NR 17.5% vs. 38% (P = 0.036). For S-R global gene expression changes, both cross-cohort concordance (CccT) and CcpT yielded markedly greater values for an R/NR vs. an R-only analysis (by 22 fold for CccT and 7 fold for CcpT). Pathway analysis of concordant global changes for R/NR in S-R revealed signals for downregulation of multiple phosphoinositide canonical pathways, plus expected evidence of a β1-adrenergic receptor gene network including enhanced Ca2+ signaling.
Conclusions: Two-platform concordant change in candidate gene expression is associated with LV biologic effects, and global expression concordant changes are best identified in an R/NR design that can yield novel information.