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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. [ABSTRACT FROM AUTHOR]

Background: Heart failure patients have inadequate nutritional intake and alterations in metabolism contributing to an overall energy depleted state. Left ventricular assist device (LVAD) support is a common and successful intervention in patients with end-stage heart failure. LVAD support leads to alterations in cardiac output, functional status, neurohormonal activity and transcriptional profiles but the effects of LVADs on myocardial metabolism are unknown. This study set out to measure cardiac metabolites in non-failing hearts, failing hearts, and hearts post-LVAD support. Methods: The study population consisted of 8 non-ischemic failing (at LVAD implant) and 8 post-LVAD hearts, plus 8 non-failing hearts obtained from the tissue bank at the University of Colorado. NMR spectroscopy was utilized to evaluate differences in myocardial energy substrates. Paired and non-paired t-tests were used to determine differences between the appropriate groups. Results: Glucose and lactate values both decreased from non-failing to failing hearts and increased again significantly in the (paired) post-LVAD hearts. Glutamine, alanine, and aromatic amino acids decreased from non-failing to failing hearts and did not change significantly post-LVAD. Total creatine and succinate decreased from non-failing to failing hearts and did not change significantly post-LVAD. Discussion: Measured metabolites related to glucose metabolism are diminished in failing hearts, but recovered their values post-LVAD. This differed from the amino acid levels, which decreased in heart failure but did not recover following LVAD. Creatine and the citric acid cycle intermediate succinate followed a similar pattern as the amino acid levels. [ABSTRACT FROM AUTHOR]

Background: Heart failure patients with reduced ejection fraction (HFREF) are heterogenous, and our ability to identify patients likely to respond to therapy is limited. We present a method of identifying disease subtypes using high-dimensional clinical phenotyping and latent class analysis that may be useful in personalizing prognosis and treatment in HFREF. Methods: A total of 1121 patients with nonischemic HFREF from the b-blocker Evaluation of Survival Trial were categorized according to 27 clinical features. Latent class analysis was used to generate two latent class models, LCM A and B, to identify HFREF subtypes. LCM A consisted of features associated with HF pathogenesis, whereas LCM B consisted of markers of HF progression and severity. The Seattle Heart Failure Model (SHFM) Score was also calculated for all patients. Mortality, improvement in left ventricular ejection fraction (LVEF) defined as an increase in LVEF ≥5% and a final LVEF of 35% after 12 months, and effect of bucindolol on both outcomes were compared across HFREF subtypes. Performance of models that included a combination of LCM subtypes and SHFM scores towards predicting mortality and LVEF response was estimated and subsequently validated using leave-one-out cross-validation and data from the Multicenter Oral Carvedilol Heart Failure Assessment Trial. Results: A total of 6 subtypes were identified using LCM A and 5 subtypes using LCM B. Several subtypes resembled familiar clinical phenotypes. Prognosis, improvement in LVEF, and the effect of bucindolol treatment differed significantly between subtypes. Prediction improved with addition of both latent class models to SHFM for both 1-year mortality and LVEF response outcomes. Conclusions: The combination of high-dimensional phenotyping and latent class analysis identifies subtypes of HFREF with implications for prognosis and response to specific therapies that may provide insight into mechanisms of disease. These subtypes may facilitate development of personalized treatment plans. [ABSTRACT FROM AUTHOR]