Multi-omics analyses identify molecular signatures with prognostic values in different heart failure aetiologies

Abstract

Background: Heart failure (HF) is the leading cause of morbidity and mortality worldwide, and there is an urgent need for more global studies and data mining approaches to uncover its underlying mechanisms. Multiple omics techniques provide a more holistic molecular perspective to study pathophysiological events involved in the development of HF.

Methods: In this study, we used a label-free whole myocardium multi-omics characterization from three commonly used mouse HF models: transverse aortic constriction (TAC), myocardial infarction (MI), and homozygous Phospholamban-R14del (PLN-R14^Δ/Δ). Genes, proteins, and metabolites were analysed for differential expression between each group and a corresponding control group. The core transcriptome and proteome datasets were used for enrichment analysis. For genes that were upregulated at both the RNA and protein levels in all models, clinical validation was performed by means of plasma level determination in patients with HF from the BIOSTAT-CHF cohort.

Results: Cell death and tissue repair-related pathways were upregulated in all preclinical models. Fatty acid oxidation, ATP metabolism, and Energy derivation processes were downregulated in all investigated HF aetiologies. Putrescine, a metabolite known for its role in cell survival and apoptosis, demonstrated a 4.9-fold (p < 0.02) increase in PLN-R14^Δ/Δ, 2.7-fold (p < 0.005) increase in TAC mice, and 2.2-fold (p < 0.02) increase in MI mice. Four Biomarkers were associated with all-cause mortality (PRELP: Hazard ratio (95% confidence interval) 1.79(1.35, 2.39), p < 0.001; CKAP4: 1.38(1.21, 1.57), p < 0.001; S100A11: 1.37(1.13, 1.65), p = 0.001; Annexin A1 (ANXA1): 1.16(1.04, 1.29) p = 0.01), and three biomarkers were associated with HF-Related Rehospitalization, (PRELP: 1.88(1.4, 2.53), p < 0.001; CSTB: 1.15(1.05, 1.27), p = 0.003; CKAP4: 1.18(1.02, 1.35), P = 0.023).

Conclusions: Cell death and tissue repair pathways were significantly upregulated, and ATP and energy derivation processes were significantly downregulated in all models. Common pathways and biomarkers with potential clinical and prognostic associations merit further investigation to develop optimal management and therapeutic strategies for all HF aetiologies.

Keywords: ATP; Autophagy; Cell death; Heart failure; Metabolomics; Multi-omics; Polyamine; Proteomics; Tissue repair; Transcriptomics.