TY - JOUR
T1 - Multi-omics analyses identify molecular signatures with prognostic values in different heart failure aetiologies
AU - Aboumsallem, Joseph Pierre
AU - Shi, Canxia
AU - De Wit, Sanne
AU - Markousis-Mavrogenis, George
AU - Bracun, Valentina
AU - Eijgenraam, Tim R.
AU - Hoes, Martijn F.
AU - Meijers, Wouter C.
AU - Screever, Elles M.
AU - Schouten, Marloes E.
AU - Voors, Adriaan A.
AU - Silljé, Herman H.W.
AU - De Boer, Rudolf A.
N1 - Funding Information:
This work was by a grant from the European Research Council (ERC CoG 818715, SECRETE-HF). Furthermore, supported by grants from the Netherlands Heart Foundation (CVON SHE-PREDICTS-HF, grant 2017–21; CVON RED-CVD, grant 2017–11; CVON PREDICT2 , grant 2018–30; and CVON DOUBLE DOSE, grant 2020B005), by a grant from the leDucq Foundation (Cure PhosphoLambaN induced Cardiomyopathy (Cure-PLaN). Canxia Shi is supported by a scholarship from the China Scholarship Council (CSC number: 201806170057).
Publisher Copyright:
© 2022 The Authors
PY - 2023/2
Y1 - 2023/2
N2 - 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-R14Δ/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-R14Δ/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.
AB - 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-R14Δ/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-R14Δ/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.
KW - ATP
KW - Autophagy
KW - Cell death
KW - Heart failure
KW - Metabolomics
KW - Multi-omics
KW - Polyamine
KW - Proteomics
KW - Tissue repair
KW - Transcriptomics
U2 - 10.1016/j.yjmcc.2022.12.001
DO - 10.1016/j.yjmcc.2022.12.001
M3 - Article
C2 - 36493852
AN - SCOPUS:85143739170
SN - 0022-2828
VL - 175
SP - 13
EP - 28
JO - Journal of molecular and cellular cardiology
JF - Journal of molecular and cellular cardiology
ER -