Metabolomic Profile in HFpEF vs HFrEF Patients

Hage, Camilla; Löfgren, Lars; Michopoulos, Filippos; Nilsson, Ralf; Davidsson, Pia; Kumar, Chanchal; Ekström, Mattias; Eriksson, Maria; Lyngå, Patrik; Persson, Bengt; Wallén, Håkan; Gan, Li; Persson, Hans; Linde, Cecilia

doi:10.1016/j.cardfail.2020.07.010

Cited by 63 publications

(58 citation statements)

References 36 publications

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“…For example, the biological processes of MLYCD , FKBP5 , PRKCD , and GDA were associated with energy metabolism and immune response, while those of SERPINE1 were associated with the inflammatory response. This was consistent with the pathological phenotypes, including immune dysregulation, metabolic dysfunction, and activation of chronic inflammation, of various tissues in patients with HFpEF ( Hage et al, 2020 ; Sava et al, 2020 ; Schiattarella et al, 2021 ).…”

Section: Resultssupporting

confidence: 87%

Multiple-Tissue and Multilevel Analysis on Differentially Expressed Genes and Differentially Correlated Gene Pairs for HFpEF

et al. 2021

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Heart failure with preserved ejection fraction (HFpEF) is a complex disease characterized by dysfunctions in the heart, adipose tissue, and cerebral arteries. The elucidation of the interactions between these three tissues in HFpEF will improve our understanding of the mechanism of HFpEF. In this study, we propose a multilevel comparative framework based on differentially expressed genes (DEGs) and differentially correlated gene pairs (DCGs) to investigate the shared and unique pathological features among the three tissues in HFpEF. At the network level, functional enrichment analysis revealed that the networks of the heart, adipose tissue, and cerebral arteries were enriched in the cell cycle and immune response. The networks of the heart and adipose tissues were enriched in hemostasis, G-protein coupled receptor (GPCR) ligand, and cancer-related pathway. The heart-specific networks were enriched in the inflammatory response and cardiac hypertrophy, while the adipose-tissue-specific networks were enriched in the response to peptides and regulation of cell adhesion. The cerebral-artery-specific networks were enriched in gene expression (transcription). At the module and gene levels, 5 housekeeping DEGs, 2 housekeeping DCGs, 6 modules of merged protein–protein interaction network, 5 tissue-specific hub genes, and 20 shared hub genes were identified through comparative analysis of tissue pairs. Furthermore, the therapeutic drugs for HFpEF-targeting these genes were examined using molecular docking. The combination of multitissue and multilevel comparative frameworks is a potential strategy for the discovery of effective therapy and personalized medicine for HFpEF.

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Section: Resultssupporting

confidence: 87%

Multiple-Tissue and Multilevel Analysis on Differentially Expressed Genes and Differentially Correlated Gene Pairs for HFpEF

et al. 2021

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“…Our findings are consistent with a study in a murine HFpEF model of metabolic disorder, in which researchers found that β-hydroxybutyrate was an effective treatment, as it targets the acetyl-CoA pool and mitochondrial acetylation ( 32 ). Furthermore, a clinical study including 46 patients with new-onset HFpEF and 75 patients with new-onset HFrEF revealed 11 plasma metabolites that differed between the two groups, and proposed that the hearts of patients with HFpEF tended to show increased rates of fibrosis, oxidative stress, and inflammation compared with those of patients with HFrEF ( 33 ). Together, these results suggested that metabolic pathways could be effective targets for HFpEF therapy.…”

Section: Discussionmentioning

confidence: 99%

A Porcine Model of Heart Failure With Preserved Ejection Fraction Induced by Chronic Pressure Overload Characterized by Cardiac Fibrosis and Remodeling

Tan

Zheng

et al. 2021

Front. Cardiovasc. Med.

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Heart failure is induced by multiple pathological mechanisms, and current therapies are ineffective against heart failure with preserved ejection fraction (HFpEF). As there are limited animal models of HFpEF, its underlying mechanisms have not yet been elucidated. Here, we employed the descending aortic constriction (DAC) technique to induce chronic pressure overload in the left ventricles of Tibetan minipigs for 12 weeks. Cardiac function, pathological and cellular changes, fibrotic signaling activation, and gene expression profiles were explored. The left ventricles developed concentric hypertrophy from weeks 4 to 6 and transition to dilation starting in week 10. Notably, the left ventricular ejection fraction was maintained at >50% in the DAC group during the 12-week period. Pathological examination, biochemical analyses, and gene profile analysis revealed evidence of inflammation, fibrosis, cell death, and myofilament dephosphorylation in the myocardium of HFpEF model animals, together with gene expression shifts promoting cardiac remodeling and downregulating metabolic pathways. Furthermore, we noted the activation of several signaling proteins that impact cardiac fibrosis and remodeling, including transforming growth factor-β/SMAD family members 2/3, type I/III/V collagens, phosphatidylinositol 3-kinase, extracellular signal-regulated kinase, matrix metalloproteinases 2 and 9, tissue inhibitor of metalloproteinases 1 and 2, interleukins 6 and 1β, and inhibitor of κBα/nuclear factor-κB. Our findings demonstrate that this chronic pressure overload-induced porcine HFpEF model is a powerful tool to elucidate the mechanisms of this disease and translate preclinical findings.

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“…Non‐cardiac comorbidities are frequently present in elderly HF patients, and the comorbidities including metabolic disorders such as cachexia have profound impacts on plasma metabolites. 12 , 13 , 19 Although plasma metabolites in cancer patients with cachexia were analysed in several earlier studies, the association of plasma amino acids with cachexia in HF patients has not been examined. An attempt to examine the association may lead to the development of a plasma marker of cachexia.…”

Section: Introductionmentioning

confidence: 99%

Plasma amino acid profiling improves predictive accuracy of adverse events in patients with heart failure

et al. 2021

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AimsThe clinical outcome of heart failure (HF) is complicated by the presence of multiple comorbidities including malnutrition and cachexia, and prediction of the outcome is still difficult in each patient. Metabolomics including amino acid profiling enables detection of alterations in whole body metabolism. The aim of this study was to determine whether plasma amino acid profiling improves prediction of clinical outcomes in patients with HF. Methods and resultsWe retrospectively examined 301 HF patients (70 ± 15 years old; 59% male). Blood samples for measurements of amino acid concentrations were collected in a fasting state after stabilization of HF. Plasma amino acid concentrations were measured using ultraperformance liquid chromatography. Clinical endpoint of this study was adverse event defined as all-cause death and unscheduled readmission due to worsening HF or lethal arrhythmia. During a mean follow-up period of 380 ± 214 days, 40 patients (13%) had adverse events. Results of analyses of variable importance in projection score, a measure of a variable's importance in partial least squares-discriminant analysis (PLS-DA) showed that the top five amino acids being associated with adverse events were 3-methylhistidine (3-Me-His), β-alanine, valine, hydroxyproline, and tryptophan. Multivariate Cox-proportional hazard analyses indicated that a high 3-Me-His concentration and low β-alanine and valine concentrations were independently associated with adverse events. When HF patients were divided according to the cut-off values of amino acids calculated from receiver operating characteristic curves, Kaplan-Meier survival curves showed that event-free survival rates were lower in HF patients with high 3-Me-His than in HF patients with low 3-Me-His (68% vs. 91%, P < 0.01). In a subgroup with high 3-Me-His, HF patients with low β-alanine and those with low valine had significantly lower event-free survival rates than did HF patients with high β-alanine and those with high valine, respectively. On the other hand, Kaplan-Meier curves of event-free survival rates did not differ between HF patients with and those without low β-alanine and low valine in subgroups of patients with low 3-Me-His. Inclusion of both high 3-Me-His and low β-alanine or low valine into the adjustment model including N-terminal pro-brain natriuretic peptide improved the accuracy of prediction of adverse events after discharge. 3-Me-His concentration was associated with muscle mass and nutritional status. Conclusions Simple measurement of 3-Me-His with either β-alanine or valine improved the predictive ability for adverse events, indicating the utility of plasma amino acid profiling in risk stratification of hospitalized HF patients.

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Metabolomic Profile in HFpEF vs HFrEF Patients

Cited by 63 publications

References 36 publications

Multiple-Tissue and Multilevel Analysis on Differentially Expressed Genes and Differentially Correlated Gene Pairs for HFpEF

Multiple-Tissue and Multilevel Analysis on Differentially Expressed Genes and Differentially Correlated Gene Pairs for HFpEF

A Porcine Model of Heart Failure With Preserved Ejection Fraction Induced by Chronic Pressure Overload Characterized by Cardiac Fibrosis and Remodeling

Plasma amino acid profiling improves predictive accuracy of adverse events in patients with heart failure

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