Plasma proteomic approach in patients with heart failure: insights into pathogenesis of disease progression and potential novel treatment targets

Kidney-tonifying blood-activating decoction delays ventricular remodeling in rats with chronic heart failure by regulating gut microbiota and metabolites and p38 mitogen-activated protein kinase/p65 nuclear factor kappa-B/aquaporin-4 signaling pathway

ETHNOPHARMACOLOGICAL RELEVANCE

Myocardial infarction has likely contributed to the increased prevalence of heart failure(HF).As a result of ventricular remodeling and reduced cardiac function, colonic blood flow decreases, causing mucosal ischemia and hypoxia of the villous structure of the intestinal wall.This damage in gut barrier function increases bowel wall permeability, leading to fluid metabolism disorder,gut microbial dysbiosis, increased gut bacteria translocation into the circulatory system and increased circulating endotoxins, thus promoting a typical inflammatory state.Traditional Chinese Medicine plays a key role in the prevention and treatment of HF.Kidney-tonifying Blood-activating(KTBA) decoction has been proved for clinical treatment of chronic HF.However,the mechanism of KTBA decoction on chronic HF is still unclear.

AIMS OF THE STUDY

The effect of KTBA decoction on gut microbiota and metabolites and p38MAPK/p65NF-κB/AQP4 signaling in rat colon was studied to investigate the mechanism that KTBA decoction delays ventricular remodeling and regulates water metabolism disorder in rats with HF after myocardial infarction based on the theory of "Kidney Storing Essence and Conducting Water".

MATERIAL AND METHODS

In vivo,a rat model of HF after myocardial infarction was prepared by ligating the left anterior descending coronary artery combined with exhaustive swimming and starvation.The successful modeling rats were randomly divided into five groups:model group, tolvaptan group(gavaged 1.35mg/(kg•D) tolvaptan),KTBA decoction group(gavaged 15.75g/(kg•D) of KTBA decoction),KTBA decoction combined with SB203580(p38MAPK inhibitor) group(gavaged 15.75g/(kg•D) of KTBA decoction and intraperitoneally injected 1.5mg/(kg•D) of SB203580),and KTBA decoction combined with PDTC(p65NF-kB inhibitor) group(gavaged 15.75g/(kg•D) of KTBA decoction and intraperitoneally injected 120mg/(kg•D) of PDTC).The sham-operation group and model group were gavaged equal volume of normal saline.After 4 weeks of intervention with KTBA decoction,the effect of KTBA decoction on the cardiac structure and function of chronic HF model rats was observed by ultrasonic cardiogram.General state and cardiac index in rats were evaluated.Enzyme linked immunosorbent assay(ELISA) was used to measure N-terminal pro-brain natriuretic peptide (NT-proBNP) concentration in rat serum.Hematoxylin and eosin(H&E) staining,and transmission electron microscope(TEM) were used to observe the morphology and ultrastructure of myocardial and colonic tissue,and myocardial fibrosis was measured by Masson's staining.Cardiac E-cadherin level was detected by Western blot.The mRNA expression and protein expression levels of p38MAPK,I-κBα, p65NF-κB,AQP4,Occludin and ZO-1 in colonic tissue were detected by reverse transcription-quantitative real-time polymerase chain reaction(RT-qPCR) and immunohistochemistry. Protein expression of p38MAPK, p-p38MAPK,I-κBα,p-I-κBα,p65NF-κB, p-p65NF-κB,AQP4,Occludin and ZO-1 in rat colon was detected using Western blot.Colonic microbiota and serum metabolites were respectively analyzed by amplicon sequencing and liquid chromatography-mass spectrometry.In vitro, CCD-841CoN cell was placed in the ischemic solution under hypoxic conditions (94%N2,5%CO2,and 1%O2) in a 37 °C incubator to establish an ischemia and hypoxia model.The CCD-841CoN cells were divided into 7 groups, namely blank group and model group with normal rat serum plus control siRNA, tolvaptan group with rat serum containing tolvaptan plus control siRNA, KTBA group with rat serum containing KTBA plus control siRNA, KTBA plus p38MAPK siRNA group, KTBA plus p65NF-κB siRNA group,and KTBA plus AQP4siRNA group.After 24h and 48h of intervention with KTBA decoction,RT-qPCR,immunofluorescence and Western blot was used to detect the mRNA expression and protein expression levels of p38MAPK,I-κBα,p65NF-κB,AQP4, Occludin and ZO-1 in CCD-841CoN cells.

RESULTS

Compared with the model, KTBA decoction improved the general state, decraesed the serum NT-proBNP level,HW/BW ratio, LVIDd and LVIDs, increased E-cadherin level,EF and FS,reduced number of collagen fibers deposited in the myocardial interstitium,and recovered irregular arrangement of myofibril and swollen or vacuolated mitochondria with broken crista in myocardium.Moreover, KTBA decoction inhibited the expression of p38MAPK,I-κBα,and p65NF-κB and upregulated AQP4, Occludin and ZO-1 in colon tissues and CCD-841CoN cells.Additionally,p38siRNA or SB203580, p65siRNA or PDTC, and AQP4siRNA partially weakened the protective effects of KTBA in vitro and vivo.Notably,The LEfSe analysis results showed that there were six gut biomaker bacteria in model group, including Allobaculum, Bacillales,Turicibacter, Turicibacterales,Turicibacteraceae,and Bacilli. Besides, three gut biomaker bacteria containing Deltaproteobacteria, Desulfovibrionaceae,and Desulfovibrionales were enriched by KTBA treatment in chronic HF model.There were five differential metabolites, including L-Leucine,Pelargonic acid, Capsidiol,beta-Carotene,and L- Erythrulose, which can be regulated back in the same changed metabolic routes by the intervention of KTBA.L-Leucine had the positive correlation with Bacillales, Turicibacterales,Turicibacteraceae,and Turicibacter.L-Leucine significantly impacts Protein digestion and absorption, Mineral absorption,and Central carbon metabolism in cancer regulated by KTBA, which is involved in the expression of MAPK and tight junction in intestinal epithelial cells.

CONCLUSIONS

KTBA decoction manipulates the expression of several key proteins in the p38MAPK/p65NF-κB/AQP4 signaling pathway, modulates gut microbiota and metabolites toward a more favorable profile, improves gut barrier function, delays cardiomyocyte hypertrophy and fibrosis,and improves cardiac function.

The brain-heart axis: Integrative analysis of the shared genetic etiology between neuropsychiatric disorders and cardiovascular disease

BACKGROUND

Multiple observational studies have reported substantial comorbidity between neuropsychiatric disorders and cardiovascular disease (CVD), but the underlying mechanisms remain largely unknown.

METHODS

Using GWAS summary datasets of 8 neuropsychiatric disorders and 6 cardiovascular diseases, an integrative analysis incorporating linkage-disequilibrium-score-regression (LDSC), Mendelian randomization (MR), functional mapping and annotation (FUMA), and functional enrichment analysis, was conducted to investigate shared genetic etiology of the brain-heart axis from the whole genome level, single-nucleotide polymorphism (SNP) level, gene level, and biological pathway level.

RESULTS

In LDSC analysis, 18 pairwise traits between neuropsychiatric disorders and CVD were identified with significant genetic overlaps, revealing extensive genome-wide genetic correlations. In bidirectional MR analysis, 19 pairwise traits were identified with significant causal relationships. Genetic liabilities to neuropsychiatric disorders, particularly attention-deficit hyperactivity disorder and major depressive disorder, conferred extensive significant causal effects on the risk of CVD, while hypertension seemed to be a risk factor for multiple neuropsychiatric disorders, with no significant heterogeneity or pleiotropy. In FUMA analysis, 13 shared independent significant SNPs and 887 overlapping protein-coding genes were detected between neuropsychiatric disorders and CVD. With GO and KEEG functional enrichment analysis, biological pathways of the brain-heart axis were highly concentrated in neurotransmitter synaptic transmission, lipid metabolism, aldosterone synthesis and secretion, glutathione metabolism, and MAPK signaling pathway.

CONCLUSION

Extensive genetic correlations and genetic overlaps between neuropsychiatric disorders and CVD were identified in this study, which might provide some new insights into the brain-heart axis and the therapeutic targets in clinical practice.

Proteome-wide mendelian randomization investigates potential associations in heart failure and its etiology: emphasis on PCSK9

BACKGROUND

Heart failure (HF) is a prevalent clinical syndrome with diverse etiologies. It is crucial to identify novel therapeutic targets based on underlying causes. Here, we aimed to use proteome-wide Mendelian randomization (MR) analyses to identify the associations between genetically predicted elevated levels of circulating proteins and distinct HF outcomes, along with specific HF etiologies.

METHODS

Protein quantitative trait loci (pQTL) data for circulating proteins were sourced from the Atherosclerosis Risk in Communities (ARIC) study, encompassing 7,213 individuals and profiling 4,657 circulating proteins. Genetic associations for outcomes were obtained from the HERMES Consortium and the FinnGen Consortium. Colocalization analysis was employed to assess the impact of linkage disequilibrium on discovered relationships. For replication, two-sample MR was conducted utilizing independent pQTL data from the deCODE study. Multivariable MR (MVMR) and two-step MR were further conducted to investigate potential mediators.

RESULTS

Two proteins (PCSK9 and AIDA) exhibited associations with HF in patients with coronary heart disease (CHD), and four proteins (PCSK9, SWAP70, NCF1, and RELT) were related with HF in patients receiving antihypertensive medication. Among these associations, strong evidence from subsequent analyses supported the positive relationship between genetically predicted PCSK9 levels and the risk of HF in the context of CHD. Notably, MVMR analysis revealed that CHD and LDL-C did not exert a complete mediating effect in this relationship. Moreover, two-step MR results yielded valuable insights into the potential mediating proportions of CHD or LDL-C in this relationship.

CONCLUSIONS

Our findings provide robust evidence supporting the association between PCSK9 and concomitant HF and CHD. This association is partly elucidated by the influence of CHD or LDL-C, underscoring the imperative for additional validation of this connection and a thorough exploration of the mechanisms through which PCSK9 directly impacts ischemic HF.

Phenotyping patients with ischaemic heart disease at risk of developing heart failure: an analysis of the HOMAGE trial

AIMS

We aim to characterize the clinical and proteomic profiles of patients at risk of developing heart failure (HF), with and without coronary artery disease (CAD) or prior myocardial infarction (MI).

METHODS AND RESULTS

HOMAGE evaluated the effect of spironolactone on plasma and serum markers of fibrosis over 9 months of follow-up in participants with (or at risk of having) CAD, and raised natriuretic peptides. In this post hoc analysis, patients were classified as (i) neither CAD nor MI; (ii) CAD; or (iii) MI. Proteomic between-group differences were evaluated through logistic regression and narrowed using backward stepwise selection and bootstrapping. Among the 527 participants, 28% had neither CAD or MI, 31% had CAD, and 41% had prior MI. Compared with people with neither CAD nor MI, those with CAD had higher baseline plasma concentrations of matrix metalloproteinase-7 (MMP-7), galectin-4 (GAL4), plasminogen activator inhibitor 1 (PAI-1), and lower plasma peptidoglycan recognition protein 1 (PGLYRP1), whilst those with a history of MI had higher plasma MMP-7, neurotrophin-3 (NT3), pulmonary surfactant-associated protein D (PSPD), and lower plasma tumour necrosis factor-related activation-induced cytokine (TRANCE). Proteomic signatures were similar for patients with CAD or prior MI. Treatment with spironolactone was associated with an increase of MMP7, NT3, and PGLYRP1 at 9 months.

CONCLUSIONS

In patients at risk of developing HF, those with CAD or MI had a different proteomic profile regarding inflammatory, immunological, and collagen catabolic processes.

Network-based identification of diagnosis-specific trans-omic biomarkers via integration of multiple omics data

The integration of multiple omics data promises to reveal new insights into the pathogenic mechanisms of complex human diseases, with the potential to identify avenues for the development of targeted therapies for disease subtypes. However, the extraction of diagnostic/disease-specific biomarkers from multiple omics data with biological pathway knowledge is a challenging issue in precision medicine. In this paper, we present a novel computational method to identify diagnosis-specific trans-omic biomarkers from multiple omics data. In the algorithm, we integrated multi-class sparse canonical correlation analysis (MSCCA) and molecular pathway analysis in order to derive discriminative molecular features that are correlated across different omics layers. We applied our proposed method to analyzing proteome and metabolome data of heart failure (HF), and extracted trans-omic biomarkers for HF subtypes; specifically, ischemic cardiomyopathy (ICM) and dilated cardiomyopathy (DCM). We were able to detect not only individual proteins that were previously reported from single-omics studies but also correlated protein-metabolite pairs characteristic of HF disease subtypes. For example, we identified hexokinase1(HK1)-d-fructose-6-phosphate as a paired trans-omic biomarker for DCM, which could significantly perturb amino-sugar metabolism. Our proposed method is expected to be useful for various applications in precision medicine.

Integrative Proteomic Analysis Reveals the Cytoskeleton Regulation and Mitophagy Difference Between Ischemic Cardiomyopathy and Dilated Cardiomyopathy

Ischemic cardiomyopathy (ICM) and dilated cardiomyopathy (DCM) are the two primary etiologies of end-stage heart failure. However, there remains a dearth of comprehensive understanding the global perspective and the dynamics of the proteome and phosphoproteome in ICM and DCM, which hinders the profound comprehension of pivotal biological characteristics as well as differences in signal transduction activation mechanisms between these two major types of heart failure. We conducted high-throughput quantification proteomics and phosphoproteomics analysis of clinical heart tissues with ICM or DCM, which provided us the system-wide molecular insights into pathogenesis of clinical heart failure in both ICM and DCM. Both protein and phosphorylation expression levels exhibit distinct separation between heart failure and normal control heart tissues, highlighting the prominent characteristics of ICM and DCM. By integrating with omics results, Western blots, phosphosite-specific mutation, chemical intervention, and immunofluorescence validation, we found a significant activation of the PRKACA-GSK3β signaling pathway in ICM. This signaling pathway influenced remolding of the microtubule network and regulated the critical actin filaments in cardiac construction. Additionally, DCM exhibited significantly elevated mitochondria energy supply injury compared to ICM, which induced the ROCK1-vimentin signaling pathway activation and promoted mitophagy. Our study not only delineated the major distinguishing features between ICM and DCM but also revealed the crucial discrepancy in the mechanisms between ICM and DCM. This study facilitates a more profound comprehension of pathophysiologic heterogeneity between ICM and DCM and provides a novel perspective to assist in the discovery of potential therapeutic targets for different types of heart failure.

Technological development of multidimensional liquid chromatography-mass spectrometry in proteome research

Liquid chromatography-mass spectrometry (LC-MS) is the method of choice for high-throughput proteomic research. Limited by the peak capacity, the separation performance of conventional single-dimensional LC hampers the development of proteomics. Combining different separation modes orthogonally, multidimensional liquid chromatography (MDLC) with high peak capacity was developed to address this challenge. MDLC has evolved rapidly since its establishment, and the progress of proteomics has been greatly facilitated by the advent of novel MDLC-MS-based methods. In this paper, we will review the advances of MDLC-MS-based methodologies and technologies in proteomics studies, from different perspectives including novel application scenarios and proteomic targets, automation, miniaturization, and the improvement of the classic methods in recent years. In addition, attempts regarding new MDLC-MS models are also mentioned together with the outlook of MDLC-MS-based proteomics methods.

Estimating the causal effects of genetically predicted plasma proteome on heart failure

Background

Heart Failure (HF) is the end-stage cardiovascular syndrome with poor prognosis. Proteomics holds great promise in the discovery of novel biomarkers and therapeutic targets for HF. The aim of this study is to investigate the causal effects of genetically predicted plasma proteome on HF using the Mendelian randomization (MR) approach.

Methods

Summary-level data for the plasma proteome (3,301 healthy individuals) and HF (47,309 cases; 930,014 controls) were extracted from genome-wide association studies (GWASs) of European descent. MR associations were obtained using the inverse variance-weighted (IVW) method, sensitivity analyses, and multivariable MR analyses.

Results

Using single-nucleotide polymorphisms as instrumental variables, 1-SD increase in MET level was associated with an approximately 10% decreased risk of HF (odds ratio [OR]: 0.92; 95% confidence interval [CI]: 0.89 to 0.95; p = 1.42 × 10^-6), whereas increases in the levels of CD209 (OR: 1.04; 95% CI: 1.02-1.06; p = 6.67 × 10^-6) and USP25 (OR: 1.06; 95% CI: 1.03-1.08; p = 7.83 × 10^-6) were associated with an increased risk of HF. The causal associations were robust in sensitivity analyses, and no evidence of pleiotropy was observed.

Conclusion

The study findings suggest that the hepatocyte growth factor/c-MET signaling pathway, dendritic cells-mediated immune processes, and ubiquitin-proteasome system pathway are involved in the pathogenesis of HF. Moreover, the identified proteins have potential to uncover novel therapies for cardiovascular diseases.

Diabetes Mellitus and Heart Failure: Epidemiology, Pathophysiologic Mechanisms, and the Role of SGLT2 Inhibitors

Diabetes mellitus (DM) and heart failure (HF) are frequently encountered afflictions that are linked by a common pathophysiologic background. According to landmark studies, those conditions frequently coexist, and this interaction represents a poor prognostic indicator. Based on mechanistic studies, HF can be propagated by multiple pathophysiologic pathways, such as inflammation, oxidative stress, endothelial dysfunction, fibrosis, cardiac autonomic neuropathy, and alterations in substrate utilization. In this regard, DM may augment myocardial inflammation, fibrosis, autonomic dysfunction, and lipotoxicity. As the interaction between DM and HF appears critical, the new cornerstone in DM and HF treatment, sodium-glucose cotransporter-2 inhibitors (SGLT2i), may be able to revert the pathophysiology of those conditions and lead to beneficial HF outcomes. In this review, we aim to highlight the deleterious pathophysiologic interaction between DM and HF, as well as demonstrate the beneficial role of SGLT2i in this field.

Markers of aging: Unsupervised integrated analyses of the human plasma proteome

Aging associates with an increased susceptibility for disease and decreased quality of life. To date, processes underlying aging are still not well understood, leading to limited interventions with unknown mechanisms to promote healthy aging. Previous research suggests that changes in the blood proteome are reflective of age-associated phenotypes such as frailty. Moreover, experimentally induced changes in the blood proteome composition can accelerate or decelerate underlying aging processes. The aim of this study is to identify a set of proteins in the human plasma associated with aging by integration of the data of four independent, large-scaled datasets using the aptamer-based SomaScan platform on the human aging plasma proteome. Using this approach, we identified a set of 273 plasma proteins significantly associated with aging (aging proteins, APs) across these cohorts consisting of healthy individuals and individuals with comorbidities and highlight their biological functions. We validated the age-associated effects in an independent study using a centenarian population, showing highly concordant effects. Our results suggest that APs are more associated to diseases than other plasma proteins. Plasma levels of APs can predict chronological age, and a reduced selection of 15 APs can still predict individuals' age accurately, highlighting their potential as biomarkers of aging processes. Furthermore, we show that individuals presenting accelerated or decelerated aging based on their plasma proteome, respectively have a more aged or younger systemic environment. These results provide novel insights in the understanding of the aging process and its underlying mechanisms and highlight potential modulators contributing to healthy aging.

Identification of the metabolic state of surviving cardiomyocytes in the human infarcted heart by spatial single-cell transcriptomics

The metabolic status of surviving cardiomyocytes (CM) in the myocardial tissues of patients who sustained myocardial infarction (MI) is largely unknown. Spatial single-cell RNA-sequencing (scRNA-seq) is a novel tool that enables the unbiased analysis of RNA signatures within intact tissues. We employed this tool to assess the metabolic profiles of surviving CM in the myocardial tissues of patients post-MI.

Methods

A spatial scRNA-seq dataset was used to compare the genetic profiles of CM from patients with MI and control patients; we analyzed the metabolic adaptations of surviving CM within the ischemic niche. A standard pipeline in Seurat was used for data analysis, including normalization, feature selection, and identification of highly variable genes using principal component analysis (PCA). Harmony was used to remove batch effects and integrate the CM samples based on annotations. Uniform manifold approximation and projection (UMAP) was used for dimensional reduction. The Seurat "FindMarkers" function was used to identify differentially expressed genes (DEGs), which were analyzed by the Gene Ontology (GO) enrichment pathway. Finally, the scMetabolism R tool pipeline with parameters method = VISION (Vision is a flexible system that utilizes a high-throughput pipeline and an interactive web-based report to annotate and explore scRNA-seq datasets in a dynamic manner) and metabolism.type = Kyoto Encyclopedia of Genes and Genomes (KEGG) was used to quantify the metabolic activity of each CM.

Results

Analysis of spatial scRNA-seq data showed fewer surviving CM in infarcted hearts than in control hearts. GO analysis revealed repressed pathways in oxidative phosphorylation, cardiac cell development, and activated pathways in response to stimuli and macromolecular metabolic processes. Metabolic analysis showed downregulated energy and amino acid pathways and increased purine, pyrimidine, and one-carbon pool by folate pathways in surviving CM.

Conclusions

Surviving CM within the infarcted myocardium exhibited metabolic adaptations, as evidenced by the downregulation of most pathways linked to oxidative phosphorylation, glucose, fatty acid, and amino acid metabolism. In contrast, pathways linked to purine and pyrimidine metabolism, fatty acid biosynthesis, and one-carbon metabolism were upregulated in surviving CM. These novel findings have implications for the development of effective strategies to improve the survival of hibernating CM within the infarcted heart.

Metabolomics profile and 10-year atherosclerotic cardiovascular disease (ASCVD) risk score

Background

The intermediate metabolites associated with the development of atherosclerotic cardiovascular disease (ASCVD) remain largely unknown. Thus, we conducted a large panel of metabolomics profiling to identify the new candidate metabolites that were associated with 10-year ASCVD risk.

Methods

Thirty acylcarnitines and twenty amino acids were measured in the fasting plasma of 1,102 randomly selected individuals using a targeted FIA-MS/MS approach. The 10-year ASCVD risk score was calculated based on 2013 ACC/AHA guidelines. Accordingly, the subjects were stratified into four groups: low-risk (n = 620), borderline-risk (n = 110), intermediate-risk (n = 225), and high-risk (n = 147). 10 factors comprising collinear metabolites were extracted from principal component analysis.

Results

C₄DC, C_8:1, C₁₆OH, citrulline, histidine, alanine, threonine, glycine, glutamine, tryptophan, phenylalanine, glutamic acid, arginine, and aspartic acid were significantly associated with the 10-year ASCVD risk score (p-values ≤ 0.044). The high-risk group had higher odds of factor 1 (12 long-chain acylcarnitines, OR = 1.103), factor 2 (5 medium-chain acylcarnitines, OR = 1.063), factor 3 (methionine, leucine, valine, tryptophan, tyrosine, phenylalanine, OR = 1.074), factor 5 (6 short-chain acylcarnitines, OR = 1.205), factor 6 (5 short-chain acylcarnitines, OR = 1.229), factor 7 (alanine, proline, OR = 1.343), factor 8 (C_18:2OH, glutamic acid, aspartic acid, OR = 1.188), and factor 10 (ornithine, citrulline, OR = 1.570) compared to the low-risk ones; the odds of factor 9 (glycine, serine, threonine, OR = 0.741), however, were lower in the high-risk group. "D-glutamine and D-glutamate metabolism", "phenylalanine, tyrosine, and tryptophan biosynthesis", and "valine, leucine, and isoleucine biosynthesis" were metabolic pathways having the highest association with borderline/intermediate/high ASCVD events, respectively.

Conclusions

Abundant metabolites were found to be associated with ASCVD events in this study. Utilization of this metabolic panel could be a promising strategy for early detection and prevention of ASCVD events.

Diagnostic value of cardiac magnetic resonance imaging for myocardial fibrosis in patients with heart failure and its predictive value for prognosis

OBJECTIVE

To determine the diagnostic value of cardiac magnetic resonance imaging (CMRI) for myocardial fibrosis (MF) in patients with heart failure (HF) and its predictive value for prognosis.

METHODS

A total of 180 patients with heart failure who were hospitalized in the Cardiology Department of The First People's Hospital of Shangqiu City from September 2019 to May 2021 were selected and assigned to Group B (n=80) given levosimendan and Group A (n=100) given levosimendan combined with ivabradine hydrochloride. The cardiac function indicators (left ventricular end-systolic volume (LVESV), left ventricular ejection fraction (LVEF), and left ventricular end-systolic diameter (LVESD) were measured by nuclear magnetic resonance (MRI). Myocardial fibrosis (MF)-related indicators (pyridinoline cross-linked carboxy-terminal telopeptide of type I collagen (ICTP), N-terminal propeptide of procollagen type III (PIIINP), connective tissue growth factor (CTGF), and hyaluronic acid (HA), inflammatory factors (Hs-CRP and IL-8) were measured using ELISA. Quality of life (QoL) and physical recovery (6-min walking test (6MWT), Fugl-Meyer Assessment (FMA), and Barthel index) of the two groups were compared. The late gadolinium enhancement (LGE) was used to analyze the occurrence of MF in patients. The patients were further divided into the LGE (+) group (cases) and LGE (-) group (cases). The changes of cardiac function indicators before treatment were analyzed, and their predictive value was analyzed.

RESULTS

Compared with Group B, Group A showed a lower incidence of complications, and presented a higher LVEF level and lower levels of LVESV, LVESD, ICTP, PIIINP, CTGF, HA, LN, and inflammatory factors. The area under the curves of LVESV, LVESD, and LVEF in predicting MF were all >0.7.

CONCLUSION

Levosimendan combined with ivabradine hydrochloride can effectively alleviate MF in patients with MF, and CMRI has a good predictive value for MF in such patients, which is worthy of clinical promotion.

Dynamic personalized risk prediction in chronic heart failure patients: a longitudinal, clinical investigation of 92 biomarkers (Bio-SHiFT study)

The aim of our observational study was to derive a small set out of 92 repeatedly measured biomarkers with optimal predictive capacity for adverse clinical events in heart failure, which could be used for dynamic, individual risk assessment in clinical practice. In 250 chronic HFrEF (CHF) patients, we collected trimonthly blood samples during a median of 2.2 years. We selected 537 samples for repeated measurement of 92 biomarkers with the Cardiovascular Panel III (Olink Proteomics AB). We applied Least Absolute Shrinkage and Selection Operator (LASSO) penalization to select the optimal set of predictors of the primary endpoint (PE). The association between repeatedly measured levels of selected biomarkers and the PE was evaluated by multivariable joint models (mvJM) with stratified fivefold cross validation of the area under the curve (cvAUC). The PE occurred in 66(27%) patients. The optimal set of biomarkers selected by LASSO included 9 proteins: NT-proBNP, ST2, vWF, FABP4, IGFBP-1, PAI-1, PON-3, transferrin receptor protein-1, and chitotriosidase-1, that yielded a cvAUC of 0.88, outperforming the discriminative ability of models consisting of standard biomarkers (NT-proBNP, hs-TnT, eGFR clinically adjusted) − 0.82 and performing equally well as an extended literature-based set of acknowledged biomarkers (NT-proBNP, hs-TnT, hs-CRP, GDF-15, ST2, PAI-1, Galectin 3) − 0.88. Nine out of 92 serially measured circulating proteins provided a multivariable model for adverse clinical events in CHF patients with high discriminative ability. These proteins reflect wall stress, remodelling, endothelial dysfunction, iron deficiency, haemostasis/fibrinolysis and innate immunity activation. A panel containing these proteins could contribute to dynamic, personalized risk assessment.

Clinical Trial Registration: 10/05/2013 https://clinicaltrials.gov/ct2/show/NCT01851538?term=nCT01851538&draw=2&rank=1.

Next-Generation Sequencing and Proteomics of Cerebrospinal Fluid From COVID-19 Patients With Neurological Manifestations

The SARS-CoV-2 and its variants are still hitting the world. Ever since the outbreak, neurological involvements as headache, ageusia, and anosmia in COVID-19 patients have been emphasized and reported. But the pathogenesis of these new-onset neurological manifestations in COVID-19 patients is still obscure and controversial. As difficulty always lay in the diagnosis of neurological infection, current reports to validate the presence of SARS-CoV-2 in cerebrospinal fluid (CSF) almost relied on the basic methods and warranted improvement. Here we reported a case series of 8 patients with prominent new-onset neurological manifestations, who were screened out from a patch of 304 COVID-19 confirmed patients. Next-generation sequencing (NGS) and proteomics were conducted in the simultaneously obtained CSF and serum samples of the selected patients, with three non-COVID-19 patients with matched demographic features used as the controls for proteomic analysis. SARS-CoV-2 RNA was detected in the CSF of four COVID-19 patients and was suspicious in the rest four remaining patients by NGS, but was negative in all serum samples. Proteomic analysis revealed that 185 and 59 proteins were differentially expressed in CSF and serum samples, respectively, and that only 20 proteins were shared, indicating that the proteomic changes in CSF were highly specific. Further proteomic annotation highlighted the involvement of complement system, PI3K-Akt signaling pathway, enhanced cellular interaction, and macrophages in the CSF proteomic alterations. This study, equipped with NGS and proteomics, reported a high detection rate of SARS-CoV-2 in the CSF of COVID-19 patients and the proteomic alteration of CSF, which would provide insights into understanding the pathological mechanism of SARS-CoV-2 CNS infection.

Extensive mitochondrial proteome disturbance occurs during the early stages of acute myocardial ischemia

Mitochondrial malfunction leads to the remodeling of myocardial energy metabolism during myocardial ischemia (MI). However, the alterations to the mitochondrial proteome profile during this period has not yet been clarified. An acute MI model was established by high position ligation of the left anterior descending artery in 8-week-old C57BL/6N mice. After 15 min of ligation, the animals were euthanized, and their hearts were collected. The myocardial ultrastructure was observed using transmission electron microscopy (TEM). The cardiac mitochondrial proteome profile was analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and bioinformatics analyses. TEM showed that the outer membrane of the mitochondria was dissolved, and the inner membrane (cristae) was corrupted and broken down extensively in the MI group. The mitochondrial membrane potential was decreased. More than 1,700 mitochondrial proteins were identified by LC-MS/MS analysis, and 119 were differentially expressed. Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes functional enrichment analysis showed that endopeptidase activity regulation, the mitochondrial inner membrane, oxidative phosphorylation, the hypoxia-inducible factor-1 signaling pathway, the pentose phosphate pathway and the peroxisome proliferator-activated receptor signaling pathway were involved in the pathophysiological process in the early stage of acute MI. Extensive and substantial changes in the mitochondrial proteins as well as mitochondrial microstructural damage occur in the early stages of acute MI. In the present study, the series of proteins crucially involved in the pathways of mitochondrial dysfunction and metabolism were identified. Further studies are needed to clarify the roles of these proteins in myocardial metabolism remodeling during acute MI injury.

A year in heart failure: an update of recent findings

Major changes have occurred in these last years in heart failure (HF) management. Landmark trials and the 2021 European Society of Cardiology guidelines for the diagnosis and treatment of HF have established four classes of drugs for treatment of HF with reduced ejection fraction: angiotensin‐converting enzyme inhibitors or an angiotensin receptor‐neprilysin inhibitor, beta‐blockers, mineralocorticoid receptor antagonists, and sodium‐glucose co‐transporter 2 inhibitors, namely, dapagliflozin or empagliflozin. These drugs consistently showed benefits on mortality, HF hospitalizations, and quality of life. Correction of iron deficiency is indicated to improve symptoms and reduce HF hospitalizations. AFFIRM‐AHF showed 26% reduction in total HF hospitalizations with ferric carboxymaltose vs. placebo in patients hospitalized for acute HF (P = 0.013). The guanylate cyclase activator vericiguat and the myosin activator omecamtiv mecarbil improved outcomes in randomized placebo‐controlled trials, and vericiguat is now approved for clinical practice. Treatment of HF with preserved ejection fraction (HFpEF) was a major unmet clinical need until this year when the results of EMPEROR‐Preserved (EMPagliflozin outcomE tRial in Patients With chrOnic HFpEF) were issued. Compared with placebo, empagliflozin reduced by 21% (hazard ratio, 0.79; 95% confidence interval, 0.69 to 0.90; P < 0.001), the primary outcome of cardiovascular death or HF hospitalization. Advances in the treatment of specific phenotypes of HF, including atrial fibrillation, valvular heart disease, cardiomyopathies, cardiac amyloidosis, and cancer‐related HF, also occurred. Coronavirus disease 2019 (COVID‐19) pandemic still plays a major role in HF epidemiology and management. All these aspects are highlighted in this review.

Towards precision medicine in heart failure

The number of therapies for heart failure (HF) with reduced ejection fraction has nearly doubled in the past decade. In addition, new therapies for HF caused by hypertrophic and infiltrative disease are emerging rapidly. Indeed, we are on the verge of a new era in HF in which insights into the biology of myocardial disease can be matched to an understanding of the genetic predisposition in an individual patient to inform precision approaches to therapy. In this Review, we summarize the biology of HF, emphasizing the causal relationships between genetic contributors and traditional structure-based remodelling outcomes, and highlight the mechanisms of action of traditional and novel therapeutics. We discuss the latest advances in our understanding of both the Mendelian genetics of cardiomyopathy and the complex genetics of the clinical syndrome presenting as HF. In the phenotypic domain, we discuss applications of machine learning for the subcategorization of HF in ways that might inform rational prescribing of medications. We aim to bridge the gap between the biology of the failing heart, its diverse clinical presentations and the range of medications that we can now use to treat it. We present a roadmap for the future of precision medicine in HF.

The year in cardiology: heart failure

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Heart failure in the last year: progress and perspective

Research about heart failure (HF) has made major progress in the last years. We give here an update on the most recent findings. Landmark trials have established new treatments for HF with reduced ejection fraction. Sacubitril/valsartan was superior to enalapril in PARADIGM‐HF trial, and its initiation during hospitalization for acute HF or early after discharge can now be considered. More recently, new therapeutic pathways have been developed. In the DAPA‐HF and EMPEROR‐Reduced trials, dapagliflozin and empagliflozin reduced the risk of the primary composite endpoint, compared with placebo [hazard ratio (HR) 0.74; 95% confidence interval (CI) 0.65–0.85; P < 0.001 and HR 0.75; 95% CI 0.65–0.86; P < 0.001, respectively]. Second, vericiguat, an oral soluble guanylate cyclase stimulator, reduced the composite endpoint of cardiovascular death or HF hospitalization vs. placebo (HR 0.90; 95% CI 0.82–0.98; P = 0.02). On the other hand, both the diagnosis and treatment of HF with preserved ejection fraction, as well as management of advanced HF and acute HF, remain challenging. A better phenotyping of patients with HF would be helpful for prognostic stratification and treatment selection. Further aspects, such as the use of devices, treatment of arrhythmias, and percutaneous treatment of valvular heart disease in patients with HF, are also discussed and reviewed in this article.

Design, synthesis and biological evaluation of novel pyxinol derivatives with anti-heart failure activity

Heart failure (HF) is an important and leading cause of substantial morbidity and mortality globally. The angiotensin-converting enzymatic (ACE) is the causative source for congestive heart failure. Natural products and its derivatives play a vital role in drug discovery and development owing to their efficacy and low toxicity. Pyxinol is a potent natural agent for cardiovascular disease. Thus we investigated the effect on ACE and HF of pyxinol derivatives. We designed and synthesized 32 novel fatty acid ester derivatives of pyxinol via esterification. Among them, compounds 2e (IC₅₀=105 nM) and 3b (IC₅₀=114 nM) displayed excellent ACE inhibitory activity in vitro, and exhibited non-toxic to H9c2 cells. The interactions between ACE and compounds were predicted by molecular docking respectively. In verapamil-induced zebrafish HF model, the activity assay showed that these two derivatives could improve cardiovascular physiological indexes including heart beats, venous congestion, heart dilation, cardiac output, ejection fraction and fractional shortening in a dose-dependent manner. A UPLC-QTOF-MS-based serum metabolomics approach was applied to explore the latent mechanism. A total of 25 differentiated metabolites and 8 perturbed metabolic pathways were identified. These results indicated that pyxinol fatty acid ester derivatives 2e and 3b might be considered as potent drug candidates against heart failure and deserved further research and development.

Finding a Needle in a Haystack: Proteomics in Heart Failure

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Proteomics has aided HF biomarker discovery, which allows for greater disease insights.

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Experiment design can be tailored to HF research to discover novel biomarkers.

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Primary methods include MS, protein microarray, aptamer, and PEA-based technologies.

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Proteomics can detect unique low abundance proteins and detect protein modifications.

Circulating protein biomarkers provide information regarding pathways in heart failure (HF) and can add important value to clinicians. Advancements in proteomics allow researchers to measure a multitude of proteins simultaneously with excellent sensitivity and selectivity to detect low abundance proteins. This helps identify previously unrecognized pathways in HF and discover biomarkers and potential targets for HF therapies. Although several proteomic methods exist, including mass spectrometry, protein microarray, aptamer, and proximity extension assay−based techniques, each have their unique advantages. This paper provides an overview of the various proteomic methods, with examples of how each has contributed to understanding the pathways in HF.

Big Data Approaches in Heart Failure Research

PURPOSE OF REVIEW

The goal of this review is to summarize the state of big data analyses in the study of heart failure (HF). We discuss the use of big data in the HF space, focusing on "omics" and clinical data. We address some limitations of this data, as well as their future potential.

RECENT FINDINGS

Omics are providing insight into plasmal and myocardial molecular profiles in HF patients. The introduction of single cell and spatial technologies is a major advance that will reshape our understanding of cell heterogeneity and function as well as tissue architecture. Clinical data analysis focuses on HF phenotyping and prognostic modeling. Big data approaches are increasingly common in HF research. The use of methods designed for big data, such as machine learning, may help elucidate the biology underlying HF. However, important challenges remain in the translation of this knowledge into improvements in clinical care.