Ups and downs in heart failure: the case of proteomics

Farmakis, Dimitrios; Papingiotis, Georgios; Parissis, John; Filippatos, Gerasimos

doi:10.1002/ejhf.1065

Cited by 7 publications

(7 citation statements)

References 32 publications

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“…The advent of proteomic technologies has allowed simultaneous quantification of thousands of proteins in human cells, blood, and tissues, in stark contrast to previous biomarker research that focused on single or several protein measurements ( 13 ). Proteomics has been increasingly applied to identify novel biomarkers, reveal pathophysiological mechanisms, and develop novel therapeutic targets for cardiovascular diseases since the late 1990s ( 14–17 ). Furthermore, improvements in proteomic techniques and integration with genomics have provided broader application prospects for proteomics.…”

Section: Introductionmentioning

confidence: 99%

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

Yang

Yan²,

Zhang³

et al. 2023

Front. Cardiovasc. Med.

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BackgroundHeart 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.MethodsSummary-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.ResultsUsing 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.ConclusionThe 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.

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Section: Introductionmentioning

confidence: 99%

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

Yang

Yan²,

Zhang³

et al. 2023

Front. Cardiovasc. Med.

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“…A combination of biomarkers and imaging technologies will be needed to improve patient stratification. ‘Omics’, artificial intelligence, and machine learning approaches will play a major role in the future 36,37 . Biomarker‐guided approaches can have further benefits, as in evaluating toxicity, dose ranging, patient stratification and therapy monitoring.…”

Section: Phenotyping Patients For Targeted Therapiesmentioning

confidence: 99%

Patient profiling in heart failure for tailoring medical therapy. A consensus document of the Heart Failure Association of the European Society of Cardiology

Rosano

Moura

Metra

et al. 2021

European J of Heart Fail

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198

192

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Despite guideline recommendations and available evidence, implementation of treatment in heart failure (HF) is poor. The majority of patients are not prescribed drugs at target doses that have been proven to positively impact morbidity and mortality. Among others, tolerability issues related to low blood pressure, heart rate, impaired renal function or hyperkalaemia are responsible. Chronic kidney disease plays an important role as it affects up to 50% of patients with HF. Also, dynamic changes in estimated glomerular filtration rate may occur during

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“…Alterations in proteome patterns, such as global changes in protein expression and post-translational modifications (PTMs), are often indicative of marked changes in functional stages in health and disease (15). Thus, investigating the varying patterns of the proteome may provide insights into pathogenic pathways (16) and these protein signatures may Abbreviations: ACTA1, skeletal alpha-actin; EF, ejection fraction; GLUT1, glucose transporter 1; GLUT4, glucose transporter 4; HF, heart failure; HFpEF, heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction; IVST, interventricular septum wall thickness; LV, left ventricle; LVEF, left ventricle ejection fraction; LVEDD, left ventricle end diastolic diameter; LVESD, left ventricle end systolic diameter; MFN1, mitofusin 1; MS/MS, tandem mass spectrometry; MYH7, beta-myosin heavy chain; MYH9, myosin heavy chain 9; OXCT1, succinyl-CoA:3-ketoacid coenzyme A transferase 1; PM1, tropomyosin alpha-1 chain; PTM, post-translational modification; RWT, relative wall thickness; SLC16A1, monocarboxylate transporter 1; SIRT3, sirtuin-3; TFAM, transcription factor A mitochondrial; TWT, total wall thickness.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Proteomic and phosphoproteomic profiling in heart failure with preserved ejection fraction (HFpEF)

Valero-Muñoz

Saw

Hekman

et al. 2022

Front. Cardiovasc. Med.

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Although the prevalence of heart failure with preserved ejection fraction (HFpEF) is increasing, evidence-based therapies for HFpEF remain limited, likely due to an incomplete understanding of this disease. This study sought to identify the cardiac-specific features of protein and phosphoprotein changes in a murine model of HFpEF using mass spectrometry. HFpEF mice demonstrated moderate hypertension, left ventricle (LV) hypertrophy, lung congestion and diastolic dysfunction. Proteomics analysis of the LV tissue showed that 897 proteins were differentially expressed between HFpEF and Sham mice. We observed abundant changes in sarcomeric proteins, mitochondrial-related proteins, and NAD-dependent protein deacetylase sirtuin-3 (SIRT3). Upregulated pathways by GSEA analysis were related to immune modulation and muscle contraction, while downregulated pathways were predominantly related to mitochondrial metabolism. Western blot analysis validated SIRT3 downregulated cardiac expression in HFpEF vs. Sham (0.8 ± 0.0 vs. 1.0 ± 0.0; P < 0.001). Phosphoproteomics analysis showed that 72 phosphosites were differentially regulated between HFpEF and Sham LV. Aberrant phosphorylation patterns mostly occurred in sarcomere proteins and nuclear-localized proteins associated with contractile dysfunction and cardiac hypertrophy. Seven aberrant phosphosites were observed at the z-disk binding region of titin. Additional agarose gel analysis showed that while total titin cardiac expression remained unaltered, its stiffer N2B isoform was significantly increased in HFpEF vs. Sham (0.144 ± 0.01 vs. 0.127 ± 0.01; P < 0.05). In summary, this study demonstrates marked changes in proteins related to mitochondrial metabolism and the cardiac contractile apparatus in HFpEF. We propose that SIRT3 may play a role in perpetuating these changes and may be a target for drug development in HFpEF.

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Ups and downs in heart failure: the case of proteomics

Cited by 7 publications

References 32 publications

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

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

Patient profiling in heart failure for tailoring medical therapy. A consensus document of the Heart Failure Association of the European Society of Cardiology

Proteomic and phosphoproteomic profiling in heart failure with preserved ejection fraction (HFpEF)

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