Soluble Glycoprotein 130 and Heat Shock Protein 27 as Novel Candidate Biomarkers of Chronic Heart Failure with Preserved Ejection Fraction

Liu, Shengchen; Iskandar, Reinard; Chen, Wen; Zhang, Jie; Wang, Yifei; Chen, Xin; Fei, Xiang

doi:10.1016/j.hlc.2016.02.011

Cited by 18 publications

(15 citation statements)

References 12 publications

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“…One prior study in two cohorts of elderly patients showed that higher circulating CATS levels are independently associated with a higher risk of death 30 . Two other studies in chronic HF patients 31 and in patients with stable coronary heart disease 32 did not show any difference in plasma CATS level when measured by ELISA, confirming our results.…”

Section: Discussionsupporting

confidence: 89%

Circulating Proteomic Signature of Early Death in Heart Failure Patients with Reduced Ejection Fraction

et al. 2019

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Heart failure (HF) remains a main cause of mortality worldwide. Risk stratification of patients with systolic chronic HF is critical to identify those who may benefit from advanced HF therapies. The aim of this study is to identify plasmatic proteins that could predict the early death (within 3 years) of HF patients with reduced ejection fraction hospitalized in cHRU de Lille. the subproteome targeted by an aptamer-based technology, the Slow Off-rate Modified Aptamer (SOMA) scan assay of 1310 proteins, was profiled in blood samples from 168 HF patients, and 203 proteins were significantly modulated between patients who died of cardiovascular death and patients who were alive after 3 years of HF evaluation (Wilcoxon test, FDR 5%). A molecular network was built using these 203 proteins, and the resulting network contained 2281 molecules assigned to 34 clusters annotated to biological pathways by Gene Ontology. This network model highlighted extracellular matrix organization as the main mechanism involved in early death in HF patients. In parallel, an adaptive Least Absolute Shrinkage and Selection Operator (LASSO) was performed on these 203 proteins, and six proteins were selected as candidates to predict early death in HF patients: complement C3, cathepsin S and F107B were decreased and MAPK5, MMP1 and MMP7 increased in patients who died of cardiovascular causes compared with patients living 3 years after HF evaluation. This proteomic signature of 6 circulating plasma proteins allows the identification of systolic HF patients with a risk of early death. Heart failure (HF) is an important cause of mortality worldwide 1. HF has different origins: non-ischaemic, such as cardiomyopathies, or ischaemic, after myocardial infarction (MI). Detection and treatment of HF are still unsatisfactory. Risk stratification of systolic HF patients is an important issue that can lead high-risk patients to invasive strategies New York Heart Association (NYHA) class, left ventricular ejection fraction (LVEF), B-type natriuretic peptide (BNP) level and peak exercise oxygen consumption (peak VO 2) have been associated with the early death of HF patients 2,3. However, this stratification needs to be improved. Prediction of mortality in HF patients using "conventional" prognostic evaluation showed moderate success and emphasized the requirement of models using a systems biology approach 4. We previously performed proteomic profiling in a case/control study that had included patients with systolic HF. Forty-two differentially intense peaks were identified and used to develop proteomic scores. These scores allowed a better discrimination of HF patients 5. Recently, a profiling by matrix-assisted laser desorption-ionization MS (MALDI-MS) showed that 14 peptides identified in plasma can predict clinical outcomes in HF patients 6. Recent advances in systems biology have opened new opportunities in the study of biomarker discovery and of the mechanistic context of HF. While previous analyses relied on the study of individual molecules, molecula...

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Section: Discussionsupporting

confidence: 89%

Circulating Proteomic Signature of Early Death in Heart Failure Patients with Reduced Ejection Fraction

et al. 2019

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“…Twenty-eight were performed in Europe [ 20 , 32 – 36 , 38 , 40 , 41 , 43 – 45 , 50 , 52 , 53 , 55 – 57 , 59 , 63 , 64 , 66 , 69 , 73 , 76 – 78 ], 11 in North America [ 22 , 37 , 39 , 46 , 49 , 54 , 65 , 70 , 72 , 74 , 75 ], 11 in Asia [ 31 , 42 , 47 , 51 , 58 , 60 – 62 , 67 , 68 , 71 ] and one was a multi-country study [ 48 ]. The control populations were either healthy controls ( N = 14) [ 31 , 35 , 59 , 60 , 62 , 65 , 67 – 69 , 71 , 72 , 75 – 77 ] or were recruited at the same department as the patient population, but without DD or HFpEF ( N = 37) [ 32 – 34 , 36 – 42 , 58 , 61 , 63 , 64 , 66 , 70 ]. The mean age of the DD and HFpEF populations ranged from 51 to 74 years and...…”

Section: Resultsmentioning

confidence: 99%

Natriuretic peptides for the detection of diastolic dysfunction and heart failure with preserved ejection fraction—a systematic review and meta-analysis

Remmelzwaal

Ballegooijen

Schoonmade

et al. 2020

BMC Med

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Background An overview of the diagnostic performance of natriuretic peptides (NPs) for the detection of diastolic dysfunction (DD) and heart failure with preserved ejection fraction (HFpEF), in a non-acute setting, is currently lacking. Methods We performed a systematic literature search in PubMed and Embase.com (May 13, 2019). Studies were included when they (1) reported diagnostic performance measures, (2) are for the detection of DD or HFpEF in a non-acute setting, (3) are compared with a control group without DD or HFpEF or with patients with heart failure with reduced ejection fraction, (4) are in a cross-sectional design. Two investigators independently assessed risk of bias of the included studies according to the QUADAS-2 checklist. Results were meta-analysed when three or more studies reported a similar diagnostic measure. Results From 11,728 titles/abstracts, we included 51 studies. The meta-analysis indicated a reasonable diagnostic performance for both NPs for the detection of DD and HFpEF based on AUC values of approximately 0.80 (0.73–0.87; I2 = 86%). For both NPs, sensitivity was lower than specificity for the detection of DD and HFpEF: approximately 65% (51–85%; I2 = 95%) versus 80% (70–90%; I2 = 97%), respectively. Both NPs have adequate ability to rule out DD: negative predictive value of approximately 85% (78–93%; I2 = 95%). The ability of both NPs to prove DD is lower: positive predictive value of approximately 60% (30–90%; I2 = 99%). Conclusion The diagnostic performance of NPs for the detection of DD and HFpEF is reasonable. However, they may be used to rule out DD or HFpEF, and not for the diagnosis of DD or HFpEF.

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“…Upregulated as well is NPPA encoding for atrial natriuretic peptide (ANP), a biomarker for cardiac hypertrophy and heart failure ( Figure 4 ). Two genes that code for recently proposed novel biomarkers for HFpEF were also upregulated: HSPB1 , which codes for cardioprotective heat shock protein 27 (hsp27) ( 14 , 15 ) and ANG which codes for angiogenin, a protein important for vascularization ( 16 ).…”

Section: Resultsmentioning

confidence: 99%

In Silico Analysis of Differential Gene Expression in Three Common Rat Models of Diastolic Dysfunction

Altara

Zouein

Brandão

et al. 2018

Front. Cardiovasc. Med.

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Standard therapies for heart failure with preserved ejection fraction (HFpEF) have been unsuccessful, demonstrating that the contribution of the underlying diastolic dysfunction pathophysiology differs from that of systolic dysfunction in heart failure and currently is far from being understood. Complicating the investigation of HFpEF is the contribution of several comorbidities. Here, we selected three established rat models of diastolic dysfunction defined by three major risk factors associated with HFpEF and researched their commonalities and differences. The top differentially expressed genes in the left ventricle of Dahl salt sensitive (Dahl/SS), spontaneous hypertensive heart failure (SHHF), and diabetes 1 induced HFpEF models were derived from published data in Gene Expression Omnibus and used for a comprehensive interpretation of the underlying pathophysiological context of each model. The diversity of the underlying transcriptomic of the heart of each model is clearly observed by the different panel of top regulated genes: the diabetic model has 20 genes in common with the Dahl/SS and 15 with the SHHF models. Advanced analytics performed in Ingenuity Pathway Analysis (IPA®) revealed that Dahl/SS heart tissue transcripts triggered by upstream regulators lead to dilated cardiomyopathy, hypertrophy of heart, arrhythmia, and failure of heart. In the heart of SHHF, a total of 26 genes were closely linked to cardiovascular disease including cardiotoxicity, pericarditis, ST-elevated myocardial infarction, and dilated cardiomyopathy. IPA Upstream Regulator analyses revealed that protection of cardiomyocytes is hampered by inhibition of the ERBB2 plasma membrane-bound receptor tyrosine kinases. Cardioprotective markers such as natriuretic peptide A (NPPA), heat shock 27 kDa protein 1 (HSPB1), and angiogenin (ANG) were upregulated in the diabetes 1 induced model; however, the model showed a different underlying mechanism with a majority of the regulated genes involved in metabolic disorders. In conclusion, our findings suggest that multiple mechanisms may contribute to diastolic dysfunction and HFpEF, and thus drug therapies may need to be guided more by phenotypic characteristics of the cardiac remodeling events than by the underlying molecular processes.

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Soluble Glycoprotein 130 and Heat Shock Protein 27 as Novel Candidate Biomarkers of Chronic Heart Failure with Preserved Ejection Fraction

Cited by 18 publications

References 12 publications

Circulating Proteomic Signature of Early Death in Heart Failure Patients with Reduced Ejection Fraction

Circulating Proteomic Signature of Early Death in Heart Failure Patients with Reduced Ejection Fraction

Natriuretic peptides for the detection of diastolic dysfunction and heart failure with preserved ejection fraction—a systematic review and meta-analysis

In Silico Analysis of Differential Gene Expression in Three Common Rat Models of Diastolic Dysfunction

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