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Cardiac myosin binding protein-C is a potential diagnostic biomarker for myocardial infarction.

ABSTRACT: Cardiac myosin binding protein-C (cMyBP-C) is a thick filament assembly protein that stabilizes sarcomeric structure and regulates cardiac function; however, the profile of cMyBP-C degradation after myocardial infarction (MI) is unknown. We hypothesized that cMyBP-C is sensitive to proteolysis and is specifically increased in the bloodstream post-MI in rats and humans. Under these circumstances, elevated levels of degraded cMyBP-C could be used as a diagnostic tool to confirm MI. To test this hypothesis, we first established that cMyBP-C dephosphorylation is directly associated with increased degradation of this myofilament protein, leading to its release in vitro. Using neonatal rat ventricular cardiomyocytes in vitro, we were able to correlate the induction of hypoxic stress with increased cMyBP-C dephosphorylation, degradation, and the specific release of N'-fragments. Next, to define the proteolytic pattern of cMyBP-C post-MI, the left anterior descending coronary artery was ligated in adult male rats. Degradation of cMyBP-C was confirmed by a reduction in total cMyBP-C and the presence of degradation products in the infarct tissue. Phosphorylation levels of cMyBP-C were greatly reduced in ischemic areas of the MI heart compared to non-ischemic regions and sham control hearts. Post-MI plasma samples from these rats, as well as humans, were assayed for cMyBP-C and its fragments by sandwich ELISA and immunoprecipitation analyses. Results showed significantly elevated levels of cMyBP-C in the plasma of all post-MI samples. Overall, this study suggests that cMyBP-C is an easily releasable myofilament protein that is dephosphorylated, degraded and released into the circulation post-MI. The presence of elevated levels of cMyBP-C in the blood provides a promising novel biomarker able to accurately rule in MI, thus aiding in the further assessment of ischemic heart disease.

SUBMITTER: Govindan S

PROVIDER: S-EPMC3246118 | biostudies-literature | 2012 Jan

REPOSITORIES: biostudies-literature

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Cardiac myosin binding protein-C is a potential diagnostic biomarker for myocardial infarction.

Govindan Suresh S McElligott Andrew A Muthusamy Saminathan S Nair Nandini N Barefield David D Martin Jody L JL Gongora Enrique E Greis Kenneth D KD Luther Pradeep K PK Winegrad Saul S Henderson Kyle K KK Sadayappan Sakthivel S

Journal of molecular and cellular cardiology 20110919 1

Cardiac myosin binding protein-C (cMyBP-C) is a thick filament assembly protein that stabilizes sarcomeric structure and regulates cardiac function; however, the profile of cMyBP-C degradation after myocardial infarction (MI) is unknown. We hypothesized that cMyBP-C is sensitive to proteolysis and is specifically increased in the bloodstream post-MI in rats and humans. Under these circumstances, elevated levels of degraded cMyBP-C could be used as a diagnostic tool to confirm MI. To test this hy ...[more]

PMID: 21971072

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Project description:BACKGROUND:Cardiac myosin-binding protein C (cMyC) is a cardiac-restricted protein that is more abundant than cardiac troponins (cTn) and is released more rapidly after acute myocardial infarction (AMI). We evaluated cMyC as an adjunct or alternative to cTn in the early diagnosis of AMI. METHODS:Unselected patients (N=1954) presenting to the emergency department with symptoms suggestive of AMI, concentrations of cMyC, and high-sensitivity (hs) and standard-sensitivity cTn were measured at presentation. The final diagnosis of AMI was independently adjudicated using all available clinical and biochemical information without knowledge of cMyC. The prognostic end point was long-term mortality. RESULTS:Final diagnosis was AMI in 340 patients (17%). Concentrations of cMyC at presentation were significantly higher in those with versus without AMI (median, 237 ng/L versus 13 ng/L, P<0.001). Discriminatory power for AMI, as quantified by the area under the receiver-operating characteristic curve (AUC), was comparable for cMyC (AUC, 0.924), hs-cTnT (AUC, 0.927), and hs-cTnI (AUC, 0.922) and superior to cTnI measured by a contemporary sensitivity assay (AUC, 0.909). The combination of cMyC with hs-cTnT or standard-sensitivity cTnI (but not hs-cTnI) led to an increase in AUC to 0.931 (P<0.0001) and 0.926 (P=0.003), respectively. Use of cMyC more accurately classified patients with a single blood test into rule-out or rule-in categories: Net Reclassification Improvement +0.149 versus hs-cTnT, +0.235 versus hs-cTnI (P<0.001). In early presenters (chest pain <3 h), the improvement in rule-in/rule-out classification with cMyC was larger compared with hs-cTnT (Net Reclassification Improvement +0.256) and hs-cTnI (Net Reclassification Improvement +0.308; both P<0.001). Comparing the C statistics, cMyC was superior to hs-cTnI and standard sensitivity cTnI (P<0.05 for both) and similar to hs-cTnT at predicting death at 3 years. CONCLUSIONS:cMyC at presentation provides discriminatory power comparable to hs-cTnT and hs-cTnI in the diagnosis of AMI and may perform favorably in patients presenting early after symptom onset. CLINICAL TRIAL REGISTRATION:URL: https://www.clinicaltrials.gov. Unique identifier: NCT00470587.

Project description:BackgroundMyocardial infarction is a well-established severe consequence of coronary artery disease. However, the lack of effective early biomarkers accounts for the lag time before clinical diagnosis of myocardial infarction. The present study aimed to predict critical genes for the diagnosis of MI by immune infiltration analysis and establish a nomogram.MethodsGene microarray data were downloaded from Gene Expression Omnibus (GEO). Differential expression analysis, single-cell sequencing, and disease ontology (DO) enrichment analysis were performed to determine the distribution of Differentially Expressed Genes (DEGs) in cell subpopulations and their correlation with MI. Next, the level of infiltration of 16 immune cells and immune functions and their hub genes were analyzed using a Single-sample Gene Set Enrichment Analysis (ssGSEA). In addition, the accuracy of critical markers for the diagnosis of MI was subsequently assessed using receiver operating characteristic curves (ROC). One datasets were used to test the accuracy of the model. Finally, the genes with the most diagnostic value for MI were screened and experimentally validated.Results335 DEGs were identified in GSE66360, including 280 upregulated and 55 downregulated genes. Single-cell sequencing results demonstrated that DEGs were mainly distributed in endothelial cells. DO enrichment analysis suggested that DEGs were highly correlated with MI. In the MI population, macrophages, neutrophils, CCR, and Parainflammation were significantly upregulated compared to the average population. NR4A2 was identified as the gene with the most significant diagnostic value in the immune scoring and diagnostic model. 191 possible drugs for the treatment of myocardial infarction were identified by drug prediction analysis. Finally, our results were validated by Real-time Quantitativepolymerase chain reaction and Western Blot of animal samples.ConclusionOur comprehensive in silico analysis revealed that NR4A2 has huge prospects for application in diagnosing patients with MI.

Project description:Acute myocardial infarction (AMI) is one of the most serious cardiovascular diseases with high morbidity and mortality. Numerous studies have indicated that S100A12 may has an essential role in the occurrence and development of AMI, and in-depth studies are currently lacking. The purpose of this study is to investigate the effect of S100A12 on inflammation and oxidative stress and to determine its clinical applicability in AMI. Here, AMI datasets used to explore the expression pattern of S100A12 in AMI were derived from the Gene Expression Omnibus (GEO) database. The pooled standard average deviation (SMD) was calculated to further determine S100A12 expression. The overlapping differentially expressed genes (DEGs) contained in all included datasets were recognized by the GEO2R tool. Then, functional enrichment analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, were carried out to determine the molecular function of overlapping DEGs. Gene set enrichment analysis (GSEA) was conducted to determine unrevealed mechanisms of S100A12. Summary receiver operating characteristic (SROC) curve analysis and receiver operating characteristic (ROC) curve analysis were carried out to identify the diagnostic capabilities of S100A12. Moreover, we screened miRNAs targeting S100A12 using three online databases (miRWalk, TargetScan, and miRDB). In addition, by comprehensively using enzyme-linked immunosorbent assay (ELISA), real-time quantitative PCR (RT-qPCR), Western blotting (WB) methods, etc., we used the AC16 cells to validate the expression and underlying mechanism of S100A12. In our study, five datasets related to AMI, GSE24519, GSE60993, GSE66360, GSE97320, and GSE48060 were included; 412 overlapping DEGs were identified. Protein-protein interaction (PPI) network and functional analyses showed that S100A12 was a pivotal gene related to inflammation and oxidative stress. Then, S100A12 overexpression was identified based on the included datasets. The pooled standard average deviation (SMD) also showed that S100A12 was upregulated in AMI (SMD = 1.36, 95% CI: 0.70-2.03, p = 0.024). The SROC curve analysis result suggested that S100A12 had remarkable diagnostic ability in AMI (AUC = 0.90, 95% CI: 0.87-0.92). And nine miRNAs targeting S100A12 were also identified. Additionally, the overexpression of S100A12 was further confirmed that it maybe promote inflammation and oxidative stress in AMI through comprehensive in vitro experiments. In summary, our study suggests that overexpressed S100A12 may be a latent diagnostic biomarker and therapeutic target of AMI that induces excessive inflammation and oxidative stress. Nine miRNAs targeting S100A12 may play a crucial role in AMI, but further studies are still needed. Our work provides a positive inspiration for the in-depth study of S100A12 in AMI.

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Cardiac myosin binding protein-C is a potential diagnostic biomarker for myocardial infarction.

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Cardiac myosin binding protein-C is a potential diagnostic biomarker for myocardial infarction.

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