ArticleFunctional & integrative genomics2010
Integrated protein network and microarray analysis to identify potential biomarkers after myocardial infarction.
Article in Functional & integrative genomics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 37 citations in OpenAlex.
- Identification of biomarkers and immune infiltration in acute myocardial infarction and heart failure by integrated analysis.Bioscience reports · 2023Article
- Article
- Integrative analysis of DNA methylation and gene expression reveals key molecular signatures in acute myocardial infarction.Clinical epigenetics · 2022Article
- Biomarkers in Cardiorenal Syndrome and Potential Insights Into Novel Therapeutics.Frontiers in cardiovascular medicine · 2022Review
- PRKAR1A and SDCBP Serve as Potential Predictors of Heart Failure Following Acute Myocardial Infarction.Frontiers in immunology · 2022Article
- Peripheral Blood RNAs and Left Ventricular Dysfunction after Myocardial Infarction: Towards Translation into Clinical Practice.Journal of cardiovascular translational research · 2021Review
- Regulation of Cellular Redox Signaling by Matricellular Proteins in Vascular Biology, Immunology, and Cancer.Antioxidants & redox signaling · 2017Article
- VEGF-B gene therapy inhibits doxorubicin-induced cardiotoxicity by endothelial protection.Proceedings of the National Academy of Sciences of the United States of America · 2016Article
- LCK: a new biomarker candidate for the early diagnosis of acute myocardial infarction.Molecular biology reports · 2014Article
- Thrombospondin-1 and CD47 regulation of cardiac, pulmonary and vascular responses in health and disease.Matrix biology : journal of the International Society for Matrix Biology · 2014Review
- Will global transcriptome analysis allow the detection of novel prognostic markers in coronary artery disease and heart failure?Current genomics · 2013Article
- A network pharmacology approach to evaluating the efficacy of chinese medicine using genome-wide transcriptional expression data.Evidence-based complementary and alternative medicine : eCAM · 2013Article
- Adenosine stimulates the migration of human endothelial progenitor cells. Role of CXCR4 and microRNA-150.PloS one · 2013Article
- Matricellular proteins in cardiac adaptation and disease.Physiological reviews · 2012Review
- Early biventricular molecular responses to an acute myocardial infarction.International journal of medical sciences · 2012Article
- Transforming growth factor β receptor 1 is a new candidate prognostic biomarker after acute myocardial infarction.BMC medical genomics · 2011Article
- Information encoded in a network of inflammation proteins predicts clinical outcome after myocardial infarction.BMC medical genomics · 2011Article
- Prognostic transcriptional association networks: a new supervised approach based on regression trees.Bioinformatics (Oxford, England) · 2011Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A significant proportion of patients develop left ventricular (LV) dysfunction and heart failure (HF) after acute myocardial infarction (MI). Existing biomarkers of HF provide limited information after MI. To identify new prognostic biomarkers in MI patients, we designed an approach combining protein interaction networks and microarray analysis of blood cells. Blood samples for RNA and protein analysis were taken from 127 acute MI patients. Echocardiography was performed at one month. Assuming that angiogenesis is related to cardiac repair after MI, a protein-protein interaction network of angiogenesis was constructed and analyzed. Among the 556 proteins and 686 interactions of this network, a cluster of 53 proteins highly specialized in regulation of cell growth was identified. Of these 53 proteins, 38 were found differentially expressed by microarrays between low (< or = 40%) and high (>40%) LV ejection fraction (EF) patients (n = 32). Among these 38 genes, prediction analysis identified a set of three genes able to predict significant LV dysfunction (EF < or = 40%) with an area under the receiver operating characteristic curve (AUC) of 0.82. These three genes-vascular endothelial growth factor B, thrombospondin-1 and placental growth factor-had a stronger predictive value than brain natriuretic peptide and troponin T (AUC of 0.63). Independent validations on protein expression and quantitative PCR datasets confirmed the results. In conclusion, a new strategy is described that allows identifying new potential biomarkers. The three specific biomarkers described here remain to be validated in a larger patient population.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.