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Differential expression profiles of long non-coding RNAs as potential biomarkers for the early diagnosis of acute myocardial infarction.

ABSTRACT: Acute myocardial infarction (AMI) is a major cause of morbidity and mortality worldwide. The early diagnosis of AMI is crucial for deciding the course of treatment and saving lives. Long non-coding RNAs (lncRNAs) are recently discovered ncRNA class and their dysregulated expression has been implicated in cardiovascular diseases. In this study, we analyzed lncRNA expression pattern by using two microarray datasets of AMI and healthy samples from the Gene Expression Omnibus (GEO) database and tried to identify novel AMI-related lncRNAs and investigate the predictive roles of lncRNAs in the early diagnosis of AMI. From the discovery cohort, 11 differentially expressed lncRNAs were identified as candidate biomarkers that were validated in the discovery cohort, internal cohort and an independent cohort, respectively. Hierarchical clustering analysis suggested that the expression pattern of these 11 candidate lncRNA biomarkers was closely associated with disease status of samples. Then a lncRNA risk classifier was developed by integrating expression value of 11 differentially expressed lncRNAs using support vector machine (SVM) algorithm. The results of leaving one out cross-validation (LOOCV) suggested that the lncRNA risk classifier has a good discrimination between AMI patients and healthy samples with the area under ROC curve (AUC) of 0.955, 0.92 and 0.701 in three cohorts, respectively. Functional enrichment analysis suggested that these 11 candidate lncRNA biomarkers might be involved in inflammation- and immune-related biological processes. Our study indicates the potential roles in the early diagnosis of AMI and will improve our understanding of the molecular mechanism of the occurrence and recurrence of AMI.

SUBMITTER: Li L

PROVIDER: S-EPMC5687631 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Differential expression profiles of long non-coding RNAs as potential biomarkers for the early diagnosis of acute myocardial infarction.

Li Ling L Cong Yingying Y Gao Xueqin X Wang Yini Y Lin Ping P

Oncotarget 20170809 51

Acute myocardial infarction (AMI) is a major cause of morbidity and mortality worldwide. The early diagnosis of AMI is crucial for deciding the course of treatment and saving lives. Long non-coding RNAs (lncRNAs) are recently discovered ncRNA class and their dysregulated expression has been implicated in cardiovascular diseases. In this study, we analyzed lncRNA expression pattern by using two microarray datasets of AMI and healthy samples from the Gene Expression Omnibus (GEO) database and trie ...[more]

PMID: 29179461

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Project description:Long noncoding RNAs (lncRNAs) are non-protein coding transcripts regulating various critical physiological and pathological processes, yet limited information is available about lncRNAs expression in acute myocardial infarction (AMI). We aimed to identified differentially expressed lncRNAs in blood samples of patients with AMI to assess their diagnostic value. Differential expression of lncRNAs in peripheral blood mononuclear cells (PBMC) of patients with non-ST-elevation myocardial infarction (NSTEMI) and ST-elevation myocardial infarction (STEMI) was compared by RNA sequencing method and validated by real-time polymerase chain reaction (PCR). The area under the receiver operating characteristic curve (ROC) was used to evaluate diagnostic accuracy. Gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of lncRNA-coexpressed mRNAs were conducted to determine the related biological modules and pathological pathways. RNA sequencing data showed that 58 lncRNAs were differentially expressed between NSTEMI patients and STEMI patients, including 42 upregulated lncRNAs and 16 down-regulated lncRNAs. The ROC curves showed that ENST00000508020.2, LNC_001265, LNC_001526, and LNC_002674 could distinguish AMI patients with preferable sensitivity and specificity. GO enrichment analysis of lncRNA-coexpressed mRNAs indicated that the biological modules were correlated with cell adhesion, calcium ion homeostasis, complement receptor mediated signaling pathway, and immune system process. KEGG pathway analysis indicated that the lncRNAs-co-expressed mRNAs were involved in the regulation of peroxisome proliferators-activated receptors (PPAR) signaling pathway, mTOR signaling pathway, Insulin signaling pathway, HIF-1 signaling, and chemokin signaling pathway. Our results are in line with the previous findings, suggesting that differential expression of lncRNAs would be helpful to understand the molecular mechanism of AMI and might be useful biomarkers for noninvasive diagnostic application. Further studies are still needed to verify our findings and hypothesis.

Project description:BackgroundMyocardial infarction (MI), a critical condition, substantially affects patient outcomes and mortality rates. Long non-coding RNAs (lncRNAs) play a critical role in the onset and progression of MI. This study aimed to explore the related research on MI-related lncRNAs from a bibliometric perspective, providing new clues and directions for researchers in the field.MethodsA comprehensive search was conducted on 7 August 2023, using the Web of Science Core Collection (WoSCC) database to compile a dataset of all English-language scientific journals. The search gathered all relevant publications from January 2000 to August 2023 that pertain to MI-related lncRNAs. Data on countries, institutions, journals, authors, and keywords were collected, sorted, statistically analyzed, and visualized using CiteSpace 6.2.R4, VOSviewer 1.6.19, an online bibliometric analysis platform (http://bibliometric.com), and the bibliometric package in R-Studio 4.3.1. Articles were screened by two independent reviewers.ResultsBetween January 2000 and August 2023, a total of 1,452 papers were published in the research field of MI-related lncRNAs. The year with the most publications was 2020, accounting for 256 papers. The publication volume displayed an exponential growth trend, fitting the equation y = 2.0215e0.2786x, R^2 = 0.97. In this domain, China leads in both the number of published papers (N = 1,034) and total citations, followed by the United States, Germany, Iran, and Italy. The most productive institution is Harbin Medical University (N = 144). The European Review for Medical and Pharmacological Sciences had the highest number of publications (N = 46), while Circulation Research had the most citations (TC = 4,537), indicating its irreplaceable standing in this field. Research mainly focuses on the cardiovascular system, cellular biology, physiology, etc. The most productive author is Zhang Y. Apart from "Myocardial Infarction" and "LncRNA," the most frequent keywords include "expression," "atherosclerosis," and "apoptosis." Cluster analysis suggests current research themes concentrate on cardiovascular diseases and gene expression, cardiac ischemia/reperfusion injury and protection, expression and proliferation, atherosclerosis and inflammatory response, among others. Keyword bursts indicate recent hot topics as targeting, autophagy, etc.ConclusionThis bibliometric analysis reveals that research on MI-related lncRNAs has rapidly expanded between January 2000 and August 2023, primarily led by China and the United States. Our study highlights the significant biological roles of lncRNAs in the pathogenesis and progression of MI, including their involvement in gene expression regulation, atherosclerosis development, and apoptosis. These findings underscore the potential of lncRNAs as therapeutic targets and biomarkers for MI. Additionally, our study provides insights into the features and quality of related publications, as well as the future directions in this research field. There is a long road ahead, highlighting the urgent need for enhanced global academic exchange.

Dataset Information

Differential expression profiles of long non-coding RNAs as potential biomarkers for the early diagnosis of acute myocardial infarction.

Publications

Differential expression profiles of long non-coding RNAs as potential biomarkers for the early diagnosis of acute myocardial infarction.

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