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Systematically Analysis of lncRNA and microRNA Dynamic Features and Reveal Diagnostic and Prognostic Biomarkers in Myocardial Infarction

43 Pages Posted: 22 Sep 2019

See all articles by Hongbo Shi

Hongbo Shi

Harbin Medical University - College of Bioinformatics Science and Technology

Haoran Sun

Harbin Medical University - College of Bioinformatics Science and Technology

Jiaya Li

Harbin Medical University - College of Bioinformatics Science and Technology

Ziyi Bai

Harbin Medical University - College of Bioinformatics Science and Technology

Xiuhong Li

Harbin Medical University - College of Bioinformatics Science and Technology

Yingli lv

Harbin Medical University - College of Bioinformatics Science and Technology

Guangde Zhang

Harbin Medical University

More...

Abstract

Background: The studies on long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) implicated in myocardial infarction (MI) have increased our understanding of gene regulatory mechanisms of MI. However, the dynamic features of lncRNAs and miRNAs in MI progression have not been investigated at a system level.

Methods: Global lncRNA and miRNA expression and functional patterns were examined using time-series gene expression data. To identify early diagnostic and prognostic biomarkers of MI, an efficient computational method for identifying dysregulated lncRNA-miRNA-mRNA competing endogenous RNA triplets (LmiRM-CTs) was developed, and a support vector machine classification model was applied.

Findings: We observed that the biggest response of cell stimulus on the transcriptome for mRNAs, lncRNAs and miRNAs all occurred in MI acute phase, and more protein-coding genes responded to cellular stimuli relative to non-coding RNAs. Biological functional analysis indicated that lncRNAs and miRNAs which were very sensitive to environmental changes and unstable during MI progression usually possessed less biological functions. We identified MI dynamic progression-related dysregulated LmiRM-CTs, from which a new panel of candidate diagnostic biomarkers defined by 7 lncRNAs were suggested to have high classification performance for patients with or without MI, and a new panel of prognostic biomarkers defined by 2 lncRNAs were identified with high discriminatory capability for MI patients who developed heart failure from those who did not.

Interpretation: This study provides a foundation for understanding dynamic regulation features of lncRNAs and miRNAs during MI progression and facilitates the discovery of early diagnostic and prognostic biomarkers for MI.

Funding Statement: This work was supported by the National Natural Science Foundation of China (Grant Nos. 31500675, 61602135), the Innovation Special Fund of Harbin Science and Technology Bureau of Heilongjiang Province (2017RAQXJ203), the Postdoctoral Foundation of Heilongjiang Province (LBH-Q17133) and the scientific research project of Heilongjiang Province Health and Family Planning Commission (Grant Nos. 2016-131).

Declaration of Interests: The authors declare no conflict of interest.

Ethics Approval Statement: Not required.

Keywords: Non-coding RNA; Myocardial infarction; Competing endogenous RNA; Expression profile

Suggested Citation

Shi, Hongbo and Sun, Haoran and Li, Jiaya and Bai, Ziyi and Li, Xiuhong and lv, Yingli and Zhang, Guangde, Systematically Analysis of lncRNA and microRNA Dynamic Features and Reveal Diagnostic and Prognostic Biomarkers in Myocardial Infarction (September 20, 2019). Available at SSRN: https://ssrn.com/abstract=3454685 or http://dx.doi.org/10.2139/ssrn.3454685

Hongbo Shi (Contact Author)

Harbin Medical University - College of Bioinformatics Science and Technology ( email )

China

Haoran Sun

Harbin Medical University - College of Bioinformatics Science and Technology

China

Jiaya Li

Harbin Medical University - College of Bioinformatics Science and Technology

China

Ziyi Bai

Harbin Medical University - College of Bioinformatics Science and Technology

China

Xiuhong Li

Harbin Medical University - College of Bioinformatics Science and Technology

China

Yingli Lv

Harbin Medical University - College of Bioinformatics Science and Technology ( email )

China

Guangde Zhang

Harbin Medical University ( email )

157 Baojian Rd
Nangang Qu
Haerbin Shi, Heilongjiang Sheng
China

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