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Transcriptome alterations of vascular smooth muscle cells in aortic wall of myocardial infarction patients.

ABSTRACT: This article contains further data and information from our published manuscript [1]. We aim to identify significant transcriptome alterations of vascular smooth muscle cells (VSMCs) in the aortic wall of myocardial infarction (MI) patients. Microarray gene analysis was applied to evaluate VSMCs of MI and non-MI patients. Prediction Analysis of Microarray (PAM) identified genes that significantly discriminated the two groups of samples. Incorporation of gene ontology (GO) identified a VSMCs-associated classifier that discriminated between the two groups of samples. Mass spectrometry-based iTRAQ analysis revealed proteins significantly differentiating these two groups of samples. Ingenuity Pathway Analysis (IPA) revealed top pathways associated with hypoxia signaling in cardiovascular system. Enrichment analysis of these proteins suggested an activated pathway, and an integrated transcriptome-proteome pathway analysis revealed that it is the most implicated pathway. The intersection of the top candidate molecules from the transcriptome and proteome highlighted overexpression.

SUBMITTER: Wongsurawat T

PROVIDER: S-EPMC5988399 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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Transcriptome alterations of vascular smooth muscle cells in aortic wall of myocardial infarction patients.

Wongsurawat Thidathip T Woo Chin Cheng CC Giannakakis Antonis A Lin Xiao Yun XY Cheow Esther Sok Hwee ESH Lee Chuen Neng CN Richards Mark M Sze Siu Kwan SK Nookaew Intawat I Kuznetsov Vladimir A VA Sorokin Vitaly V

Data in brief 20180206

This article contains further data and information from our published manuscript [1]. We aim to identify significant transcriptome alterations of vascular smooth muscle cells (VSMCs) in the aortic wall of myocardial infarction (MI) patients. Microarray gene analysis was applied to evaluate VSMCs of MI and non-MI patients. Prediction Analysis of Microarray (PAM) identified genes that significantly discriminated the two groups of samples. Incorporation of gene ontology (GO) identified a VSMCs-asso ...[more]

PMID: 29876469

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Project description:BackgroundSmooth muscle cells (SMCs), which make up the medial layer of arteries, are key cell types involved in cardiovascular diseases (CVD), the leading cause of mortality and morbidity worldwide. In response to microenvironment alterations, SMCs dedifferentiate from a "contractile" to a "synthetic" phenotype characterized by an increased proliferation, migration, production of extracellular matrix (ECM) components, and decreased expression of SMC-specific contractile markers. These phenotypic changes result in vascular remodeling and contribute to the pathogenesis of CVD, including coronary artery disease (CAD), stroke, hypertension, and aortic aneurysms. Here, we aim to identify the genetic variants that regulate ECM secretion in SMCs and predict the causal proteins associated with vascular disease-related loci identified in genome-wide association studies (GWAS).MethodsUsing human aortic SMCs from 123 multi-ancestry healthy heart transplant donors, we collected the serum-free media in which the cells were cultured for 24 hours and conducted Liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomic analysis of the conditioned media.ResultsWe measured the abundance of 270 ECM and related proteins. Next, we performed protein quantitative trait locus mapping (pQTL) and identified 20 loci associated with secreted protein abundance in SMCs. We functionally annotated these loci using a colocalization approach. This approach prioritized the genetic variant rs6739323-A at the 2p22.3 locus, which is associated with lower expression of LTBP1 in SMCs and atherosclerosis-prone areas of the aorta, and increased risk for SMC calcification. We found that LTBP1 expression is abundant in SMCs, and its expression at mRNA and protein levels was reduced in unstable and advanced atherosclerotic plaque lesions.ConclusionsOur results unravel the SMC proteome signature associated with vascular disorders, which may help identify potential therapeutic targets to accelerate the pathway to translation.

Dataset Information

Transcriptome alterations of vascular smooth muscle cells in aortic wall of myocardial infarction patients.

Publications

Transcriptome alterations of vascular smooth muscle cells in aortic wall of myocardial infarction patients.

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