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Identification of Biomarkers Associated with Metabolic Cardiovascular Disease Using Mrna-SNP-Mirna Regulatory Network Analysis

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Identification of Biomarkers Associated with Metabolic Cardiovascular Disease Using Mrna-SNP-Mirna Regulatory Network Analysis Fan et al. BMC Cardiovasc Disord (2021) 21:351 https://doi.org/10.1186/s12872-021-02166-4 RESEARCH Open Access Identifcation of biomarkers associated with metabolic cardiovascular disease using mRNA-SNP-miRNA regulatory network analysis Zhiyuan Fan1, Wenjuan Peng1, Zhiwen Wang2, Ling Zhang1 and Kuo Liu1* Abstract Background: CVD is the leading cause of death in T2DM patients. However, few biomarkers have been identifed to detect and diagnose CVD in the early stage of T2DM. The aim of our study was to identify the important mRNAs, micro (mi)RNAs and SNPs (single nucleotide polymorphisms) that are associated with metabolic cardiovascular disease. Materials and methods: Expression profles and GWAS data were obtained from Gene Expression Omnibus (GEO) database. MiRNA-sequencing was conducted by Illumina HiSeq 2000 platform in T2DM patients and T2DM with CVD patients. EQTL analysis and gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrich- ment analyses were conducted. MRNA-miRNA co-expression network and mRNA-SNP-miRNA interaction network were established and visualized by Cytoscape 3.7.2. Results: In our study, we identifed 56 genes and 16 miRNAs that were signifcantly diferentially expressed. KEGG analyses results indicated that B cell receptor signaling pathway and hematopoietic cell lineage were included in the biological functions of diferentially expressed genes. MRNA-miRNA co-expression network and mRNA-SNP-miRNA interaction network illustrated that let-7i-5p, RASGRP3, KRT1 and CEP41 may be potential biomarkers for the early detection and diagnosis of CVD in T2DM patients. Conclusion: Our results suggested that downregulated let-7i-5p, and upregulated RASGRP3, KRT1 and CEP41 may play crucial roles in molecular mechanisms underlying the initiation and development of CVD in T2DM patients. Keywords: CVD, T2DM, mRNA, SNP, miRNA, Interaction network Background diseases (CVD), but its mechanism of action is not fully It is estimated that in 2019 463 million adults aged understood [2]. Even newly diagnosed diabetics were 20–79 years would develop diabetes with type 2 diabe- reported to have at least one vascular complication, and tes (T2DM) accounting for > 90% of cases [1]. Te inci- CVD is the leading cause of death in T2DM patients [3, dence of T2DM has greatly increased in recent years and 4]. Furthermore, people with T2DM are 2–6 times more has become a great threat to human health worldwide. likely to die of CVD than those without diabetes [5]. T2DM is one of major risk factors of cardiovascular However, few biomarkers have been identifed to diag- nose CVD at the early stage of T2DM. MicroRNAs (miRNAs) bind to complementary *Correspondence: [email protected] 1 Department of Epidemiology and Health Statistics, School of Public sequences of their target mRNA by base pairing to Health, Capital Medical University, and Beijing Municipal Key Laboratory induce mRNA degradation and/or inhibit translation, of Clinical Epidemiology, Beijing, China thus afecting gene expression after transcription [6]. Full list of author information is available at the end of the article © The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. The Creative Commons Public Domain Dedication waiver (http:// creat iveco mmons. org/ publi cdoma in/ zero/1. 0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Fan et al. BMC Cardiovasc Disord (2021) 21:351 Page 2 of 12 MiRNA has been found to have high specifcity for dis- Diabetes Association Criteria 【24357215【. Ischemic heart ease status and may be used as a potential biomarker disease was defned by clinical history, including acute to predict disease progression. In recent years, multi- myocardium infarction, angina pectoris and/or ischemic ple miRNAs have been demonstrated to be involved in electrocardiographic alterations. All the participants angiogenesis and endothelial cells dysfunction [7–9]. did not have diabetic retinopathy, nor diabetic micro- Expression of miRNAs can be afected by many factors. vascular complications. Tis study was approved by the Te miRNA seed region can specifcally bind to miRNA Ethics Committee of Capital Medical University (No. recognition element (MRE) in the 3′UTR (3′ untrans- 2016SY24). lated region) of their target mRNA [10]. Terefore, any Total RNA extraction was performed using TRIzol anomalies of miRNA-MRE interaction may have an (Invitrogen, USA) according to manufacturer’s instruc- impact on gene expression and lead to diseases [11–13]. tions. After removing DNA contamination by DNase I Single nucleotide polymorphism (SNP), the most com- treatment, total RNA was assessed by NanoDrop spec- mon genetic variants, can interfere with the base pair- trophotometer (NanoDrop, USA). A total of 2 μg of ing between miRNA and its target mRNA, afecting RNA/sample was used for the miRNA library. TruSeq normal expression of genes and eventually contributing Small RNA Sample Preparation Kit (Illumina, Inc., San to disease pathogenesis [14]. Genome-Wide Association Diego, CA, USA) was used to generate miRNA sequenc- Studies (GWAS) have found that genetic variants play an ing libraries. Te library concentration was assessed by important role in pathogenesis of CVD [15], and associa- Qubit Spectrophotometer and the miRNA sequencing tion between some genetic variants and CVD has criti- library quality was obtained by using the Agilent 2100 cal biological signifcance for T2DM patients [16, 17]. Bioanalyzer system with a High Sensitivity DNA Kit Genome-wide expression quantitative trait locus (eQTL) (Agilent Technologies). Sequencing was performed on analysis is an efective method to study the efect of SNPs an Illumina HiSeq 2000 platform and 50 bp of single- on gene expression [18, 19]. However, eQTL analysis end reads were generated. We used fastqc v0.10.1 (http:// mainly focuses on mRNA expression and rarely involves www. bioin forma tics. babraham.ac.uk/projects/fastqc/) to miRNA, which leads to incomplete interaction patterns check the quality of raw reads. Te reads were mapped to [20]. hg19 reference genome to identify mature miRNA, and To more comprehensively reveal the complicated asso- the expression profle was generated by using miRDeep2 ciation between mRNA, miRNA and SNP, and to fnd software (https:// www. mdc- berlin. de/ 85519 03/ en/). potential biomarkers with high specifcity and sensitiv- ity to diagnose CVD at the early stage of T2DM, we per- Microarray datasets and preprocessing formed an integrative analysis. EQTL analysis and gene We searched GEO data repository (https:// www. ncbi. ontology (GO), KEGG pathway enrichment analyses nlm. nih. gov/ geo/) for eligible studies until January 20, were also conducted to better understand the connection 2020. Te following terms and diferent combination of between mRNA, miRNA and SNP, and their potential them were used: “type 2 diabetes”, “cardiovascular dis- efect on CVD in T2DM patients. ease”, “atherosclerosis”, “coronary artery disease”, “heart disease”, “angina pectoris”, “myocardial infarction”, “coro- Materials and methods nary angiography”, “chronic myocardial ischemia syn- Sample processing and miRNA profling drome”, and “acute coronary syndrome”. Based on the Six diabetes patients and fve diabetes with ischemic search strategy, three datasets were downloaded from heart disease were recruited from communities in Bei- GEO, among which GSE90074 and GSE90073 (see Addi- jing after informed consent was obtained from each par- tional fle 1: Table S1 for more details) were from same ticipant. T2DM was diagnosed according to American study. Details of each dataset are provided in Table 1. Table 1 Details of microarray datasets from GEO database GSE Type Sample size Chip T2DM T2DM CVD + GSE90074 mRNA 17 38 Agilent-014850 whole human genome micro- array 4 44 K G4112F × GSE66175 mRNA 48 57 Afymetrix human genome U133A 2.0 array GSE90073 SNP 13 25 Afymetrix genome-wide human SNP 6.0 array Fan et al. BMC Cardiovasc Disord (2021) 21:351 Page 3 of 12 Quality evaluation and data preprocessing Construction of mRNA‑miRNA co‑expression network Te quality of the original CEL fles from the data- We performed Pearson correlation analysis to test cor- set GSE66175 (see Additional fle 1: Table S1 for more relation of diferentially expressed mRNA and miRNA. details) was evaluated in this study. We plotted the rela- Ten, mRNA-miRNA pairs (p value < 0.05, absolute value tive log expression boxplot and normalized unscaled of correlation coefcient > 0.5) were used to construct standard errors boxplot to evaluate the consistency of mRNA-miRNA co-expression network by using software chip quality using afyPLM package (https:// git. bioco Cytoscape 3.7.2. nduct or. org/ packa ges/ afyP LM/). Te degradation of RNA would have a great impact on the quality of chips, GO and KEGG pathway enrichment analyses thus RNA degradation plot was plotted to show the GO and KEGG pathway enrichment analyses were per- trend. Ten RMA algorithm was used for background formed to explore the biological process, cellular compo- correction and normalization of the data. We could nent, molecular function of diferentially expressed genes obtain the matrix fle after quality control and preproc- and other pathways they might get involved in.
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