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Tissue-specific miRNA Expression Profiling in Mouse Heart Sections Using In Situ Hybridization
Published on: September 15, 2018
Characterization of the circulating transcriptome expression profile and identification of novel miRNA biomarkers in
Lanyan Guo1, Yue Cai1, Bo Wang2
1Department of Cardiology, Xijing Hospital, the Fourth Military Medical University, 127 Changle West Road, Xi'an, 710032, Shaan Xi, China.
Insights
This study investigated microRNA (miRNA) profiles in peripheral blood mononuclear cells (PBMCs) of patients with hypertrophic cardiomyopathy (HCM). Three specific miRNAs (miR-924, miR-98, and miR-1) were identified as potential biomarkers for HCM detection.
Area of Science:
- Cardiovascular Genetics
- Molecular Biology
- Biomarker Discovery
Background:
- Hypertrophic cardiomyopathy (HCM) is a common genetic cardiovascular disease with complex genetic underpinnings.
- Circulating microRNAs (miRNAs) are stable molecules implicated in disease pathophysiology.
- The role of miRNA expression changes in human peripheral blood mononuclear cells (PBMCs) in HCM remains unclear.
Purpose of the Study:
- To investigate the circulating non-coding RNA (ncRNA) expression profile in PBMCs from HCM patients.
- To identify potential microRNA (miRNA) biomarkers for the detection of HCM.
Main Methods:
- Differential expression analysis of mRNAs, miRNAs, and ncRNAs using a Custom CeRNA Human Gene Expression Microarray.
- Weighted gene co-expression network analysis (WGCNA) to identify key miRNA and mRNA modules associated with HCM.
- Machine learning algorithms and external validation (GEO database) to identify and confirm potential miRNA biomarkers.
Main Results:
- Identification of 1194 differentially expressed mRNAs, 232 DE-miRNAs, and 7696 DE-ncRNAs in HCM PBMCs.
- Construction of a miRNA-mRNA co-expression network revealing key modules linked to HCM.
- Identification of three hub miRNAs (miR-924, miR-98, and miR-1) with high diagnostic accuracy (AUCs ranging from 0.829 to 0.866).
Conclusions:
- Elucidation of the transcriptome expression profile in PBMCs of HCM patients.
- Identification of miR-924, miR-98, and miR-1 as promising circulating biomarkers for HCM diagnosis.
Background:
Hypertrophic cardiomyopathy (HCM), one of the most common genetic cardiovascular diseases, but cannot be explained by single genetic factors. Circulating microRNAs (miRNAs) are stable and highly conserved. Inflammation and immune response participate in HCM pathophysiology, but whether the miRNA profile changes correspondingly in human peripheral blood mononuclear cells (PBMCs) with HCM is unclear. Herein, we aimed to investigate the circulating non-coding RNA (ncRNA) expression profile in PBMCs and identify potential miRNAs for HCM biomarkers.
Methods:
A Custom CeRNA Human Gene Expression Microarray was used to identify differentially expressed (DE) mRNAs, miRNAs, and ncRNAs (including circRNA and lncRNA) in HCM PBMCs. Weighted correlation network analysis (WGCNA) was used to identify HCM-related miRNA and mRNA modules. The mRNAs and miRNAs from the key modules were used to construct a co-expression network. Three separate machine learning algorithms (random forest, support vector machine, and logistic regression) were applied to identify potential biomarkers based on miRNAs from the HCM co-expression network. Gene Expression Omnibus (GEO) database (GSE188324) and experimental samples were used for further verification. Gene set enrichment analysis (GSEA) and competing endogenous RNA (ceRNA) network was used to determine the potential functions of the selected miRNAs in HCM.
Results:
We identified 1194 DE-mRNAs, 232 DE-miRNAs and 7696 DE-ncRNAs in HCM samples compared with normal controls from the microarray data sets. WGCNA identified key miRNA modules and mRNA modules evidently associated with HCM. We constructed a miRNA‒mRNA co-expression network based on these modules. A total of three hub miRNAs (miR-924, miR-98 and miR-1) were identified by random forest, and the areas under the receiver operator characteristic curves of miR-924, miR-98 and miR-1 were 0.829, 0.866, and 0.866, respectively.
Conclusions:
We elucidated the transcriptome expression profile in PBMCs and identified three hub miRNAs (miR-924, miR-98 and miR-1) as potential biomarkers for HCM detection.
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