Dataset Information

A Comprehensive Analysis of MicroRNAs in Human Osteoporosis.

ABSTRACT: MicroRNAs (miRNAs) are single-stranded RNA molecules that control gene expression in various processes, such as cancers, Alzheimer's disease, and bone metabolic diseases. However, the regulatory roles of miRNAs in osteoporosis have not been systematically analyzed. Here, we performed a comprehensive analysis to identify the differentially expressed miRNAs involved in osteoporosis. MiRNAs associated with osteoporosis were collected through literature retrieval and further screened based on specific inclusion and exclusion criteria. The osteoporosis therapeutic targets of miRNAs were obtained by the integration of miRWalk 3.0 database and five human disease therapeutic target databases. Then, the network analysis and functional enrichment analysis of miRNAs and their targets were performed. As a result, 11 eligible miRNAs were identified highly associated with osteoporosis. MiRNA-mRNA network demonstrated there were the complex mutual interactions between miRNAs and their targets. Besides, ADRB2, AR, ESR1, FGFR1, TRAF6, etc., were identified as the top hub genes in protein-protein interaction (PPI) network. Functional enrichment analysis revealed that miRNAs and their targets were mainly mapped on processes associated with bone and immune system, such as bone remolding, bone mineralization, PI3K/AKt, TNF signaling pathways and Th17 cell differentiation. RT-PCR results showed that the expression of miR-335-3p was significantly down-regulated in hind limb unloading (HLU) mice tibia samples compared with controls, the remaining 10 miRNAs were significantly up-regulated after HLU (P < 0.01). In summary, we identified 11 differentially expressed miRNAs and their hub target genes in osteoporosis, which may be novel diagnostic biomarkers for osteoporosis.

SUBMITTER: Huai Y

PROVIDER: S-EPMC7609919 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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A Comprehensive Analysis of MicroRNAs in Human Osteoporosis.

Huai Ying Y Zhang Wenjuan W Chen Zhihao Z Zhao Fan F Wang Wei W Dang Kai K Xue Kaiyue K Gao Yongguang Y Jiang Shanfeng S Miao Zhiping Z Li Meng M Hao Qiang Q Chen Chu C Qian Airong A

Frontiers in endocrinology 20201021

MicroRNAs (miRNAs) are single-stranded RNA molecules that control gene expression in various processes, such as cancers, Alzheimer's disease, and bone metabolic diseases. However, the regulatory roles of miRNAs in osteoporosis have not been systematically analyzed. Here, we performed a comprehensive analysis to identify the differentially expressed miRNAs involved in osteoporosis. MiRNAs associated with osteoporosis were collected through literature retrieval and further screened based on specif ...[more]

PMID: 33193074

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Project description:Osteoporosis (OP) is a systemic bone disease caused by various factors, including, the decrease of bone density and quality, the destruction of bone microstructure, and the increase of bone fragility. It is a disease with a high incidence in a large proportion of the world's elderly population. However, osteoporosis lacks obvious symptoms and sensitive biomarkers. Therefore, it is extremely urgent to discover and identify disease-related biomarkers for early clinical diagnosis and effective intervention for osteoporosis. In our study, the Linear Models for Microarray Data (LIMMA) tool was used to screen differential expressed genes from transcriptome sequencing data of OP blood samples downloaded from the GEO database, and cluster Profiler was used for enriching analysis of differently expressed genes. In order to analyzed the relevance of gene modules, clinical symptoms, and the most related module setting genes associated with disease progression, we adapted Weighted Gene Co-expression Network Analysis (WGCNA) to screen and analyze the related pathways and relevant molecules. We used the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database to construct protein interaction network of key modules, and Cytoscape software was used to complete network visualization and screen of core genes in the network. Various plug-in algorithms of cytoHubba were used to identify key genes of OP. Finally, correlation analysis and single-gene gene probe concentration analysis (GSEA) analysis were performed for each core gene. Results of a total of 8 key genes that were closely related to the occurrence and development of OP were screened out, which provided a brand-new idea for the clinical diagnosis and early prevention of OP. Quantitative real-time PCR (qRT-PCR) was performed for validation, the expression levels of CUL1, PTEN and STAT1 genes in the OS group were significantly higher than in the non-OS groups. Receiver operating characteristic analysis demonstrated that CUL1, PTEN and STAT1 displayed considerable diagnostic accuracy for OS.

Project description:BackgroundIt is unclear whether microRNAs could be a potential diagnostic biomarker for asthma or not. The objective of this study is to figure out the diagnostic value of microRNAs in asthma.MethodsLiterature retrieval, screening of publications, specific data extraction, and quality evaluation were conducted according to the standard criteria. Stata 14.0 software was used to analyze the diagnostic value of microRNA for asthma, including the combined sensitivity (Sen), specificity (Spe), the area under the curve (AUC), positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR).ResultsA total of 72 studies, containing 4143 cases and 2188 controls, were included for this comprehensive analysis. None of the included publications were rated low in quality. We summarized that, compared with controls, more than 100 miRNAs were reported differently expressed in asthma, although the expression trends were inconsistent. Besides, there were five studies among these 72 articles that applied the diagnostic evaluation of microRNAs in asthma. We found that the pooled Sen, Spe, and AUC for the combination of miR-185-5p, miR-155, let-7a, miR-21, miR-320a, miR-1246, miR-144-5p, and miR-1165-3p in asthma were 0.87 (95%CI: 0.72-0.95), 0.84 (95%CI: 0.74-0.91), and 0.93 (95%CI: 0.89-0.94) individually, and the PLR, NLR, and DOR were 5.5 (95%CI: 3.1-9.7), 0.15 (95%CI: 0.07-0.36), and 35 (95%CI: 10-127) in asthma, respectively. In terms of subgroup analyses, we found that the Sen for these combination miRNAs from serum was higher than that in plasma, while the Spe in plasma worked better than that in serum. Furthermore, compared with children, the combination of above miRNAs from adults had higher Spe and similar Sen.ConclusionsFrom our analysis, the combination of miR-185-5p, miR-155, let-7a, miR-21, miR-320a, miR-1246, miR-144-5p, and miR-1165-3p from peripheral blood could potentially act as a diagnostic biomarker for asthma.The reviews of this paper are available via the supplemental material section.

Project description:Colorectal cancer (CRC) has been defined as a common malignancy due to its prevailing incidence in both males and females. Recently, the intrinsic value of microRNAs (miRNAs) with respect to early cancer diagnosis has been contentious as the diagnostic accuracy of miRNAs significantly varied across different studies. As a result of this, this pioneer meta-analysis was proposed to address this issue. Qualified studies were obtained through electronic systematical searching in Medline, Embase, and PubMed. On the basis of the random-effects model, we calculated the pooled sensitivity (SEN), specificity (SPE), and area under the receiver operating characteristics curve (AUC) to assess the diagnostic accuracy of miRNAs. Subgroup analysis and meta-regression were implemented to determine how different confounding factors affect the overall diagnostic accuracy which were considered important sources of heterogeneity. All the statistical analyses were conducted with R 3.2.1 software. We incorporated 103 studies from 36 articles with a total of 3124 CRC patients and 2579 healthy individuals. MiRNAs have a good performance with the following pooled estimates: SEN = 0.769 (95% CI = 0.733-0.802), SPE = 0.806 (95% CI = 0.781-0.829), AUC = 0.857, and partial AUC = 0.773. As suggested by subgroup analyses and meta-regression, multiple miRNAs appeared to be more favorable than single miRNA (AUC: 0.918 > 0.813, partial AUC: 0.848 > 0.701, sensitivity = 0.853 > 0.718, specificity = 0.860 > 0.772). Compared with samples of plasma, blood, tissue, and feces, miRNA obtained from serum samples were more powerful for detecting CRC particularly in Asian. Our study provided exclusive evidence that multiple miRNAs extracted from serum samples had superior diagnostic performance over single miRNA for screening CRC. Therefore, this approach that is characterized by high specificity and noninvasive nature may assist in early diagnosis of CRC particularly in Asian.

Dataset Information

A Comprehensive Analysis of MicroRNAs in Human Osteoporosis.

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A Comprehensive Analysis of MicroRNAs in Human Osteoporosis.

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