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Bioinformatics analysis of miRNA and mRNA expression profiles to reveal the key miRNAs and genes in osteoarthritis

BACKGROUND: Osteoarthritis (OA) is a chronic degenerative joint disease and the most frequent type of arthritis. This study aimed to identify the key miRNAs and genes associated with OA progression. METHODS: The GSE105027 (microRNA [miRNA/miR] expression profile; 12 OA samples and 12 normal samples)...

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Autores principales: Huang, Pei-yan, Wu, Jun-guo, Gu, Jun, Zhang, Tie-qi, Li, Ling-feng, Wang, Si-qun, Wang, Minghai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7814623/
https://www.ncbi.nlm.nih.gov/pubmed/33468167
http://dx.doi.org/10.1186/s13018-021-02201-2
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author Huang, Pei-yan
Wu, Jun-guo
Gu, Jun
Zhang, Tie-qi
Li, Ling-feng
Wang, Si-qun
Wang, Minghai
author_facet Huang, Pei-yan
Wu, Jun-guo
Gu, Jun
Zhang, Tie-qi
Li, Ling-feng
Wang, Si-qun
Wang, Minghai
author_sort Huang, Pei-yan
collection PubMed
description BACKGROUND: Osteoarthritis (OA) is a chronic degenerative joint disease and the most frequent type of arthritis. This study aimed to identify the key miRNAs and genes associated with OA progression. METHODS: The GSE105027 (microRNA [miRNA/miR] expression profile; 12 OA samples and 12 normal samples) and GSE48556 (messenger RNA [mRNA] expression profile; 106 OA samples and 33 normal samples) datasets were selected from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) and miRNAs (DEMs) were analyzed using the limma and ROCR packages in R, respectively. The target genes that negatively correlated with the DEMs were predicted, followed by functional enrichment analysis and construction of the miRNA-gene and miRNA-transcription factor (TF)-gene regulatory networks. Additionally, key miRNAs and genes were screened, and their expression levels were verified by real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). RESULTS: A total of 1696 DEGs (739 upregulated and 957 downregulated) and 108 DEMs (56 upregulated and 52 downregulated) were identified in the OA samples. Furthermore, 56 target genes that negatively correlated with the DEMs were predicted and found to be enriched in three functional terms (e.g., positive regulation of intracellular protein transport) and three pathways (e.g., human cytomegalovirus infection). In addition, three key miRNAs (miR-98-5p, miR-7-5p, and miR-182-5p) and six key genes (murine double minute 2, MDM2; glycogen synthase kinase 3-beta, GSK3B; transmembrane P24-trafficking protein 10, TMED10; DDB1 and CUL4-associated factor 12, DCAF12; caspase 3, CASP3; and ring finger protein 44, RNF44) were screened, among which the miR-7-5p → TMED10/DCAF12, miR-98-5p → CASP3/RNF44, and miR-182-5p → GSK3B pairs were observed in the regulatory network. Moreover, the expression levels of TMED10, miR-7-5p, CASP3, miR-98-5p, GSK3B, and miR-182-5p showed a negative correlation with qRT-PCR verification. CONCLUSION: MiR-98-5p, miR-7-5p, miR-182-5p, MDM2, GSK3B, TMED10, DCAF12, CASP3, and RNF44 may play critical roles in OA progression. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13018-021-02201-2.
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spelling pubmed-78146232021-01-19 Bioinformatics analysis of miRNA and mRNA expression profiles to reveal the key miRNAs and genes in osteoarthritis Huang, Pei-yan Wu, Jun-guo Gu, Jun Zhang, Tie-qi Li, Ling-feng Wang, Si-qun Wang, Minghai J Orthop Surg Res Research Article BACKGROUND: Osteoarthritis (OA) is a chronic degenerative joint disease and the most frequent type of arthritis. This study aimed to identify the key miRNAs and genes associated with OA progression. METHODS: The GSE105027 (microRNA [miRNA/miR] expression profile; 12 OA samples and 12 normal samples) and GSE48556 (messenger RNA [mRNA] expression profile; 106 OA samples and 33 normal samples) datasets were selected from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) and miRNAs (DEMs) were analyzed using the limma and ROCR packages in R, respectively. The target genes that negatively correlated with the DEMs were predicted, followed by functional enrichment analysis and construction of the miRNA-gene and miRNA-transcription factor (TF)-gene regulatory networks. Additionally, key miRNAs and genes were screened, and their expression levels were verified by real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). RESULTS: A total of 1696 DEGs (739 upregulated and 957 downregulated) and 108 DEMs (56 upregulated and 52 downregulated) were identified in the OA samples. Furthermore, 56 target genes that negatively correlated with the DEMs were predicted and found to be enriched in three functional terms (e.g., positive regulation of intracellular protein transport) and three pathways (e.g., human cytomegalovirus infection). In addition, three key miRNAs (miR-98-5p, miR-7-5p, and miR-182-5p) and six key genes (murine double minute 2, MDM2; glycogen synthase kinase 3-beta, GSK3B; transmembrane P24-trafficking protein 10, TMED10; DDB1 and CUL4-associated factor 12, DCAF12; caspase 3, CASP3; and ring finger protein 44, RNF44) were screened, among which the miR-7-5p → TMED10/DCAF12, miR-98-5p → CASP3/RNF44, and miR-182-5p → GSK3B pairs were observed in the regulatory network. Moreover, the expression levels of TMED10, miR-7-5p, CASP3, miR-98-5p, GSK3B, and miR-182-5p showed a negative correlation with qRT-PCR verification. CONCLUSION: MiR-98-5p, miR-7-5p, miR-182-5p, MDM2, GSK3B, TMED10, DCAF12, CASP3, and RNF44 may play critical roles in OA progression. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13018-021-02201-2. BioMed Central 2021-01-19 /pmc/articles/PMC7814623/ /pubmed/33468167 http://dx.doi.org/10.1186/s13018-021-02201-2 Text en © The Author(s) 2021 Open AccessThis 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://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Huang, Pei-yan
Wu, Jun-guo
Gu, Jun
Zhang, Tie-qi
Li, Ling-feng
Wang, Si-qun
Wang, Minghai
Bioinformatics analysis of miRNA and mRNA expression profiles to reveal the key miRNAs and genes in osteoarthritis
title Bioinformatics analysis of miRNA and mRNA expression profiles to reveal the key miRNAs and genes in osteoarthritis
title_full Bioinformatics analysis of miRNA and mRNA expression profiles to reveal the key miRNAs and genes in osteoarthritis
title_fullStr Bioinformatics analysis of miRNA and mRNA expression profiles to reveal the key miRNAs and genes in osteoarthritis
title_full_unstemmed Bioinformatics analysis of miRNA and mRNA expression profiles to reveal the key miRNAs and genes in osteoarthritis
title_short Bioinformatics analysis of miRNA and mRNA expression profiles to reveal the key miRNAs and genes in osteoarthritis
title_sort bioinformatics analysis of mirna and mrna expression profiles to reveal the key mirnas and genes in osteoarthritis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7814623/
https://www.ncbi.nlm.nih.gov/pubmed/33468167
http://dx.doi.org/10.1186/s13018-021-02201-2
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