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Integrated bioinformatics analysis elucidates granulosa cell whole-transcriptome landscape of PCOS in China
BACKGROUND: Polycystic ovary syndrome (PCOS) is a common reproductive, neuroendocrine, and metabolic disorder in women of reproductive age that affects up to 5–10% of women of reproductive age. The aetiology of follicle development arrest and critical issues regarding the abnormal follicular develop...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10398987/ https://www.ncbi.nlm.nih.gov/pubmed/37537636 http://dx.doi.org/10.1186/s13048-023-01223-0 |
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author | Li, Qingfang Sang, Yimiao Chen, Qingqing Ye, Bingru Zhou, Xiaoqian Zhu, Yimin |
author_facet | Li, Qingfang Sang, Yimiao Chen, Qingqing Ye, Bingru Zhou, Xiaoqian Zhu, Yimin |
author_sort | Li, Qingfang |
collection | PubMed |
description | BACKGROUND: Polycystic ovary syndrome (PCOS) is a common reproductive, neuroendocrine, and metabolic disorder in women of reproductive age that affects up to 5–10% of women of reproductive age. The aetiology of follicle development arrest and critical issues regarding the abnormal follicular development in PCOS remain unclear. The present study aims to systematically evaluate granulosa cell whole-transcriptome sequencing data to gain more insights into the transcriptomic landscape and molecular mechanism of PCOS in China. METHODS: In the present study, the microarray datasets GSE138518, GSE168404, GSE193123, GSE138572, GSE95728, and GSE145296 were downloaded from the Gene Expression Omnibus (GEO) database. Subsequently, differential expression analysis was performed on the PCOS and control groups, followed by functional interaction prediction analysis to investigate gene-regulatory circuits in PCOS. Finally, hub genes and their associated ncRNAs were validated by qPCR in human-luteinized granulosa (hGL) cells and were correlated with the clinical characteristics of the patients. RESULTS: A total of 200 differentially expressed mRNAs, 3 differentially expressed miRNAs, 52 differentially expressed lncRNAs, and 66 differentially expressed circRNAs were found in PCOS samples compared with controls. GO and KEGG enrichment analyses indicated that the DEGs were mostly enriched in phospholipid metabolic processes, steroid biosynthesis and inflammation related pathways. In addition, the upregulated miRNA hsa-miR-205-5p was significantly enriched in the ceRNA network, and two hub genes, MVD and PNPLA3, were regulated by hsa-miR-205-5p, which means that hsa-miR-205-5p may play a fundamental role in the pathogenesis of PCOS. We also found that MVD and PNPLA3 were related to metabolic processes and ovarian steroidogenesis, which may be the cause of the follicle development arrest in PCOS patients. CONCLUSIONS: In summary, we systematically constructed a ceRNA network depicting the interactions between the ncRNAs and the hub genes in PCOS and control subjects and correlated the hub genes with the clinical characteristics of the patients, which provides valuable insights into the granulosa cell whole-transcriptome landscape of PCOS in China. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13048-023-01223-0. |
format | Online Article Text |
id | pubmed-10398987 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-103989872023-08-04 Integrated bioinformatics analysis elucidates granulosa cell whole-transcriptome landscape of PCOS in China Li, Qingfang Sang, Yimiao Chen, Qingqing Ye, Bingru Zhou, Xiaoqian Zhu, Yimin J Ovarian Res Research BACKGROUND: Polycystic ovary syndrome (PCOS) is a common reproductive, neuroendocrine, and metabolic disorder in women of reproductive age that affects up to 5–10% of women of reproductive age. The aetiology of follicle development arrest and critical issues regarding the abnormal follicular development in PCOS remain unclear. The present study aims to systematically evaluate granulosa cell whole-transcriptome sequencing data to gain more insights into the transcriptomic landscape and molecular mechanism of PCOS in China. METHODS: In the present study, the microarray datasets GSE138518, GSE168404, GSE193123, GSE138572, GSE95728, and GSE145296 were downloaded from the Gene Expression Omnibus (GEO) database. Subsequently, differential expression analysis was performed on the PCOS and control groups, followed by functional interaction prediction analysis to investigate gene-regulatory circuits in PCOS. Finally, hub genes and their associated ncRNAs were validated by qPCR in human-luteinized granulosa (hGL) cells and were correlated with the clinical characteristics of the patients. RESULTS: A total of 200 differentially expressed mRNAs, 3 differentially expressed miRNAs, 52 differentially expressed lncRNAs, and 66 differentially expressed circRNAs were found in PCOS samples compared with controls. GO and KEGG enrichment analyses indicated that the DEGs were mostly enriched in phospholipid metabolic processes, steroid biosynthesis and inflammation related pathways. In addition, the upregulated miRNA hsa-miR-205-5p was significantly enriched in the ceRNA network, and two hub genes, MVD and PNPLA3, were regulated by hsa-miR-205-5p, which means that hsa-miR-205-5p may play a fundamental role in the pathogenesis of PCOS. We also found that MVD and PNPLA3 were related to metabolic processes and ovarian steroidogenesis, which may be the cause of the follicle development arrest in PCOS patients. CONCLUSIONS: In summary, we systematically constructed a ceRNA network depicting the interactions between the ncRNAs and the hub genes in PCOS and control subjects and correlated the hub genes with the clinical characteristics of the patients, which provides valuable insights into the granulosa cell whole-transcriptome landscape of PCOS in China. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13048-023-01223-0. BioMed Central 2023-08-03 /pmc/articles/PMC10398987/ /pubmed/37537636 http://dx.doi.org/10.1186/s13048-023-01223-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/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://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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 Li, Qingfang Sang, Yimiao Chen, Qingqing Ye, Bingru Zhou, Xiaoqian Zhu, Yimin Integrated bioinformatics analysis elucidates granulosa cell whole-transcriptome landscape of PCOS in China |
title | Integrated bioinformatics analysis elucidates granulosa cell whole-transcriptome landscape of PCOS in China |
title_full | Integrated bioinformatics analysis elucidates granulosa cell whole-transcriptome landscape of PCOS in China |
title_fullStr | Integrated bioinformatics analysis elucidates granulosa cell whole-transcriptome landscape of PCOS in China |
title_full_unstemmed | Integrated bioinformatics analysis elucidates granulosa cell whole-transcriptome landscape of PCOS in China |
title_short | Integrated bioinformatics analysis elucidates granulosa cell whole-transcriptome landscape of PCOS in China |
title_sort | integrated bioinformatics analysis elucidates granulosa cell whole-transcriptome landscape of pcos in china |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10398987/ https://www.ncbi.nlm.nih.gov/pubmed/37537636 http://dx.doi.org/10.1186/s13048-023-01223-0 |
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