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      Integrated bioinformatics analysis elucidates granulosa cell whole-transcriptome landscape of PCOS in China

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          Abstract

          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.

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          Consensus on women's health aspects of polycystic ovary syndrome (PCOS): the Amsterdam ESHRE/ASRM-Sponsored 3rd PCOS Consensus Workshop Group.

          Bart C.J.M. Fauser, Basil Tarlatzis, Robert W Rebar … (2012)
          Polycystic ovary syndrome (PCOS) is the most common endocrine disorder in females, with a high prevalence. The etiology of this heterogeneous condition remains obscure, and its phenotype expression varies. Two widely cited previous ESHRE/ASRM sponsored PCOS consensus workshops focused on diagnosis (published in 2004) and infertility management (published in 2008), respectively. The present third PCOS consensus report summarizes current knowledge and identifies knowledge gaps regarding various women's health aspects of PCOS. Relevant topics addressed-all dealt with in a systematic fashion-include adolescence, hirsutism and acne, contraception, menstrual cycle abnormalities, quality of life, ethnicity, pregnancy complications, long-term metabolic and cardiovascular health, and finally cancer risk. Additional, comprehensive background information is provided separately in an extended online publication. Copyright © 2012 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.
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            Polycystic ovary syndrome.

            Ricardo Azziz, Enrico Carmina, ZiJiang Chen … (2016)
            Polycystic ovary syndrome (PCOS) affects 5-20% of women of reproductive age worldwide. The condition is characterized by hyperandrogenism, ovulatory dysfunction and polycystic ovarian morphology (PCOM) - with excessive androgen production by the ovaries being a key feature of PCOS. Metabolic dysfunction characterized by insulin resistance and compensatory hyperinsulinaemia is evident in the vast majority of affected individuals. PCOS increases the risk for type 2 diabetes mellitus, gestational diabetes and other pregnancy-related complications, venous thromboembolism, cerebrovascular and cardiovascular events and endometrial cancer. PCOS is a diagnosis of exclusion, based primarily on the presence of hyperandrogenism, ovulatory dysfunction and PCOM. Treatment should be tailored to the complaints and needs of the patient and involves targeting metabolic abnormalities through lifestyle changes, medication and potentially surgery for the prevention and management of excess weight, androgen suppression and/or blockade, endometrial protection, reproductive therapy and the detection and treatment of psychological features. This Primer summarizes the current state of knowledge regarding the epidemiology, mechanisms and pathophysiology, diagnosis, screening and prevention, management and future investigational directions of the disorder.
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              Polycystic ovary syndrome.

              Richard S Legro, Theresa Hickey, J. Norman … (2007)
              Polycystic ovary syndrome is a heterogeneous endocrine disorder that affects about one in 15 women worldwide. The major endocrine disruption is excessive androgen secretion or activity, and a large proportion of women also have abnormal insulin activity. Many body systems are affected in polycystic ovary syndrome, resulting in several health complications, including menstrual dysfunction, infertility, hirsutism, acne, obesity, and metabolic syndrome. Women with this disorder have an established increased risk of developing type 2 diabetes and a still debated increased risk of cardiovascular disease. The diagnostic traits of polycystic ovary syndrome are hyperandrogenism, chronic anovulation, and polycystic ovaries, after exclusion of other conditions that cause these same features. A conclusive definition of the disorder and the importance of the three diagnostic criteria relative to each other remain controversial. The cause of polycystic ovary syndrome is unknown, but studies suggest a strong genetic component that is affected by gestational environment, lifestyle factors, or both.
              Article 0 comments Cited 202 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Qingfang Li: concordia@zju.edu.cn
                Yimiao Sang: 11918380@zju.edu.cn
                Qingqing Chen: 22018161@zju.edu.cn
                Bingru Ye: 22018454@zju.edu.cn
                Xiaoqian Zhou: 22118400@zju.edu.cn
                Yimin Zhu: zhuyim@zju.edu.cn
                Journal
                Journal ID (nlm-ta): J Ovarian Res
                Journal ID (iso-abbrev): J Ovarian Res
                Title: Journal of Ovarian Research
                Publisher: BioMed Central (London )
                ISSN (Electronic): 1757-2215
                Publication date (Electronic): 3 August 2023
                Publication date PMC-release: 3 August 2023
                Publication date Collection: 2023
                Volume: 16
                Electronic Location Identifier: 154
                Affiliations
                [1 ]GRID grid.13402.34, ISNI 0000 0004 1759 700X, School of Medicine, , Women’s Hospital, Zhejiang University, ; 1 Xueshi Road, Shangcheng District, Hangzhou, 310006 China
                [2 ]GRID grid.419897.a, ISNI 0000 0004 0369 313X, Key Laboratory of Reproductive Genetics, , Ministry of Education Zhejiang University, ; Hangzhou, 310006 China
                [3 ]GRID grid.13402.34, ISNI 0000 0004 1759 700X, Department of Reproductive Endocrinology, , Women’s Hospital, Zhejiang University School of Medicine, ; Hangzhou, Zhejiang 310006 China
                Article
                Publisher ID: 1223
                DOI: 10.1186/s13048-023-01223-0
                PMC ID: 10398987
                SO-VID: 1749380d-3067-4e88-b918-352e2e56637d
                Copyright © © BioMed Central Ltd., part of Springer Nature 2023
                License:

                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/. 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.

                History
                Date received : 17 April 2023
                Date accepted : 20 June 2023
                Funding
                Funded by: Natural Science Foundation of China
                Award ID: 81873819
                Funded by: Zhejiang Provincial Science and Technology project of China
                Award ID: 2021C03100
                Categories
                Subject: Research
                Custom metadata
                issue-copyright-statement © BioMed Central Ltd., part of Springer Nature 2023

                ScienceOpen disciplines: Obstetrics & Gynecology
                Keywords: pcos (polycystic ovarian syndrome),bioinformatics analysis,geo database,cerna network,correlation analysis
                Data availability:
                ScienceOpen disciplines: Obstetrics & Gynecology
                Keywords: pcos (polycystic ovarian syndrome), bioinformatics analysis, geo database, cerna network, correlation analysis

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