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Relationship between the characteristic traits of polycystic ovary syndrome and susceptibility genes.

ABSTRACT: Polycystic ovary syndrome (PCOS) is a highly complex disorder influenced by genetic and environmental factors. Previous genome-wide association studies (GWAS) on Han Chinese, Korean, and European populations identified multiple PCOS-susceptible loci; however, only a few studies reported the association of susceptibility genes with disease phenotypic traits. This cross-sectional study aimed to investigate the association between PCOS susceptibility genes from GWAS and disease-related clinical features. A total of 1,810 reproductive-aged women were recruited, including 927 control women and 883 women with PCOS, diagnosed based on the European Society for Human Reproduction and Embryology criteria. Genomic DNA was extracted and genotyped, and a Bonferroni test was performed to determine the association between 12 independent SNPs and the clinical features of PCOS. In women with PCOS, rs11031006, nearest to FSHB, was significantly associated with free testosterone (P?=?1.94 × 10-3) and luteinizing hormone (P?=?1.96 × 10-3) levels. The menstruation number per year, ovarian follicular number, ovarian volume, and insulin sensitivity index were not associated with any SNP. In the control group, no SNPs were associated with any PCOS traits. Collectively, our results suggest that FSHB may play an important role in the development and progression of PCOS.

SUBMITTER: Hong SH

PROVIDER: S-EPMC7320020 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Relationship between the characteristic traits of polycystic ovary syndrome and susceptibility genes.

Hong So-Hyeon SH Hong Young Sun YS Jeong Kyungah K Chung Hyewon H Lee Hyejin H Sung Yeon-Ah YA

Scientific reports 20200626 1

Polycystic ovary syndrome (PCOS) is a highly complex disorder influenced by genetic and environmental factors. Previous genome-wide association studies (GWAS) on Han Chinese, Korean, and European populations identified multiple PCOS-susceptible loci; however, only a few studies reported the association of susceptibility genes with disease phenotypic traits. This cross-sectional study aimed to investigate the association between PCOS susceptibility genes from GWAS and disease-related clinical fea ...[more]

PMID: 32591571

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Project description:BackgroundIn recent years, clinical studies have found that there is a close relationship between osteoporosis and polycystic ovary syndrome. However, there are few literature on the pathogenesis of osteoporosis and polycystic ovary syndrome. In order to clarify their common pathogenic mechanism and provide potential targets for drugs to regulate them at the same time, bioinformatics methods are used to explore, so as to provide a new direction for the study of the relationship between diseases in the future.MethodsTo screen the targets of osteoporosis and polycystic ovary syndrome by Genecards, Online Mendelian Inheritance in Man databases and Therapeutic Target Database to take the intersection of the two mappings and upload the intersection targets to the STRING database to construct protein-protein interaction network; to screen the core targets by degree value and import them to Metascape database for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis; and finally, to construct the visualization network of core targets and pathways by Cytoscape software. Ethical approval and informed consent of patients are not required because the data used in this study is publicly available and does not involve individual patient data or privacy.ResultsThe core targets of polycystic ovary syndrome and osteoporosis were insulin gene, insulin-like growth factor 1, CTNNB1, serine/threonine kinase 1, signal transducer and activator of transcription 3, LEP, etc. The biological processes involved include the regulation of protein phosphorylation, cell proliferation and differentiation, hormone endocrine, reproductive system and skeletal system. The related pathways were concentrated in Foxo signaling pathway, HTLV-I infection, PI3K-AKT signaling pathway, MAPK signaling pathway and AGE-RAGE signaling pathway in diabetic complications.ConclusionsThere is a close relationship between osteoporosis and polycystic ovary syndrome in terms of target and molecular mechanism. This study used bioinformatics to clarify their targets and mechanisms, providing potential targets for drugs to regulate both diseases simultaneously and providing new directions to explore the relationship between the diseases.

Project description:ObjectiveTo investigate how body fat influences glucose metabolism and hormone profiles in women with polycystic ovary syndrome (PCOS), compared to women without PCOS.MethodsWe conducted a cross-sectional study of 166 women with PCOS and 139 age-matched control women at Peking University Third Hospital (Beijing, China) from March 2016 to December 2021. All participants underwent bioimpedance rate assessment of clinical, anthropometric, hormonal, and metabolic features. In particular, body composition parameters were assessed, based on the methods used in a previous study. Homeostasis model assessment-insulin resistance (HOMA-IR) and other indices calculated from fasting glucose and insulin were used to measure insulin resistance. The hormonal profiles [follicle-stimulating hormone (FSH), luteinizing hormone (LH), estrogen (E2), prolactin (PRL), total testosterone (T), and androstenedione (A2)] were assessed by using biochemical methods. Two subgroup analyses were conducted according to waist-to-hip ratio (WHR; < 0.85, non-central obesity and ≥ 0.85, central obesity) and body fat percentage (BFP; < 35% for lean and ≥35% for obesity). The indices above were analyzed using a two-sided t-test or Wilcoxon rank sum test. Linear regression was used to investigate the effects of body composition on metabolism and sex hormones in the PCOS and control groups.ResultsCompared to women without PCOS, women with PCOS and central obesity (P=0.021), PCOS and noncentral obesity (P<0.001), PCOS and high BFP (P<0.001), and PCOS and low BFP (P<0.001) had more severe glucose metabolism evaluated with HOMA-IR. Women with PCOS experienced greater insulin sensitivity impairment than did the normal population for every equal increase in BFP. LH, LH/FSH, total testosterone, and androstenedione were significantly higher in patients with PCOS than in healthy controls, regardless of WHR and BFP stratification. However, negative correlations existed between body fat indices (i.e., BFP and body mass index) and hormone indices (i.e., LH and androstenedione) in the PCOS group, but were absent in the control group.ConclusionsObese and non-obese women with PCOS have more severe insulin resistance and sex-hormone disorders than women without PCOS. The effect of body fat on sex-hormone disorders is only exist in women with PCOS. These findings suggested that PCOS clinical guidelines should be more specific to body fat.Clinical trial registrationhttps://clinicaltrials.gov/, Registration No. NCT04264832.

Dataset Information

Relationship between the characteristic traits of polycystic ovary syndrome and susceptibility genes.

Publications

Relationship between the characteristic traits of polycystic ovary syndrome and susceptibility genes.

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