Candidate genes for polycystic ovary syndrome are regulated by TGFβ in the bovine foetal ovary.
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ABSTRACT:
SUBMITTER: Azumah R
PROVIDER: S-EPMC9156849 | biostudies-literature | 2022 May
REPOSITORIES: biostudies-literature
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Candidate genes for polycystic ovary syndrome are regulated by TGFβ in the bovine foetal ovary.
Azumah Rafiatu R Liu Menghe M Hummitzsch Katja K Bastian Nicole A NA Hartanti Monica D MD Irving-Rodgers Helen F HF Anderson Richard A RA Rodgers Raymond J RJ
Human reproduction (Oxford, England) 20220501 6
<h4>Study question</h4>Could changes in transforming growth factor β (TGFβ) signalling during foetal ovary development alter the expression of polycystic ovary syndrome (PCOS) candidate genes leading to a predisposition to PCOS?<h4>Summary answer</h4>TGFβ signalling molecules are dynamically expressed during foetal ovary development and TGFβ1 inhibits expression of the androgen receptor (AR) and 7 (INSR, C8H9orf3, RAD50, ERBB3, NEIL2, IRF1 and ZBTB16) of the 25 PCOS candidate genes in foetal ova ...[more]
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Project description:ContextPolycystic ovary syndrome (PCOS) is a complex disorder having both genetic and environmental components. A number of association studies based on candidate genes have reported significant association, but few have been replicated. D19S884, a polymorphic marker in fibrillin 3 (FBN3), is one of the few association findings that has been replicated in independent sets of families.ObjectiveThe aims of the study are: 1) to genotype single nucleotide polymorphisms (SNPs) in the region of D19S884; and 2) to follow up with an independent data set, published results reporting evidence for PCOS candidate gene associations.DesignThe transmission disequilibrium test (TDT) was used to analyze linkage and association between PCOS and SNPs in candidate genes previously reported by us and by others as significantly associated with PCOS.SettingThe study was conducted at academic medical centers.Patients or other participantsA total of 453 families having a proband with PCOS participated in the study. Sisters with PCOS were also included. There was a total of 502 probands and sisters with PCOS.Intervention(s)There were no interventions.Main outcome measure(s)The outcome measure was transmission frequency of SNP alleles.ResultsWe identified a six-SNP haplotype block spanning a 6.7-kb region on chromosome 19p13.2 that includes D19S884. SNP haplotype allele-C alone and in combination with D19S884-allele 8 is significantly associated with PCOS: haplotype-C TDT chi(2) = 10.0 (P = 0.0016) and haplotype-C/A8 TDT chi(2) = 7.6 (P = 0.006). SNPs in four of the other 26 putative candidate genes that were tested using the TDT were nominally significant (ACVR2A, POMC, FEM1B, and SGTA). One SNP in POMC (rs12473543, chi(2) = 9.1; P(corrected) = 0.042) is significant after correction for multiple testing.ConclusionsA polymorphic variant, D19S884, in FBN3 is associated with risk of PCOS. POMC is also a candidate gene of interest.
| S-EPMC2869537 | biostudies-literature
Project description:BackgroundHuman homologs (FEM1A, FEM1B, FEM1C) of nematode sex determination genes are candidate genes for polycystic ovary syndrome (PCOS). We previously identified a FEM1A mutation (H500Y) in a woman with PCOS; FEM1B has been implicated in insulin secretion.MethodsWomen with and without PCOS (287 cases, 187 controls) were genotyped for H500Y and six FEM1A single nucleotide polymorphisms (SNPs), five FEM1B SNPs and five FEM1C SNPs. SNPs and haplotypes were determined and tested for association with PCOS and component phenotypes.ResultsNo subject carried the FEM1A H500Y mutation. FEM1A SNPs rs8111933 (P = 0.001) and rs12460989 (P = 0.046) were associated with an increased likelihood of PCOS whereas FEM1A SNP rs1044386 was associated with a reduced probability of PCOS (P = 0.013). FEM1B SNP rs10152450 and a linked SNP were associated with a reduced likelihood of PCOS (P = 0.005), and lower homeostasis model assessment (HOMA) for beta-cell function (HOMA-%B, P = 0.011) and lower HOMA for insulin resistance (HOMA-IR, P = 0.018). FEM1B SNP rs12909277 was associated with lower HOMA-%B (P = 0.008) and lower HOMA-IR (P = 0.037). Haplotype associations were consistent with SNP results, and also revealed association of FEM1B haplotype TGAGG with increased HOMA-%B (P = 0.007) and HOMA-IR (P = 0.024). FEM1C variants were not associated with PCOS.ConclusionsThis study presents evidence suggesting a role for FEM1A and FEM1B in the pathogenesis of PCOS. Only FEM1B variants were associated with insulin-related traits in PCOS women, consistent with prior evidence linking this gene to insulin secretion. Replication of these associations and mechanistic studies will be necessary to establish the role of these genes in PCOS.
| S-EPMC2583941 | biostudies-literature
Project description:Novel pathways in polycystic ovary syndrome (PCOS) are being identified in gene expression studies in PCOS tissues; such pathways may contain key genes in disease etiology. Previous expression studies identified both dickkopf homolog 1 (DKK1) and DnaJ (Hsp40) homolog, subfamily B, member 1 (DNAJB1) as differentially expressed in PCOS tissue, implicating them as candidates for PCOS susceptibility. To test this, we genotyped a discovery cohort of 335 PCOS cases and 198 healthy controls for three DKK1 single nucleotide polymorphisms (SNPs) and four DNAJB1 SNPs and a replication cohort of 396 PCOS cases and 306 healthy controls for 1 DKK1 SNP and 1 DNAJB1 SNP. SNPs and haplotypes were determined and tested for association with PCOS and component phenotypes. We found that no single nucleotide polymorphisms were associated with PCOS risk; however, the major allele of rs1569198 from DKK1 was associated with increased total testosterone (discovery cohort P?=?0.0035) and dehydroepiandrosterone sulfate (replication cohort P?=?0.05). Minor allele carriers at rs3962158 from DNAJB1 had increased fasting insulin (discovery cohort P?=?0.003), increased HOMA-IR (discovery cohort P?=?0.006; replication cohort P?=?0.036), and increased HOMA-%B (discovery cohort P?=?0.004). Carriers of haplotype 2 at DNAJB1 also had increased fasting insulin, HOMA-IR, and HOMA-%B. These findings suggest that genetic variation in DKK1 and DNAJB1 may have a role in the hyperandrogenic and metabolic dysfunction of PCOS, respectively. Our results also demonstrate the utility of gene expression data as a source of novel candidate genes in PCOS, a complex and still incompletely defined disease, for which alternative methods of gene identification are needed.
| S-EPMC3096662 | biostudies-literature
Project description:The role of metabolic disturbance in polycystic ovary syndrome (PCOS) has been well established, with insulin resistance and the resulting compensatory hyperinsulinemia thought to promote hyperandrogenemia. Genome-wide association studies (GWAS) have established a large number of loci for metabolic conditions such as type 2 diabetes and obesity. A subset of these loci has been investigated for a role in PCOS; these studies generally have not revealed a confirmed role for these loci in PCOS risk. However, a large scale investigation of genes related to these pathways has not previously been performed. We conducted a two stage case control association study of 121,715 single nucleotide polymorphisms (SNPs) selected to represent susceptibility loci associated with traits such as type 2 diabetes, obesity measures, lipid levels and cardiovascular function using the Cardio-Metabochip in 847 PCOS cases and 845 controls. Several hypothesis-generating associations with PCOS were observed (top SNP rs2129107, P=3.8×10(-6)). We did not find any loci definitively associated with PCOS after strict correction for multiple testing, suggesting that cardio-metabolic loci are not major risk factors underlying the susceptibility to PCOS.
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Project description:ObjectiveTo replicate variants in candidate genes associated with polycystic ovary syndrome (PCOS) in a population of European women with PCOS and control subjects.DesignCase-control association analysis and meta-analysis.SettingMajor academic hospital.Patient(s)Women of European ancestry with PCOS (n = 525) and controls (n = 472), aged 18-45 years.Intervention(s)Variants previously associated with PCOS in candidate gene studies were genotyped (n = 39). Metabolic, reproductive, and anthropomorphic parameters were examined as a function of the candidate variants. All genetic association analyses were adjusted for age, body mass index, and ancestry and were reported after correction for multiple testing.Main outcome measure(s)Association of candidate gene variants with PCOS.Result(s)Three variants, rs3797179 (SRD5A1), rs12473543 (POMC), and rs1501299 (ADIPOQ), were nominally associated with PCOS. However, they did not remain significant after correction for multiple testing, and none of the variants replicated in a sufficiently powered meta-analysis. Variants in the FBN3 gene (rs17202517 and rs73503752) were associated with smaller waist circumferences, and variant rs727428 in the SHBG gene was associated with lower sex hormone-binding globulin levels.Conclusion(s)Previously identified variants in candidate genes do not seem to be associated with PCOS risk.Clinical trial registration numberNCT00166569.
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Project description:Polycystic ovary syndrome (PCOS) is a common endocrine disorder of women, characterized by hyperandrogenism and chronic anovulation. It is a leading cause of female infertility and is associated with polycystic ovaries, hirsutism, obesity, and insulin resistance. We tested a carefully chosen collection of 37 candidate genes for linkage and association with PCOS or hyperandrogenemia in data from 150 families. The strongest evidence for linkage was with the follistatin gene, for which affected sisters showed increased identity by descent (72%; chi(2) = 12.97; nominal P = 3.2 x 10(-4)). After correction for multiple testing (33 tests), the follistatin findings were still highly significant (P(c) = 0.01). Although the linkage results for CYP11A were also nominally significant (P = 0.02), they were no longer significant after correction. In 11 candidate gene regions, at least one allele showed nominally significant evidence for population association with PCOS in the transmission/disequilibrium test (chi(2) >/= 3.84; nominal P < 0.05). The strongest effect in the transmission/disequilibrium test was observed in the INSR region (D19S884; allele 5; chi(2) = 8.53) but was not significant after correction. Our study shows how a systematic screen of candidate genes can provide strong evidence for genetic linkage in complex diseases and can identify those genes that should have high (or low) priority for further study.
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Project description:Polycystic Ovary Syndrome (PCOS) is a multifactorial syndrome with reproductive, endocrine, and metabolic symptoms, affecting about 10% women of reproductive age. Pathogenesis of the syndrome is poorly understood with genetic and fetal origins being the focus of the conundrum. Genetic predisposition of PCOS has been confirmed by candidate gene studies and Genome-Wide Association Studies (GWAS). Recently, the expression of PCOS candidate genes across gestation has been studied in human and bovine fetal ovaries. The current study sought to identify potential upstream regulators and mechanisms associated with PCOS candidate genes. Using RNA sequencing data of bovine fetal ovaries (62-276 days, n = 19), expression of PCOS candidate genes across gestation was analysed using Partek Flow. A supervised heatmap of the expression data of all 24,889 genes across gestation was generated. Most of the PCOS genes fell into one of four clusters according to their expression patterns. Some genes correlated negatively (early genes; C8H9orf3, TOX3, FBN3, GATA4, HMGA2, and DENND1A) and others positively (late genes; FDFT1, LHCGR, AMH, FSHR, ZBTB16, and PLGRKT) with gestational age. Pathways associated with PCOS candidate genes and genes co-expressed with them were determined using Ingenuity pathway analysis (IPA) software as well as DAVID Bioinformatics Resources for KEGG pathway analysis and Gene Ontology databases. Genes expressed in the early cluster were mainly involved in mitochondrial function and oxidative phosphorylation and their upstream regulators included PTEN, ESRRG/A and MYC. Genes in the late cluster were involved in stromal expansion, cholesterol biosynthesis and steroidogenesis and their upstream regulators included TGFB1/2/3, TNF, ERBB2/3, VEGF, INSIG1, POR, and IL25. These findings provide insight into ovarian development of relevance to the origins of PCOS, and suggest that multiple aetiological pathways might exist for the development of PCOS.
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Project description:BackgroundIn this study, we aimed to identify novel biomarkers for polycystic ovary syndrome (PCOS) and analyze their potential roles in immune infiltration during PCOS pathogenesis.MethodsFive datasets, namely GSE137684, GSE80432, GSE114419, GSE138518, and GSE155489, were obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were selected from the train datasets. The least absolute shrinkage and selection operator logistic regression model and support vector machine-recursive feature elimination algorithm were combined to screen potential biomarkers. The test datasets validated the expression levels of these biomarkers, and the area under the curve (AUC) was calculated to analyze their diagnostic value. Quantitative real-time PCR was conducted to verify biomarkers' expression in clinical samples. CIBERSORT was used to assess differential immune infiltration, and the correlations of biomarkers with infiltrating immune cells were evaluated.ResultsHerein, 1265 DEGs were identified between PCOS and control groups. The gene sets related to immune response and adaptive immune response were differentially activated in PCOS. The two diagnostic biomarkers of PCOS identified by us were HD domain containing 3 (HDDC3) and syndecan 2 (SDC2; AUC, 0.918 and 0.816, respectively). The validation of hub biomarkers in clinical samples using RT-qPCR was consistent with bioinformatics results. Immune infiltration analysis indicated that decreased activated mast cells (P = 0.033) and increased eosinophils (P = 0.040) may be a part of the pathogenesis of PCOS. HDDC3 was positively correlated with T regulatory cells (P = 0.0064), activated mast cells (P = 0.014), and monocytes (P = 0.024) but negatively correlated with activated memory CD4 T cells (P = 0.016) in PCOS. In addition, SDC2 was positively correlated with activated mast cells (P = 0.0021), plasma cells (P = 0.0051), and M2 macrophages (P = 0.038) but negatively correlated with eosinophils (P = 0.01) and neutrophils (P = 0.031) in PCOS.ConclusionHDDC3 and SDC2 can serve as candidate biomarkers of PCOS and provide new insights into the molecular mechanisms of immune regulation in PCOS.
| S-EPMC9258136 | biostudies-literature
Project description:Human polycystic ovary syndrome (PCOS) is a highly heritable disease regulated by genetic and environmental factors. Identifying PCOS genes is time consuming and costly in wet-lab. Developing an algorithm to predict PCOS candidates will be helpful. In this study, for the first time, we systematically analyzed properties of human PCOS genes. Compared with genes not yet known to be involved in PCOS regulation, known PCOS genes display distinguishing characteristics: (i) they tend to be located at network center; (ii) they tend to interact with each other; (iii) they tend to enrich in certain biological processes. Based on these features, we developed a machine-learning algorithm to predict new PCOS genes. 233 PCOS candidates were predicted with a posterior probability >0.9. Evidence supporting 7 of the top 10 predictions has been found.
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Project description:ObjectiveTo identify key genes involved in occurrence and development of polycystic ovary syndrome (PCOS).MethodsBy downloading the GSE85932 dataset from the GEO database, we used bioinformatical analysis to analyse differentially expressed genes (DEGs) from blood samples of eight women with PCOS and eight matched controls. Following bioinformatic analysis, we performed a cross-sectional study of serum samples taken from 79 women with PCOS and 36 healthy controls.ResultsFrom the 178 DEGs identified by bioinformatical analysis, 15 genes were identified as significant, and of these, ORM1 and ORM2 were selected for further verification as potential biomarkers for PCOS. Serum ORM1 and ORM2 levels were significantly increased in women with PCOS, and had a high diagnostic value. ORM1 and ORM2 were positively correlated with testosterone, cholesterol, and triglycerides. ORM1 levels were negatively correlated with high density lipoprotein (HDL) while ORM2 levels showed no significant correlation.ConclusionsORM may be an effective biomarker for the diagnosis of PCOS and its monitoring may be a useful therapeutic strategy.
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