Dataset Information

Evaluating reported candidate gene associations with polycystic ovary syndrome.

ABSTRACT:

Objective

To replicate variants in candidate genes associated with polycystic ovary syndrome (PCOS) in a population of European women with PCOS and control subjects.

Design

Case-control association analysis and meta-analysis.

Setting

Major 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 number

NCT00166569.

SUBMITTER: Pau C

PROVIDER: S-EPMC3722586 | biostudies-literature | 2013 May

REPOSITORIES: biostudies-literature

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Publications

Evaluating reported candidate gene associations with polycystic ovary syndrome.

Pau Cindy C Saxena Richa R Welt Corrine Kolka CK

Fertility and sterility 20130130 6

<h4>Objective</h4>To replicate variants in candidate genes associated with polycystic ovary syndrome (PCOS) in a population of European women with PCOS and control subjects.<h4>Design</h4>Case-control association analysis and meta-analysis.<h4>Setting</h4>Major academic hospital.<h4>Patient(s)</h4>Women of European ancestry with PCOS (n = 525) and controls (n = 472), aged 18-45 years.<h4>Intervention(s)</h4>Variants previously associated with PCOS in candidate gene studies were genotyped (n = 39 ...[more]

PMID: 23375202

Similar Datasets

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.

Dataset Information

Evaluating reported candidate gene associations with polycystic ovary syndrome.

Objective

Design

Setting

Patient(s)

Intervention(s)

Main outcome measure(s)

Result(s)

Conclusion(s)

Clinical trial registration number

Publications

Evaluating reported candidate gene associations with polycystic ovary syndrome.

Similar Datasets

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