Correction: Large-scale genome-wide meta-analysis of polycystic ovary syndrome suggests shared genetic architecture for different diagnosis criteria.
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SUBMITTER: Day F
PROVIDER: S-EPMC6894746 | biostudies-literature | 2019 Dec
REPOSITORIES: biostudies-literature
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Correction: Large-scale genome-wide meta-analysis of polycystic ovary syndrome suggests shared genetic architecture for different diagnosis criteria.
Day Felix F Karaderi Tugce T Jones Michelle R MR Meun Cindy C He Chunyan C Drong Alex A Kraft Peter P Lin Nan N Huang Hongyan H Broer Linda L Magi Reedik R Saxena Richa R Laisk Triin T Urbanek Margrit M Hayes M Geoffrey MG Thorleifsson Gudmar G Fernandez-Tajes Juan J Mahajan Anubha A Mullin Benjamin H BH Stuckey Bronwyn G A BGA Spector Timothy D TD Wilson Scott G SG Goodarzi Mark O MO Davis Lea L Obermayer-Pietsch Barbara B Uitterlinden André G AG Anttila Verneri V Neale Benjamin M BM Jarvelin Marjo-Riitta MR Fauser Bart B Kowalska Irina I Visser Jenny A JA Andersen Marianne M Ong Ken K Stener-Victorin Elisabet E Ehrmann David D Legro Richard S RS Salumets Andres A McCarthy Mark I MI Morin-Papunen Laure L Thorsteinsdottir Unnur U Stefansson Kari K Styrkarsdottir Unnur U Perry John R B JRB Dunaif Andrea A Laven Joop J Franks Steve S Lindgren Cecilia M CM Welt Corrine K CK
PLoS genetics 20191205 12
[This corrects the article DOI: 10.1371/journal.pgen.1007813.]. ...[more]
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Project description:Polycystic ovary syndrome (PCOS) is a disorder characterized by hyperandrogenism, ovulatory dysfunction and polycystic ovarian morphology. Affected women frequently have metabolic disturbances including insulin resistance and dysregulation of glucose homeostasis. PCOS is diagnosed with two different sets of diagnostic criteria, resulting in a phenotypic spectrum of PCOS cases. The genetic similarities between cases diagnosed based on the two criteria have been largely unknown. Previous studies in Chinese and European subjects have identified 16 loci associated with risk of PCOS. We report a fixed-effect, inverse-weighted-variance meta-analysis from 10,074 PCOS cases and 103,164 controls of European ancestry and characterisation of PCOS related traits. We identified 3 novel loci (near PLGRKT, ZBTB16 and MAPRE1), and provide replication of 11 previously reported loci. Only one locus differed significantly in its association by diagnostic criteria; otherwise the genetic architecture was similar between PCOS diagnosed by self-report and PCOS diagnosed by NIH or non-NIH Rotterdam criteria across common variants at 13 loci. Identified variants were associated with hyperandrogenism, gonadotropin regulation and testosterone levels in affected women. Linkage disequilibrium score regression analysis revealed genetic correlations with obesity, fasting insulin, type 2 diabetes, lipid levels and coronary artery disease, indicating shared genetic architecture between metabolic traits and PCOS. Mendelian randomization analyses suggested variants associated with body mass index, fasting insulin, menopause timing, depression and male-pattern balding play a causal role in PCOS. The data thus demonstrate 3 novel loci associated with PCOS and similar genetic architecture for all diagnostic criteria. The data also provide the first genetic evidence for a male phenotype for PCOS and a causal link to depression, a previously hypothesized comorbid disease. Thus, the genetics provide a comprehensive view of PCOS that encompasses multiple diagnostic criteria, gender, reproductive potential and mental health.
| S-EPMC6300389 | biostudies-literature
Project description:Objective To study whether application of the new 2018 guidelines for the diagnosis of polycystic ovary syndrome (PCOS) would decrease the diagnosis of PCOS. Second, to compare the metabolic profiles of women included and excluded in this new definition. Design Retrospective cross-sectional chart review. Setting University-affiliated hospital system. Patient(s) Women, ages 12–50, with the International Classification of Diseases code “Polycystic Ovary Syndrome” in 2017. Intervention(s) Application of the new 2018 guidelines for the diagnosis of PCOS. Main Outcome Measure(s) The primary outcome was the retention of PCOS diagnosis after applying the new 2018 guidelines. Secondary outcomes included the comparison of metabolic risk factors. Analysis was performed using chi-square tests for categorical variables and unpaired t tests for continuous variables, with a P value of <.05 determined to be significant. Result(s) Of 258 women with PCOS based on Rotterdam criteria, only 195 (76%) met the criteria based on the new 2018 guidelines. Those women who only met Rotterdam criteria (n = 63) had significantly lower body mass index (32.7 vs. 35.8), lower total cholesterol levels (151 vs. 176 mg/dL), lower triglyceride levels (96 vs. 124 mg/dL), lower total (33.2 vs. 52.3 ng/dL) and free testosterone levels (4.7 vs. 8.3), lower antimüllerian hormone levels (3.1 vs. 7.7 ng/mL), and were more likely to be multiparous (50% vs. 29%) than women who met 2018 criteria. Conclusion(s) Increasing the minimum antral follicle count to ≥20 antral follicles significantly decreases the number of women with the diagnosis of PCOS. Furthermore, the women that meet the new criteria have more health risks for metabolic syndrome than those who only meet the Rotterdam criteria.
| S-EPMC10310972 | biostudies-literature
Project description:ObjectiveTo determine age-based criteria for polycystic ovary morphology.DesignCross-sectional, case-control design.SettingOutpatient setting.Subject(s)Women with polycystic ovary syndrome (PCOS) defined by hyperandrogenism and irregular menses (n = 544) and controls with regular menses and no evidence of hyperandrogenism (n = 666) participated. Parameters were tested in a second cohort of women with PCOS (n = 105) and controls (n = 32) meeting the same criteria.Intervention(s)Subjects underwent a pelvic ultrasound documenting ovarian volume and maximum follicle number in a single plane.Main outcome measure(s)A receiver operating characteristic curve was constructed to determine the ovarian volume and follicle number with the best sensitivity and specificity to define PCOS for age groups at approximately 5-year intervals from age 18 to >44 years.Result(s)The best sensitivity and specificity were obtained using a threshold volume of 12 mL and 13 follicles for ages ≤24 years, 10 mL and 14 follicles for ages 25-29 years, 9 mL and 10 follicles for ages 30-34 years, 8 mL and 10 follicles for ages 35-39 years, 10 mL and 9 follicles for ages 40-44 years, and 6 mL and 7 follicles for ages >44 years. Data from a second cohort confirmed the need to decrease volume and follicle number with increasing age to diagnose PCOS. Polycystic ovary morphology was most accurate at predicting the PCOS diagnosis for women ages 30-39 years.Conclusion(s)The ovarian volume and follicle number threshold to define polycystic ovary morphology should be lowered starting at age 30.
| S-EPMC5657450 | biostudies-literature
Project description:BackgroundThe comorbidity between polycystic ovary syndrome (PCOS) and obesity has long been observed in clinical settings, but their shared genetic basis remains unclear.MethodsLeveraging summary statistics of large-scale GWAS(s) conducted in European-ancestry populations on body mass index (adult BMI, Nfemale=434,794; childhood BMI, N=39,620), waist-to-hip ratio (WHR, Nfemale=381,152), WHR adjusted for BMI (WHRadjBMI, Nfemale=379,501), and PCOS (Ncase=10,074, Ncontrol=103,164), we performed a large-scale genome-wide cross-trait analysis to quantify overall and local genetic correlation, to identify shared loci, and to infer causal relationship.ResultsWe found positive genetic correlations between PCOS and adult BMI (rg=0.47, P=2.19×10-16), childhood BMI (rg=0.31, P=6.72×10-5), and WHR (rg=0.32, P=1.34×10-10), all withstanding Bonferroni correction. A suggestive significant genetic correlation was found between PCOS and WHRadjBMI (rg=0.09, P=0.04). Partitioning the whole genome into 1703 nearly independent regions, we observed a significant local genetic correlation for adult BMI and PCOS at chromosome 18: 57630483-59020751. We identified 16 shared loci underlying PCOS and obesity-related traits via cross-trait meta-analysis including 9 loci shared between BMI and PCOS (adult BMI and PCOS: 5 loci; childhood BMI and PCOS: 4 loci), 6 loci shared between WHR and PCOS, and 5 loci shared between WHRadjBMI and PCOS. Mendelian randomization (MR) supported the causal roles of both adult BMI (OR=2.92, 95% CI=2.33-3.67) and childhood BMI (OR=2.76, 95% CI=2.09-3.66) in PCOS, but not WHR (OR=1.19, 95% CI=0.93-1.52) or WHRadjBMI (OR=1.03, 95% CI=0.87-1.22). Genetic predisposition to PCOS did not seem to influence the risk of obesity-related traits.ConclusionsOur cross-trait analysis suggests a shared genetic basis underlying obesity and PCOS and provides novel insights into the biological mechanisms underlying these complex traits. Our work informs public health intervention by confirming the important role of weight management in PCOS prevention.
| S-EPMC8832782 | biostudies-literature
Project description:Genome-wide association studies (GWAS) have identified several common variants associated with polycystic ovary syndrome (PCOS). However, the etiology behind PCOS remains incomplete. Available evidence suggests a potential genetic correlation between PCOS and type 2 diabetes (T2D). The publicly available data may provide an opportunity to enhance the understanding of the PCOS etiology. Here, we quantified the polygenic overlap between PCOS and T2D using summary statistics of PCOS and T2D and then identified the novel genetic variants associated with PCOS behind this phenotypic association. A bivariate causal mixture model (MiXeR model) found a moderate genetic overlap between PCOS and T2D (Dice coefficient = 44.1% and after adjusting for body mass index, 32.1%). The conditional/conjunctional false discovery rate method identified 11 potential risk variants of PCOS conditional on associations with T2D, 9 of which were novel and 6 of which were jointly associated with two phenotypes. The functional annotation of these genetic variants supports a significant role for genes involved in lipid metabolism, immune response, and the insulin signaling pathway. An expression quantitative trait locus functionality analysis successfully repeated that 5 loci were significantly associated with the expression of candidate genes in many tissues, including the whole blood, subcutaneous adipose, adrenal gland, and cerebellum. We found that SCN2A gene is co-localized with PCOS in subcutaneous adipose using GWAS-eQTL co-localization analyses. A total of 11 candidate genes were differentially expressed in multiple tissues of the PCOS samples. These findings provide a new understanding of the shared genetic architecture between PCOS and T2D and the underlying molecular genetic mechanism of PCOS.
| S-EPMC9464923 | biostudies-literature
Project description:ConceptOvaries meeting criteria for polycystic ovary morphology during peak reproductive years may no longer meet the criteria with age.ObjectiveOvarian volume and follicle number decrease with age in women with polycystic ovary syndrome (PCOS), permitting age-dependent criteria for PCOM.Design and settingWe conducted longitudinal (7-15 year interval) and cross-sectional studies to examine polycystic ovarian morphology over time at an outpatient clinic and pathology laboratory in a tertiary care hospital.PatientsSubjects included those with PCOS defined by the National Institutes of Health criteria (n = 11 and 483 for longitudinal and cross-sectional, respectively) and control women with regular menstrual cycles and no hyperandrogenism (n = 15 and 367), age 18-64 yr.InterventionsSubjects underwent an ovarian ultrasound by a single observer.Main outcome measuresOvarian volume and follicle number were measured and ultrasound findings confirmed by a pathologist in a subset (n = 9).ResultsOvarian volume (15.2 +/- 7.4 vs. 7.1 +/- 3.7 ml; P < 0.01) and follicle number (12.8 +/- 3.2 vs. 8.1 +/- 3.9; P < 0.05) decreased longitudinally in PCOS and control women (volume 11.6 +/- 4.4 vs. 5.4 +/- 2.2 ml and follicle number 8.3 +/- 1.9 vs. 6.3 +/- 1.8; both P < 0.005). Using cross-sectional data, log ovarian volume and follicle number decreased in both groups, but the decrease in log ovarian volume was less pronounced in women with PCOS than in controls (P < 0.01). A combination of age, log ovarian volume, follicle number, and testosterone distinguished PCOS subjects from controls with a receiver operator characteristic curve area of 0.90.ConclusionsOvarian volume and follicle number decrease with age in women with PCOS and controls necessitating age-based criteria to define polycystic ovarian morphology. It is possible to use these criteria to distinguish PCOS in women over age 40 yr.
| S-EPMC2795657 | biostudies-literature
Project description:Polycystic ovary syndrome (PCOS) is a common endocrine disorder in adolescent girls that has both reproductive and metabolic implications. Patients with PCOS typically present to their pediatrician for evaluation of menstrual irregularity and/or signs of hyperandrogenism, such as hirsutism and acne. The diagnosis of PCOS is made by clinical symptoms and laboratory evaluation. Because of the long-term health consequences that can accompany the disorder, pediatricians should consider PCOS in their initial evaluation of menstrual irregularity. Lifestyle modification is the cornerstone of treatment for girls with PCOS; however, hormonal medication such as oral contraceptive pills and insulin-sensitizing agents are useful and effective adjuncts to therapy. The goals of treatment for girls with PCOS are to improve clinical manifestations of the disorder, health-related quality of life, and long-term health outcomes.
| S-EPMC5659205 | biostudies-literature
Project description:A growing number of studies clearly demonstrate a substantial link between metabolic dysfunction and the risk of Alzheimer's disease (AD), especially glucose-related dysfunction; one hypothesis for this comorbidity is the presence of a common genetic etiology. We conducted a large-scale cross-trait GWAS to investigate the genetic overlap between AD and ten metabolic traits. Among all the metabolic traits, fasting glucose, fasting insulin and HDL were found to be genetically associated with AD. Local genetic covariance analysis found that 19q13 region had strong local genetic correlation between AD and T2D (P = 6.78 × 10- 22), LDL (P = 1.74 × 10- 253) and HDL (P = 7.94 × 10- 18). Cross-trait meta-analysis identified 4 loci that were associated with AD and fasting glucose, 3 loci that were associated with AD and fasting insulin, and 20 loci that were associated with AD and HDL (Pmeta < 1.6 × 10- 8, single trait P < 0.05). Functional analysis revealed that the shared genes are enriched in amyloid metabolic process, lipoprotein remodeling and other related biological pathways; also in pancreas, liver, blood and other tissues. Our work identifies common genetic architectures shared between AD and fasting glucose, fasting insulin and HDL, and sheds light on molecular mechanisms underlying the association between metabolic dysregulation and AD.
| S-EPMC7193309 | biostudies-literature
Project description:Background: Accumulating evidence has suggested that there is a positive association between asthma and cardiovascular diseases (CVDs), implying a common architecture between them. However, the shared genetic architecture and causality of asthma and CVDs remain unclear. Methods: Based on the genome-wide association study (GWAS) summary statistics of recently published studies, our study examined the genetic correlation, shared genetic variants, and causal relationship between asthma (N = 127,669) and CVDs (N = 86,995-521,612). Statistical methods included high-definition likelihood (HDL), cross-trait meta-analyses of large-scale GWAS, transcriptome-wide association studies (TWAS), and Mendelian randomization (MR). Results: First, we observed a significant genetic correlation between asthma and heart failure (HF) (Rg = 0.278, P = 5 × 10-4). Through cross-trait analyses, we identified a total of 145 shared loci between asthma and HF. Fifteen novel loci were not previously reported for association with either asthma or HF. Second, we mapped these 145 loci to a total of 99 genes whose expressions are enriched in a broad spectrum of tissues, including the seminal vesicle, tonsil, appendix, spleen, skin, lymph nodes, breast, cervix and uterus, skeletal muscle, small intestine, lung, prostate, cardiac muscle, and liver. TWAS analysis identified five significant genes shared between asthma and HF in tissues from the hemic and immune system, digestive system, integumentary system, and nervous system. GSDMA, GSDMB, and ORMDL3 are statistically independent genetic effects from all shared TWAS genes between asthma and HF. Third, through MR analysis, genetic liability to asthma was significantly associated with heart failure at the Bonferroni-corrected significance level. The odds ratio (OR) is 1.07 [95% confidence interval (CI): 1.03-1.12; p = 1.31 × 10-3] per one-unit increase in loge odds of asthma. Conclusion: These findings provide strong evidence of genetic correlations and causal relationship between asthma and HF, suggesting a shared genetic architecture for these two diseases.
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Project description:Facioscapulohumeral muscular dystrophy (FSHD) is a common hereditary myopathy causally linked to reduced numbers (?8) of 3.3 kilobase D4Z4 tandem repeats at 4q35. However, because individuals carrying D4Z4-reduced alleles and no FSHD and patients with FSHD and no short allele have been observed, additional markers have been proposed to support an FSHD molecular diagnosis. In particular a reduction in the number of D4Z4 elements combined with the 4A(159/161/168)PAS haplotype (which provides the possibility of expressing DUX4) is currently used as the genetic signature uniquely associated with FSHD. Here, we analyzed these DNA elements in more than 800 Italian and Brazilian samples of normal individuals unrelated to any FSHD patients. We find that 3% of healthy subjects carry alleles with a reduced number (4-8) of D4Z4 repeats on chromosome 4q and that one-third of these alleles, 1.3%, occur in combination with the 4A161PAS haplotype. We also systematically characterized the 4q35 haplotype in 253 unrelated FSHD patients. We find that only 127 of them (50.1%) carry alleles with 1-8 D4Z4 repeats associated with 4A161PAS, whereas the remaining FSHD probands carry different haplotypes or alleles with a greater number of D4Z4 repeats. The present study shows that the current genetic signature of FSHD is a common polymorphism and that only half of FSHD probands carry this molecular signature. Our results suggest that the genetic basis of FSHD, which is remarkably heterogeneous, should be revisited, because this has important implications for genetic counseling and prenatal diagnosis of at-risk families.
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