Thyroid function and polycystic ovary syndrome: a Mendelian randomization study
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PROVIDER: S-EPMC10995335 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:Polycystic ovary syndrome (PCOS) is defined as a chronic low-grade inflammatory reproductive endocrine disorder. PCOS can induce various metabolic disorders, which are associated with a state of mild and slow-acting inflammation. Nevertheless, the causal relationship between polycystic ovary syndrome and inflammatory factors is uncertain. The causality between inflammatory cytokines and PCOS was analyzed by bidirectional Mendelian randomization (MR) in this current probe. We performed an interactive MR study to assess the causal relationships between 91 inflammatory cytokines and PCOS using Genome Wide Association Study (GWAS) data. We underwent dual-sample MR analysis with inverse variance weights (IVW) as the predominant MR methodology with multiple validity and heterogeneity analyses. MR-Egger, weighted median, simple mode, weighted mode and MR-PRESSO were analyzed as multiple likelihood sensitivity analyses to enhance the final results.The results came out interleukin-1-alpha (IL-1 A) levels (odds ratio [OR] = 1.051, 95% fiducial interval [95% CI] = 1.009-1.095, P = 0.02) and oncostatin-M (OSM) levels ( [OR] = 1.041, [95% CI] = 1.001-1.082, P = 0.04) were positively associated with the development of PCOS. Moreover, interleukin-7 (IL-7) levels ([OR] = 0.935, [95% CI] = 0.884-0.989, P = 0.02); interleukin-15 receptor subunit alpha (IL15RA) levels ([OR] = 0.959, [95% CI] = 0.929-0.99, P = 0.01); and C-X-C motif chemokine 11 (CXCL11) levels ([OR] = 0.959, [95% CI] = 0.922-0.996. P = 0.03) were strongly negatively associated with PCOS. However, we did not find any strong positive results in the reverse analysis, suggesting that although inflammatory factors contribute to the pathogenesis of PCOS, PCOS itself does not trigger inflammatory factor production.Our study provides genetic evidence for the connection between systemic inflammatory regulators and PCOS. Treatments targeting specific inflammatory factors may help to mitigate the risk of PCOS. The levels of five of the 91 inflammatory factors included in this study, namely, IL1A and OSM, were associated with PCOS. IL1A and OSM contribute to the progression of PCOS while IL-7, IL15RA, and CXCL11 levels are negatively correlated with the development of PCOS.
| S-EPMC11539607 | biostudies-literature
Project description:BackgroundAccumulating observational studies have indicated that vitamin D deficiency (serum 25-hydroxyvitamin D (25OHD) < 50 nmol/L) is common in women with polycystic ovary syndrome (PCOS). However, the direction and causal nature remain unclear. In this study, we aimed to investigate the causal association between PCOS and 25OHD.MethodsA bidirectional two-sample Mendelian randomization (MR) study was used to evaluate the causal association between PCOS and 25OHD. From the publicly available European-lineage genome-wide association studies (GWAS) summary statistics for PCOS (4,890 cases of PCOS and 20,405 controls) and 25OHD (n = 417,580), we selected 11 and 102 single nucleotide polymorphisms (SNPs) as instrumental variables (IVs), respectively. In univariate MR (uvMR) analysis, inverse-variance weighted (IVW) method was employed in the primary MR analysis and multiple sensitivity analyses were implemented. Additionally, a multivariable MR (mvMR) design was carried to adjust for obesity and insulin resistance (IR) as well.ResultsUvMR demonstrated that genetically determined PCOS was negatively associated with 25OHD level (IVW Beta: -0.02, P = 0.008). However, mvMR found the causal effect disappeared when adjusting the influence of obesity and IR. Both uvMR and mvMR analysis didn't support the causal effect of 25OHD deficiency on risk of PCOS (IVW OR: 0.86, 95% CI: 0.66 ~ 1.12, P = 0.280).ConclusionOur findings highlighted that the casual effect of PCOS on 25OHD deficiency might be mediated by obesity and IR, and failed to find substantial causal effect of 25OHD deficiency on risk of PCOS. Further observational studies and clinical trials are necessary.
| S-EPMC10034407 | biostudies-literature
Project description:ObjectivePolycystic ovary syndrome is one of the most common endocrine disorders among women of childbearing age. The relationship between polycystic ovary syndrome and chronic kidney disease remains unclear and controversial. In this study, we investigated the causal role of polycystic ovary syndrome in the development of chronic kidney disease using the two-sample Mendelian randomization method.MethodsPublic shared summary-level data was acquired from European-ancestry genome wide association studies. We finally obtained 12 single nucleotide polymorphisms as instrumental variables, which were associated with polycystic ovary syndrome in European at genome-wide significance (P < 5 × 10-8). Inverse-variance weighted method was employed in the Mendelian randomization analysis and multiple sensitivity analyses were implemented. Outcome data were obtained from the Open GWAS database.ResultsA positive causal association was observed between polycystic ovary syndrome and chronic kidney disease (odds ratio [OR]=1.180, 95% confidence interval [CI]: 1.038-1.342; P=0.010). Further analyses clarified that causal relationship exist between polycystic ovary syndrome and some serological indicators of chronic kidney disease (fibroblast growth factor 23: OR= 1.205, 95% CI: 1.031-1.409, P=0.019; creatinine: OR= 1.012, 95% CI: 1.001-1.023, P=0.035; cystatin C: OR= 1.024, 95% CI: 1.006-1.042, P=0.009). However, there was no causal association of polycystic ovary syndrome with other factors in the data sources we employed.ConclusionsOur results indicate an important role of polycystic ovary syndrome in the development of chronic kidney disease. This study suggests that regular follow-up of renal function in patients with polycystic ovary syndrome is necessary for the early treatment of chronic kidney disease.
| S-EPMC10050750 | biostudies-literature
Project description:BackgroundPolycystic ovary syndrome (PCOS) is a complex endocrine disorder with an estimated prevalence of 4-21% in reproductive aged women. Recently, the Ovarian Cancer Association Consortium (OCAC) reported a decreased risk of invasive ovarian cancer among women with self-reported PCOS. However, given the limitations of self-reported PCOS, the validity of these observed associations remains uncertain. Therefore, we sought to use Mendelian randomization with genetic markers as a proxy for PCOS, to examine the association between PCOS and ovarian cancer.MethodsUtilizing 14 single nucleotide polymorphisms (SNPs) previously associated with PCOS we assessed the association between genetically predicted PCOS and ovarian cancer risk, overall and by histotype, using summary statistics from a previously conducted genome-wide association study (GWAS) of ovarian cancer among European ancestry women within the OCAC (22 406 with invasive disease, 3103 with borderline disease and 40 941 controls).ResultsAn inverse association was observed between genetically predicted PCOS and invasive ovarian cancer risk: odds ratio (OR)=0.92 [95% confidence interval (CI)=0.85-0.99; P = 0.03]. When results were examined by histotype, the strongest inverse association was observed between genetically predicted PCOS and endometrioid tumors (OR = 0.77; 95% CI = 0.65-0.92; P = 0.003). Adjustment for individual-level body mass index, oral contraceptive use and parity did not materially change the associations.ConclusionOur study provides evidence for a relationship between PCOS and reduced ovarian cancer risk, overall and among specific histotypes of invasive ovarian cancer. These results lend support to our previous observational study results. Future studies are needed to understand mechanisms underlying this association.
| S-EPMC6659359 | biostudies-literature
Project description:Polycystic ovary syndrome (PCOS) is a common endocrine disorder with unclear etiology. Some genes may be pleiotropically or potentially causally associated with PCOS. In the present study, the summary data-based Mendelian randomization (SMR) method integrating genome-wide association study (GWAS) for PCOS and expression quantitative trait loci (eQTL) data was applied to identify genes that were pleiotropically associated with PCOS. Separate SMR analysis was performed using eQTL data in the ovary and whole blood. Although no genes showed significant pleiotropic association with PCOS after correction for multiple testing, some of the genes exhibited suggestive significance. RPS26 showed the strongest suggestive pleiotropic association with PCOS in both SMR analyses (β[SE]=0.10[0.03], PSMR=1.72×10-4 for ovary; β[SE]=0.11[0.03], PSMR=1.40×10-4 for whole blood). PM20D1 showed the second strongest suggestive pleiotropic association with PCOS in the SMR analysis using eQTL data for the whole blood and was also among the top ten hit genes in the SMR analysis using eQTL data for the ovary. Two other genes, including CTC-457L16.2 and NEIL2, were among the top ten hit genes in both SMR analyses. In conclusion, this study revealed multiple genes that were potentially involved in the pathogenesis of PCOS.
| S-EPMC8547723 | biostudies-literature
Project description:BackgroundPolycystic ovary syndrome (PCOS) is a multifaceted endocrine and metabolic syndrome with complex origins and pathogenesis that has not yet been fully elucidated. Recently, the interconnection between gut microbiota and metabolic diseases has gained prominence in research, generating new insights into the correlation between PCOS and gut microbiota composition. However, the causal link between PCOS and gut microbiota remains relatively unexplored, indicating a crucial gap in current research.MethodsWe conducted a two-sample Mendelian randomization analysis using summary statistics obtained from the MiBioGen Consortium's extensive genome-wide association studies (GWAS) meta-analysis, focusing on the gut microbiota. Summary statistics for PCOS were acquired from the FinnGen Consortium R7 release data. Various statistical approaches, including inverse variance weighted, MR-Egger, maximum likelihood, weighted model, and weighted median, have been employed to investigate the causal association between the gut microbiota and PCOS. Additionally, we performed a reverse causal analysis. Cochran's Q statistic was used to assess the heterogeneity of the instrumental variables. Regarding the relationships between PCOS and specific genera within the gut microbiota, a significance level of P < 0.05 was observed, but only when q ≥ 0.1.ResultsOur analysis revealed that specific microbial genera, namely Bilophila (P = 4.62 × 10-3), Blautia (P = 0.02), and Holdemania (P = 0.04), displayed a protective effect against PCOS. Conversely, the presence of the Lachnospiraceae family of bacteria was associated with a detrimental effect on PCOS (P = 0.04). Furthermore, reverse Mendelian randomization analysis confirmed the significant influence of Lachnospiraceae on PCOS. No significant variations in instrumental variables or evidence of horizontal pleiotropy were observed.ConclusionsThe results revealed a definitive causal link between PCOS and the presence of Bilophila, Blautia, Holdemania, and Lachnospiraceae in the gut microbiota. This discovery could provide pivotal insights, leading to novel preventive and therapeutic approaches for PCOS.
| S-EPMC10730437 | biostudies-literature
Project description:BackgroundPolycystic ovary syndrome (PCOS) is defined by oligo/anovulation, hyperandrogenism, and polycystic ovaries with uncertain pathogenesis. The proteome represents a substantial source of therapeutic targets, and their coding genes may elucidate the mechanisms underlying PCOS. However, reports on the profiles of the human plasma protein-coding genes and PCOS are limited. Here, we aimed to investigate novel biomarkers or drug targets for PCOS by integrating genetics and the human plasma proteome.MethodsOur study acquired the protein quantitative trait loci from DECODE Genetics, offering 4,907 proteins in 35,559 individuals while obtaining PCOS summary statistics by accessing the FinnGen biobank (1,639 cases and 218,970 controls) and the genome-wide association study catalog (797 cases and 140,558 controls). Herein, we sequentially used two-sample Mendelian randomization (MR) analyses and colocalization to verify the causal link between candidate proteins, their coding genes, and PCOS. Further PCOS data download was conducted by accessing the Gene Expression Omnibus and Zenodo platforms. Gene expression level analysis, pathway enrichment analysis, immune cell infiltration, and transcription factor prediction were performed, aiming at detecting specific cell types with enriched expression and exploring potential optimized treatments for PCOS.ResultsMR analysis revealed 243 protein-coding genes with a causal relationship to PCOS risk, of which 12 were prioritized with the most significant evidence. Through colocalization analysis, three key genes, CUB domain-containing protein 1 (CDCP1), glutaredoxin 2 (GLRX2), and kirre-like nephrin family adhesion molecule 2 (KIRREL2), were identified. Subsequently, the three genes were strongly related to immune function and metabolism in terms of biological significance. In single-cell analysis, the expression levels of genes in ovarian theca cells were explored.ConclusionOverall, three protein-coding genes (CDCP1, GLRX2, and KIRREL2) may be related to a higher PCOS risk, suggesting that they may be entry points for exploration of PCOS pathogenesis and treatment, warranting further clinical investigations.
| S-EPMC11417002 | biostudies-literature
Project description:BackgroundThe contribution of gut microbiota to the pathogenesis of polycystic ovary syndrome (PCOS) is controversial. The causal relationship to this question is worth an in-depth comprehensive of known single nucleotide polymorphisms associated with gut microbiota.MethodsWe conducted bidirectional Mendelian randomization (MR) utilizing instrumental variables associated with gut microbiota (N = 18,340) from MiBioGen GWAS to assess their impact on PCOS risk in the FinnGen GWAS (27,943 PCOS cases and 162,936 controls). Two-sample MR using inverse variance weighting (IVW) was undertaken, followed by the weighted median, weighted mode, and MR-Egger regression. In a subsample, we replicated our findings using the meta-analysis PCOS consortium (10,074 cases and 103,164 controls) from European ancestry.ResultsIVWMR results suggested that six gut microbiota were causally associated with PCOS features. After adjusting BMI, SHBG, fasting insulin, testosterone, and alcohol intake frequency, the effect sizes were significantly reduced. Reverse MR analysis revealed that the effects of PCOS features on 13 gut microbiota no longer remained significant after sensitivity analysis and Bonferroni corrections. MR replication analysis was consistent and the results suggest that gut microbiota was likely not an independent cause of PCOS.ConclusionOur findings did not support the causal relationships between the gut microbiota and PCOS features at the genetic level. More comprehensive genome-wide association studies of the gut microbiota and PCOS are warranted to confirm their genetic relationship.DeclarationThis study contains 3533 words, 0 tables, and six figures in the text as well as night supplementary files and 0 supplementary figures in the Supplementary material.
| S-EPMC10838976 | biostudies-literature
Project description: Not available
| S-EPMC11239387 | biostudies-literature
Project description:Associations between lower birth weight and higher polycystic ovary syndrome (PCOS) risk have been reported in previous observational studies, however, the causal relationship is still unknown. Based on decomposed fetal and maternal genetic effects on birth weight (n = 406,063), we conducted a two-sample Mendelian randomization (MR) analysis to assess potential causal relationships between fetal genome predicted birth weight and PCOS risk using a large-scale genome-wide association study (GWAS) including 4,138 PCOS cases and 20,129 controls. To further eliminate the maternally transmitted or non-transmitted effects on fetal growth, we performed a secondary MR analysis by utilizing genetic instruments after excluding maternally transmitted or non-transmitted variants, which were identified in another birth weight GWAS (n = 63,365 parent-offspring trios from Icelandic birth register). Linkage disequilibrium score regression (LDSR) analysis was conducted to estimate the genetic correlation. We found little evidence to support a causal effect of fetal genome determined birth weight on the risk of developing PCOS (primary MR analysis, OR: 0.86, 95% CI: 0.52 to 1.43; secondary MR analysis, OR: 0.86, 95% CI: 0.54 to 1.39). In addition, a marginally significant genetic correlation (rg = -0.14, se = 0.07) between birth weight and PCOS was revealed via LDSR analysis. Our findings indicated that observed associations between birth weight and future PCOS risk are more likely to be attributable to genetic pleiotropy driven by the fetal genome rather than a causal mechanism.
| S-EPMC10282929 | biostudies-literature