Investigating the causal impact of polycystic ovary syndrome on gestational diabetes mellitus: a two-sample Mendelian randomization study.

Introduction: Determining the causal relationship between polycystic ovary syndrome (PCOS) and gestational diabetes mellitus (GDM) holds significant implications for GDM prevention and treatment. Despite numerous observational studies suggesting an association between PCOS and GDM, it remains unclear whether a definitive causal relationship exists between these two conditions and which specific features of PCOS contribute to increased incidence of GDM. Methods: The causal relationship between polycystic ovary syndrome (PCOS), its characteristic indices, and gestational diabetes mellitus (GDM) was investigated using a two-sample Mendelian randomization study based on publicly available statistics from genome-wide association studies (GWAS). The inverse-variance weighted method was employed as the primary analytical approach to examine the association between PCOS, its characteristic indices, and GDM. MR Egger intercept was used to assess pleiotropy, while Q values and their corresponding P values were utilized to evaluate heterogeneity. It is important to note that this study adopts a two-sample MR design where PCOS and its characteristic indices are considered as exposures, while GDM is treated as an outcome. Results: The study results indicate that there is no causal relationship between PCOS and GDM (all methods P > 0.05, 95% CI of OR values passed 1). The IVW OR value was 1.007 with a 95% CI of 0.906 to 1.119 and a P value of 0.904. Moreover, the MR Egger Q value was 8.141 with a P value of 0.701, while the IVW Q value was also 8.141 with a P value of 0.774, indicating no significant heterogeneity. Additionally, the MR Egger intercept was 0.0004, which was close to zero with a P value of 0.988, suggesting no pleiotropy. However, the study did find a causal relationship between several other factors such as testosterone, high-density lipoprotein, sex hormone-binding globulin, body mass index, waist-hip ratio, apolipoprotein A-I, number of children, diabetes illnesses of mother, father and siblings, hemoglobin A1c, fasting insulin, fasting blood glucose, years of schooling, and GDM based on the IVW method. Conclusion: We observed no association between genetically predicted PCOS and the risk of GDM, implying that PCOS itself does not confer an increased susceptibility to GDM. The presence of other PCOS-related factors such as testosterone, high-density lipoprotein, and sex hormone-binding globulin may elucidate the link between PCOS and GDM. Based on these findings, efforts aimed at preventing GDM in individuals with PCOS should prioritize those exhibiting high-risk features rather than encompassing all women with PCOS.

Progress of the application clinical prediction model in polycystic ovary syndrome.

Clinical prediction models play an important role in the field of medicine. These can help predict the probability of an individual suffering from disease, complications, and treatment outcomes by applying specific methodologies. Polycystic ovary syndrome (PCOS) is a common disease with a high incidence rate, huge heterogeneity, short- and long-term complications, and complex treatments. In this systematic review study, we reviewed the progress of clinical prediction models in PCOS patients, including diagnosis and prediction models for PCOS complications and treatment outcomes. We aimed to provide ideas for medical researchers and clues for the management of PCOS. In the future, models with poor accuracy can be greatly improved by adding well-known parameters and validations, which will further expand our understanding of PCOS in terms of precision medicine. By developing a series of predictive models, we can make the definition of PCOS more accurate, which can improve the diagnosis of PCOS and reduce the likelihood of false positives and false negatives. It will also help discover complications earlier and treatment outcomes being known earlier, which can result in better outcomes for women with PCOS.

Evidence for causal effects of polycystic ovary syndrome on oxidative stress: a two-sample mendelian randomisation study.

BACKGROUND: Polycystic ovary syndrome (PCOS) is often accompanied by increased oxidative stress levels; however, it is still unclear whether PCOS itself is causally related to oxidative stress (OS), whether OS can increase the occurrence of PCOS, and which characteristics of PCOS increase OS levels. Therefore, this study explored the causal relationship between PCOS, its characteristics, and OS. METHODS: Two-sample bidirectional and two-sample Mendelian randomisation studies were performed based on publicly available statistics from genome-wide association studies. PCOS; its characteristics, such as testosterone, low-density lipoprotein, high-density lipoprotein; and 11 major OS markers (superoxide dismutase, glutathione S-transferase, glutathione peroxidase, catalase, uric acid, zinc, tocopherol, ascorbic acid, retinol, albumin, and total bilirubin), were studied. The main analytical method used was inverse variance weighting (IVW). Pleiotropy was evaluated using the Mendelian randomisation-Egger intercept. Q and P values were used to assess heterogeneity. RESULTS: There was no causal relationship between PCOS and the OS indices (all P > 0.05). There was a causal relationship between the OS index, ascorbate level, and PCOS (IVW, odds ratio: 2.112, 95% confidence interval: 1.257-3.549, P = 0.005). In addition, there was a causal relationship between testosterone, low-density lipoprotein, high-density lipoprotein, sex hormone-binding globulin, body mass index, triacylglycerol, age at menarche, and most OS indices according to the IVW method. The F statistics showed that there was no weak instrumental variable. A sensitivity analysis was performed using the leave-one-out method. No pleiotropy was observed. The results were robust, and the conclusions were reliable. CONCLUSIONS: This study showed for the first time that there was no causal relationship between PCOS and OS. However, there was a causal relationship between the OS index, ascorbate level, and PCOS. It revealed that PCOS itself could not increase OS, and the increase in OS in PCOS was related to other potential factors, such as testosterone, low-density lipoprotein, high-density lipoprotein, sex hormone-binding globulin, body mass index, triacylglycerol, and age at menarche.

Sperm DNA fragmentation index with unexplained recurrent spontaneous abortion: A systematic review and meta-analysis.

BACKGROUND: A high sperm DNA fragmentation index (DFI) influences human reproduction and is observed in infertile men. However, the influence of DFI on unexplained recurrent spontaneous abortion (RSA) remains controversial. OBJECTIVE: We explored the influence of DFI on unexplained recurrent spontaneous abortion. DATA SOURCES: We conducted a meta-analysis of DFI (assessed by sperm chromatin structure assay(SCSA), terminal deoxynucleotidyl transferase-mediated deoxyuridine (TdT)triphosphate (dUTP) nick end labeling assay(TUNEL), sperm chromatin dispersion(SCD), single cell gel electrophoresis assay(COMET assay), and acridine orange test(AOT) with unexplained RSA from the Cochrane Library, EMBASE, Pubmed and Web of Science database. METHODS: Records were screened for eligible studies and data were extracted to an online data extraction form. The main outcome was the sperm DFI. Summary measures were reported as the mean difference(MD) and Odds Ratio(OR) with 95 % confifidence interval (CI). RESULT: We identified 27 articles including 3, 2, 9, 9, and 8 studies using AO, COMET, SCSA, SCD and TUNEL respectively; 7 articles used qualitative methods and 21 articles used in quantitative methods. The combined MD estimates of 7 SCSA studies (MD=5.4; 95 % CI: 1.76-9.03; P<0.01), 9 SCD studies (MD=11.16; 95 % CI:6.70-15.62; P<0.01), and 8 TUNEL studies (MD=12.12; 95 % CI: 3.34-20.91; P<0.01) showed significant differences. Notably, qualitative studies showed consistent results with quantitative studies. CONCLUSION(S): These findings support an association between sperm DFI and recurrent pregnancy loss. Previous studies revealed that DFI negatively impacts unexplained RSA.

Shortened postpartum magnesium sulfate treatment vs traditional 24h for severe preeclampsia: a systematic review and meta-analysis of randomized trials.

Objectives: This meta-analysis aimed to compare the benefits and risks of shortened magnesium sulfate with traditional 24 h for severe postpartum preeclampsia.Methods: We systematically searched the Cochrane, Embase, Web of science and Pubmed database from inception till May 15 2019. Studies included type is limited to randomized controlled trial (RCT). Pooled risks difference (RDs), odds risks (ORs), mean difference (MD), standard mean difference (SMD) and 95% confifidence intervals (CIs) were used to summarize the effect sizes.Results: Totally studies included are 7 randomized controlled trials (RCTs). Shortened magnesium sulfate treatment has the same risk as eclampsia (RD 0.00, 95%CI-0.01-0.01) and total complications (OR 0.78, 95% CI 0.53-1.15), however, significant difference was observed in both groups pertaining to flushing (OR 0.40, 95% CI 0.20-0.82), and the need for prolonged treatment (RD 0.05, 95% CI 0.01 - 0.1), Others factors,namely the benefits of shortened magnesium sulfate treatment,showed differences in both groups.Conclusions: Shortened postpartum magnesium sulfate treatment was as effective as traditional 24 h magnesium sulfate in seizure prevention and total complications. But flushing and needed for prolonged treatment in the shortened groups warrants further research.