Background: Polycystic ovary syndrome (PCOS) and Alzheimer’s disease (AD) are two prevalent and complex conditions characterized by overlapping features such as metabolic dysfunction, hormonal imbalance, and chronic inflammation. These commonalities raise the possibility of a shared causal pathway. However, observational studies often face limitations due to confounding factors, complicating causal inference. Objectives: The present study aimed to explore the causal link between PCOS and AD through Mendelian randomization (MR) analysis. Methods: We conducted a two-sample MR analysis using summary-level data from two large genome-wide association studies (GWAS). For the exposure, genetic variants strongly associated with PCOS were obtained from a GWAS meta-analysis involving 10,074 cases and 103,164 controls of European ancestry. For the outcome, AD data were sourced from a separate GWAS comprising 1,036,225 cases and 90,338 controls, also of European descent. Multiple MR approaches were employed, with inverse variance weighted (IVW) as the primary method, supported by MR-Egger, weighted median, and weighted mode methods. Sensitivity analyses were performed to assess the robustness of the findings. Results: The two-sample MR analysis did not provide evidence for a significant causal effect of genetically predicted PCOS on AD risk. The initial IVW analysis using all instrumental variables (IVs) yielded an odds ratio (OR) of 0.967 [95% confidence interval (CI): 0.905 - 1.03; P = 0.311]. After removing outlier single nucleotide polymorphisms (SNPs) based on sensitivity analyses, the refined IVW model showed an OR of 0.93 (95% CI: 0.866 - 1.002; P = 0.057), indicating no statistically significant association. The results were consistent across various MR methods, and sensitivity tests confirmed the robustness of the findings. Conclusions: This MR study found no evidence of a significant causal relationship between genetically predicted PCOS and AD. These findings suggest that genetic predisposition to PCOS does not increase the risk of AD, indicating that previously observed associations in epidemiological studies may not reflect a causal link. Further studies are needed to explore alternative explanations beyond genetic causality.

Background: Alterations in levels of 25-Hydroxyvitamin D have been associated with the risk of thyroid disease. This study uses Mendelian randomization (MR) to infer the possible causal association of 25-Hydroxyvitamin D with hypothyroidism. Methods: We performed two-sample MR using the summary statistics data from genome-wide association studies (GWAS) from populations with European ancestry to infer the causality of genetically controlled levels of 25-Hydroxyvitamin D on the risk of hypothyroidism, Hashimoto’s thyroiditis, as well as biochemical parameters of thyroid diseases. The inverse-variance method (IVW) was used as the primary method to calculate the combined effect of all SNPs. Other methods were adopted to evaluate the stability and reliability of the results. Comprehensive sensitivity analyses were conducted to ensure that none of the MR analysis’s primary assumptions were violated. Results: The results of the IVW analysis revealed a significant causal association between higher levels of 25-Hydroxyvitamin D and lower risk of hypothyroidism (beta = −0.197, 95% CI (− 0.301, −0.093); SE = 0.053, P _beta = 2.256×10 ^-4 ) as well as increased levels of free T4 (beta = 0.204, 95% CI (0.305, 0.094); SE = 0.056, P _beta = 3.0506×10 ⁻⁴ ). On the other hand, no significant causality was determined for higher levels of 25-Hydroxyvitamin D in association with Hashimoto’s thyroiditis (beta=-0.047, 95% CI (−0.245, 0.151), p=0.641) and TSH levels (beta = −0.024, 95% CI (−0.099, - 0.051); P _beta = 0.524). Conclusion: The results of this two-sample MR study provide evidence supporting the potential of 25-Hydroxyvitamin D supplementation in reducing the risk of hypothyroidism.