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Updated: Jan 7, 2026

Evaluation of Hepatic Glucose Production in a Polycystic Ovary Syndrome Mouse Model
Published on: March 5, 2022
Association between childhood obesity and polycystic ovary syndrome: a two-sample Mendelian randomization study
Shiyang Wei1, Yafeng Wang2, Niping Liu1
1Department of Gynecology, People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical Sciences, 6# Taoyuan Road, Nanning, Guangxi, China.
Purpose:
The causal relationship between childhood obesity and polycystic ovary syndrome (PCOS) risk remains unclear, despite established links between adult obesity and PCOS. This study employed a two-sample Mendelian randomization approach to examine whether childhood obesity might have a causal effect on PCOS development.
Methods:
A genome-wide association study (GWAS) identifies SNPs associated with childhood obesity based on 13848 individuals of European ancestry. Data at the summary level for PCOS were obtained from a GWAS conducted by the FinnGen consortium, which included a large sample size of 118870 individuals, consisting of 642 cases and 118228 controls. MR methods including inverse variance weighted (IVW), MR-Egger, weighted median, simple mode, and weighted mode analysis were performed in this study. Sensitivity analyses were conducted to evaluate the precision and robustness of the findings.
Results:
The impact of genetically determined childhood obesity on PCOS is substantial, as evidenced by the IVW analysis (OR = 1.507, 95% CI 1.193-1.903; P = 5.77 × 10-4) and the weighted median analysis (OR = 1.578, 95% CI 1.183-2.104; P = 1.91 × 10-3). The main findings were supported by sensitivity analyses, which yielded consistent estimates using the IVW and MR-Egger methods.
Conclusions:
It is suggested that an elevated prevalence of childhood obesity could be associated with an increased risk of PCOS. The prevention of PCOS should be promoted in childhood populations with high obesity. Additional investigation is necessary to confirm these discoveries and explore the underlying biological processes.
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