Body Mass Index and Polycystic Ovary Syndrome: A 2-Sample Bidirectional Mendelian Randomization Study

• Published in: The journal of clinical endocrinology and metabolism 2020-06, Vol.105 (6), p.1778-1784
• Main Authors: Zhao, Yalin, Xu, Yuping, Wang, Xiaomeng, Xu, Lin, Chen, Jianhua, Gao, Chengwen, Wu, Chuanhong, Pan, Dun, Zhang, Qian, Zhou, Juan, Chen, Ruirui, Wang, Zhuo, Zhao, Han, You, Li, Cao, Yunxia, Li, Zhiqiang, Shi, Yongyong
• Format: Article
• Language: English
• Subjects: Biomarkers - analysis; Body Mass Index; Care and treatment; Development and progression; Female; Genetic aspects; Genome-Wide Association Study; Genomes; Health aspects; Humans; Mendelian Randomization Analysis - statistics & numerical data; Polycystic ovary syndrome; Polycystic Ovary Syndrome - genetics; Polycystic Ovary Syndrome - pathology; Polymorphism, Single Nucleotide; Prognosis; Sensitivity analysis; Single nucleotide polymorphisms; Single-nucleotide polymorphism; Statistical analysis; Stein-Leventhal syndrome
• ISSN: 0021-972X; 1945-7197
• DOI: 10.1210/clinem/dgaa125

Observational studies have shown a link between elevated body mass index (BMI) and the risk of polycystic ovary syndrome (PCOS). While Mendelian randomization (MR) studies in Europeans have suggested a causal role of increased BMI in PCOS, whether the same role is suggested in Asians has yet to be investigated. We used MR studies to infer causal effects using genetic data from East Asian populations. We performed a 2-sample bidirectional MR analysis using summary statistics from genome-wide association studies (GWAS) of BMI (with up to 173 430 individuals) and PCOS (4386 cases and 8017 controls) in East Asian populations. Seventy-eight single nucleotide polymorphisms (SNPs) correlated with BMI were selected as genetic instrumental variables to estimate the causal effect of BMI on PCOS using the inverse-variance weighted (IVW) method. To test the reliability of the results, further sensitivity analyses included MR-Egger regression, weighted median estimates, and leave-one-out analysis. The IVW analysis indicated a significant association between high BMI and the risk of PCOS (odds ratio per standard deviation higher BMI, 2.208; 95% confidence interval 1.537 to 3.168, P = 1.77 × 10-5). In contrast, the genetic risk of PCOS had no significant effect on BMI. The results of our bidirectional MR study showed that an increase in BMI causes PCOS, while PCOS does not cause an increased BMI. This study provides further genetic support for a link between BMI and PCOS. Further research is needed to interpret the potential mechanisms of this association.