Bidirectional Mendelian randomization to explore the causal relationships between body mass index and polycystic ovary syndrome

STUDY QUESTION: What are the causal relationships between polycystic ovary syndrome (PCOS) and body mass index (BMI)? SUMMARY ANSWER: Bidirectional Mendelian randomization analyses suggest that increased BMI is causal for PCOS while the reverse is not the case. WHAT IS KNOWN ALREADY: The contribution of obesity to the pathogenesis of PCOS is controversial. To date, published genetic studies addressing this question have generated conflicting results and have not utilized the full extent of known single nucleotide polymorphisms associated with body mass index (BMI). STUDY DESIGN, SIZE, DURATION: This cross-sectional Mendelian randomization (MR) and genetic association study was conducted in 750 individuals of European origin and with PCOS and 1567 BMI-matched controls. PARTICIPANTS/MATERIALS, SETTING, METHODS: Cases and controls were matched for BMI as well as for distribution of weight categories (normal weight, overweight, obese). Two-sample MR using inverse variance weighting (IVW) was conducted using a 92-SNP instrument variable for BMI with PCOS as the outcome, followed by two-sample MR with a 16-SNP instrument variable for PCOS with BMI as the outcome. Sensitivity analyses included MR-Egger and maximum likelihood methods. Secondary analyses assessed associations of genetic risk scores and individual SNPs with PCOS, BMI and quantitative androgen-related and glucose homeostasis-related traits. MAIN RESULTS AND THE ROLE OF CHANCE: Each standard deviation genetically higher BMI was associated with a 4.89 (95% CI 1.46-16.32) higher odds of PCOS. Conversely, genetic risk of PCOS did not influence BMI. Sensitivity analyses yielded directionally consistent results. The genetic risk score of 92 BMI SNPs was associated with the diagnosis of PCOS (OR 1.043, 95% CI 1.009-1.078, P = 0.012). Of the 92 BMI risk variants evaluated, none were associated individually with PCOS after considering multiple testing. The association of FTO SNP rs1421085 with BMI was stronger in women with PCOS (beta = 0.071, P = 0.0006) than in controls (beta = 0.046, P = 0.065). LIMITATIONS, REASONS FOR CAUTION: The current sample size, while providing good power for MR and genetic risk score analyses, had limited power to demonstrate association of individual SNPs with PCOS. Cases and controls were not matched for age; however, this was mitigated by adjusting analyses for age. Dietary and lifestyle data, which could have been used to explore the greater association of the FTO SNP with BMI in women with PCOS, was not available. WIDER IMPLICATIONS OF THE FINDINGS: Increasing BMI appears to be causal for PCOS but having PCOS does not appear to affect BMI. This study used the most comprehensive set of SNPs for BMI currently available. Prior studies using fewer SNPs had yielded conflicting results and may have been confounded because cases and controls were not matched for weight categories. The current results highlight the potential utility of weight management in the prevention and treatment of PCOS.