Genetically Predicted Cigarette Smoking in Relation to Risk of Polycystic Ovary Syndrome

Clin Epidemiol. 2021 Jul 2:13:527-532. doi: 10.2147/CLEP.S311785. eCollection 2021.

Abstract

Background: Evidence from observational studies has suggested a link between cigarette smoking and the risk of polycystic ovary syndrome (PCOS). However, it remains uncertain whether the observed relationship is causal or due to biases inherent in observational studies. Therefore, we adopted two-sample Mendelian randomization (MR) design to assess the potential causal association between smoking and the risk of PCOS.

Methods: Summary level data of PCOS was obtained from a genome-wide association study (GWAS) meta-analysis including 4,138 cases and 20,129 controls of European ancestry. Single-nucleotide polymorphisms (SNPs) associated with smoking initiation (n=360) were selected and used as genetic instrumental variables (IVs). MR analysis was performed using inverse-variance weighted (IVW) method, supplemented with the likelihood-based method, weighted median method, MR pleiotropy residual sum and outlier (MR-PRESSO) test, and MR-Egger regression.

Results: Genetically predicted smoking initiation was associated with an increased risk of PCOS in the primary analysis (odds ratio (OR) =1.38, 95% confidence interval (CI) =1.12-1.69). MR-Egger regression did not detect the horizontal pleiotropy. Sensitivity analyses using alternative MR methods and restricted IVs produced similar results.

Conclusion: Our study provided evidence to support a potential causal association between smoking initiation and an increased risk of PCOS, providing a better understanding of the etiology and prevention of PCOS. Further studies are warranted to clarify the underlying biological mechanisms of smoking in the development of PCOS.

Keywords: Mendelian randomization; causal inference; cigarette smoking; polycystic ovary syndrome; single-nucleotide polymorphism.

Grants and funding

This work was supported by grants from the National Natural Science Foundation of China (81602917), the Natural Science Foundation of Zhejiang Province (LQ20H260008, LQ21H260001), the Talent Project of Zhejiang Association for Science and Technology (2018YCGC003), the Foundation of Zhejiang Chinese Medical University (KC201905, 2020ZR09, 2020ZG01, 2020ZG06), and the Medical Health Science and Technology Project of Health Commission of Zhejiang Province (2019RC134, 2020KY195).