Causal Associations Between Sleep Traits and Polycystic Ovary Syndrome: A Univariable, Bidirectional, and Multivariable Mendelian Randomization Study

睡眠特征与多囊卵巢综合征的因果关联:一项单变量、双向和多变量孟德尔随机化研究

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Abstract

BACKGROUND: Observational studies have reported associations between various sleep traits and polycystic ovary syndrome (PCOS); however, it remains unclear whether these relationships are causal or driven by confounding factors. This study aimed to clarify the direction and magnitude of potential causal effects between eight self-reported sleep characteristics and PCOS risk using a bidirectional and multivariable Mendelian randomization (MR) framework. METHODS: Genome-wide association study (GWAS) summary statistics for eight sleep traits (sleeplessness/insomnia, sleep duration, snoring, daytime dozing, chronotype, getting up in the morning, daytime napping, and sleep apnea syndrome) and PCOS were analyzed. Univariable MR analyses were conducted using inverse-variance weighted (IVW) meta-analysis as the primary method, supplemented by weighted median and MR-Egger regression. Sensitivity analyses included Cochran's Q test, the MR-Egger intercept, MR-PRESSO, and leave-one-out analyses. Multivariable MR analyses were further performed with adjustment for adiposity and insulin resistance. RESULTS: Genetically predicted sleeplessness/insomnia was associated with an increased risk of PCOS (IVW OR = 1.67, 95% CI = 1.24-2.27, p = 8.6 × 10(-4)). Sleep apnea syndrome was also associated with PCOS in univariable analyses (IVW OR = 1.07, 95% CI = 1.03-1.11, p = 1.3 × 10(-3)); however, this association was attenuated after multivariable adjustment (p = 0.20). No evidence of reverse causation from PCOS to sleep traits was observed. The results were consistent across sensitivity analyses, with no evidence of horizontal pleiotropy. CONCLUSION: Our MR analyses support a potential causal role of sleeplessness/insomnia in increasing the risk of PCOS, whereas the association with sleep apnea syndrome may be mediated by adiposity or other confounding factors. These findings highlight the importance of sleep management in strategies for the prevention of PCOS.

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