Causal Association Between BMI and Polycystic Ovarian Syndrome: Bidirectional 2-Sample Mendelian Randomization Study.

Autor:	Fang Y; Fujian Children's Hospital (Fujian Branch of Shanghai Children's Medical Center), College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, 350000, Fujian, China., Liu L; Fujian Children's Hospital (Fujian Branch of Shanghai Children's Medical Center), College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, 350000, Fujian, China., Yang Y; Fujian Children's Hospital (Fujian Branch of Shanghai Children's Medical Center), College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, 350000, Fujian, China., Zhang B; Fujian Children's Hospital (Fujian Branch of Shanghai Children's Medical Center), College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, 350000, Fujian, China., Xie S; Fujian Children's Hospital (Fujian Branch of Shanghai Children's Medical Center), College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, 350000, Fujian, China.
Jazyk:	angličtina
Zdroj:	The Journal of clinical endocrinology and metabolism [J Clin Endocrinol Metab] 2024 Dec 18; Vol. 110 (1), pp. 41-47.
DOI:	10.1210/clinem/dgae446
Abstrakt:	Objective: This study aimed to explore the causal effect of body mass index (BMI) on polycystic ovarian syndrome (PCOS). Methods: Genome-wide association data for BMI and PCOS were sourced from the Mendelian randomization (MR) base platform. Significantly associated single nucleotide polymorphisms (SNPs) for BMI served as instrumental variables in bidirectional 2-sample MR analyses to investigate the causal relationship between BMI and PCOS. Analytical techniques utilized encompassed the inverse variance weighted (IVW) method, weighted median estimator, and MR-Egger regression. Results: We identified 427 SNPs significantly associated with BMI (P < 5 × 10-8; linkage disequilibrium r2 < 0.001). Various methods consistently revealed a positive association between BMI and PCOS (IVW: odds ratio [OR] 2.027 [95% CI 1.599-2.596]; weighted median estimator: OR 2.368 [95% CI 1.653-3.392]; MR-Egger method: OR 3.610 [95% CI 1.795-7.263]), indicating that higher BMI correlates with an increased risk of PCOS. Additionally, we observed a causal effect of genetic predisposition to PCOS on BMI (IVW: OR 1.020 [95% CI 1.019-1.022]; weighted median estimator: OR 1.017 [95% CI 1.015-1.019]; MR-Egger method: OR 1.000 [95% CI 0.995-1.005]). Conclusion: The MR analysis furnished compelling evidence suggesting a causal relationship between elevated BMI and the risk of PCOS, as well as indicating that the severity of PCOS may contribute to elevated BMI levels. (© The Author(s) 2024. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com. See the journal About page for additional terms.)
Databáze:	MEDLINE
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