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Maternal Polycystic Ovary Syndrome and Offspring Birth Weight: A Mendelian Randomization Study

Authors :
Yuexin Gan
Jun Zhang
Donghao Lu
Jian Zhao
Chonghuai Yan
Source :
The Journal of Clinical Endocrinology & Metabolism. 107:1020-1029
Publication Year :
2021
Publisher :
The Endocrine Society, 2021.

Abstract

Context Observational associations between maternal polycystic ovary syndrome (PCOS) and offspring birth weight (BW) have been inconsistent and the causal relationship is still uncertain. Objective We conducted a 2-sample Mendelian randomization (MR) study to estimate the causal effect of maternal PCOS on offspring BW. Methods We constructed genetic instruments for PCOS with 14 single nucleotide polymorphisms (SNPs) which were identified in a genome-wide association study (GWAS) meta-analysis including 10 074 PCOS cases and 103 164 controls of European ancestry from 7 cohorts. The genetic associations of these SNPs with the offspring BW were extracted from summary statistics estimated by the Early Growth Genetics consortium (n = 406 063 European ancestry individuals) using the weighted linear model, an approximation method of structural equation model, which separated maternal genetic effects from fetal genetic effects. We used a 2-sample MR design to examine the causal relationship between maternal PCOS and offspring BW. Sensitivity analyses were conducted to assess the robustness of the MR results. Results We found little evidence for a causal effect of maternal PCOS on offspring BW (–6.1 g, 95% CI –16.8 g, 4.6 g). Broadly consistent results were found in the sensitivity analyses. Conclusion Despite the large scale of this study, our results suggested little causal effect of maternal PCOS on offspring BW. MR studies with a larger sample size of women with PCOS or more genetic instruments that would increase the variation of PCOS explained are needed in the future.

Details

ISSN :
19457197 and 0021972X
Volume :
107
Database :
OpenAIRE
Journal :
The Journal of Clinical Endocrinology & Metabolism
Accession number :
edsair.doi.dedup.....e5d11d1e2b7ae77939a363bb6bba909e