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Genetically predicted maternal prepregnancy BMI increased risk of childhood intestinal malformation: evidence from a
Siqi Xie1, Xiaojin Zhuang1, Lan Liu1
1Fujian Children's Hospital (Fujian Branch of Shanghai Children's Medical Center), College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, Fujian, China.
The study aimed to explore the causal effect of maternal prepregnancy body mass index (BMI) on congenital malformations of intestine (CMI). The genome-wide association data of BMI and CMI were obtained via the Mendelian randomization (MR) base platform. Single nucleotide polymorphisms (SNPs) significantly associated with BMI in females were identified and used as instrumental variables, and the causal relationship between BMI in females and CMI was examined using the bidirectional two-sample MR analyses research method. Three statistical methods including inverse-variance weighted (IVW) method, weighted median estimator, and MR-Egger regression were employed. A total of 36 SNPs significantly associated with BMI in females were identified in the study (P < 5 × 10−8; linkage disequilibrium r2 < 0.001). Consistent association between BMI in females and CMI was observed when evaluated by different methods (IVW: odds ratio (OR) 0.364, 95% confidence interval (CI) 0.144–0.922; weighted median estimator: OR 0.395, 95% CI 0.096–1.619; MR-Egger Method: OR 0.244, 95% CI 0.020–2.974), which suggests that BMI in females is negatively associated with increased risk of CMI. The MR analysis provided the strong evidence to indicate that decreasing BMI in females might be causally associated with the risk of CMI.
The study aimed to explore the causal effect of maternal prepregnancy body mass index (BMI) on congenital malformations of intestine (CMI). The genome-wide association data of BMI and CMI were obtained via the Mendelian randomization (MR) base platform. Single nucleotide polymorphisms (SNPs) significantly associated with BMI in females were identified and used as instrumental variables, and the causal relationship between BMI in females and CMI was examined using the bidirectional two-sample MR analyses research method. Three statistical methods including inverse-variance weighted (IVW) method, weighted median estimator, and MR-Egger regression were employed. A total of 36 SNPs significantly associated with BMI in females were identified in the study (P < 5 × 10−8; linkage disequilibrium r2 < 0.001). Consistent association between BMI in females and CMI was observed when evaluated by different methods (IVW: odds ratio (OR) 0.364, 95% confidence interval (CI) 0.144–0.922; weighted median estimator: OR 0.395, 95% CI 0.096–1.619; MR-Egger Method: OR 0.244, 95% CI 0.020–2.974), which suggests that BMI in females is negatively associated with increased risk of CMI. The MR analysis provided the strong evidence to indicate that decreasing BMI in females might be causally associated with the risk of CMI.
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