Wang Yingying, Li Shanshan, Lu Jiajin, Yuan Tianming
Department of Neonatology, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Department of Neonatology, Shaoxing Keqiao Women & Children's Hospital, Shaoxing, China.
Transl Pediatr. 2024 Dec 31;13(12):2193-2203. doi: 10.21037/tp-24-335. Epub 2024 Dec 27.
Some studies have suggested that complications during pregnancy, such as preeclampsia, leiomyoma during pregnancy, oxytocin induction, and mode of delivery, may be risk factors for neonatal jaundice. Herein, we applied Mendelian randomization (MR) analysis to investigate a causal association between pregnancy disorders and neonatal jaundice.
Data related to neonatal jaundice and pregnancy disorders (including pre-eclampsia or eclampsia, gestational diabetes, and gestational edema) were sourced from the FinnGen Consortium and Integrated Epidemiology Unit (IEU) databases. Inverse-variance weighted (IVW) was used as a main approach for data analysis, while MR-Egger, weighted median (WM), and weighted mode methods were used to validate the robustness of the results. MR-Egger regression method was applied to explore the presence of horizontal pleiotropy. MR pleiotropy residual sum and outlier (MR-PRESSO) method was used to detect potential outliers. Cochran's Q test was used to assess heterogeneity among instrumental variables (IVs); leave-one-out (LOO) analyses were used to evaluate the presence of predominant IVs.
The IVW approach showed that pre-eclampsia or eclampsia {odds ratio (OR) [95% confidence interval (CI)]: 0.86 (0.36-2.07), P=0.73}, gestational edema and proteinuria [OR (95% CI): 1.04 (0.62-1.74), P=0.87], and gestational diabetes mellitus [OR (95% CI): 0.95 (0.60-1.49), P=0.81] were not associated with neonatal jaundice. The MR-Egger regression results showed that horizontal pleiotropy did not affect the relationship between exposure factors and outcomes. Also, no heterogeneity was observed. The MR-PRESSO analysis showed no outliers, confirming that these data were robust.
Our data suggested no genetic causal association between pre-eclampsia or eclampsia, gestational edema, proteinuria, gestational diabetes mellitus, and neonatal jaundice. However, further research is needed to determine if these results apply to other races.
一些研究表明,孕期并发症,如先兆子痫、孕期平滑肌瘤、催产素引产和分娩方式,可能是新生儿黄疸的危险因素。在此,我们应用孟德尔随机化(MR)分析来研究妊娠疾病与新生儿黄疸之间的因果关系。
与新生儿黄疸和妊娠疾病(包括先兆子痫或子痫、妊娠期糖尿病和妊娠水肿)相关的数据来自芬兰基因组联盟和综合流行病学单位(IEU)数据库。逆方差加权(IVW)用作数据分析的主要方法,而MR-Egger、加权中位数(WM)和加权模式方法用于验证结果的稳健性。应用MR-Egger回归方法探索水平多效性的存在。使用MR多效性残差和异常值(MR-PRESSO)方法检测潜在异常值。使用 Cochr an Q检验评估工具变量(IV)之间的异质性;留一法(LOO)分析用于评估主要IV的存在。
IVW方法显示,先兆子痫或子痫{优势比(OR)[95%置信区间区间(CI]:0.86(0.36 - 2.07),P = 0.73}、妊娠水肿和蛋白尿[OR(95%CI):1.04(0.62 - 1.74),P = 0.87]以及妊娠期糖尿病[OR(95%CI):0.95(0.60 - 1.49),P = 0.81]与新生儿黄疸无关。MR-Egger回归结果表明,水平多效性不影响暴露因素与结局之间的关系。此外,未观察到异质性。MR-PRESSO分析未显示异常值,证实这些数据是稳健的。
我们的数据表明,先兆子痫或子痫、妊娠水肿、蛋白尿、妊娠期糖尿病与新生儿黄疸之间不存在遗传因果关系。然而,需要进一步研究以确定这些结果是否适用于其他种族。