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Published on: August 7, 2017
Asthma and risk of adverse pregnancy outcomes: A Mendelian randomization study
Xinyu Han1, Tian Qiang Wu1, Yuanyuan Bian1
1Department of First Clinical Medical College, Heilongjiang University of Chinese Medicine, Harbin, China.
Background:
Multiple empirical investigations have indicated a connection between asthma and adverse pregnancy outcomes (APOs). Nevertheless, the effects of asthma on APOs remain uncertain.
Methods:
We performed bi-directional Univariable Mendelian randomization (UVMR) analyses using combined information obtained from genome-wide association studies (GWAS) data that is publicly accessible. The principal approach used to analyze the causal association between asthma or age when diagnosed and APOs was the inverse variance weighted (IVW) method. The two types of data regarding exposure originate from the IEU Open GWAS project, which includes 56,167 and 47,222 European asthma patients, respectively. The data of four APOs were acquired via the GWAS dataset of the FinnGen collaboration. In addition, we implemented multivariable Mendelian randomization (MVMR), controlling for confounding factors such as smoking status, frequent drinking, body mass index (BMI), and live birth quantity. Furthermore, we executed several meticulous sensitivity studies to ascertain the reliability of our MR results.
Results:
Following the implementation of the Bonferroni adjustment, the UVMR assessment revealed that in the IVW model, asthma was significantly linked to an elevated risk of spontaneous abortion (SA) (odds ratio [OR]: 1.115; 95 % confidence interval [CI]: 1.031-1.206; P = 0.006) and gestational diabetes mellitus (GDM) (OR: 1.125; 95 % CI: 1.037-1.220; P = 0.005). However, there was no causal correlation between asthma and preterm birth (PTB) (OR: 0.979; 95 % CI: 0.897-1.068; P = 0.629) or preeclampsia (PE) (OR: 1.059; 95 % CI: 0.951-1.179; P = 0.297). After adjusting for confounding factors, including smoking status, frequent drinking, BMI, and live birth quantity, the MVMR analysis shows a statistically significant causal relationship between asthma and SA or GDM. Furthermore, our investigation's findings did not reveal a substantial correlation between the age of asthma onset based on genetics and the likelihood of SA or GDM. The inverse MR outcomes indicate a lack of causal connection linking APOs to the incidence of asthma. The validity of these findings were verified by sensitivity analyses.
Conclusions:
The evidence provided by this study proves that genetically determined asthma is linked to a higher likelihood of SA and GDM. Further research is required to examine potential pathways. However, no conclusive evidence has been found to support the increased risk of SA and GDM in early asthma diagnosis or the interaction between asthma and PTB or PE, indicating that confounding factors may affect the results of previous observational studies.
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