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Updated: Sep 15, 2025

Author Spotlight: Modeling an Aspect of Preeclampsia in Female Mice Using Hypoxic Human Placenta-Derived Small Extracellular Vesicles
Published on: January 26, 2024
Gestational Exposure to Particulate Matter and Preeclampsia Risk: Evidence from a Meta-Analysis and Mendelian
Ruilin Ma1, Yanan Li1, Jianjian Cui1
1Department of Obstetrics and Gynecology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Abstract:
Preeclampsia (PE) is a severe hypertensive disorder that occurs during pregnancy. Exposure to particulate matter (PM), particularly fine particles such as PM2.5/PM10, has been investigated as a potential environmental risk factor for its development. In this study, we employed both meta-analysis and Mendelian randomization (MR) to investigate the relationship between PM exposure and PE risk. The meta-analysis of 26 studies (>2 million pregnancies) found modest associations between PM exposure and PE risk. In particular, PM2.5 exposure during the second trimester (OR = 1.03, 95% CI: 1.01-1.04) and PM10 exposure (OR = 1.06, 95% CI: 1.00-1.12) showed significant associations. Subgroup and meta-regression analyses revealed that regional differences, particularly between Europe and Asia, were major contributors to heterogeneity, while publication year showed minimal impact. In contrast, no significant associations were found for PM exposure during the first and third trimesters, with greater statistical uncertainty likely due to heterogeneity in study design and exposure assessment methods. The MR analysis, using genetic instruments from European genome-wide association studies data, did not support a causal relationship between PM exposure and PE risk (PM2.5: OR = 1.128, 95% CI: -0.593- 0.834; PM10: OR = 0.668, 95% CI: -1.482-0.675). These findings suggest that while PM exposure, particularly during mid-pregnancy, may be associated with increased PE risk in observational studies, the lack of a confirmed causal link in MR analysis indicates potential influence from residual confounding, exposure misclassification, and study heterogeneity. Therefore, the observed associations should be interpreted with caution.
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