The impact of basal metabolic rate on preeclampsia etiology: a Mendelian randomization study
Year: 2026
Type: article
Study design: Observational Study
Abstract: Objective Preeclampsia complicates 3–8% of pregnancies worldwide, an obstetric condition contributed to the short- and long-term morbidity and mortality of mothers and newborns. For its treatment and prevention, it is essential to comprehend the risk factors. This study aimed to investigate the potential causal influence of basal metabolic rate (BMR) on preeclampsia risk.Methods We utilized data from publicly available genome-wide association studies (GWAS) of European populations, focusing on BMR and preeclampsia. We selected single-nucleotide polymorphisms (SNPs) as instrumental variables for basal metabolic rate (BMR). Causal estimates were derived using multiple Mendelian Randomization (MR) methods: inverse-variance weighted (IVW), MR-Egger, weighted median, simple mode, and weighted mode. To ensure result robustness, we conducted comprehensive sensitivity analyses assessing potential pleiotropy and heterogeneity.Results We found evidence of a causal relationship between specific BMR indicators (ebi-a-GCST90029025, ukb-a-268, and ukb-a-16446) and preeclampsia risk. The IVW model indicated that genetically predicted higher BMR was associated with increased odds of preeclampsia. Cochran’s Q test and I2 statistics indicated no significant heterogeneity between ukb-a-16446 and preeclampsia, however, slight heterogeneity was observed for the other indicators. According to the MR-Egger regression, our findings were barely impacted by horizontal pleiotropy.Conclusion This MR study supports a causal role of BMR in preeclampsia risk. This highlights the potential of targeting metabolic pathways in preeclampsia prevention. Future research should be performed to explore the underlying mechanisms and evaluate the potential interventions modulating BMR to reduce preeclampsia incidence.
Authors: Qi Xu, Guoli Liu
Institution: Peking University People's Hospital
Language: English
Subfield: Obstetrics and Gynecology
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W7128522486
