Abstract

Background

Pre-eclampsia (PE) and pregnancy hypertension (PH) are common and serious complications during pregnancy, which can lead to maternal and fetal death in severe cases. Therefore, further research on the potential therapeutic targets of PE and PH is of great significance for developing new treatment strategies.

Methods

This study used the summary data-based Mendelian randomization (SMR) method to analyze expression quantitative trait loci (eQTL) data from blood, aorta, and uterus with Genome-wide association studies (GWAS) data on PE and PH, exploring potential genetic loci involved in PE and PH. Since proteinuria is a clinical manifestation of PE, we also analyzed genes related to the kidney and PE. The HEIDI test was used for heterogeneity testing, and results were adjusted using FDR. The cis-eQTL data were obtained from the blood summary-level data of the eQTLGen Consortium and the aorta and uterus data from the V8 release of the GTEx eQTL summary data. The GWAS data for PE and PH were obtained from the FinnGen Documentation of R10 release. This study utilized the STROBE-MR checklist for reporting Mendelian Randomization (MR) studies.

Results

This study identified several potential therapeutic targets by integrating eQTL data from blood, uterus, and aorta with GWAS data for PE and PH, as well as kidney eQTL data with GWAS data for PE. Additionally, the study discovered some genes with common roles in PE and PH, offering new insights into the shared pathological mechanisms of these two conditions. These findings not only provide new clues to the pathogenesis of PE and PH but also offer crucial foundational data for the development of future therapeutic strategies.

Conclusion

This study revealed multiple potential therapeutic targets for PE and PH, providing new insights for basic experimental research and clinical treatment to mitigate the severe consequences of PE and PH.

Clinical trial number

Not applicable.

Details

Title
Uncovering therapeutic targets for Pre-eclampsia and pregnancy hypertension via multi-tissue data integration
Author
Yao, Hang; Chen, Jiahao; Wang, Yu; Li, Yuxin; Tang, Peiyu; Liang, Mingpeng; Jiang, Qingling
Pages
1-11
Section
Research
Publication year
2025
Publication date
2025
Publisher
BioMed Central
e-ISSN
14712393
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3201524369
Copyright
© 2025. This work is licensed under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.