| Title: | Polygenic prediction of preeclampsia and gestational hypertension |
| Journal: | Nature Medicine |
| Published: | 29 May 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/37248299/ |
| DOI: | https://doi.org/10.1038/s41591-023-02374-9 |
| URL: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10330886 |
| Citations: | 24 (24 in last 2 years) as of 8 Aug 2024 |
Publication 11503
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
Abstract
Preeclampsia and gestational hypertension are common pregnancy complications associated with adverse maternal and child outcomes. Current tools for prediction, prevention and treatment are limited. Here we tested the association of maternal DNA sequence variants with preeclampsia in 20,064 cases and 703,117 control individuals and with gestational hypertension in 11,027 cases and 412,788 control individuals across discovery and follow-up cohorts using multi-ancestry meta-analysis. Altogether, we identified 18 independent loci associated with preeclampsia/eclampsia and/or gestational hypertension, 12 of which are new (for example, MTHFR-CLCN6, WNT3A, NPR3, PGR and RGL3), including two loci (PLCE1 and FURIN) identified in the multitrait analysis. Identified loci highlight the role of natriuretic peptide signaling, angiogenesis, renal glomerular function, trophoblast development and immune dysregulation. We derived genome-wide polygenic risk scores that predicted preeclampsia/eclampsia and gestational hypertension in external cohorts, independent of clinical risk factors, and reclassified eligibility for low-dose aspirin to prevent preeclampsia. Collectively, these findings provide mechanistic insights into the hypertensive disorders of pregnancy and have the potential to advance pregnancy risk stratification.</p>
32 Authors
- Michael C. Honigberg
- Buu Truong
- Raiyan R. Khan
- Brenda Xiao
- Laxmi Bhatta
- Ha My T. Vy
- Rafael F. Guerrero
- Art Schuermans
- Margaret Sunitha Selvaraj
- Aniruddh P. Patel
- Satoshi Koyama
- So Mi Jemma Cho
- Shamsudheen Karuthedath Vellarikkal
- Mark Trinder
- Sarah M. Urbut
- Kathryn J. Gray
- Ben M. Brumpton
- Snehal Patil
- Sebastian Zöllner
- Mariah C. Antopia
- Richa Saxena
- Girish N. Nadkarni
- Ron Do
- Qi Yan
- Itsik Pe'er
- Shefali Setia Verma
- Rajat M. Gupta
- David M. Haas
- Hilary C. Martin
- David A. van Heel
- Triin Laisk
- Pradeep Natarajan
1 Application
| Application ID | Title |
|---|---|
| 7089 | Exome Sequencing of All Premature Coronary Artery Disease Participants in UK Biobank |
Enabling scientific discoveries that improve human health