Cohort Profile: The Mendelian Randomization in Pregnancy (MR-PREG) collaboration - Improving evidence for prevention and treatment of adverse pregnancy and perinatal outcomes

PurposeAdverse pregnancy and perinatal outcomes (APPOs), including pre-term birth, pre-eclampsia, and gestational diabetes, can result in maternal and neonatal morbidity and mortality, parental anxiety, and increased health care costs. Better understanding of causes of APPOs is essential to inform lifestyle and pharmaceutical interventions for their prevention and management. Given the difficulty of undertaking randomised control trials in pregnant women, triangulating evidence from across different methods with different sources of bias could improve our understanding of the causes of APPOs. The purpose of the Mendelian Randomization in Pregnancy (MR-PREG) collaboration is to support triangulation of evidence from genetic (e.g., Mendelian randomization [MR]) and non-genetic (e.g., partner negative controls) methods to explore causal effects of maternal exposures on a comprehensive set of APPOs ParticipantsThe MR-PREG collaboration includes individual participant data from three birth cohorts (two from the UK and one from Norway) and UK Biobank, and summary data from FinnGen and publicly available genome wide association studies (GWAS). We have harmonised data across studies so that currently includes exposures on up to 34 APPOs in up to 678,001 women. Findings to dateThe main aims of MR-PREG are to improve the evidence base for 1) prevention, by advancing our understanding of maternal modifiable causes of APPOs, 2) better understanding of the effect of pre-existing conditions on APPOs, and 3) treatment, by advancing our knowledge of the efficacy and safety of existing medications that women may require for pre-existing conditions, and identifying and testing the efficacy and safety of novel medications, and those that might be repurposed to effectively and safely treat APPOs. To date, our published research mainly addresses aims 1 and 3; some examples include triangulation of evidence from MR, conventional multivariable regression and a paternal negative control, showing that higher maternal body mass index increases the risk of many APPOs, and identification of maternal circulating metabolites and proteins that may influence birthweight. Future PlansOur future priorities include increasing diversity in the MR-PREG collaboration by expanding participant representation from non-European ancestries. We are also integrating molecular data, such as circulating protein levels and placental transcriptomics, to better understand the molecular mechanisms underlying APPOs. Additionally, we are using exome and whole-genome sequencing to identify novel causal genes for APPOs and advance our knowledge on candidate targets for APPOs. Strengths and limitationsO_LIWe have curated data for 34 APPOs and harmonized data across multiple studies to support large-scale investigations of causes of APPOs. C_LIO_LIThe scope and type of the data supports triangulation of evidence from a range of genetic and non-genetic methods, with different unrelated sources of bias, to identify causes of APPOs. C_LIO_LIOver the coming year we will enhance the data to enable identification of molecular mechanism underlying APPOs. C_LIO_LIMR-PREG has limited power to detect causal effects on rarer APPOs, such as congenital anomalies and low Apgar scores at 5 minutes, particularly when using genetic methods. Future work will include larger samples and rare genetic variant data. C_LIO_LIParticipants are mostly of European ancestry; future efforts will be focussed on diversifying the ancestry representation in the data. C_LI