Collaborate with us on pregnancy research

The group led by Professor Deborah A. Lawlor and Assoc Prof. Carolina Borges conduct translational research aimed at strengthening the evidence base for predicting, preventing, and treating health complications during and after pregnancy.

To support this work, they established the MR-PREG collaboration — a comprehensive resource encompassing data from over 500,000 women, including genetic and clinical information — alongside partnerships that link large-scale electronic health records from multiple countries. 

By leveraging these extensive datasets and expertise in novel causal inference methods, their research advances understanding of the safety and efficacy of medications used during pregnancy and identifies novel or repurposed therapeutic targets for managing pregnancy-related complications. They are also applying machine learning approaches to multi-omics and electronic health record data to enhance risk stratification and enable the early identification of women at increased risk of adverse pregnancy outcomes.

Previous research from their group has shown that higher maternal pre- or early-pregnancy BMI increases the risk of multiple adverse pregnancy and perinatal outcomes (APPOs), highlighting the importance of pre-conception interventions to improve outcomes for both mothers and infants. They have also demonstrated that specific metabolite markers can improve risk prediction for certain.