Integrating DNA Methylation and Polygenic Risk Scores to Predict Pregnancy Outcomes and Offspring Health

Adverse pregnancy outcomes and early childhood health problems can have long-lasting effects on the health and wellbeing of mothers and their offspring. Earlier and more accurate identification of families at higher risk could help improve prevention strategies and guide future interventions. However, current prediction tools based on clinical or demographic information alone remain limited.
The primary aim of this project is to improve prediction of pregnancy outcomes and offspring health by using DNA-based biological information collected during pregnancy. In particular, we will focus on DNA methylation risk scores, which summarise pregnancy-related biological markers and exposures into a single measure reflecting maternal factors such as inflammation, smoking exposure, stress, and metabolism. These scores provide a practical way to capture complex biological information in a form suitable for prediction in large population studies.
Using data from mothers and children in the Born in Bradford cohort, we will evaluate whether maternal DNA methylation risk scores improve prediction of pregnancy outcomes and children’s growth, physical development, and cognitive health as they grow up. We will also assess whether combining methylation risk scores with genetic risk scores further improves predictive performance compared with genetic information alone.
A secondary aim of the project is to better understand which biological pathways may contribute to differences in risk through integrated analyses of genomic, epigenomic, metabolomic, and proteomic data. Overall, this work aims to develop more accurate and informative prediction tools relevant to families in Bradford and similar communities, with the longer-term goal of informing early identification and prevention strategies.