Scientific rationale: Developmental disorders contribute significantly to global disease burden, accounting for 11.2 million disability-adjusted life-years annually according to the GBD-2021 dataset. These lifelong conditions often originate in the prenatal environment, influenced by modifiable maternal factors. However, the specific etiologies remain poorly understood.
Research questions: By capturing real-time molecular snapshots through maternal blood proteomics and metabolomics during the periconceptional window, this study aims to uncover how genetic regulation and environmental responses converge to shape pregnancy outcomes. What are the individual and joint contributions of maternal health status, living environment, psycho-social stress, health behaviors, and genetic susceptibility to pregnancy outcomes and fetal development? Can we identify novel predictive biomarkers and modifiable pathways that influence adverse pregnancy outcomes and abnormal fetal development?
Objectives: To integrate high-resolution environmental models, deep maternal phenotyping, and genome-wide genotypic data with pregnancy outcomes and fetal development data from the UK Biobank. To apply multidimensional epidemiological and causal-analytic approaches-including logistic regression and Mendelian randomization-to quantify associations and infer causal pathways. To develop predictive models for adverse pregnancy outcomes and suboptimal fetal development. To translate findings into actionable, modifiable targets for pre-conception public health interventions.
