Reproductive, psychiatric, and neurological disorders are major global contributors to morbidity, disability, and healthcare burden. Increasing evidence indicates that these conditions are biologically and behaviorally interconnected through shared neuroendocrine, immune, vascular, and psychosocial mechanisms. Reproductive events (e.g., pregnancy, childbirth, menopause) may alter long-term brain and emotional regulation through hormonal and inflammatory pathways, predisposing to psychiatric and neurological morbidity such as depression, anxiety, stroke, and dementia. Conversely, psychiatric and neurological disorders can adversely affect reproductive health, forming a bidirectional relationship.
Using the UK Biobank’s large-scale phenotypic, genetic, imaging, and biomarker data, this study will integrate multi-omics, hormonal, and behavioral dimensions to delineate shared and disease-specific determinants. By combining epidemiological modeling, genetic analyses, neuroimaging, and machine learning, we will establish a comprehensive framework linking reproductive, psychiatric, and neurological health across the life course.
Research Questions
1. What are the behavioral, hormonal, genetic, and microecological predictors for reproductive, psychiatric, and neurological disorders?
2. How do hormonal transitions, inflammation, and neuroimmune dysregulation mediate cross-disease risk?
3. What causal relationships exist between reproductive events and subsequent psychiatric and neurological disorders?
4. Can multimodal machine learning models predict comorbidity and progression across these domains?
Research Objectives
– Identify shared and unique risk factors through integrated UK Biobank data.
– Elucidate molecular and systemic mechanisms using multi-omics and neuroimaging.
– Characterize multimorbidity networks and causal pathways.
– Build predictive models to guide precision prevention and clinical intervention.
