This project aims to investigate the biological mechanisms and potential predictive biomarkers of anesthesia-related outcomes, including cognitive decline, delirium, and pain. Leveraging the extensive genomic, proteomic, metabolomic, neuroimaging, and electronic health record data available in the UK Biobank, the study will integrate multi-modal data to identify risk factors, explore causality, and develop predictive models for these neurological complications.
Research Questions:
1.What are the shared and distinct molecular (proteomic/metabolomic) and neuroimaging signatures associated with sleep, cognitive decline, delirium, and pain?
2.Do genetic variants contribute causally to these outcomes, and how do they interact with perioperative exposures?
3.Can integrative models combining genetic, molecular, imaging, and clinical data accurately predict individuals at risk?
Objectives:
1.Use UK Biobank proteomic and metabolomic data to identify molecular pathways linked to adverse outcomes.
2.Analyze brain MRI to detect changes related to sleep, cognitive function and pain processing.
3.Apply Mendelian Randomization using genome-wide association data to test causal relationships between molecular traits and outcomes.
4.Develop machine learning-based predictive models that integrate multi-omics, imaging, and clinical data for personalized risk stratification.
Scientific Rationale:
Anesthesia and surgery may trigger long-term neurological effects, especially in genetically susceptible individuals. The UK Biobank provides a unique opportunity to explore these complex outcomes at scale, with operative health data, extensive omics datasets, and high-resolution brain imaging. Integrating these resources enables a systems-level understanding of how genetic and molecular profiles contribute to anesthesia-related cognitive and pain outcomes, paving the way for biomarker discovery and precision perioperative care.
