Patients undergoing anesthesia and surgery are at risk for a range of neurocognitive disorders, including delirium, amnesia, cognition disorders, consciousness disorders, dementia, etc. These perioperative neurocognitive disorders (PND) significantly impact patients’ quality of life and place a burden on healthcare systems. Recently, various risk factors for PND are known, but the exploration of multiomics (such as genomics, proteomics, and metabolomics) remains limited. This research utilizes the extensive UK Biobank dataset, which includes multiomics data and clinical profiles of individuals who have undergone surgery, aiming to identify the underlying mechanisms of PND from a multilevel perspective.
Our study will include three phases:
1. First phase: We will leverage the demographic data, surgical details, anesthesia protocols and other clinical information collected by the UK Biobank to find the key risk factors of PND.
2. Second phase: We will further focus on neurophysiological factors, such as multiomics, molecular biomarkers, and brain imaging information, contributing to PND.
3. Third phase: Based on the findings from the clinical and multiomics data in the first two phases, we will build predictive models through machine learning to individually estimate the risk for PND.
Through this systematic study, we hope to optimize management strategies for PND, covering all stages of clinical care, from early warning and prevention to diagnosis and treatment, ultimately benefiting a wide population of surgical patients.
