This study aims to explore how lifestyle and natural/socioeconomic environments interact with genetic expression to influence both bodily and cognitive states. Focusing on colorectal cancer(CRC),glioma (brain), and mental/cognitive assessments. Evidence confirms such interactions affect physiological, cognitive, and mental states, revealing complex body-brain interactions, though underlying mechanisms remain unclear. Using the two cancers and behavioral metrics as models, our key question is how the differential environmental and liftstyle factors modulate genetic expression to influence the potential pathogenesis of metabolic diseases (e.g. type-2 diabetes, obesity etc.), CRC, glioma and their combodity as well as mental and cognitive aspects of patients.
The objectives are to identify biomarkers such as genetic variants, plasma proteins, metabolites, imaging, physical activity, and microbial species, the subgroups of the diseases grouped by the combination of the environmental, lifestyle, biomarker factors and the risk factors that involve specific environmental exposure, genetic aspects, and lifestyle. Using longitude analysis and advanced machine learning, we will integrate the multi-modal data to analyze high-dimensional datasets, deriving data-driven insights into mechanisms and therapeutic targets.
The scientific rationale stems from the necessity to study the body holistically within complex environment-gene-lifestyle interactions. CRC, glioma and their combodities affected by lots of factors and may interact with cogntive/mental states- require investigation into how pathologies emerge from these interactions, relate to cognitive/mental states, and differ from healthy individuals. By exploring UK Biobank’s extensive datasets to understand these relationships, which is vital for elucidating mechanisms, enabling early risk detection, developing interventions, and preventing disease, ultimately improving public health and reducing disease burd.
