1.Research Questions:
How do genetic variants (e.g., metabolic/immune pathway SNPs), dietary patterns (ultra-processed foods, fiber), lifestyle behaviors (physical activity, sleep), and gut microbiome composition interact to influence NCD (cardiovascular disease, type 2 diabetes, cancer) incidence?
What are the mechanistic links through which gene-diet-lifestyle-microbiome interactions drive NCD pathogenesis via inflammatory (CRP, IL-6) and metabolic (insulin resistance, lipids) biomarkers?
Can integrated multi-omics data (genomics, microbiomics, metabolomics) enable predictive models for NCD risk stratification and personalized prevention?
2. Objectives
Associate Factors: Identify individual and combined associations between genetic/dietary/lifestyle/microbiome factors and NCD outcomes using large biobank datasets.
Elucidate Mechanisms: Investigate interaction mechanisms via multivariate modeling and causal inference (e.g., Mendelian randomization).
Develop Models: Create multi-omics predictive models to inform precision nutrition and microbiome-targeted interventions.
3. Scientific Rationale
NCDs account for >70% of global deaths, driven by genetic and environmental factors. Western diets/sedentary lifestyles disrupt gut microbiome homeostasis, causing dysbiosis linked to inflammation and metabolic syndrome. For example, dietary fiber fermented by gut bacteria produces SCFAs regulating glucose/lipid metabolism, while processed foods enrich pro-inflammatory taxa.
Intra-population NCD risk variation implies gene-microbiome-environment interactions. Current research lacks integration of genes, diet, lifestyle, and microbiome. Using UK Biobank’s multi-omics data, this study provides a systems biology view of NCD pathogenesis to identify modifiable risk factors and microbial mediators, advancing precision medicine and informing public health policies to reduce NCD burden in aging populations.
