nutrigenomics
Definition
Nutrigenomics is the study of how nutrients and bioactive food compounds interact with the genome to influence gene expression, protein synthesis, and metabolic pathways. This field integrates genomics, transcriptomics, proteomics, and metabolomics to understand individual variations in nutritional responses based on genetic makeup. Nutrigenomics examines both how dietary components regulate gene activity and how genetic polymorphisms affect nutrient metabolism and dietary requirements. It enables personalized nutrition strategies by identifying gene-diet interactions that influence disease susceptibility, metabolic health, and therapeutic responses. Key applications include understanding how specific nutrients modulate inflammatory pathways, lipid metabolism, and oxidative stress responses at the molecular level.
Visualize nutrigenomics in Nodes Bio
Researchers can map nutrient-gene interaction networks showing how dietary compounds regulate transcription factors, signaling cascades, and metabolic enzymes. Nodes Bio enables visualization of multi-omics data layers connecting SNPs, differentially expressed genes, altered proteins, and metabolite changes in response to dietary interventions. Users can identify hub genes mediating nutritional responses and trace causal pathways from nutrient exposure to phenotypic outcomes across population subgroups.
Visualization Ideas:
- Gene-nutrient interaction networks showing transcription factor binding and downstream target genes
- Multi-omics integration maps connecting genetic variants, gene expression, protein levels, and metabolite changes
- Comparative pathway networks showing differential responses to dietary interventions across genotypes
Example Use Case
A research team investigates why omega-3 fatty acids reduce cardiovascular risk in some individuals but not others. They integrate genomic data identifying FADS1/FADS2 gene variants with transcriptomic profiles from dietary intervention trials. Network analysis reveals that individuals with specific SNPs show altered expression of inflammatory mediators (IL-6, TNF-α) and lipid metabolism genes (SREBP1, PPAR-α) in response to omega-3 supplementation. This multi-layered network identifies genetic biomarkers predicting omega-3 treatment efficacy for personalized cardiovascular disease prevention strategies.