Diet Impacts on Gene Expression in Healthy Colon Tissue: Insights from the BarcUVa-Seq Study

Abstract

(1) Introduction: The global rise of gastrointestinal diseases, including colorectal cancer and inflammatory bowel diseases, highlights the need to understand their causes. Diet is a common risk factor and a crucial regulator of gene expression, with alterations observed in both conditions. This study aims to elucidate the specific biological mechanisms through which diet influences the risk of bowel diseases. (2) Methods: We analyzed data from 436 participants from the BarcUVa-Seq population-based cross-sectional study utilizing gene expression profiles (RNA-Seq) from frozen colonic mucosal biopsies and dietary information from a semi-quantitative food frequency questionnaire. Dietary variables were evaluated based on two dietary patterns and as individual variables. Differential expression gene (DEG) analysis was performed for each dietary factor using edgeR. Protein-protein interaction (PPI) analysis was conducted with STRINGdb v11 for food groups with more than 10 statistically significant DEGs, followed by Reactome-based enrichment analysis for the resulting networks. (3) Results: Our findings reveal that food intake, specifically the consumption of blue fish, alcohol, and potatoes, significantly influences gene expression in the colon of individuals without tumor pathology, particularly in pathways related to DNA repair, immune system function, and protein glycosylation. (4) Discussion: These results demonstrate how these dietary components may influence human metabolic processes and affect the risk of bowel diseases.

Keywords: colon; diet; dietary patterns; gene expression; nutrigenomics; tissue.

Figure 1

Correlation plot of dietary patterns and food group variables adjusted by the residual method.

Figure 2

Network plot of top enriched pathways and their genes involved for the top three food groups. (A) Blue fish, (B) alcoholic beverages, and (C) potatoes. Grey nodes represent pathways, with size proportional to the number of DEGs within each pathway. Genes are color-coded based on their expression levels: deep red indicates genes that are upregulated in low consumers, while deep blue indicates genes that are upregulated in high consumers. The gradient from red to blue represents varying levels of log fold change values.