Associations between dietary patterns and gene expression pattern in peripheral blood mononuclear cells: a cross-sectional study

Background Diet may alter gene expression in immune cells involved in cardio-metabolic disease susceptibility. However, we still lack a robust understanding of the association between diet and immune cell-related gene expression in humans. Objective Our objective was to examine the associations between dietary patterns (DPs) and gene expression profiles in peripheral blood mononuclear cells (PBMCs) in a population of healthy, Norwegian adults. Methods We used factor analysis to define a posteriori DPs from food frequency questionnaire-based dietary assessment data. In addition, we derived interpretable features from microarray-based gene expression data (13 967 transcripts) using two algorithms: CIBERSORT for estimation of cell subtype proportions, and weighted gene co-expression network analysis (WGCNA) for cluster discovery. Finally, we associated DPs with either CIBERSORT-predicted PBMC leukocyte distribution or WGCNA gene clusters using linear regression models. All analyses were gender-stratified (n = 130 women and 105 men). Results We detected three DPs that broadly reflected Western, Vegetarian , and Low carbohydrate diets. CIBERSORT-predicted percentage of monocytes associated strongly and negatively with the Vegetarian DP in both women and men. For women, the Vegetarian DP associated most strongly with a large gene cluster consisting of 600 genes mainly involved in regulation of DNA transcription. For men, the Western DP inversely associated most strongly with a smaller cluster of 36 genes mainly involved in regulation of metabolic and inflammatory processes. In subsequent protein-protein interaction network analysis, the most important driver genes within these WGCNA gene clusters seemed to physically interact in biological networks. Conclusions DPs may affect percentage monocytes and regulation of key biological processes within the PBMC pool. Although the present findings are exploratory, our analysis pipeline serves a useful framework for studying the association between diet and gene expression.