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 carb 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.