Resting CD4+ T cells exposed to oleic acid upregulate genes involved in immunometabolism resulting in increased IL-9+ frequencies post-activation [RNA-seq]

T cells are the most common immune cell in atherosclerotic plaques. Furthermore, T cell function is influenced by fatty acids that are abundant in the circulation and atherosclerotic plaques. Here, we define the effect of oleic acid, one of the most abundant fatty acids in the human circulation, on the transcriptome of resting CD4+ T cells and subsequently the polarization of the cells into T cell subsets post-activation. We first performed RNA sequencing of resting CD4+ T cells from 9 donors after 0.5, 3, 24, 48, and 72 hours exposure to 30µg/mL oleic acid. This revealed the upregulation of genes involved in cholesterol biosynthesis (HMGCR, SQLE, MVD and MVK) and de novo fatty acid biosynthesis (ACACA and FASN). Both pathways point to a metabolic reprogramming of the cells towards a pro-inflammatory state. Subsequently, a 26-marker spectral flow cytometry panel showed increased frequencies of IL-9+ and IL-17A+ cells among activated CD4+ T cells pre-exposed to oleic acid. IL-9 and IL-17A are primarily produced by the respective T helper (TH) subsets TH9 and TH17, where, especially TH9, has been implicated in the aggravation of atherosclerosis. Our data shows that oleic acid may induce a shift in immunometabolism in resting CD4+ T cells towards an activated profile that leads to more pro-inflammatory and pro-atherogenic polarization of these cells post-activation. Taken together, our study signals a potential role for the interaction between circulating fatty acids and CD4+ T cells in the development and pathogenesis of atherosclerosis. Comparative gene expression profiling analysis of RNA-seq data and comparative DNA methylation analysis of 850k DNA methylation array data for resting human buffy coat derived CD4+ T cells exposed to control or 30μg/mL for either 0.5, 3, 24, 48, or 72 hours. The RNA and DNA was simultaneously extracted from the cell samples and thus the RNA seq and DNA methylation data is representative of the same bulk cell sample.