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Immune-mediated diseases such as autoimmunity are complex traits which collectively affect around 10% of the European population. Genome-wide association studies (GWAS) have demonstrated that genetic susceptibility to these diseases is explained by thousands of loci spread throughout the genome, most of which lie within non-coding DNA. Moreover, these loci are enriched in CD4+ T cell regulatory elements, which suggests they might disrupt the expression of nearby genes in T cells. Nonetheless, the target genes of most immune disease loci have yet to be discovered. In this dissertation, I describe three studies designed to further our understanding of the relationship between genetic variation, CD4+ T cell function, and disease risk. I first introduce a large epigenetic study which profiled active promoters and enhancers in 55 different CD4+ T cell and macrophage states. By integrating these data with GWAS loci with a novel statistical approach, I conclude that immune disease loci are enriched in enhancers and promoters specifically active during early memory T cell activation. In a second study, I proceed to characterize memory CD4+ T cells at single-cell resolution by profiling cells in the resting state and after stimulation with 11 different cytokine combinations. My observations reveal that CD4+ T cells are formed of a continuum of cell states which reflect a naïve-to-memory progression, and that as cells advance in this progression they express increasingly higher levels of cytokines, chemokines, and other effector molecules. Finally, I describe the results from a single-cell expression quantitative trait locus (sc-eQTL) mapping study performed on CD4+ T cells undergoing activation. I identify over 6,000 genes regulated by an eQTL, of which approximately 2,000 show evidence of a gene-by-environment interaction, where the eQTL effect size changes as a function of T cell activation time. Integration with GWAS associations demonstrates that immune disease loci alter the expression of genes in cis at specific stages of T cell activation. This results in the prioritization of 139 candidate disease genes which could be relevant for drug target identification. These results expand our understanding of CD4+ T cells and suggest that dysregulation of gene expression dynamics during T cell activation could be a hallmark of disease.