Impact of Genetic Polymorphisms on Human Immune Cell Gene Expression

While many genetic variants have been associated with risk for human diseases, how these variants affect gene expression in various cell types remains largely unknown. To address this gap, the DICE (database of immune cell expression, expression quantitative trait loci [eQTLs], and epigenomics) project was established. Considering all human immune cell types and conditions studied, we identified cis-eQTLs for a total of 12,254 unique genes, which represent 61% of all protein-coding genes expressed in these cell types. Strikingly, a large fraction (41%) of these genes showed a strong cis-association with genotype only in a single cell type. We also found that biological sex is associated with major differences in immune cell gene expression in a highly cell-specific manner. These datasets will help reveal the effects of disease risk-associated genetic polymorphisms on specific immune cell types, providing mechanistic insights into how they might influence pathogenesis (https://dice-database.org). [Display omitted] •Cis-eQTLs for 12,254 unique genes were identified in 13 human immune cell types•41% of eGenes showed strong cis-association with genotype in a single cell type•GWAS variants were linked to cell types where their effects are most pronounced•Biological sex was associated with major differences in immune cell gene expression Surveying gene expression and SNP genotypes across immune cell types from healthy humans reveals cis-eQTLs affecting over half of all expressed genes and demonstrates that variant effects often manifest in cell types other than those with highest gene expression.