Demographic and genetic factors influence the abundance of infiltrating immune cells in human tissues.

Despite infiltrating immune cells having an essential function in human disease and patients’ responses to treatments, mechanisms influencing variability in infiltration patterns remain unclear. Here, using bulk RNA-seq data from 46 tissues in the Genotype-Tissue Expression project, we apply cell-type deconvolution algorithms to evaluate the immune landscape across the healthy human body. We discover that 49 of 189 infiltration-related phenotypes are associated with either age or sex (FDR < 0.1). Genetic analyses further show that 31 infiltration-related phenotypes have genome-wide significant associations (iQTLs) (P < 5.0 × 10−8), with a significant enrichment of same-tissue expression quantitative trait loci in suggested iQTLs (P < 10−5). Furthermore, we find an association between helper T cell content in thyroid tissue and a COMMD3/DNAJC1 regulatory variant (P = 7.5 × 10−10), which is associated with thyroiditis in other cohorts. Together, our results identify key factors influencing inter-individual variability of immune infiltration, to provide insights on potential therapeutic targets. Immune infiltration provides critical information for health and disease, yet it is unclear what factors influence infiltration levels. Here, the authors analyze human tissue transcriptomes from the Genotype-Tissue Expression project to find infiltration patterns regulated by age, sex and host genetic information.