Abstract
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.
Highlights
Despite infiltrating immune cells having an essential function in human disease and patients’ responses to treatments, mechanisms influencing variability in infiltration patterns remain unclear
To describe immune content from bulk RNA-seq samples, we used two central algorithms: xCell[13] and CIBERSORT14. Both algorithms include slightly different cell types and reference gene sets for estimation. xCell relies on a modification of single sample gene-set enrichment analysis to estimate cell-type scores of 64 immune and stroma cell types, including various subtypes of CD8+ T cells, CD4+ T cells, B cells, dendritic cells, macrophage polarization states, and other innate immune cells
Even after a Benjamini-Hochberg false discovery rate (FDR) correction[21], we found that 183/189 infiltration phenotypes were significantly correlated with at least one principal component (FDR < 0.1)
Summary
Despite infiltrating immune cells having an essential function in human disease and patients’ responses to treatments, mechanisms influencing variability in infiltration patterns remain unclear. The immune system extends beyond peripheral blood, as infiltrating immune cells comprise a subset of the diverse cell types that compose bulk tissues and organs The variability in this infiltration across individuals and between tissues has not been documented and the mechanisms enabling such variation in baseline infiltration have not been elucidated. Large-scale sequencing efforts such as the Genotype-Tissue Expression (GTEx) project[16] have enabled a detailed exploration of the links between genomic and transcriptomic variations across different tissues Together, these cell-type estimation methods can be utilized in synergy with massive bulk sequenced data sets to infer cellular heterogeneity and achieve statistically well-powered associations that uncover the intrinsic drivers of heterogeneity[17,18,19]. We identify several genetic and non-genetic associations with immune cell patterns, which can serve as leading candidates for understanding the basic biology behind tissue infiltration
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