Single-cell eQTL models reveal dynamic T cell state dependence of disease loci

Abstract

Non-coding genetic variants may cause disease by modulating gene expression. However, identifying these expression quantitative trait loci (eQTLs) is complicated by gene-regulation differences across fluid functional cell states within cell types. These states—for example, neurotransmitter-driven programs in astrocytes or perivascular fibroblast differentiation—are obscured in eQTL studies that aggregate cells1,2. Here, we modeled eQTLs at single-cell resolution in one complex cell type: memory T cells. Using >500,000 unstimulated memory T cells from 259 Peruvians, we show that around one-third of 6,511 cis-eQTLs had effects mediated by continuous multimodally defined cell states, such as cytotoxicity and regulatory capacity. In some loci, independent eQTL variants had opposing cell-state relationships. Autoimmune variants were enriched in cell-state-dependent eQTLs, including rheumatoid-arthritis risk variants near ORMDL3 and CTLA4, arguing that cell-state context is crucial to understanding potential eQTL pathogenicity. Moreover, continuous cell states explained more eQTL variation than conventional discrete categories, such as CD4+/CD8+, suggesting that modeling eQTLs and cell states at single-cell resolution can expand insight into gene regulation in functionally heterogeneous cell types.