Federated single-cell QTL meta-analysis reveals novel disease mechanisms

Abstract Genetic effects on gene expression are often cell type-specific and obscured in bulk analyses. To resolve this context-dependent regulation, we performed a federated cis- eQTL meta-analysis across 12 PBMC datasets (2,032 individuals, 2.5 million cells). Across six immune cell types, we identified cis- eQTLs for 6,592 genes and fine-mapped 14,985 independent loci. Notably, the 42% of eQTLs that were undetected in a bulk eQTL study on 43,301 whole blood samples also showed stronger enrichment for disease GWAS loci. We further identified three genome-wide significant and 65 suggestive loci affecting the abundance of (rare) immune cell types and validated these using previously reported hematological GWAS and bulk-derived trans- eQTLs. Integrating single-cell cis -eQTLs with bulk trans- eQTLs enabled us to anchor 6,382 trans- eGenes (37.2% novel) to upstream regulators and reconstruct directed gene regulatory relationships. For example, a hemorrhoidal disease-associated variant showed a CD4+ T cell-specific cis- eQTL on BACH1 that colocalized with 45 immune and metabolic trans -eGenes. These results demonstrate the power of single-cell QTL meta-analysis in interpreting complex trait genetics.