Identifying independent causal cell types for human diseases and risk variants.

Genome-wide association studies (GWASs) have shown that disease-associated variants are concentrated in candidate regulatory elements (cREs) from disease-relevant cell types. Here, we introduce cell-type fine-mapping (CT-FM) and CT-FM-SNP, probabilistic methods that account for cRE sharing across cell types to infer independent causal cell-type sets for complex traits and candidate causal variants. Applying CT-FM to 63 GWASs using 924 cRE annotations, we inferred 79 independent cell-type sets explaining 39.0% ± 1.8% of trait SNP heritability and identified 14 traits with multiple independent cellular mechanisms, including height, schizophrenia, and autoimmune diseases. Applying CT-FM-SNP to 39 UK Biobank traits, we assigned high-confidence causal cell types to 3,091 candidate non-coding variant-trait pairs. Most variants appeared to act through a single cell-type set, whereas pleiotropic variants often acted through different cell types depending on the phenotype context. Together, CT-FM and CT-FM-SNP provide a framework for dissecting the cellular architecture of complex traits.