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Identifying independent causal cell types for human diseases and risk variants
Artem Kim1, Zixuan Eleanor Zhang1, Come Legros1
1Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Cell Genomics
|August 14, 2026
Summary
New methods, cell-type fine-mapping (CT-FM) and CT-FM-SNP, identify cell types driving complex traits. These approaches explain significant heritability and reveal multiple cellular mechanisms for diseases like schizophrenia.
Area of Science:
- Genomics
- Computational Biology
- Human Genetics
Background:
- Genome-wide association studies (GWASs) link genetic variants to complex traits.
- Disease-associated variants often reside in regulatory elements within specific cell types.
- Understanding cell-type specific regulation is crucial for complex trait genetics.
Purpose of the Study:
- Introduce novel probabilistic methods, cell-type fine-mapping (CT-FM) and CT-FM-SNP.
- Infer independent causal cell-type sets for complex traits and identify causal variants.
- Dissect the cellular architecture underlying complex human traits.
Main Methods:
- Developed CT-FM to analyze cell-type sharing in regulatory elements across multiple GWASs.
- Applied CT-FM-SNP to fine-map non-coding variants to specific cell types for UK Biobank traits.
- Utilized probabilistic inference to account for cell-type specific regulatory element activity.
Main Results:
- CT-FM identified 79 independent cell-type sets, explaining 39.0% ± 1.8% of trait heritability across 63 GWASs.
- Discovered multiple independent cellular mechanisms for 14 complex traits, including height and schizophrenia.
- CT-FM-SNP assigned high-confidence causal cell types to 3,091 variant-trait pairs, revealing context-dependent pleiotropy.
Conclusions:
- CT-FM and CT-FM-SNP provide a robust framework for dissecting the cellular basis of complex traits.
- These methods enhance the interpretation of GWAS findings by pinpointing cell-type specific effects.
- The findings highlight the importance of cell-type resolution in understanding genetic contributions to human diseases and traits.
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