An atlas of single-cell eQTLs dissects autoimmune disease genes and identifies novel drug classes for treatment
Most variants identified from genome-wide association studies (GWASs) are non-coding and regulate gene expression. However, many risk loci fail to colocalize with expression quantitative trait loci (eQTLs), potentially due to limited GWAS and eQTL analysis power or cellular heterogeneity. Population-scale single-cell RNA-sequencing (scRNA-seq) datasets are emerging, enabling mapping of eQTLs in different cell types (sc-eQTLs). Compared to eQTL data from bulk tissues (bk-eQTLs), sc-eQTL datasets are smaller. We propose a joint model of bk-eQTLs as a weighted sum of sc-eQTLs (JOBS) from constituent cell types to improve power. Applying JOBS to One1K1K and eQTLGen data, we identify 586% more eQTLs, matching the power of 4× the sample sizes of OneK1K. Integrating sc-eQTLs with GWAS data creates an atlas for 14 immune-mediated disorders, colocalizing 29.9% or 32.2% more loci than using sc-eQTL or bk-eQTL alone. Extending JOBS, we develop a drug-repurposing pipeline and identify novel drugs validated by real-world data.
Authors
- Chachrit Khunsriraksakul (ORCID: https://orcid.org/0000-0001-5131-1229)
- Bibo Jiang (ORCID: https://orcid.org/0000-0001-8336-9302)
- Dieyi Chen
- Galen Foulke (ORCID: https://orcid.org/0000-0002-4390-5200)
- Havell Markus (ORCID: https://orcid.org/0000-0001-7060-4350)
- Nancy J. Olsen (ORCID: https://orcid.org/0000-0002-6588-3364)
- Dajiang J. Liu (ORCID: https://orcid.org/0000-0001-6553-858X)
- Lida Wang (ORCID: https://orcid.org/0000-0002-7990-7347)
- Fang Chen (ORCID: https://orcid.org/0000-0003-3108-8204)
- Shuang Gao (ORCID: https://orcid.org/0000-0002-0191-1522)
- Laura Carrel (ORCID: https://orcid.org/0000-0002-5868-4228)
- Siyuan Chen (ORCID: https://orcid.org/0009-0001-8475-0305)
- Fan Zhang (ORCID: https://orcid.org/0000-0002-2858-0698)
Institutions
- Pennsylvania State University (US)
- Department of Public Health (MM)
- Penn State Milton S. Hershey Medical Center (US)
Publication Details
- Journal
- Cell Genomics
- Published
- 2025-03-29
- DOI
- https://doi.org/10.1016/j.xgen.2025.100820
- Citations
- 3
- Primary Topic
- T-cell and B-cell Immunology
- Type
- article
- Field-Weighted Citation Impact
- 2.39
Funders
- National Institutes of Health
- National Heart, Lung, and Blood Institute
- National Human Genome Research Institute
- National Institute of General Medical Sciences
- National Institute of Allergy and Infectious Diseases
- National Institute of Environmental Health Sciences