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Functional genomics

Single-cell RNA-seq relates GWAS variants to disease risk

Nature Biotechnology volume 40, page 1574 (2022)Cite this article

While genome-wide association studies (GWAS) have identified thousands of variants associated with disease, elucidating the mechanisms through which the variants confer disease risk and the cell types where they are relevant remains a challenge. A method called sc-linker, published in Nature Genetics, integrates single-cell RNA sequencing data from multiple tissues, epigenomics, and GWAS summary statistics to identify disease-critical cell types and cellular processes for 60 diseases and complex traits.

The algorithm starts by defining gene programs — sets of genes that are characteristic for a specific cell type — for a disease state or a cellular process. The second step links these genes to single nucleotide polymorphisms (SNPs) that regulate them by combining two previously published strategies based on histone modification patterns, DNA accessibility, DNA methylation and chromatin contacts. As 95% of disease-associated SNPs lie outside coding regions, this is a non-trivial task; using tissue-specific enhancer–gene links improves the performance of sc-linker. In the last step a linkage-disequilibrium-aware regression model is applied to connect the SNP annotations to diseases or traits. The algorithm recovers known disease enrichments as well as novel ones — for example, a disease-dependent M-cell program in ulcerative colitis and a disease-specific complement cascade process in multiple sclerosis.

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  1. Nature Biotechnology https://www.nature.com/nbt

    Anne Dörr

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  1. Anne Dörr
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Correspondence to Anne Dörr.

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Dörr, A. Single-cell RNA-seq relates GWAS variants to disease risk. Nat Biotechnol 40, 1574 (2022). https://doi.org/10.1038/s41587-022-01570-1

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