Identifying disease-critical cell types and cellular processes by integrating single-cell RNA-sequencing and human genetics

Autor: Karthik A, Jagadeesh, Kushal K, Dey, Daniel T, Montoro, Rahul, Mohan, Steven, Gazal, Jesse M, Engreitz, Ramnik J, Xavier, Alkes L, Price, Aviv, Regev
Rok vydání: 2021
Předmět:
Zdroj: Nature genetics. 54(10)
ISSN: 1546-1718
Popis: Genome-wide association studies provide a powerful means of identifying loci and genes contributing to disease, but in many cases, the related cell types/states through which genes confer disease risk remain unknown. Deciphering such relationships is important for identifying pathogenic processes and developing therapeutics. In the present study, we introduce sc-linker, a framework for integrating single-cell RNA-sequencing, epigenomic SNP-to-gene maps and genome-wide association study summary statistics to infer the underlying cell types and processes by which genetic variants influence disease. The inferred disease enrichments recapitulated known biology and highlighted notable cell-disease relationships, including γ-aminobutyric acid-ergic neurons in major depressive disorder, a disease-dependent M-cell program in ulcerative colitis and a disease-specific complement cascade process in multiple sclerosis. In autoimmune disease, both healthy and disease-dependent immune cell-type programs were associated, whereas only disease-dependent epithelial cell programs were prominent, suggesting a role in disease response rather than initiation. Our framework provides a powerful approach for identifying the cell types and cellular processes by which genetic variants influence disease.
Databáze: OpenAIRE
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