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

Nat Genet. 2022 Oct;54(10):1479-1492. doi: 10.1038/s41588-022-01187-9. Epub 2022 Sep 29.

Abstract

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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Depressive Disorder, Major* / genetics
  • Genetic Predisposition to Disease
  • Genome-Wide Association Study*
  • Human Genetics
  • Humans
  • Polymorphism, Single Nucleotide / genetics
  • RNA
  • gamma-Aminobutyric Acid

Substances

  • gamma-Aminobutyric Acid
  • RNA