Polygenic enrichment distinguishes disease associations of individual cells in single-cell RNA-seq data
Year: 2022
Type: article
Abstract: Gene expression at the individual cell-level resolution, as quantified by single-cell RNA-sequencing (scRNA-seq), can provide unique insights into the pathology and cellular origin of diseases and complex traits. Here, we introduce single-cell Disease Relevance Score (scDRS), an approach that links scRNA-seq with polygenic risk of disease at individual cell resolution; scDRS identifies individual cells that show excess expression levels for genes in a disease-specific gene set constructed from GWAS data. We determined via simulations that scDRS is well-calibrated and powerful in identifying individual cells associated to disease. We applied scDRS to GWAS data from 74 diseases and complex traits (average N=341K) in conjunction with 16 scRNA-seq data sets spanning 1.3 million cells from 31 tissues and organs. At the cell type level, scDRS broadly recapitulated known links between classical cell types and disease, and also produced novel biologically plausible findings. At the individual cell level, scDRS identified subpopulations of disease-associated cells that are not captured by existing cell type labels, including subpopulations of CD4+ T cells associated with inflammatory bowel disease, partially characterized by their effector-like states; subpopulations of hippocampal CA1 pyramidal neurons associated with schizophrenia, partially characterized by their spatial location at the proximal part of the hippocampal CA1 region; and subpopulations of hepatocytes associated with triglyceride levels, partially characterized by their higher ploidy levels. At the gene level, we determined that genes whose expression across individual cells was correlated with the scDRS score (thus reflecting co-expression with GWAS disease genes) were strongly enriched for gold-standard drug target and Mendelian disease genes.
Source: Nature Genetics
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
Funders: U.S. Department of Health and Human Services, National Institutes of Health, Medical Research Council, National Institute on Aging, National Institute of Mental Health, National Human Genome Research Institute, National Institute of Allergy and Infectious Diseases, National Institute of Arthritis and Musculoskeletal and Skin Diseases, Eunice Kennedy Shriver National Institute of Child Health and Human Development
Awards: G1021745955, G1607541870, RA-SLE Molecular Deconstruction Leadership Center, G1728779317, G1926670083, G1941721978, G1984340220, G223491490, G3107071911, G3177290858, Isoform-level probabilistic transcriptome-wide association to undercover neurogenetic mechanisms underlying complex psychiatric traits, G378455773, G4320204098, Leveraging functional data to predict disease risk in multi-ethnic populations, G5620410560, G5850737185, G6186324268, New approaches for leveraging single-cell data to identify disease-critical genes and gene sets, G6439312160, Functionally specialized components of disease heritability in ENCODE data, Observation Stays and Readmissions for Older Adults: Implications for Medicare Policies, Defining the influence of RA genetic susceptibility factors on T cell antigen specificity and functional state, Single cell atlas as a roadmap for interpreting human genetic variation in complex disease, G7523544532, Population-level and mechanistic dissection of 17q21 structural variant association with psychiatric traits, G7994220604, G9000247532, G9000286330, Integrative analysis of high dimensional tissue molecular data to define key biological systems in autoimmune diseases (SBC), Predoctoral Training in Developmental Biology, Cellular and developmental genetic regulation of 3' isoform diversity in the human brain and its contribution to neuropsychiatric disorders, Statistical methods to localize disease heritability and identify biological mechanisms, Training in Bioinformatics and Integrative Genomics, Functional and population genetic architectures of complex disease, Differentiation of immune cells and fibrobalsts in inflamed tissue in RA and SLE, Integrating case-control transcriptomic and genetic data in admixed individuals to identify disease genes for schizophrenia and bipolar disorder, Predicting the impact of genetic variants, genes and pathways on human Disease, G932915660
OpenAlex ID: W4294051824