Polygenic enrichment distinguishes disease associations of individual cells in single-cell RNA-seq data

Martin Jinye Zhang; Kangcheng Hou; Kushal K Dey; Saori Sakaue; Karthik A Jagadeesh; Kathryn Weinand; Aris Taychameekiatchai; Poorvi Rao; Angela Oliveira Pisco; James Zou; Bruce Wang; Michael Gandal; Soumya Raychaudhuri; Bogdan Pasaniuc; Alkes L Price

doi:10.1038/s41588-022-01167-z

Polygenic enrichment distinguishes disease associations of individual cells in single-cell RNA-seq data

Nat Genet. 2022 Oct;54(10):1572-1580. doi: 10.1038/s41588-022-01167-z. Epub 2022 Sep 1.

Authors

Martin Jinye Zhang^#^{1

2}, Kangcheng Hou^#^{3

4

5}, Kushal K Dey^{6

7}, Saori Sakaue^{7

8

9

10

11}, Karthik A Jagadeesh^{6

7}, Kathryn Weinand^{7

8

9

10

11}, Aris Taychameekiatchai^{12

13}, Poorvi Rao¹², Angela Oliveira Pisco¹⁴, James Zou^{14

15

16}, Bruce Wang¹², Michael Gandal^{17

18

19}, Soumya Raychaudhuri^{7

8

9

10

11

20}, Bogdan Pasaniuc^{21

22

23}, Alkes L Price^{24

25

26}

Affiliations

¹ Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA. [email protected].
² Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA. [email protected].
³ Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA. [email protected].
⁴ Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA. [email protected].
⁵ Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA. [email protected].
⁶ Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
⁷ Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
⁸ Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA.
⁹ Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
¹⁰ Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
¹¹ Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
¹² Department of Medicine and Liver Center, University of California, San Francisco, San Francisco, CA, USA.
¹³ Developmental and Stem Cell Biology Graduate Program, University of California, San Francisco, San Francisco, CA, USA.
¹⁴ Chan Zuckerberg Biohub, San Francisco, CA, USA.
¹⁵ Department of Electrical Engineering, Stanford University, Palo Alto, CA, USA.
¹⁶ Department of Biomedical Data Science, Stanford University, Palo Alto, CA, USA.
¹⁷ Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
¹⁸ Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
¹⁹ Program in Neurobehavioral Genetics, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
²⁰ Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK.
²¹ Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA. [email protected].
²² Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA. [email protected].
²³ Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA. [email protected].
²⁴ Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA. [email protected].
²⁵ Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA. [email protected].
²⁶ Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA. [email protected].

^# Contributed equally.

Abstract

Single-cell RNA sequencing (scRNA-seq) provides unique insights into the pathology and cellular origin of disease. We introduce single-cell disease relevance score (scDRS), an approach that links scRNA-seq with polygenic disease risk at single-cell resolution, independent of annotated cell types. scDRS identifies cells exhibiting excess expression across disease-associated genes implicated by genome-wide association studies (GWASs). We applied scDRS to 74 diseases/traits and 1.3 million single-cell gene-expression profiles across 31 tissues/organs. Cell-type-level results broadly recapitulated known cell-type-disease associations. Individual-cell-level results identified subpopulations of disease-associated cells not captured by existing cell-type labels, including T cell subpopulations associated with inflammatory bowel disease, partially characterized by their effector-like states; neuron subpopulations associated with schizophrenia, partially characterized by their spatial locations; and hepatocyte subpopulations associated with triglyceride levels, partially characterized by their higher ploidy levels. Genes whose expression was correlated with the scDRS score across cells (reflecting coexpression with GWAS disease-associated genes) were strongly enriched for gold-standard drug target and Mendelian disease genes.

Publication types

Research Support, N.I.H., Extramural

MeSH terms

Gene Expression Profiling / methods
Genome-Wide Association Study*
Multifactorial Inheritance / genetics
RNA-Seq
Single-Cell Analysis* / methods
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Substances

Triglycerides

Abstract

Publication types

MeSH terms

Substances

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