Leveraging single-cell ATAC-seq and RNA-seq to identify disease-critical fetal and adult brain cell types

Samuel S. Kim (), Buu Truong (), Karthik Jagadeesh, Kushal K. Dey, Amber Z. Shen, Soumya Raychaudhuri, Manolis Kellis and Alkes L. Price ()
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Samuel S. Kim: Massachusetts Institute of Technology
Buu Truong: Harvard T.H. Chan School of Public Health
Karthik Jagadeesh: Harvard T.H. Chan School of Public Health
Kushal K. Dey: Harvard T.H. Chan School of Public Health
Amber Z. Shen: Massachusetts Institute of Technology
Soumya Raychaudhuri: Brigham and Women’s Hospital and Harvard Medical School
Manolis Kellis: Massachusetts Institute of Technology
Alkes L. Price: Massachusetts Institute of Technology

Nature Communications, 2024, vol. 15, issue 1, 1-11

Abstract: Abstract Prioritizing disease-critical cell types by integrating genome-wide association studies (GWAS) with functional data is a fundamental goal. Single-cell chromatin accessibility (scATAC-seq) and gene expression (scRNA-seq) have characterized cell types at high resolution, and studies integrating GWAS with scRNA-seq have shown promise, but studies integrating GWAS with scATAC-seq have been limited. Here, we identify disease-critical fetal and adult brain cell types by integrating GWAS summary statistics from 28 brain-related diseases/traits (average N = 298 K) with 3.2 million scATAC-seq and scRNA-seq profiles from 83 cell types. We identified disease-critical fetal (respectively adult) brain cell types for 22 (respectively 23) of 28 traits using scATAC-seq, and for 8 (respectively 17) of 28 traits using scRNA-seq. Significant scATAC-seq enrichments included fetal photoreceptor cells for major depressive disorder, fetal ganglion cells for BMI, fetal astrocytes for ADHD, and adult VGLUT2 excitatory neurons for schizophrenia. Our findings improve our understanding of brain-related diseases/traits and inform future analyses.

Date: 2024
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DOI: 10.1038/s41467-024-44742-0

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