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

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  • Samuel S. Kim

    (Massachusetts Institute of Technology
    Harvard T.H. Chan School of Public Health)

  • Buu Truong

    (Harvard T.H. Chan School of Public Health
    Broad Institute of MIT and Harvard)

  • Karthik Jagadeesh

    (Harvard T.H. Chan School of Public Health)

  • Kushal K. Dey

    (Harvard T.H. Chan School of Public Health
    Memorial Sloan Kettering Cancer Center)

  • 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
    Harvard T.H. Chan School of Public Health
    Broad Institute of MIT and Harvard
    Harvard T.H. Chan School of Public Health)

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.

Suggested Citation

  • Samuel S. Kim & Buu Truong & Karthik Jagadeesh & Kushal K. Dey & Amber Z. Shen & Soumya Raychaudhuri & Manolis Kellis & Alkes L. Price, 2024. "Leveraging single-cell ATAC-seq and RNA-seq to identify disease-critical fetal and adult brain cell types," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-44742-0
    DOI: 10.1038/s41467-024-44742-0
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