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Leveraging single-cell ATAC-seq and RNA-seq to identify disease-critical fetal and adult brain cell types.
Kim, Samuel S; Truong, Buu; Jagadeesh, Karthik; Dey, Kushal K; Shen, Amber Z; Raychaudhuri, Soumya; Kellis, Manolis; Price, Alkes L.
Afiliación
  • Kim SS; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, UK. samuelkim484@gmail.com.
  • Truong B; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, UK. samuelkim484@gmail.com.
  • Jagadeesh K; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, UK. btruong@broadinstitute.org.
  • Dey KK; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, UK. btruong@broadinstitute.org.
  • Shen AZ; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, UK.
  • Raychaudhuri S; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, UK.
  • Kellis M; Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Price AL; Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA, USA.
Nat Commun ; 15(1): 563, 2024 Jan 17.
Article en En | MEDLINE | ID: mdl-38233398
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.
Asunto(s)

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Trastorno Depresivo Mayor / Secuenciación de Inmunoprecipitación de Cromatina Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Nat Commun Asunto de la revista: BIOLOGIA / CIENCIA Año: 2024 Tipo del documento: Article

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Trastorno Depresivo Mayor / Secuenciación de Inmunoprecipitación de Cromatina Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Nat Commun Asunto de la revista: BIOLOGIA / CIENCIA Año: 2024 Tipo del documento: Article