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

被引:0
|
作者
Kim, Samuel S. [1 ,2 ]
Truong, Buu [2 ,3 ]
Jagadeesh, Karthik [2 ]
Dey, Kushal K. [2 ,4 ]
Shen, Amber Z. [5 ]
Raychaudhuri, Soumya [6 ,7 ]
Kellis, Manolis [1 ]
Price, Alkes L. [1 ,2 ,3 ,8 ]
机构
[1] MIT, Dept Elect Engn & Comp Sci, Cambridge, MA 02139 USA
[2] Harvard TH Chan Sch Publ Hlth, Dept Epidemiol, Boston, MA 02115 USA
[3] Broad Inst MIT & Harvard, Program Med & Populat Genet, Cambridge, MA 02142 USA
[4] Sloan Kettering Inst, Mem Sloan Kettering Canc Ctr, Computat & Syst Biol Program, New York, NY USA
[5] MIT, Dept Math, Cambridge, MA USA
[6] Brigham & Womens Hosp, Dept Med, Div Genet, Boston, MA USA
[7] Harvard Med Sch, Boston, MA USA
[8] Harvard TH Chan Sch Publ Hlth, Dept Biostat, Boston, MA 02115 USA
关键词
GENOME-WIDE ASSOCIATION; CHROMATIN; BDNF; PATHOPHYSIOLOGY; TRANSCRIPTOME; HERITABILITY; ENRICHMENT; VARIANT; COMMON; GENES;
D O I
10.1038/s41467-024-44742-0
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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. This study analyzed data from human cells assayed using single-cell technologies, together with data associating genetic variants to disease, to identify fetal and brain cell types whose biologically critically influences the etiology of disease.
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页数:11
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