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Cell-type-specific cis-eQTLs in eight human brain cell types identify novel risk genes for psychiatric and neurological disorders

Abstract

To date, most expression quantitative trait loci (eQTL) studies, which investigate how genetic variants contribute to gene expression, have been performed in heterogeneous brain tissues rather than specific cell types. In this study, we performed an eQTL analysis using single-nuclei RNA sequencing from 192 individuals in eight brain cell types derived from the prefrontal cortex, temporal cortex and white matter. We identified 7,607 eGenes, a substantial fraction (46%, 3,537/7,607) of which show cell-type-specific effects, with strongest effects in microglia. Cell-type-level eQTLs affected more constrained genes and had larger effect sizes than tissue-level eQTLs. Integration of brain cell type eQTLs with genome-wide association studies (GWAS) revealed novel relationships between expression and disease risk for neuropsychiatric and neurodegenerative diseases. For most GWAS loci, a single gene co-localized in a single cell type, providing new clues into disease etiology. Our findings demonstrate substantial contrast in genetic regulation of gene expression among brain cell types and reveal potential mechanisms by which disease risk genes influence brain disorders.

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Fig. 1: Study summary.
Fig. 2: cis-eQTL discoveries.
Fig. 3: Cell-type-specific genetic effects on gene expression.
Fig. 4: Co-localization results.
Fig. 5: Epigenomic overlap of GWAS SNPs around co-localized genes.

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Data availability

A shinyApp to browse the result of this study is available at https://malhotralab.shinyapps.io/brain_cell_type_eqtl/. The full eQTL summary statistics are available on Zenodo at https://doi.org/10.5281/zenodo.5543734. Single-nuclei RNA-seq data and genotype data for the Roche datasets have been deposited at the European Genome-phenome Archive, which is hosted by the European Bioinformatics Institute and the Centre for Genomic Regulation, under accession number EGAS00001006345. Genotypes for the ROSMAP datasets are available at https://www.synapse.org/#!Synapse:syn10901595. Single-nuclei RNA-seq data for the ROSMAP datasets are available at https://www.synapse.org/#!Synapse:syn18485175, https://www.synapse.org/Portal.html#!Synapse:syn3157322, https://adknowledgeportal.synapse.org/Explore/Studies?Study=syn21670836 and https://www.synapse.org/#!Synapse:syn16780177. GRCh38 reference human genome: http://ftp.ensembl.org/pub/release-96/fasta/homo_sapiens/dna/. Ensembl Homo_sapiens GRCh38.96 reference annotation: http://ftp.ensembl.org/pub/release-96/gtf/homo_sapiens/. Ensembl Homo_sapiens GRCh38.91 reference annotation: http://ftp.ensembl.org/pub/release-91/gtf/homo_sapiens/. GWAS summary statistics are available here: Alzheimer’s disease: http://ftp.ebi.ac.uk/pub/databases/gwas/summary_statistics/GCST90012001-GCST90013000/GCST90012877/GCST90012877_buildGRCh37.tsv.gz; Parkinson’s disease: https://drive.google.com/drive/folders/10bGj6HfAXgl-JslpI9ZJIL_JIgZyktxn; multiple sclerosis: https://imsgc.net/?page_id=31; and schizophrenia: https://www.med.unc.edu/pgc/download-results.

Code availability

The code used to perform the analysis described in this study is available at https://jbryois.github.io/snRNA_eqtl/.

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Acknowledgements

The results presented here are, in whole or in part, based on data obtained from the AD Knowledge Portal (https://adknowledgeportal.org). Study data were provided by the Rush Alzheimer’s Disease Center, Rush University Medical Center. Data collection was supported through funding by National Institute on Aging grants P30AG10161 (ROS), R01AG15819 (ROSMAP; genomics and RNA-seq), R01AG17917 (MAP), R01AG30146, R01AG36042 (5hC methylation, ATAC-seq), RC2AG036547 (H3K9Ac), R01AG36836 (RNA-seq), R01AG48015 (monocyte RNA-seq) RF1AG57473 (single-nuclei RNA-seq), U01AG32984 (genomic and whole-exome sequencing), U01AG46152 (ROSMAP AMP-AD, targeted proteomics), U01AG46161 (TMT proteomics), U01AG61356 (whole-genome sequencing, targeted proteomics, ROSMAP AMP-AD), the Illinois Department of Public Health (ROSMAP) and the Translational Genomics Research Institute (genomic). Additional phenotypic data can be requested at www.radc.rush.edu.

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J.B. and D.M. designed the study and wrote the manuscript. J.B. mapped raw sequencing data, performed quality control on the AD datasets and performed the eQTL, Coloc and fine-mapping analysis. D.C. generated single-nuclei RNA-seq data on AD and MS samples. W.M. performed quality control on the MS dataset and provided critical statistical comments. L.F. provided AD samples. A.W., E.U., E.N., M.M., G.C.-B. and S.A. provided MS samples. W.O., V.A.I. and S.S. genotyped MS and a subset of AD samples and performed imputation of the genotype data. V.M. and P.D.J. provided single-nuclei RNA-seq and whole-genome sequencing data on a subset of the AD samples.

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Correspondence to Julien Bryois or Dheeraj Malhotra.

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J.B., D.C., W.M., L.F., E.U., W.O., V.A.I., S.S. and D.M. are employees of Roche/Genentech. The authors received internal funding for this work. All other authors declare no competing interests.

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Nature Neuroscience thanks Jason Stein and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Bryois, J., Calini, D., Macnair, W. et al. Cell-type-specific cis-eQTLs in eight human brain cell types identify novel risk genes for psychiatric and neurological disorders. Nat Neurosci 25, 1104–1112 (2022). https://doi.org/10.1038/s41593-022-01128-z

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