Common schizophrenia risk variants are enriched in open chromatin regions of human glutamatergic neurons
Nat Commun. 2020-11-04;11(1):5581.
- The chromatin landscape of human brain cells encompasses key information to understanding brain function. Here we use ATAC-seq to profile the chromatin structure in four distinct populations of cells (glutamatergic neurons, GABAergic neurons, oligodendrocytes, and microglia/astrocytes) from three different brain regions (anterior cingulate cortex, dorsolateral prefrontal cortex, and primary visual cortex) in human postmortem brain samples. We find that chromatin accessibility varies greatly by cell type and, more moderately, by brain region, with glutamatergic neurons showing the largest regional variability. Transcription factor footprinting implicates cell-specific transcriptional regulators and infers cell-specific regulation of protein-coding genes, long intergenic noncoding RNAs and microRNAs. In vivo transgenic mouse experiments validate the cell type specificity of several of these human-derived regulatory sequences. We find that open chromatin regions in glutamatergic neurons are enriched for neuropsychiatric risk variants, particularly those associated with schizophrenia. Integration of cell-specific chromatin data with a bulk tissue study of schizophrenia brains increases statistical power and confirms that glutamatergic neurons are most affected. These findings illustrate the utility of studying the cell-type-specific epigenome in complex tissues like the human brain, and the potential of such approaches to better understand the genetic basis of human brain function.
- Consortium data used in this publication
- The ATAC-seq data generated as part of this publication have been deposited in Gene Expression Omnibus and are accessible through GEO Series accession number “GSE143666”. Further, UCSC tracks and downloads are provided at our webpage http://icahn.mssm.edu/boca2. The following reference datasets were downloaded from for the purpose of comparison with our study: https://www.synapse.org/#!Synapse:syn5584622, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE96614, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?token=ofwzsggybrihviv&acc=GSE96949, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE108066. The following online resources and databases were used: dbSNP: https://www.ncbi.nlm.nih.gov/snp, REMC: http://www.roadmapepigenomics.org, MSigDB (GO, KEGG, and Biocarta gene sets): https://www.gsea-msigdb.org, lincRNA and microRNA from FANTOM: https://fantom.gsc.riken.jp, and miRBase: http://www.mirbase.org. Summary statistics are available from the following links: “Complex Trait Genetics Lab [ctg.cncr.nl/software/summary_statistics]”, “Coronary Artery Disease [cardiogramplusc4d.org]”, “Genetic Investigation of ANthropometric Traits [portals.broadinstitute.org/collaboration/giant], “International Inflammatory Bowel Disease Genetics Consortium [ibdgenetics.org]”, “The Psychiatric Genomics Consortium [med.unc.edu/pgc]”, “Social Science Genetic Association Consortium [thessgac.org/data]”. All other relevant data supporting the key findings of this study are available within the article and its Supplementary Information files or from the corresponding author upon reasonable request. A reporting summary for this article is available as a Supplementary Information file.
- DSR611RIB, DSR341UVB, DSR357LJU, DSR223FVD, DSR936UDZ, DSR539KBS, DSR952CDU, DSR171UQM, DSR401CEU, DSR581SFM, DSR493OBM, DSR849HLJ, DSR024FFE, DSR654KKD, DSR852BCS, DSR765ZAW, DSR423GJG, DSR819JVG, DSR271IFB, DSR640UOX, DSR200ZHE