Leveraging mouse chromatin data for heritability enrichment informs common disease architecture and reveals cortical layer contributions to schizophrenia

Abstract

<jats:p>Genome-wide association studies have implicated thousands of non-coding variants across human phenotypes. However, they cannot directly inform the cellular context in which disease-associated variants act. Here, we use open chromatin profiles from discrete mouse cell populations to address this challenge. We applied stratified linkage disequilibrium score regression and evaluated heritability enrichment in 64 genome-wide association studies, emphasizing schizophrenia. We provide evidence that mouse-derived human open chromatin profiles can serve as powerful proxies for difficult to obtain human cell populations, facilitating the illumination of common disease heritability enrichment across an array of human phenotypes. We demonstrate signatures from discrete subpopulations of cortical excitatory and inhibitory neurons are significantly enriched for schizophrenia heritability with maximal enrichment in discrete cortical layer V excitatory neurons. We also show differences between schizophrenia and bipolar disorder are concentrated in excitatory neurons in layers II-III, IV, V as well as the dentate gyrus. Finally, we use these data to fine-map variants in 177 schizophrenia loci, nominating variants in 104/177 loci, and place them in the cellular context where they may modulate risk.</jats:p>

Defining the Genetic, Genomic, Cellular, and Diagnostic Architectures of Psychiatric Disorders

“…MDD risk was clustered in cortical interneurons and embryonic midbrain neurons (these findings replicate in multiple new datasets, Bryois et al, 2019). Orthogonal functional genomic data are consistent with these findings, as open chromatin in neuronal nuclei (NeuN+) from 14 regions from human adult brain showed significant enrichment of SCZ GWAS findings in cortex and striatum (Fullard et al, 2018), and open chromatin in mouse cortical layers showed SCZ enrichment in excitatory neurons in layer V (Hook and McCallion, 2018).…”

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

“…We identified 168 significant disease-cell type pairs (FDR < 5% for positive τ * conditional on other annotations; Table 1, Table 2, Figure 2A, Table S15). Consistent with previous genetic studies 8,17,19,39 , we identified strong enrichments of excitatory neurons in SCZ and bipolar disorder (genetic correlation = 0.70) (Figure 2A). Although an analysis of mouse scATAC-seq identified a significant enrichment of excitatory neurons in SCZ cases vs. bipolar cases 19 , we did not replicate this finding ( p = 0.66 for positive τ *; Table S15).…”

“…We note 4 key distinctions between our work and previous studies identifying disease-critical tissues and cell types [4][5][6][7][8]10,12,[18][19][20][21] . First, we explicitly compared results from scATAC-seq vs.…”

“…With the emergence of single-cell profiling of diverse tissues and cell types [13][14][15][16][17] , several studies have integrated GWAS data with single-cell chromatin accessibility (scATAC-seq) [16][17][18][19] and singlecell gene expression (scRNA-seq) 10,20,21 . However, compared to scRNA-seq data, scATAC-seq data has been less well-studied for identifying disease-critical cell types.…”

Cardiac cell type–specific gene regulatory programs and disease risk association

“…Noncoding genetic variants contributing to risk of complex diseases are enriched within cCREs in a tissue and cell type-dependent manner (24,(44)(45)(46)(47). To examine the enrichment of cardiovascular disease variants within cCREs active in cardiac cell types, we performed cell type-stratified LD (linkage disequilibrium) score regression analysis (48) using genome-wide association study (GWAS) summary statistics for cardiovascular diseases (Fig.…”