Chromatin domain alterations linked to 3D genome organization in a large cohort of schizophrenia and bipolar disorder brains

Abstract

Chromosomal organization, scaling from the 147-base pair (bp) nucleosome to megabase-ranging domains encompassing multiple transcriptional units, including heritability loci for psychiatric traits, remains largely unexplored in the human brain. In this study, we constructed promoter- and enhancer-enriched nucleosomal histone modification landscapes for adult prefrontal cortex from H3-lysine 27 acetylation and H3-lysine 4 trimethylation profiles, generated from 388 controls and 351 individuals diagnosed with schizophrenia (SCZ) or bipolar disorder (BD) (n = 739). We mapped thousands of cis-regulatory domains (CRDs), revealing fine-grained, 10⁴-10⁶-bp chromosomal organization, firmly integrated into Hi-C topologically associating domain stratification by open/repressive chromosomal environments and nuclear topography. Large clusters of hyper-acetylated CRDs were enriched for SCZ heritability, with prominent representation of regulatory sequences governing fetal development and glutamatergic neuron signaling. Therefore, SCZ and BD brains show coordinated dysregulation of risk-associated regulatory sequences assembled into kilobase- to megabase-scaling chromosomal domains.

Figure 1:. Histone peak profiling in 739 ChIP-Seq datasets from two studies consisting of SCZ, BD and control subjects

(A) (left) Datasets and studies; study-1, FANS isolated PFC NeuN⁺ nuclei: H3K4me3 (purple), H3K27ac (blue). study-2, total (non-sorted) tissue PFC nuclei: H3K27ac (green). (middle) Bar plot, genomic coverage (%) of each ChIP-Seq dataset. Numbers of subjects as indicated and bar plot to show % of regulatory elements in each dataset. (B) Bar plots (colored sectors marking significantly different peaks) showing the proportion of differentially regulated histone peaks in our four datasets of case control comparisons, as indicated. See also Figure S2 for overlap of disease-sensitive peaks across the various H3K27ac datasets (C) Spearman correlation of effect sizes of H3K27ac NeuN+ peaks altered (*) in SCZ study-1, compared with effect sizes for corresponding peaks in SCZ study-2 subjects with bulk PFC Tissue as input. Green dots mark H3K27ac NeuN+ at FDR < 5%. P value (p), Spearman rank correlation test. (D) Meta-analysis of H3K27ac NeuN+ and H3K27ac Tissue: The bar shows differential SCZ-specific peaks of H3K27ac Meta NeuN+ at FDR < 5%. Volcano plot of differentially modified H3K27ac Meta NeuN+ peaks by fixed effect model. Orange dots represent peaks with FDR < 5%. P values for t-test of limma pipeline, with FDR correction (Benjamini & Hochberg) across all peaks. (E) (top) Visualization of the hyperacetylated region covering STX1A gene. H3K27ac NeuN+ ChIP-Seq landscape from (gray) controls and (blue) SCZ individuals. (bottom) Differential peak profile, horizontal bars demarcate linear extension of disease-sensitive peak population for each of the three H3K27ac datasets, as indicated (blue) H3K27ac NeuN+ study 1, (green) H3K27ac Tissue study-2, (orange) H3K27ac NeuN+ meta-analysis.

Figure 2:. Enrichment of common SCZ risk variants in dysregulated peaks in NeuN+ and bulk tissue.

(A) SCZ heritability coefficients of genetic variants overlapping histone peaks from study-1 H3K27ac NeuN+, study-2 H3K27ac Tissue and H3K27ac Meta NeuN+ stratified by 1) “ΔSCZ”: dysregulated peaks (n=3360, 5656 and 6219 peaks, respectively) 2) “ΔSCZ↑”:hyperacetylated dysregulated peaks (n=1918, 2681 and 4031 peaks, respectively) and 3) “ΔSCZ↓”: hypoacetylated dysregulated peaks (n=1442, 2975 and 2188 peaks, respectively) with log₂FC (SCZ vs controls) >0 and <0 respectively. Error bars represent standard error in SCZ heritability from LDSc regression (B) Heatmap of enrichment P-values of brain-related GWAS traits. The overlap of peaks with genetic variants was assessed using LD score regression. ”#”: Significant for enrichment in LD score regression after FDR correction of multiple testing across all tests in the plot (Benjamini & Hochberg test); ”*”: Nominally significant for enrichment.

Figure 3:. PFC histone CRDs reveal subTAD chromosomal organization.

(A) CRD analyses were conducted separately for each of our three ChIP-seq datasets (H3K4me3 NeuN+, H3K27ac NeuN+ , H3K27ac Tissue) (see also Figure 1A,B). The numbers next to bars indicate the proportion of total peak population integrated into CRD structures. (B) Venn diagrams summarizing genome-wide sequences, in Mb megabases, integrated into CRD structures, including overlap and Jaccard similarity index between different histones and cell population (NeuN⁺ or tissue). (C) (top) Representative 10Mb window of chromosome 4 showing PFC NeuN+ Hi-C TAD, chromosomal loop and H3K27ac landscape including CRD structure. (bottom, shaded in gray color) Higher resolution (2Mb) peak-to-CRD assignments and peak correlational structure expressed as an interaction matrix. (D) Neuronal CTCF chromatin occupancies (Y-axis, using CTCF ENCODE reference ChIP-seq from H1 stem cell-differentiated neuronal culture) in relation to distance from CRD (colored graphs) and TAD (black graph) boundaries.

Figure 4:. Acetylated CRDs dysregulated in SCZ.

(A) Proportional representation of SCZ-sensitive H3K27ac NeuN+ ΔCRDs stratified by hypoacetylation (blue), hyperacetylation (red) and not dysregulated (gray). Pie chart shows the proportion of dysregulated histone peaks ΔCRD_ΔPeaks inside ΔCRD (B) SCZ heritability coefficients shown separately for (blue) H3K27ac NeuN+ and (green) H3K27ac Tissue, as indicated, by 1) “All CRD”: all peaks inside CRD (n=114,123 and 143,092 peaks in CRD), 2) “ΔCRD”: dysregulated CRD (n=28,866 and 15,787 peaks in ΔCRD; 3,507 and 1,673 peaks in ΔCRD_ΔPeaks), 3) “ΔCRD↑”: hyperacetylated with mean log₂FC (SCZ vs controls) > 0 (n=14,710 and 7,770 peaks in ΔCRD↑, 1,825 and 873 peaks in ΔCRD↑_ΔPeaks),and 4) “ΔCRD↓”: hypoacetylated with mean log₂FC (SCZ vs controls) < 0 (n=14,156 and 8,017 peaks in ΔCRD↓; 1,682 and 800 peaks in ΔCRD↓_ΔPeaks) classified on x-axis as ΔCRD for all peaks and ΔCRD_ΔPeaks for only dysregulated histone peaks. The overlap of peaks within the dysregulated CRDs in clusters with SCZ risk variants was assessed using LD score regression. ”#”: Significant for enrichment in LD score regression after FDR correction of multiple testing across all tests in the plot (Benjamini & Hochberg, multiple testing p value <0.05); ”*”: Nominally significant for enrichment (p value <0.05) . Error bars show standard error in SCZ heritability from LDSc regression (C) Representative example of a genomic region which spans ten peaks. Horizontal bars (blue, FDR 5%, gray n.s.) mark (top row) peak level analysis with a single differential peak; (mid row) hyperacetylated CRD and (bottom row) ΔCRD_ΔPeaks.

Figure 5:. Fingerprinting disease-sensitive CRDs.

(A) CRD contact matrix of SCZ-sensitive H3K27ac NeuN+ CRDs clustered into three large clusters; notice striking separation of cluster 1 and cluster 3 representing hyperacetylated H3K27ac CRDs in red, and clusters 2 overwhelmingly defined by hypoacetylated H3K27ac CRDs in navy. (B) Composition of annotated CRDs by cell type (GABA in light blue , GLU in pink), compartments (A in cyan., B in indianred.), dysregulation (hypo vs hyper-acetylation in red and navy) and development (fetal in yellow, adult in purple). For every annotation, not significant or not annotated CRDs are shown in gray. (C) Coefficients of heritability of SCZ by cluster and annotation. The overlap of peaks within the dysregulated CRDs in clusters with genetic variants was assessed using LD score regression. P Values from LDSc regression. ”#”: Significant for enrichment in LD score regression after Benjamini and Hochberg FDR correction for multiple testing across all tests in the plot (FDR < 5%). ”*”: Nominally significant for enrichment (p value<.05). Error bars show standard error in SCZ heritability from LDSc regression.

Figure 6:. Spatial organization of diseased CRDs in the virtual chrom 3D model of the neuronal nucleus.

(A) Box plots show for SCZ H3K27ac NeuN+ cohort, showing for diseased ΔCRDs the pairwise Euclidean distance of PFC NeuN+ TAD, and all CRDs, and diseased ΔCRDs from cluster-1, cluster-2 and cluster-3 (from figure 5) with n=11,103, 8,690 and 9,073 peaks for each clusters as indicated. (B) Box plots for H3K27ac Tissue cohort, separated by SCZ sensitive and BD sensitive ΔCRDs, with n = n=8,553 in cluster 1 and and 7,234 peaks in cluster 2 (from figure 5). Barplots in the bottom in red and navy show the dysregulation status of clusters. The center shows the median, the box shows the interquartile range, whiskers indicate the highest/lowest values within 1.5x the interquartile range, and potential outliers from this are shown as dots. * represents p value < .05 while p values are estimated using the Wilcoxon test.