Neuronal and glial 3D chromatin architecture informs the cellular etiology of brain disorders

In the paper

“We detected 187,674 and 167,551 promoter-based interactions3,4 from NeuN+ and NeuN− cells, respectively (Fig. 2a).”

What the sources say

• Not checked yetcites [3] Wang, D. et al. Comprehensive functional genomic resource and integrative model for the human brain. Science 362, eaat8464 (2018).
• Partly supported

  The Methods section (‘Identification of Hi-C interacting regions’; page unavailable) describes identifying enhancer–promoter interactions, so the source supports the general type of interaction cited. It does not report 187,674 interactions in NeuN+ cells or 167,551 in NeuN− cells; searches for both the counts and NeuN terminology found no supporting passage. The citing sentence presents those counts as its authors’ own detections. (LLM, conf=0.82)

  cites [4] Won, H. et al. Chromosome conformation elucidates regulatory relationships in developing human brain. Nature 538, 523–527 (2016). sourceExperimental — accuracy not yet measured

In the paper

“In contrast to AD in which multiple glial cells are implicated, previous work has indicated neurons as the central cell-type harboring genetic risk for the majority of psychiatric disorders3,22,46,58–61.”

What the sources say

• Not checked yetcites [3] Wang, D. et al. Comprehensive functional genomic resource and integrative model for the human brain. Science 362, eaat8464 (2018).
• Partly supported

  The Cellular Determinants of Disease section (p. 11) reports that most ASD risk genes were expressed in developing glutamatergic neurons; the discussion on p. 11 reports similar neuronal findings for epilepsy and enrichment in neurons for intellectual disability. But the paper does not establish that neurons are the central risk-bearing cell type for the majority of psychiatric disorders. Its schizophrenia analysis (p. 13) also implicates progenitors, OPCs, and microglia. (LLM, conf=0.87)

  cites [22] Polioudakis, D. et al. A single-cell transcriptomic atlas of human neocortical development during mid-gestation. Neuron 103, 785–801.e8 (2019). sourceExperimental — accuracy not yet measured
• Supported

  The Results section, under “Cell-type specificity” (page not provided), reports that psychiatric disorder-associated genes coalesced in neurons, in contrast to degenerative disorder-associated genes, which were highly expressed in glia. It also reports excitatory-neuron enrichment across development, supporting the cited contrast. (LLM, conf=0.91)

  cites [46] Sey, N. Y. A. et al. A computational tool (H-MAGMA) for improved prediction of brain-disorder risk genes by incorporating brain chromatin interaction profiles. Nat. Neurosci. https://doi.org/10.1038/s41593-020-0603-0 (2020). source
• Partly supported

  The section “ASD Genes Are Enriched in Maturing Inhibitory and Excitatory Neurons” (p. 13) reports enrichment of ASD risk genes in neuronal lineages. It does not establish that neurons harbor genetic risk for the majority of psychiatric disorders; the finding presented here is specific to ASD. (LLM, conf=0.87)

  cites [58] Satterstrom, F. K. et al. Large-scale exome sequencing study implicates both developmental and functional changes in the neurobiology of autism. Cell. https://doi.org/10.1016/j.cell.2019.12.036 (2020). sourceExperimental — accuracy not yet measured
• Partly supported

  In “Neuronal Isoform Networks Capture Disease Specificity” (page not available), the paper reports genetic-risk enrichment in a neuronal module for schizophrenia, bipolar disorder, and major depressive disorder, consistent with a role for neurons in psychiatric risk. It does not establish neurons as the central cell type harboring genetic risk for the majority of psychiatric disorders; the Discussion also describes glial alterations. (LLM, conf=0.84)

  cites [59] Gandal, M. J. et al. Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder. Science 362, eaat8127 (2018). sourceExperimental — accuracy not yet measured
• Partly supported

  The Results (page unavailable) report enrichment of ASD-risk genes in mid-gestation and adult glutamatergic projection neurons. That supports a neuronal role in autism genetic risk, but this paper does not establish that neurons are the central cell type harboring risk for the majority of psychiatric disorders. (LLM, conf=0.86)

  cites [60] Ruzzo, E. K. et al. Inherited and de novo genetic risk for autism impacts shared networks. Cell 178, 850–866.e26 (2019). sourceExperimental — accuracy not yet measured
• Not checked yetcites [61] Skene, N. G. et al. Genetic identification of brain cell types underlying schizophrenia. Nat. Genet. 50, 825–833 (2018). source

In the paper

“Over 95% of super-FIREs overlapped with differential H3K27ac peaks and all super-FIREs overlapped with promoters, indicating that they have a particularly strong cell-type-specific regulatory impact (Supplementary Fig. 5b, c).”

In the paper

“We detected extensive compartment switching between NeuN+ and NeuN− cells: 4,333 regions (in 100kb resolution) switched from compartment A to B between NeuN− to NeuN+ cells, while 2098 regions switched from compartment B to A in NeuN+ to NeuN− cells.”

In the paper

“Only 9 super-FIREs were detected in both NeuN+ and NeuN− cells, leaving 253 and 157 cell-type-specific super-FIREs in NeuN+ and NeuN− cells, respectively (Supplementary Fig. 5a, Supplementary Data 2).”

In the paper

“detecting 287 differential FIREs between NeuN+ (145) and NeuN− (142) cells (hereby referred to as NeuN+ and NeuN− FIREs, respectively, Fig. 1b, Supplementary Data 2).”

In the paper

“We detected 3966 and 3967 FIREs in NeuN+ and NeuN− cells, respectively (Fig. 1a and Supplementary Data 1)24.”

What the sources say

• Not checked yetcites [24] Crowley, C. et al. FIREcaller: detecting frequently interacting regions from Hi-C data. Comput. Struct. Biotechnol. J. 19, 355–362 (2021). source

In the paper

“Importantly, genes located in compartments that switch from A to B between NeuN− and NeuN+ were highly expressed in oligodendrocytes and astrocytes, while those that switch from B to A in NeuN− to NeuN+ were highly expressed in neurons, suggesting that the difference in chromosome conformation between NeuN+ and NeuN− cells is associated with cell-type-specific gene regulation (Supplementary Fig. 3”

In the paper

“NeuN+ super-FIREs overlapped with genes functioning in synapses and ion gated channels that were highly expressed in neurons, while NeuN− super-FIREs overlapped with genes involved in cell adhesion, myelination, and ensheathment of neurons, with high expression in glia (Supplementary Fig. 5d-f, 6).”

In the paper

“NeuN+ cells showed high similarity with adult brains, fetal brains, and iPSC-derived neurons.”

In the paper

“Roughly 37% of interactions occurred between enhancers and promoters and ~23% of interactions occurred between two different promoters (Supplementary Fig. 7b).”

In the paper

“Salient examples include GRIN2B, which overlaps with a NeuN+ FIRE, and OLIG1 and OLIG2, which overlap with a NeuN− FIRE (Fig. 1e, f, Supplementary Fig. 4).”

In the paper

“Indeed, NeuN+ FIREs overlapped with neuronal genes that were enriched for synaptic function (Fig. 1g), while NeuN− FIREs overlapped with genes involved in myelination, glial differentiation, and oligodendrocyte differentiation (Fig. 1h).”

In the paper

“We were able to link hypoacetylated peaks in AD to 460 genes using NeuN+ Hi–C data and hyperacetylated peaks in AD to 676 genes using NeuN− Hi–C data (hereby referred to as NeuN+ hypo- and NeuN− hyperacetylated genes, respectively, Fig. 3c, Supplementary Data 5).”

In the paper

“Consistent with previous studies16,42,49, these genes were highly expressed in the postnatal brain samples (Fig. 4d) and microglia (Fig. 4e).”

What the sources say

• Not checked yetcites [16] Nott, A. et al. Brain cell type–specific enhancer–promoter interactome maps and disease-risk association. Science 366, 1134–1139 (2019). source
• Not checked yetcites [42] Lambert, J. C. et al. Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer’s disease. Nat. Genet. 45, 1452–1458 (2013). source
• Not checked yetcites [49] Jansen, I. E. et al. Genome-wide meta-analysis identifies new loci and functional pathways influencing Alzheimer’s disease risk. Nat. Genet. 51, 404–413 (2019). source

In the paper

“For example, a gene that encodes a synaptic scaffolding protein, HOMER132, was engaged in NeuN+ specific peaks and loops and its expression was significantly higher in NeuN+ cells compared with NeuN− cells (Fig. 2b).”

What the sources say

• Not checked yetcites [32] Tu, J. C. et al. Homer binds a novel proline-rich motif and links group 1 metabotropic glutamate receptors with IP3 receptors. Neuron 21, 717–726 (1998). source

In the paper

“We obtained 45,911 Glu-specific and 32,169 GABA-specific H3K27ac peaks and assigned them to 6234 and 4342 genes, respectively (Supplementary Fig. 8a, Supplementary Data 4).”

In the paper

“Lastly, genes assigned to NeuN+ specific peaks were more highly expressed in neurons, while those assigned to NeuN− specific peaks were highly expressed in oligodendrocytes and astrocytes (Fig. 2f), demonstrating the tight relationship between cell-type-specific chromatin architecture and expression signature.”

In the paper

“In line with these findings, NeuN+ enhancer–promoter interactions were enriched for synaptic and axonal genes, whereas NeuN− enhancer–promoter interactions were associated with actin-based motility (Supplementary Data 3).”

In the paper

“GO analysis demonstrated that NeuN+ hypoacetylated genes included synaptic genes while NeuN− hyperacetylated genes were involved in catalytic activity and glycoprotein binding (Supplementary Data 5).”

In the paper

“Notably, the BIN1 promoter was connected to multiple enhancers in NeuN−, but not in NeuN+ cells, demonstrating the highly cell-type-specific gene regulatory landscape within the locus.”

In the paper

“These modules were involved in transcriptional regulation and cellular proliferation and were annotated as astrocyte-specific41.”

What the sources say

• Not checked yetcites [41] Seyfried, N. T. et al. A multi-network approach identifies protein-specific co-expression in asymptomatic and symptomatic Alzheimer’s disease. Cell Syst. 4, 60–72.e4 (2017). source

In the paper

“Cellular expression profiles also confirmed these findings, as NeuN+ hypoacetylated genes were highly expressed in neurons, while NeuN− hyperacetylated genes were highly expressed in oligodendrocytes, astrocytes, and endothelial cells (Fig. 3f).”

In the paper

“In contrast, a glial gene, SOX1033, was engaged in NeuN− specific H3K27ac peaks and Hi–C loops, and had higher expression in NeuN− cells than in NeuN+ cells (Fig. 2c).”

What the sources say

• Not checked yetcites [33] Kuhlbrodt, K., Herbarth, B., Sock, E., Hermans-Borgmeyer, I. & Wegner, M. Sox10, a novel transcriptional modulator in glial cells. J. Neurosci. 18, 237–250 (1998). source

In the paper

“AD risk genes were enriched for amyloid−beta (Aβ) pathways, lipoprotein assembly, and immune processes (Fig. 4c, Supplementary Data 6).”

In the paper

“Genes assigned to Glu peaks were highly expressed in excitatory neurons, such as layers (L)2/3 pyramidal neurons (Ex1) and L5/6 corticothalamic projection neurons (Ex7), while genes assigned to GABA peaks were highly expressed in inhibitory neurons, such as parvalbumin-expressing GABA interneurons (In6, Supplementary Fig. 8b, the definition of Ex1–8 and In1–8 neuronal subtypes is available in”

In the paper

“EHD1 was both hyperacetylated and highly expressed in neurotypical NeuN− cells compared to NeuN+ cells.”

In the paper

“We detected that AD-associated hyperacetylated peaks were largely active in NeuN− cells, while AD-associated hypoacetylated peaks were largely active in NeuN+ cells in neurotypical controls (Fig. 3b).”

In the paper

“NeuN+ hypoacetylated genes include CACNG3, whose promoter formed a loop with a peak, which was preferentially active in NeuN+ cells and was hypoacetylated in postmortem AD brain.”

In the paper

“GRIK4, a gene that encodes an ionotropic class of glutamate receptor36, displayed complex chromatin interactions with multiple Glu peaks. In contrast, GAD1, a gene that encodes a well-known cellular marker for inhibitory neurons37, was engaged in GABA peaks via chromatin interactions (Supplementary Fig. 8c).”

What the sources say

• Not checked yetcites [36] Szpirer, C. et al. The genes encoding the glutamate receptor subunits KA1 and KA2 (GRIK4 and GRIK5) are located on separate chromosomes in human, mouse, and rat. Proc. Natl Acad. Sci. USA 91, 11849–11853 (1994). source
• Not checked yetcites [37] Erlander, M. G., Tillakaratne, N. J., Feldblum, S., Patel, N. & Tobin, A. J. Two genes encode distinct glutamate decarboxylases. Neuron 7, 91–100 (1991). source

In the paper

“We were able to assign 10,167 and 11,242 cell-type-specific H3K27ac peaks to 7828 and 8851 genes via chromatin interactions in NeuN+ and NeuN− cells, respectively (Fig. 2a, Supplementary Data 3).”

In the paper

“Glu-BD genes were enriched for neurogenesis, cell adhesion molecules, and synapses, while GABA-BD genes were enriched for transcriptional regulation and NMDA receptor activity (Supplementary Data 7).”

In the paper

“It is of note that while AD-associated hyperacetylation was linked to oligodendrocyte genes and astrocyte co-expression modules, genetic risk factors for AD were mapped onto a different glial cell type, microglia.”

In the paper

“Notably, AD-associated hyperacetylation was enriched for glial enhancers that are associated with upregulation of astrocytic co-expression modules in AD, while AD-associated hypoacetylation was enriched for neuronal enhancers that potentially affect downregulation of a neuronal co-expression module in AD.”

In the paper

“obtaining 753 SCZ risk genes from Glu (hereby referred to as Glu-SCZ genes) and 624 risk genes from GABA-specific regulatory interactions integrated via H-MAGMA (GABA-SCZ genes) (Supplementary Data 7).”

In the paper

“The genome-wide analysis of chromosome conformation in these two cell classes captures the major known elements of 3D architecture such as compartments, FIREs, and loops, addressing the roles and impact of these different hierarchical units in cell-type-specific gene regulation.”

In the paper

“Glu-SCZ genes displayed widespread expression among many Glu neuronal subclasses, with relatively higher expression signatures in L3/4 neurons (Ex2) and L5/6 corticothalamic projection neurons (Ex7).”

What the sources say

• Not checked yetcites [8] Lake, B. B. et al. Neuronal subtypes and diversity revealed by single-nucleus RNA sequencing of the human brain. Science 352, 1586–1590 (2016). source

In the paper

“We also identified 143 and 101 BD candidate risk genes from Glu (Glu-BD genes) and GABA (GABA-BD genes) H-MAGMA, respectively (Supplementary Data 7).”

In the paper

“We further refined maps of neuronal chromatin architecture by integrating Hi–C data from sorted neurons with H3K27ac peaks identified in two major neuronal subtypes, Glu and GABA neurons, which led to a successful delineation of neuronal subtype-specific regulatory relationships.”

In the paper

“Glu-SCZ genes were implicated in synaptic organization, ion channel activity, and neuron projection, while GABA-SCZ genes were associated with dendrite, axon, and hormonal response (Supplementary Data 7).”

In the paper

“It is also of note that common genetic risk for SCZ and BD also indicated shared pathways coalescing onto parvalbumin-positive interneurons, paralleling what has been among the most robust pathologic findings in SCZ and BD63,64.”

What the sources say

• Not checked yetcites [63] Enwright Iii, J. F. et al. Transcriptome alterations of prefrontal cortical parvalbumin neurons in schizophrenia. Mol. Psychiatry 23, 1606–1613 (2018). source
• Not checked yetcites [64] Mellios, N. et al. Molecular determinants of dysregulated GABAergic gene expression in the prefrontal cortex of subjects with schizophrenia. Biol. Psychiatry 65, 1006–1014 (2009). source

In the paper

“The fact that NeuN+ cells show high similarity with fetal brain may reflect extensive neurogenesis at midgestation, the developmental stage at which the fetal brain was obtained22.”

What the sources say

• Not checked yetcites [22] Polioudakis, D. et al. A single-cell transcriptomic atlas of human neocortical development during mid-gestation. Neuron 103, 785–801.e8 (2019). source

In the paper

“Together, our results confirmed that gene expression was coordinately controlled by physical interactions of promoters with enhancers, indicative of transcriptional regulators that underlie cell-type-specific gene regulation.”

In the paper

“consistent with the previous findings that multiple enhancers can interact with one promoter3,7.”

What the sources say

• Not checked yetcites [3] Wang, D. et al. Comprehensive functional genomic resource and integrative model for the human brain. Science 362, eaat8464 (2018).
• Not checked yetcites [7] Jung, I. et al. A compendium of promoter-centered long-range chromatin interactions in the human genome. Nat. Genet. 51, 1442–1449 (2019). source

In the paper

“Notably, we found that samples were clustered by cell types, not individuals, and showed high correlation between the same cell types from different individuals (NeuN+ = 0.95–0.97; NeuN− = 0.86-0.91; Supplementary Fig. 3a), demonstrating the reproducibility across Hi–C libraries.”

What the sources say

• Not checked yetcites [19] Yang, T. et al. HiCRep: assessing the reproducibility of Hi-C data using a stratum-adjusted correlation coefficient. Genome Res. 27, 1939–1949 (2017). source

In the paper

“Recently, promoter interaction profiles were inferred from three types of brain cells (neurons, oligodendrocytes, and microglia) obtained from the postnatal human cerebral cortex16.”

What the sources say

• Not checked yetcites [16] Nott, A. et al. Brain cell type–specific enhancer–promoter interactome maps and disease-risk association. Science 366, 1134–1139 (2019). source

In the paper

“These results collectively suggest that in AD brains, many neuronal genes are downregulated due to their hypoacetylation in neurons, whereas many glial genes are upregulated due to their hyperacetylation in glia.”

In the paper

“which contains key regulators of neural immune pathways expressed in glial cells31.”

What the sources say

• Not checked yetcites [31] Tamura, T., Yanai, H., Savitsky, D. & Taniguchi, T. The IRF family transcription factors in immunity and Oncogenesis. Annu. Rev. Immunol. 26, 535–584 (2008). source

In the paper

“Since genetic risk resides at the initiation of the causal chain in disease pathogenesis, this differential enrichment of genetic risk factors and epigenetic regulation underscores different expression signatures in AD with distinct cellular specificities and likely causal relationships.”

In the paper

“This is consistent with recent single-cell sequencing studies identifying genetic risk enrichment and gene expression changes within microglia in AD, accompanied by significant gene expression changes in other cells, including astrocytes50–52, which is where we observe epigenetic signature enrichment.”

What the sources say

• Not checked yetcites [50] Mathys, H. et al. Single-cell transcriptomic analysis of Alzheimer’s disease. Nature 570, 332–337 (2019). source
• Not checked yetcites [51] Grubman, A. et al. A single-cell atlas of entorhinal cortex from individuals with Alzheimer’s disease reveals cell-type-specific gene expression regulation. Nat. Neurosci. 22, 2087–2097 (2019). source
• Not checked yetcites [52] Sala Frigerio, C. et al. The major risk factors for Alzheimer’s disease: age, sex, and genes modulate the microglia response to Aβ plaques. Cell Rep. 27, 1293–1306.e6 (2019). source

In the paper

“These results highlight the importance of obtaining cell-type-specific epigenetic landscapes in diseases.”

In the paper

“so this initial assignment is likely to be underpowered and inaccurate.”

In the paper

“Furthermore, these peaks were obtained from the brain homogenates, which would mask opposing interactions and obscure the cell-type-specific substrate of these changes.”

In the paper

“Here, we reasoned that neuronal subtype-specific gene regulatory networks would help refine the cellular etiology of disease and potentially identify discrete molecular neuropathology across psychiatric disorders.”

In the paper

“these findings suggest cellular substrates for molecular convergence (Ex7 and In6 are shared between two disorders) and divergence (Ex1 is BD-specific, while Ex2 is SCZ-specific) among two highly genetically correlated disorders.”

In the paper

“In their original work, Marzi et al.38 reported AD-associated H3K27ac peaks that are either hypo- or hyperacetylated in AD-affected individuals compared to age-matched low-pathology controls38 and linked these peaks to target genes on the basis of linear distance.”

What the sources say

• Not checked yetcites Marzi et al.38 Marzi, S. J. et al. A histone acetylome-wide association study of Alzheimer’s disease identifies disease-associated H3K27ac differences in the entorhinal cortex. Nat. Neurosci. 21, 1618–1627 (2018). source

In the paper

“Our study provides a foundation for such future study by characterizing cell-type-specific 3D chromatin structure in the adult human brain, which we show can be used to improve our understanding of gene regulatory landscape in brain disorders.”