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

Cellular heterogeneity in the human brain obscures the identification of robust cellular regulatory networks, which is necessary to understand the function of non-coding elements and the impact of non-coding genetic variation. Here we integrate genome-wide chromosome conformation data from purified...

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Detalles Bibliográficos
Autores: Hu, Benxia, Won, Hyejung, Mah, Won, Park, Royce B, Kassim, Bibi, Spiess, Keeley, Kozlenkov, Alexey, Crowley, Cheynna A, Pochareddy, Sirisha, PsychENCODE Consortium, Li, Yun, Dracheva, Stella, Sestan, Nenad, Akbarian, Schahram, Geschwind, Daniel H.
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2021
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10230/59050
Acceso en línea:http://hdl.handle.net/10230/59050
http://dx.doi.org/10.1038/s41467-021-24243-0
Access Level:acceso abierto
Palabra clave:Chromatin
Epigenetics
Epigenetics in the nervous system
Epigenomics
Genetics of the nervous system
Descripción
Sumario:Cellular heterogeneity in the human brain obscures the identification of robust cellular regulatory networks, which is necessary to understand the function of non-coding elements and the impact of non-coding genetic variation. Here we integrate genome-wide chromosome conformation data from purified neurons and glia with transcriptomic and enhancer profiles, to characterize the gene regulatory landscape of two major cell classes in the human brain. We then leverage cell-type-specific regulatory landscapes to gain insight into the cellular etiology of several brain disorders. We find that Alzheimer’s disease (AD)-associated epigenetic dysregulation is linked to neurons and oligodendrocytes, whereas genetic risk factors for AD highlighted microglia, suggesting that different cell types may contribute to disease risk, via different mechanisms. Moreover, integration of glutamatergic and GABAergic regulatory maps with genetic risk factors for schizophrenia (SCZ) and bipolar disorder (BD) identifies shared (parvalbumin-expressing interneurons) and distinct cellular etiologies (upper layer neurons for BD, and deeper layer projection neurons for SCZ). Collectively, these findings shed new light on cell-type-specific gene regulatory networks in brain disorders.