Author
Listed:
- Benxia Hu
(University of North Carolina
University of North Carolina)
- Hyejung Won
(University of North Carolina
University of North Carolina)
- Won Mah
(University of North Carolina
University of North Carolina)
- Royce B. Park
(Icahn School of Medicine at Mount Sinai
Icahn School of Medicine at Mount Sinai)
- Bibi Kassim
(Icahn School of Medicine at Mount Sinai
Icahn School of Medicine at Mount Sinai)
- Keeley Spiess
(University of North Carolina)
- Alexey Kozlenkov
(Icahn School of Medicine at Mount Sinai
Icahn School of Medicine at Mount Sinai
James J. Peters VA Medical Center)
- Cheynna A. Crowley
(University of North Carolina)
- Sirisha Pochareddy
(Yale School of Medicine)
- Yun Li
(University of North Carolina
University of North Carolina
University of North Carolina)
- Stella Dracheva
(Icahn School of Medicine at Mount Sinai
Icahn School of Medicine at Mount Sinai
James J. Peters VA Medical Center)
- Nenad Sestan
(Yale School of Medicine
Yale School of Medicine
Program in Integrative Cell Signaling and Neurobiology of Metabolism, Yale School of Medicine
Yale School of Medicine)
- Schahram Akbarian
(Icahn School of Medicine at Mount Sinai
Icahn School of Medicine at Mount Sinai)
- Daniel H. Geschwind
(David Geffen School of Medicine University of California
David Geffen School of Medicine University of California
David Geffen School of Medicine University of California
Semel Institute, David Geffen School of Medicine University of California)
Abstract
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.
Suggested Citation
Benxia Hu & Hyejung Won & Won Mah & Royce B. Park & Bibi Kassim & Keeley Spiess & Alexey Kozlenkov & Cheynna A. Crowley & Sirisha Pochareddy & Yun Li & Stella Dracheva & Nenad Sestan & Schahram Akbari, 2021.
"Neuronal and glial 3D chromatin architecture informs the cellular etiology of brain disorders,"
Nature Communications, Nature, vol. 12(1), pages 1-13, December.
Handle:
RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-24243-0
DOI: 10.1038/s41467-021-24243-0
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