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Comprehensive analyses of brain cell communications based on multiple scRNA‐seq and snRNA‐seq datasets for revealing novel mechanism in neurodegenerative diseases
AIMS: Complex cellular communications between glial cells and neurons are critical for brain normal function and disorders, and single‐cell level RNA‐sequencing datasets display more advantages for analyzing cell communications. Therefore, it is necessary to systematically explore brain cell communi...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10493674/ https://www.ncbi.nlm.nih.gov/pubmed/37269061 http://dx.doi.org/10.1111/cns.14280 |
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author | Zhang, Chunlong Tan, Guiyuan Zhang, Yuxi Zhong, Xiaoling Zhao, Ziyan Peng, Yunyi Cheng, Qian Xue, Ke Xu, Yanjun Li, Xia Li, Feng Zhang, Yunpeng |
author_facet | Zhang, Chunlong Tan, Guiyuan Zhang, Yuxi Zhong, Xiaoling Zhao, Ziyan Peng, Yunyi Cheng, Qian Xue, Ke Xu, Yanjun Li, Xia Li, Feng Zhang, Yunpeng |
author_sort | Zhang, Chunlong |
collection | PubMed |
description | AIMS: Complex cellular communications between glial cells and neurons are critical for brain normal function and disorders, and single‐cell level RNA‐sequencing datasets display more advantages for analyzing cell communications. Therefore, it is necessary to systematically explore brain cell communications when considering factors such as sex and brain region. METHODS: We extracted a total of 1,039,459 cells derived from 28 brain single‐cell RNA‐sequencing (scRNA‐seq) or single‐nucleus RNA‐sequencing (snRNA‐seq) datasets from the GEO database, including 12 human and 16 mouse datasets. These datasets were further divided into 71 new sub‐datasets when considering disease, sex, and region conditions. In the meanwhile, we integrated four methods to evaluate ligand–receptor interaction score among six major brain cell types (microglia, neuron, astrocyte, oligodendrocyte, OPC, and endothelial cell). RESULTS: For Alzheimer's disease (AD), disease‐specific ligand–receptor pairs when compared with normal sub‐datasets, such as SEMA4A‐NRP1, were identified. Furthermore, we explored the sex‐ and region‐specific cell communications and identified that WNT5A‐ROR1 among microglia cells displayed close communications in male, and SPP1‐ITGAV displayed close communications in the meninges region from microglia to neurons. Furthermore, based on the AD‐specific cell communications, we constructed a model for AD early prediction and confirmed the predictive performance using multiple independent datasets. Finally, we developed an online platform for researchers to explore brain condition‐specific cell communications. CONCLUSION: This research provided a comprehensive study to explore brain cell communications, which could reveal novel biological mechanisms involved in normal brain function and neurodegenerative diseases such as AD. |
format | Online Article Text |
id | pubmed-10493674 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-104936742023-09-12 Comprehensive analyses of brain cell communications based on multiple scRNA‐seq and snRNA‐seq datasets for revealing novel mechanism in neurodegenerative diseases Zhang, Chunlong Tan, Guiyuan Zhang, Yuxi Zhong, Xiaoling Zhao, Ziyan Peng, Yunyi Cheng, Qian Xue, Ke Xu, Yanjun Li, Xia Li, Feng Zhang, Yunpeng CNS Neurosci Ther Meta‐analysis AIMS: Complex cellular communications between glial cells and neurons are critical for brain normal function and disorders, and single‐cell level RNA‐sequencing datasets display more advantages for analyzing cell communications. Therefore, it is necessary to systematically explore brain cell communications when considering factors such as sex and brain region. METHODS: We extracted a total of 1,039,459 cells derived from 28 brain single‐cell RNA‐sequencing (scRNA‐seq) or single‐nucleus RNA‐sequencing (snRNA‐seq) datasets from the GEO database, including 12 human and 16 mouse datasets. These datasets were further divided into 71 new sub‐datasets when considering disease, sex, and region conditions. In the meanwhile, we integrated four methods to evaluate ligand–receptor interaction score among six major brain cell types (microglia, neuron, astrocyte, oligodendrocyte, OPC, and endothelial cell). RESULTS: For Alzheimer's disease (AD), disease‐specific ligand–receptor pairs when compared with normal sub‐datasets, such as SEMA4A‐NRP1, were identified. Furthermore, we explored the sex‐ and region‐specific cell communications and identified that WNT5A‐ROR1 among microglia cells displayed close communications in male, and SPP1‐ITGAV displayed close communications in the meninges region from microglia to neurons. Furthermore, based on the AD‐specific cell communications, we constructed a model for AD early prediction and confirmed the predictive performance using multiple independent datasets. Finally, we developed an online platform for researchers to explore brain condition‐specific cell communications. CONCLUSION: This research provided a comprehensive study to explore brain cell communications, which could reveal novel biological mechanisms involved in normal brain function and neurodegenerative diseases such as AD. John Wiley and Sons Inc. 2023-06-02 /pmc/articles/PMC10493674/ /pubmed/37269061 http://dx.doi.org/10.1111/cns.14280 Text en © 2023 The Authors. CNS Neuroscience & Therapeutics published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Meta‐analysis Zhang, Chunlong Tan, Guiyuan Zhang, Yuxi Zhong, Xiaoling Zhao, Ziyan Peng, Yunyi Cheng, Qian Xue, Ke Xu, Yanjun Li, Xia Li, Feng Zhang, Yunpeng Comprehensive analyses of brain cell communications based on multiple scRNA‐seq and snRNA‐seq datasets for revealing novel mechanism in neurodegenerative diseases |
title | Comprehensive analyses of brain cell communications based on multiple scRNA‐seq and snRNA‐seq datasets for revealing novel mechanism in neurodegenerative diseases |
title_full | Comprehensive analyses of brain cell communications based on multiple scRNA‐seq and snRNA‐seq datasets for revealing novel mechanism in neurodegenerative diseases |
title_fullStr | Comprehensive analyses of brain cell communications based on multiple scRNA‐seq and snRNA‐seq datasets for revealing novel mechanism in neurodegenerative diseases |
title_full_unstemmed | Comprehensive analyses of brain cell communications based on multiple scRNA‐seq and snRNA‐seq datasets for revealing novel mechanism in neurodegenerative diseases |
title_short | Comprehensive analyses of brain cell communications based on multiple scRNA‐seq and snRNA‐seq datasets for revealing novel mechanism in neurodegenerative diseases |
title_sort | comprehensive analyses of brain cell communications based on multiple scrna‐seq and snrna‐seq datasets for revealing novel mechanism in neurodegenerative diseases |
topic | Meta‐analysis |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10493674/ https://www.ncbi.nlm.nih.gov/pubmed/37269061 http://dx.doi.org/10.1111/cns.14280 |
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