Cargando…

Multimodal single-cell/nucleus RNA sequencing data analysis uncovers molecular networks between disease-associated microglia and astrocytes with implications for drug repurposing in Alzheimer's disease

Because disease-associated microglia (DAM) and disease-associated astrocytes (DAA) are involved in the pathophysiology of Alzheimer's disease (AD), we systematically identified molecular networks between DAM and DAA to uncover novel therapeutic targets for AD. Specifically, we develop a network...

Descripción completa

Detalles Bibliográficos
Autores principales: Xu, Jielin, Zhang, Pengyue, Huang, Yin, Zhou, Yadi, Hou, Yuan, Bekris, Lynn M., Lathia, Justin, Chiang, Chien-Wei, Li, Lang, Pieper, Andrew A., Leverenz, James B., Cummings, Jeffrey, Cheng, Feixiong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8494225/
https://www.ncbi.nlm.nih.gov/pubmed/33627474
http://dx.doi.org/10.1101/gr.272484.120
_version_ 1784579266097184768
author Xu, Jielin
Zhang, Pengyue
Huang, Yin
Zhou, Yadi
Hou, Yuan
Bekris, Lynn M.
Lathia, Justin
Chiang, Chien-Wei
Li, Lang
Pieper, Andrew A.
Leverenz, James B.
Cummings, Jeffrey
Cheng, Feixiong
author_facet Xu, Jielin
Zhang, Pengyue
Huang, Yin
Zhou, Yadi
Hou, Yuan
Bekris, Lynn M.
Lathia, Justin
Chiang, Chien-Wei
Li, Lang
Pieper, Andrew A.
Leverenz, James B.
Cummings, Jeffrey
Cheng, Feixiong
author_sort Xu, Jielin
collection PubMed
description Because disease-associated microglia (DAM) and disease-associated astrocytes (DAA) are involved in the pathophysiology of Alzheimer's disease (AD), we systematically identified molecular networks between DAM and DAA to uncover novel therapeutic targets for AD. Specifically, we develop a network-based methodology that leverages single-cell/nucleus RNA sequencing data from both transgenic mouse models and AD patient brains, as well as drug-target network, metabolite-enzyme associations, the human protein–protein interactome, and large-scale longitudinal patient data. Through this approach, we find both common and unique gene network regulators between DAM (i.e., PAK1, MAPK14, and CSF1R) and DAA (i.e., NFKB1, FOS, and JUN) that are significantly enriched by neuro-inflammatory pathways and well-known genetic variants (i.e., BIN1). We identify shared immune pathways between DAM and DAA, including Th17 cell differentiation and chemokine signaling. Last, integrative metabolite-enzyme network analyses suggest that fatty acids and amino acids may trigger molecular alterations in DAM and DAA. Combining network-based prediction and retrospective case-control observations with 7.2 million individuals, we identify that usage of fluticasone (an approved glucocorticoid receptor agonist) is significantly associated with a reduced incidence of AD (hazard ratio [HR] = 0.86, 95% confidence interval [CI] 0.83–0.89, P < 1.0 × 10(−8)). Propensity score–stratified cohort studies reveal that usage of mometasone (a stronger glucocorticoid receptor agonist) is significantly associated with a decreased risk of AD (HR = 0.74, 95% CI 0.68–0.81, P < 1.0 × 10(−8)) compared to fluticasone after adjusting age, gender, and disease comorbidities. In summary, we present a network-based, multimodal methodology for single-cell/nucleus genomics-informed drug discovery and have identified fluticasone and mometasone as potential treatments in AD.
format Online
Article
Text
id pubmed-8494225
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Cold Spring Harbor Laboratory Press
record_format MEDLINE/PubMed
spelling pubmed-84942252021-10-07 Multimodal single-cell/nucleus RNA sequencing data analysis uncovers molecular networks between disease-associated microglia and astrocytes with implications for drug repurposing in Alzheimer's disease Xu, Jielin Zhang, Pengyue Huang, Yin Zhou, Yadi Hou, Yuan Bekris, Lynn M. Lathia, Justin Chiang, Chien-Wei Li, Lang Pieper, Andrew A. Leverenz, James B. Cummings, Jeffrey Cheng, Feixiong Genome Res Method Because disease-associated microglia (DAM) and disease-associated astrocytes (DAA) are involved in the pathophysiology of Alzheimer's disease (AD), we systematically identified molecular networks between DAM and DAA to uncover novel therapeutic targets for AD. Specifically, we develop a network-based methodology that leverages single-cell/nucleus RNA sequencing data from both transgenic mouse models and AD patient brains, as well as drug-target network, metabolite-enzyme associations, the human protein–protein interactome, and large-scale longitudinal patient data. Through this approach, we find both common and unique gene network regulators between DAM (i.e., PAK1, MAPK14, and CSF1R) and DAA (i.e., NFKB1, FOS, and JUN) that are significantly enriched by neuro-inflammatory pathways and well-known genetic variants (i.e., BIN1). We identify shared immune pathways between DAM and DAA, including Th17 cell differentiation and chemokine signaling. Last, integrative metabolite-enzyme network analyses suggest that fatty acids and amino acids may trigger molecular alterations in DAM and DAA. Combining network-based prediction and retrospective case-control observations with 7.2 million individuals, we identify that usage of fluticasone (an approved glucocorticoid receptor agonist) is significantly associated with a reduced incidence of AD (hazard ratio [HR] = 0.86, 95% confidence interval [CI] 0.83–0.89, P < 1.0 × 10(−8)). Propensity score–stratified cohort studies reveal that usage of mometasone (a stronger glucocorticoid receptor agonist) is significantly associated with a decreased risk of AD (HR = 0.74, 95% CI 0.68–0.81, P < 1.0 × 10(−8)) compared to fluticasone after adjusting age, gender, and disease comorbidities. In summary, we present a network-based, multimodal methodology for single-cell/nucleus genomics-informed drug discovery and have identified fluticasone and mometasone as potential treatments in AD. Cold Spring Harbor Laboratory Press 2021-10 /pmc/articles/PMC8494225/ /pubmed/33627474 http://dx.doi.org/10.1101/gr.272484.120 Text en © 2021 Xu et al.; Published by Cold Spring Harbor Laboratory Press https://creativecommons.org/licenses/by-nc/4.0/This article, published in Genome Research, is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Method
Xu, Jielin
Zhang, Pengyue
Huang, Yin
Zhou, Yadi
Hou, Yuan
Bekris, Lynn M.
Lathia, Justin
Chiang, Chien-Wei
Li, Lang
Pieper, Andrew A.
Leverenz, James B.
Cummings, Jeffrey
Cheng, Feixiong
Multimodal single-cell/nucleus RNA sequencing data analysis uncovers molecular networks between disease-associated microglia and astrocytes with implications for drug repurposing in Alzheimer's disease
title Multimodal single-cell/nucleus RNA sequencing data analysis uncovers molecular networks between disease-associated microglia and astrocytes with implications for drug repurposing in Alzheimer's disease
title_full Multimodal single-cell/nucleus RNA sequencing data analysis uncovers molecular networks between disease-associated microglia and astrocytes with implications for drug repurposing in Alzheimer's disease
title_fullStr Multimodal single-cell/nucleus RNA sequencing data analysis uncovers molecular networks between disease-associated microglia and astrocytes with implications for drug repurposing in Alzheimer's disease
title_full_unstemmed Multimodal single-cell/nucleus RNA sequencing data analysis uncovers molecular networks between disease-associated microglia and astrocytes with implications for drug repurposing in Alzheimer's disease
title_short Multimodal single-cell/nucleus RNA sequencing data analysis uncovers molecular networks between disease-associated microglia and astrocytes with implications for drug repurposing in Alzheimer's disease
title_sort multimodal single-cell/nucleus rna sequencing data analysis uncovers molecular networks between disease-associated microglia and astrocytes with implications for drug repurposing in alzheimer's disease
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8494225/
https://www.ncbi.nlm.nih.gov/pubmed/33627474
http://dx.doi.org/10.1101/gr.272484.120
work_keys_str_mv AT xujielin multimodalsinglecellnucleusrnasequencingdataanalysisuncoversmolecularnetworksbetweendiseaseassociatedmicrogliaandastrocyteswithimplicationsfordrugrepurposinginalzheimersdisease
AT zhangpengyue multimodalsinglecellnucleusrnasequencingdataanalysisuncoversmolecularnetworksbetweendiseaseassociatedmicrogliaandastrocyteswithimplicationsfordrugrepurposinginalzheimersdisease
AT huangyin multimodalsinglecellnucleusrnasequencingdataanalysisuncoversmolecularnetworksbetweendiseaseassociatedmicrogliaandastrocyteswithimplicationsfordrugrepurposinginalzheimersdisease
AT zhouyadi multimodalsinglecellnucleusrnasequencingdataanalysisuncoversmolecularnetworksbetweendiseaseassociatedmicrogliaandastrocyteswithimplicationsfordrugrepurposinginalzheimersdisease
AT houyuan multimodalsinglecellnucleusrnasequencingdataanalysisuncoversmolecularnetworksbetweendiseaseassociatedmicrogliaandastrocyteswithimplicationsfordrugrepurposinginalzheimersdisease
AT bekrislynnm multimodalsinglecellnucleusrnasequencingdataanalysisuncoversmolecularnetworksbetweendiseaseassociatedmicrogliaandastrocyteswithimplicationsfordrugrepurposinginalzheimersdisease
AT lathiajustin multimodalsinglecellnucleusrnasequencingdataanalysisuncoversmolecularnetworksbetweendiseaseassociatedmicrogliaandastrocyteswithimplicationsfordrugrepurposinginalzheimersdisease
AT chiangchienwei multimodalsinglecellnucleusrnasequencingdataanalysisuncoversmolecularnetworksbetweendiseaseassociatedmicrogliaandastrocyteswithimplicationsfordrugrepurposinginalzheimersdisease
AT lilang multimodalsinglecellnucleusrnasequencingdataanalysisuncoversmolecularnetworksbetweendiseaseassociatedmicrogliaandastrocyteswithimplicationsfordrugrepurposinginalzheimersdisease
AT pieperandrewa multimodalsinglecellnucleusrnasequencingdataanalysisuncoversmolecularnetworksbetweendiseaseassociatedmicrogliaandastrocyteswithimplicationsfordrugrepurposinginalzheimersdisease
AT leverenzjamesb multimodalsinglecellnucleusrnasequencingdataanalysisuncoversmolecularnetworksbetweendiseaseassociatedmicrogliaandastrocyteswithimplicationsfordrugrepurposinginalzheimersdisease
AT cummingsjeffrey multimodalsinglecellnucleusrnasequencingdataanalysisuncoversmolecularnetworksbetweendiseaseassociatedmicrogliaandastrocyteswithimplicationsfordrugrepurposinginalzheimersdisease
AT chengfeixiong multimodalsinglecellnucleusrnasequencingdataanalysisuncoversmolecularnetworksbetweendiseaseassociatedmicrogliaandastrocyteswithimplicationsfordrugrepurposinginalzheimersdisease