In:
Genome Research, Cold Spring Harbor Laboratory, Vol. 31, No. 10 ( 2021-10), p. 1900-1912
Abstract:
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.
Type of Medium:
Online Resource
ISSN:
1088-9051
,
1549-5469
DOI:
10.1101/gr.272484.120
Language:
English
Publisher:
Cold Spring Harbor Laboratory
Publication Date:
2021
detail.hit.zdb_id:
1483456-X
SSG:
12
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