Identification and drug-induced reversion of molecular signatures of Alzheimer’s disease onset and progression in AppNL-G-F, AppNL-F, and 3xTg-AD mouse models

Background In spite of many years of research, our understanding of the molecular bases of Alzheimer's disease (AD) is still incomplete, and the medical treatments available mainly target the disease symptoms and are hardly effective. Indeed, the modulation of a single target (e.g., [beta]-secr...

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Published in:Genome medicine 2021-10, Vol.13 (1), p.1-168, Article 168
Main Authors: Pauls, Eduardo, Bayod, Sergi, Mateo, Lídia, Alcalde, Víctor, Juan-Blanco, Teresa, Sánchez-Soto, Marta, Saido, Takaomi C, Saito, Takashi, Berrenguer-Llergo, Antoni, Attolini, Camille Stephan-Otto, Gay, Marina, de Oliveira, Eliandre, Duran-Frigola, Miquel, Aloy, Patrick
Format: Article
Language:English
Subjects:
Advertising executives
Aging
Alzheimer's disease
Analysis
Animal cognition
Animal models
Antibiotics
Antihypertensives
Cognitive ability
Computational neuroscience
Drugs
Genes
Health aspects
Hippocampus
Homeopathy
Hypertension
Materia medica and therapeutics
Medical treatment
Neurodegenerative diseases
Nonsteroidal anti-inflammatory drugs
Pathogenesis
Pathology
Penbutolol
Physiological aspects
Proteins
Proteomics
Reversion
Scientific equipment and supplies industry
Secretase
Senile plaques
Therapeutics
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Summary:Background In spite of many years of research, our understanding of the molecular bases of Alzheimer's disease (AD) is still incomplete, and the medical treatments available mainly target the disease symptoms and are hardly effective. Indeed, the modulation of a single target (e.g., [beta]-secretase) has proven to be insufficient to significantly alter the physiopathology of the disease, and we should therefore move from gene-centric to systemic therapeutic strategies, where AD-related changes are modulated globally. Methods Here we present the complete characterization of three murine models of AD at different stages of the disease (i.e., onset, progression and advanced). We combined the cognitive assessment of these mice with histological analyses and full transcriptional and protein quantification profiling of the hippocampus. Additionally, we derived specific A[beta]-related molecular AD signatures and looked for drugs able to globally revert them. Results We found that AD models show accelerated aging and that factors specifically associated with A[beta] pathology are involved. We discovered a few proteins whose abundance increases with AD progression, while the corresponding transcript levels remain stable, and showed that at least two of them (i.e., lfit3 and Syt11) co-localize with A[beta] plaques in the brain. Finally, we found two NSAIDs (dexketoprofen and etodolac) and two anti-hypertensives (penbutolol and bendroflumethiazide) that overturn the cognitive impairment in AD mice while reducing A[beta] plaques in the hippocampus and partially restoring the physiological levels of AD signature genes to wild-type levels. Conclusions The characterization of three AD mouse models at different disease stages provides an unprecedented view of AD pathology and how this differs from physiological aging. Moreover, our computational strategy to chemically revert AD signatures has shown that NSAID and anti-hypertensive drugs may still have an opportunity as anti-AD agents, challenging previous reports. Keywords: Alzheimer's disease, Transcriptomics, Proteomics, Data-driven drug discovery, In vivo models
ISSN:1756-994X
1756-994X
DOI:10.1186/s13073-021-00983-y