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Repositioning of Immunomodulators: A Ray of Hope for Alzheimer's Disease?

ABSTRACT: Alzheimer's disease (AD) is the most common age-related neurodegenerative disorder characterized by cognitive decline and by the presence of amyloid ? plaques and neurofibrillary tangles in the brain. Despite recent advances in understanding its pathophysiological mechanisms, to date, there are no disease-modifying therapeutic options, to slow or halt the evolution of neurodegenerative processes in AD. Current pharmacological treatments only transiently mitigate the severity of symptoms, with modest or null overall improvement. Emerging evidence supports the concept that AD is affected by the impaired ability of the immune system to restrain the brain's pathology. Deep understanding of the relationship between the nervous and the immune system may provide a novel arena to develop effective and safe drugs for AD treatment. Considering the crucial role of inflammatory/immune pathways in AD, here we discuss the current status of the immuno-oncological, immunomodulatory and anti-TNF-? drugs which are being used in preclinical studies or in ongoing clinical trials by means of the drug-repositioning approach.

SUBMITTER: Munafo A

PROVIDER: S-EPMC7746859 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Repositioning of Immunomodulators: A Ray of Hope for Alzheimer's Disease?

Munafò Antonio A Burgaletto Chiara C Di Benedetto Giulia G Di Mauro Marco M Di Mauro Rosaria R Bernardini Renato R Cantarella Giuseppina G

Frontiers in neuroscience 20201204

Alzheimer's disease (AD) is the most common age-related neurodegenerative disorder characterized by cognitive decline and by the presence of amyloid β plaques and neurofibrillary tangles in the brain. Despite recent advances in understanding its pathophysiological mechanisms, to date, there are no disease-modifying therapeutic options, to slow or halt the evolution of neurodegenerative processes in AD. Current pharmacological treatments only transiently mitigate the severity of symptoms, with mo ...[more]

PMID: 33343293

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Project description:Numerous clinical trials of drug candidates for Alzheimer's disease (AD) have failed, and computational drug repositioning approaches using omics data have been proposed as effective alternative approaches to the discovery of drug candidates. However, little multi-omics data is available for AD, due to limited availability of brain tissues. Even if omics data exist, systematic drug repurposing study for AD has suffered from lack of big data, insufficient clinical information, and difficulty in data integration on account of sample heterogeneity derived from poor diagnosis or shortage of qualified post-mortem tissue. In this study, we developed a proteotranscriptomic-based computational drug repositioning method named Drug Repositioning Perturbation Score/Class (DRPS/C) based on inverse associations between disease- and drug-induced gene and protein perturbation patterns, incorporating pharmacogenomic knowledge. We constructed a Drug-induced Gene Perturbation Signature Database (DGPSD) comprised of 61,019 gene signatures perturbed by 1,520 drugs from the Connectivity Map (CMap) and the L1000 CMap. Drugs were classified into three DRPCs (High, Intermediate, and Low) according to DRPSs that were calculated using drug- and disease-induced gene perturbation signatures from DGPSD and The Cancer Genome Atlas (TCGA), respectively. The DRPS/C method was evaluated using the area under the ROC curve, with a prescribed drug list from TCGA as the gold standard. Glioblastoma had the highest AUC. To predict anti-AD drugs, DRPS were calculated using DGPSD and AD-induced gene/protein perturbation signatures generated from RNA-seq, microarray and proteomic datasets in the Synapse database, and the drugs were classified into DRPCs. We predicted 31 potential anti-AD drug candidates commonly belonged to high DRPCs of transcriptomic and proteomic signatures. Of these, four drugs classified into the nervous system group of Anatomical Therapeutic Chemical (ATC) system are voltage-gated sodium channel blockers (bupivacaine, topiramate) and monamine oxidase inhibitors (selegiline, iproniazid), and their mechanism of action was inferred from a potential anti-AD drug perspective. Our approach suggests a shortcut to discover new efficacy of drugs for AD.

Project description:BACKGROUND:Alzheimer's disease (AD) is a multifactorial and complex neuropathology that involves impairment of many intricate molecular mechanisms. Despite recent advances, AD pathophysiological characterization remains incomplete, which hampers the development of effective treatments. In fact, currently, there are no effective pharmacological treatments for AD. Integrative strategies such as transcription regulatory network and master regulator analyses exemplify promising new approaches to study complex diseases and may help in the identification of potential pharmacological targets. METHODS:In this study, we used transcription regulatory network and master regulator analyses on transcriptomic data of human hippocampus to identify transcription factors (TFs) that can potentially act as master regulators in AD. All expression profiles were obtained from the Gene Expression Omnibus database using the GEOquery package. A normal hippocampus transcription factor-centered regulatory network was reconstructed using the ARACNe algorithm. Master regulator analysis and two-tail gene set enrichment analysis were employed to evaluate the inferred regulatory units in AD case-control studies. Finally, we used a connectivity map adaptation to prospect new potential therapeutic interventions by drug repurposing. RESULTS:We identified TFs with already reported involvement in AD, such as ATF2 and PARK2, as well as possible new targets for future investigations, such as CNOT7, CSRNP2, SLC30A9, and TSC22D1. Furthermore, Connectivity Map Analysis adaptation suggested the repositioning of six FDA-approved drugs that can potentially modulate master regulator candidate regulatory units (Cefuroxime, Cyproterone, Dydrogesterone, Metrizamide, Trimethadione, and Vorinostat). CONCLUSIONS:Using a transcription factor-centered regulatory network reconstruction we were able to identify several potential molecular targets and six drug candidates for repositioning in AD. Our study provides further support for the use of bioinformatics tools as exploratory strategies in neurodegenerative diseases research, and also provides new perspectives on molecular targets and drug therapies for future investigation and validation in AD.

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Repositioning of Immunomodulators: A Ray of Hope for Alzheimer's Disease?

Publications

Repositioning of Immunomodulators: A Ray of Hope for Alzheimer's Disease?

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