Literature DB >> 33362460

Unraveling Targetable Systemic and Cell-Type-Specific Molecular Phenotypes of Alzheimer's and Parkinson's Brains With Digital Cytometry.

Marie C Bordone1, Nuno L Barbosa-Morais1.   

Abstract

Alzheimer's disease (AD) and Parkinson's disease (PD) are the two most common neurodegenerative disorders worldwide, with age being their major risk factor. The increasing worldwide life expectancy, together with the scarcity of available treatment choices, makes it thus pressing to find the molecular basis of AD and PD so that the causing mechanisms can be targeted. To study these mechanisms, gene expression profiles have been compared between diseased and control brain tissues. However, this approach is limited by mRNA expression profiles derived for brain tissues highly reflecting their degeneration in cellular composition but not necessarily disease-related molecular states. We therefore propose to account for cell type composition when comparing transcriptomes of healthy and diseased brain samples, so that the loss of neurons can be decoupled from pathology-associated molecular effects. This approach allowed us to identify genes and pathways putatively altered systemically and in a cell-type-dependent manner in AD and PD brains. Moreover, using chemical perturbagen data, we computationally identified candidate small molecules for specifically targeting the profiled AD/PD-associated molecular alterations. Our approach therefore not only brings new insights into the disease-specific and common molecular etiologies of AD and PD but also, in these realms, foster the discovery of more specific targets for functional and therapeutic exploration.
Copyright © 2020 Bordone and Barbosa-Morais.

Entities:  

Keywords:  Alzheimer’s disease; Parkinson’s disease; cellular deconvolution; chemo-transcriptomics; digital cytometry; neurodegeneration; single-cell RNA-seq

Year:  2020        PMID: 33362460      PMCID: PMC7756021          DOI: 10.3389/fnins.2020.607215

Source DB:  PubMed          Journal:  Front Neurosci        ISSN: 1662-453X            Impact factor:   4.677


  142 in total

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Journal:  Front Neurosci       Date:  2015-01-09       Impact factor: 4.677

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8.  Determining cell type abundance and expression from bulk tissues with digital cytometry.

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