Literature DB >> 29331684

Reprogramming neurodegeneration in the big data era.

Lujia Zhou1, Patrik Verstreken2.   

Abstract

Recent genome-wide association studies (GWAS) have identified numerous genetic risk variants for late-onset Alzheimer's disease (AD) and Parkinson's disease (PD). However, deciphering the functional consequences of GWAS data is challenging due to a lack of reliable model systems to study the genetic variants that are often of low penetrance and non-coding identities. Pluripotent stem cell (PSC) technologies offer unprecedented opportunities for molecular phenotyping of GWAS variants in human neurons and microglia. Moreover, rapid technological advances in whole-genome RNA-sequencing and epigenome mapping fuel comprehensive and unbiased investigations of molecular alterations in PSC-derived disease models. Here, we review and discuss how integrated studies that utilize PSC technologies and genome-wide approaches may bring new mechanistic insight into the pathogenesis of AD and PD.
Copyright © 2018 Elsevier Ltd. All rights reserved.

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Year:  2018        PMID: 29331684     DOI: 10.1016/j.conb.2017.12.015

Source DB:  PubMed          Journal:  Curr Opin Neurobiol        ISSN: 0959-4388            Impact factor:   6.627


  1 in total

Review 1.  Applications of machine learning to diagnosis and treatment of neurodegenerative diseases.

Authors:  Monika A Myszczynska; Poojitha N Ojamies; Alix M B Lacoste; Daniel Neil; Amir Saffari; Richard Mead; Guillaume M Hautbergue; Joanna D Holbrook; Laura Ferraiuolo
Journal:  Nat Rev Neurol       Date:  2020-07-15       Impact factor: 42.937

  1 in total

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