Differential expression of microRNAs in Alzheimer's disease brain, blood, and cerebrospinal fluid.

Alzheimer's disease Biomarker Dementia Diagnosis Epigenetics Genetics Meta-analysis Pathophysiology Prognosis Systematic review

Journal

Alzheimer's & dementia : the journal of the Alzheimer's Association
ISSN: 1552-5279
Titre abrégé: Alzheimers Dement
Pays: United States
ID NLM: 101231978

Informations de publication

Date de publication:
11 2019
Historique:
received: 01 03 2019
revised: 13 06 2019
accepted: 23 06 2019
pubmed: 10 9 2019
medline: 1 9 2020
entrez: 10 9 2019
Statut: ppublish

Résumé

Several microRNAs (miRNAs) have been implicated in Alzheimer's disease pathogenesis, but the evidence from individual case-control studies remains inconclusive. A systematic literature review was performed, followed by standardized multistage data extraction, quality control, and meta-analyses on eligible data for brain, blood, and cerebrospinal fluid specimens. Results were compared with miRNAs reported in the abstracts of eligible studies or recent qualitative reviews to assess novelty. Data from 147 independent data sets across 107 publications were quantitatively assessed in 461 meta-analyses. Twenty-five, five, and 32 miRNAs showed studywide significant differential expression (α < 1·08 × 10 Our systematic assessment of differential miRNA expression is the first of its kind in Alzheimer's disease and highlights several miRNAs of potential relevance.

Identifiants

pubmed: 31495604
pii: S1552-5260(19)35119-2
doi: 10.1016/j.jalz.2019.06.4952
pii:
doi:

Substances chimiques

Biomarkers 0
MicroRNAs 0

Types de publication

Journal Article Meta-Analysis Research Support, Non-U.S. Gov't Systematic Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

1468-1477

Informations de copyright

Copyright © 2019 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Auteurs

Petros Takousis (P)

Ageing Epidemiology (AGE) Research Unit, School of Public Health, Imperial College London, London, UK.

Angélique Sadlon (A)

Ageing Epidemiology (AGE) Research Unit, School of Public Health, Imperial College London, London, UK.

Jessica Schulz (J)

Genetic and Molecular Epidemiology Group, Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), Institutes of Neurogenetics & Cardiogenetics, University of Lübeck, Lübeck, Germany.

Inken Wohlers (I)

Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), Institutes of Neurogenetics & Cardiogenetics, University of Lübeck, Lübeck, Germany.

Valerija Dobricic (V)

Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), Institutes of Neurogenetics & Cardiogenetics, University of Lübeck, Lübeck, Germany.

Lefkos Middleton (L)

Ageing Epidemiology (AGE) Research Unit, School of Public Health, Imperial College London, London, UK.

Christina M Lill (CM)

Genetic and Molecular Epidemiology Group, Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), Institutes of Neurogenetics & Cardiogenetics, University of Lübeck, Lübeck, Germany.

Robert Perneczky (R)

Ageing Epidemiology (AGE) Research Unit, School of Public Health, Imperial College London, London, UK; Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany; German Center for Neurodegenerative Diseases (DZNE) Munich, Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany. Electronic address: robert.perneczky@med.uni-muenchen.de.

Lars Bertram (L)

Ageing Epidemiology (AGE) Research Unit, School of Public Health, Imperial College London, London, UK; Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), Institutes of Neurogenetics & Cardiogenetics, University of Lübeck, Lübeck, Germany; Department of Psychology, University of Oslo, Oslo, Norway. Electronic address: lars.bertram@uni-luebeck.de.

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Classifications MeSH