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A Meta-Analysis of Alzheimer’s Disease Brain Transcriptomic Data

Patel, H; Dobson, RJB; Newhouse, SJ; (2019) A Meta-Analysis of Alzheimer’s Disease Brain Transcriptomic Data. Journal of Alzheimer's Disease , 68 (4) pp. 1635-1656. 10.3233/JAD-181085. Green open access

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Abstract

BACKGROUND: Microarray technologies have identified imbalances in the expression of specific genes and biological pathways in Alzheimer's disease (AD) brains. However, there is a lack of reproducibility across individual AD studies, and many related neurodegenerative and mental health disorders exhibit similar perturbations. OBJECTIVE: Meta-analyze publicly available transcriptomic data from multiple brain-related disorders to identify robust transcriptomic changes specific to AD brains. METHODS: Twenty-two AD, eight schizophrenia, five bipolar disorder, four Huntington's disease, two major depressive disorder, and one Parkinson's disease dataset totaling 2,667 samples and mapping to four different brain regions (temporal lobe, frontal lobe, parietal lobe, and cerebellum) were analyzed. Differential expression analysis was performed independently in each dataset, followed by meta-analysis using a combining p-value method known as Adaptively Weighted with One-sided Correction. RESULTS: Meta-analysis identified 323, 435, 1,023, and 828 differentially expressed genes specific to the AD temporal lobe, frontal lobe, parietal lobe, and cerebellum brain regions, respectively. Seven of these genes were consistently perturbed across all AD brain regions with SPCS1 gene expression pattern replicating in RNA-Seq data. A further nineteen genes were perturbed specifically in AD brain regions affected by both plaques and tangles, suggesting possible involvement in AD neuropathology. In addition, biological pathways involved in the "metabolism of proteins" and viral components were significantly enriched across AD brains. CONCLUSION: This study identified transcriptomic changes specific to AD brains, which could make a significant contribution toward the understanding of AD disease mechanisms and may also provide new therapeutic targets.

Type: Article
Title: A Meta-Analysis of Alzheimer’s Disease Brain Transcriptomic Data
Location: Netherlands
Open access status: An open access version is available from UCL Discovery
DOI: 10.3233/JAD-181085
Publisher version: http://doi.org/10.3233/JAD-181085
Language: English
Additional information: © 2019 – IOS Press and the authors. All rights reserved. This article is published online with Open Access and distributed under the terms of the Creative Commons Attribution Non-Commercial License (CC BY-NC 4.0).
Keywords: Alzheimer’s disease, gene expression, human, mental disorders, meta-analysis, microarray analysis, neurodegenerative disorders, neuropathology
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics > Clinical Epidemiology
URI: https://discovery.ucl.ac.uk/id/eprint/10072298
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