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Systematic Analysis and Biomarker Study for Alzheimer's Disease.

Li, X; Wang, H; Long, J; Pan, G; He, T; Anichtchik, O; Belshaw, R; Albani, D; Edison, P; Green, EK; et al. Li, X; Wang, H; Long, J; Pan, G; He, T; Anichtchik, O; Belshaw, R; Albani, D; Edison, P; Green, EK; Scott, J (2018) Systematic Analysis and Biomarker Study for Alzheimer's Disease. Sci Rep, 8 (1). p. 17394. ISSN 2045-2322 https://doi.org/10.1038/s41598-018-35789-3
SGUL Authors: He, Taigang

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Abstract

Revealing the relationship between dysfunctional genes in blood and brain tissues from patients with Alzheimer's Disease (AD) will help us to understand the pathology of this disease. In this study, we conducted the first such large systematic analysis to identify differentially expressed genes (DEGs) in blood samples from 245 AD cases, 143 mild cognitive impairment (MCI) cases, and 182 healthy control subjects, and then compare these with DEGs in brain samples. We evaluated our findings using two independent AD blood datasets and performed a gene-based genome-wide association study to identify potential novel risk genes. We identified 789 and 998 DEGs common to both blood and brain of AD and MCI subjects respectively, over 77% of which had the same regulation directions across tissues and disease status, including the known ABCA7, and the novel TYK2 and TCIRG1. A machine learning classification model containing NDUFA1, MRPL51, and RPL36AL, implicating mitochondrial and ribosomal function, was discovered which discriminated between AD patients and controls with 85.9% of area under the curve and 78.1% accuracy (sensitivity = 77.6%, specificity = 78.9%). Moreover, our findings strongly suggest that mitochondrial dysfunction, NF-κB signalling and iNOS signalling are important dysregulated pathways in AD pathogenesis.

Item Type: Article
Additional Information: This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. © The Author(s) 2018
SGUL Research Institute / Research Centre: Academic Structure > Molecular and Clinical Sciences Research Institute (MCS)
Journal or Publication Title: Sci Rep
ISSN: 2045-2322
Language: eng
Dates:
DateEvent
26 November 2018Published
28 October 2018Accepted
Publisher License: Creative Commons: Attribution 4.0
PubMed ID: 30478411
Go to PubMed abstract
URI: https://openaccess.sgul.ac.uk/id/eprint/110450
Publisher's version: https://doi.org/10.1038/s41598-018-35789-3

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