Insights into the changes in the proteome of Alzheimer disease elucidated by a meta-analysis

Author:

Haytural HazalORCID,Benfeitas Rui,Schedin-Weiss Sophia,Bereczki Erika,Rezeli Melinda,Unwin Richard D.,Wang Xusheng,Dammer Eric B.ORCID,Johnson Erik C. B.,Seyfried Nicholas T.ORCID,Winblad BengtORCID,Tijms Betty M.ORCID,Visser Pieter Jelle,Frykman Susanne,Tjernberg Lars O.ORCID

Abstract

AbstractMass spectrometry (MS)-based proteomics is a powerful tool to explore pathogenic changes of a disease in an unbiased manner and has been used extensively in Alzheimer disease (AD) research. Here, by performing a meta-analysis of high-quality proteomic studies, we address which pathological changes are observed consistently and therefore most likely are of great importance for AD pathogenesis. We retrieved datasets, comprising a total of 21,588 distinct proteins identified across 857 postmortem human samples, from ten studies using labeled or label-free MS approaches. Our meta-analysis findings showed significant alterations of 757 and 1,195 proteins in AD in the labeled and label-free datasets, respectively. Only 33 proteins, some of which were associated with synaptic signaling, had the same directional change across the individual studies. However, despite alterations in individual proteins being different between the labeled and the label-free datasets, several pathways related to synaptic signaling, oxidative phosphorylation, immune response and extracellular matrix were commonly dysregulated in AD. These pathways represent robust changes in the human AD brain and warrant further investigation.

Funder

Gun och Bertil Stohnes Stiftelse

RCUK | Medical Research Council

Alzheimer's Research UK

U.S. Department of Health & Human Services | NIH | National Institute on Aging

Vetenskapsrådet

Alzheimerfonden

Stiftelsen för Gamla Tjänarinnor

Demensförbundet

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Statistics, Probability and Uncertainty,Computer Science Applications,Education,Information Systems,Statistics and Probability

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