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Modeling of pathological traits in Alzheimer's disease based on systemic extracellular signaling proteome


Britschgi, M; Rufibach, K; Bauer Huang, S L; Clark, C M; Kaye, J A; Li, G; Peskind, E R; Quinn, J F; Galasko, D R; Wyss-Coray, T (2011). Modeling of pathological traits in Alzheimer's disease based on systemic extracellular signaling proteome. Molecular & Cellular Proteomics, 10(10):1-11.

Abstract

The study of chronic brain diseases including Alzheimer's disease in patients is typically limited to brain imaging or psychometric testing. Given the epidemic rise and insufficient knowledge about pathological pathways in sporadic Alzheimer's disease, new tools are required to identify the molecular changes underlying this disease. We hypothesize that levels of specific secreted cellular signaling proteins in cerebrospinal fluid or plasma correlate with pathological changes in the Alzheimer's disease brain and can thus be used to discover signaling pathways altered in the disease. Here we measured 91 proteins of this subset of the cellular communication proteome in plasma or cerebrospinal fluid in patients with Alzheimer's disease and cognitively normal controls to mathematically model disease-specific molecular traits. We found small numbers of signaling proteins that were able to model key pathological markers of Alzheimer's disease, including levels of cerebrospinal fluid β-amyloid and tau, and classify disease in independent samples. Several of these factors had previously been implicated in Alzheimer's disease supporting the validity of our approach. Our study also points to proteins which were previously unknown to be associated with Alzheimer's disease thereby implicating novel signaling pathways in this disorder.

Abstract

The study of chronic brain diseases including Alzheimer's disease in patients is typically limited to brain imaging or psychometric testing. Given the epidemic rise and insufficient knowledge about pathological pathways in sporadic Alzheimer's disease, new tools are required to identify the molecular changes underlying this disease. We hypothesize that levels of specific secreted cellular signaling proteins in cerebrospinal fluid or plasma correlate with pathological changes in the Alzheimer's disease brain and can thus be used to discover signaling pathways altered in the disease. Here we measured 91 proteins of this subset of the cellular communication proteome in plasma or cerebrospinal fluid in patients with Alzheimer's disease and cognitively normal controls to mathematically model disease-specific molecular traits. We found small numbers of signaling proteins that were able to model key pathological markers of Alzheimer's disease, including levels of cerebrospinal fluid β-amyloid and tau, and classify disease in independent samples. Several of these factors had previously been implicated in Alzheimer's disease supporting the validity of our approach. Our study also points to proteins which were previously unknown to be associated with Alzheimer's disease thereby implicating novel signaling pathways in this disorder.

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Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Epidemiology, Biostatistics and Prevention Institute (EBPI)
Dewey Decimal Classification:610 Medicine & health
Scopus Subject Areas:Physical Sciences > Analytical Chemistry
Life Sciences > Biochemistry
Life Sciences > Molecular Biology
Language:English
Date:2011
Deposited On:17 Nov 2011 15:22
Last Modified:08 Jul 2022 13:02
Publisher:American Society for Biochemistry and Molecular Biology
ISSN:1535-9476
Additional Information:This research was originally published in: Britschgi, M; Rufibach, K; Bauer Huang, S L; Clark, C M; Kaye, J A; Li, G; Peskind, E R; Quinn, J F; Galasko, D R; Wyss-Coray, T (2011). Modeling of pathological traits in Alzheimer's disease based on systemic extracellular signaling proteome. Molecular & Cellular Proteomics, 10(10):1-11. © the American Society for Biochemistry and Molecular Biology
OA Status:Hybrid
Publisher DOI:https://doi.org/10.1074/mcp.M111.008862
PubMed ID:21742799