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PMID: 12462422 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't

Proteomic profiling and neurodegeneration in Alzheimer's disease.

Neurochemical research ·Vol. 27 ·No. 10 ·2002-10-00 ·Pages 1245-53

Tsuji T, Shiozaki A, Kohno R, Yoshizato K, Shimohama S

Abstract

Quantitative proteome analysis of Alzheimer's disease (AD) brains was performed using 2-D gels to identify disease specific changes in protein expression. The task of characterizing the proteome and its components is now practically achievable because of the development and integration of four important tools: protein, EST, and complete genome sequence databases, mass spectrometry, matching software for protein sequences and protein separation technology. Mass spectrometry (MS) instrumentation has undergone a tremendous change over the past decade, culminating in the development of highly sensitive, robust instruments that can reliably analyze biomolecules, particularly proteins and peptides; we identified 35 proteins from over 100 protein spots on a 2-D gel. Using this current technology, protein-expression profiling, which is actually a specialized form of mining, is an important principal application of proteomics. The information obtained has tremendous potential as a means of determining the pathogenesis, and detecting disease markers and potential targets for drug therapy in AD.

MeSH Terms

Aged Aged, 80 and over Alzheimer Disease/metabolism,pathology Brain/metabolism,pathology Electrophoresis, Gel, Two-Dimensional Humans Mass Spectrometry Middle Aged Nerve Degeneration/pathology Proteome/metabolism

Chemicals

Proteome

Authors & Affiliations

5 authors, click to expand affiliations / ORCID

Tsuji T

Department of Neurology, Faculty of Medicine, Kyoto University, Sakyoku, Kyoto, Japan.

Shiozaki A

Kohno R

Yoshizato K

Shimohama S

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Article Info

Journal

Neurochemical research

Abbr.

Neurochem Res

ISSN

0364-3190

DOI

10.1023/a:1020941929414

Published

2002-10-00

Pages

1245-53

Language

English

Region

United States

NLM ID

7613461

Subset

External Links

PubMed source DOI: 10.1023/a:1020941929414 View journal details

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