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A novel quantification-driven proteomic strategy identifies an endogenous peptide of pleiotrophin as a new biomarker of Alzheimer's disease

Journal article
Authors Tobias Skillbäck
Niklas Mattsson
Karl Hansson
Ekaterina Mirgorodskaya
Rahil Dahlén
W. van der Flier
P. Scheltens
F. Duits
O. Hansson
C. Teunissen
Kaj Blennow
Henrik Zetterberg
Johan Gobom
Published in Scientific Reports
Volume 7
ISSN 2045-2322
Publication year 2017
Published at Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry
Core Facilities, Proteomics
Language en
Links doi.org/10.1038/s41598-017-13831-0
Keywords cerebrospinal-fluid biomarkers, tandem mass-spectra, tyrosine-phosphatase beta/zeta, mild cognitive impairment, affin, regulatory peptide, molecule hb-gam, diagnostic-criteria, chondroitin, sulfate, growth, receptor
Subject categories Neurosciences

Abstract

We present a new, quantification-driven proteomic approach to identifying biomarkers. In contrast to the identification-driven approach, limited in scope to peptides that are identified by database searching in the first step, all MS data are considered to select biomarker candidates. The endopeptidome of cerebrospinal fluid from 40 Alzheimer's disease (AD) patients, 40 subjects with mild cognitive impairment, and 40 controls with subjective cognitive decline was analyzed using multiplex isobaric labeling. Spectral clustering was used to match MS/MS spectra. The top biomarker candidate cluster (215% higher in AD compared to controls, area under ROC curve = 0.96) was identified as a fragment of pleiotrophin located near the protein's C-terminus. Analysis of another cohort (n = 60 over four clinical groups) verified that the biomarker was increased in AD patients while no change in controls, Parkinson's disease or progressive supranuclear palsy was observed. The identification of the novel biomarker pleiotrophin 151-166 demonstrates that our quantification-driven proteomic approach is a promising method for biomarker discovery, which may be universally applicable in clinical proteomics.

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