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@MISC{Muqaku:279481,
author = {Muqaku, Besnik and Oeckl, Patrick},
title = {{D}ataset: {P}eptidomic analysis of {CSF} reveals new
biomarker candidates for amyotrophic lateral sclerosis},
publisher = {PRoteomics IDEntifications Database},
reportid = {DZNE-2025-00808},
year = {2025},
abstract = {Amyotrophic lateral sclerosis (ALS) is a devastating
neurodegenerative disease and novel biomarkers are needed.
We applied mass-spectrometry-based peptidomic analysis in
cerebrospinal fluid (CSF) samples of ALS and
non-neurodegenerative control patients (Con) from a
discovery (n=48) and validation (n=109) cohort for biomarker
discovery. We identified 33605 peptides in CSF samples from
the discovery cohort. Systematic selection for the best
candidates revealed a targeted method with eight peptides
derived from seven proteins. In the validation cohort, NFL,
MAP1B, MYL1, APOC1 peptides were up-regulated and peptides
from CADM3, SCG1 and PENK down-regulated in ALS compared to
Con. Combination of all peptides in a logistic regression
model led to an area under the curve value of $98\%$ for the
discrimination of ALS from controls. Data of the NFL peptide
strongly correlated with an established NFL immunoassay
(Ella, r=0.97). The peptide biomarker candidates are derived
from proteins with different function and their
determination with our method provides the opportunity for
simultaneous investigation of key processes in ALS and other
neurodegenerative diseases.},
cin = {AG Öckl},
cid = {I:(DE-2719)5000073},
pnm = {353 - Clinical and Health Care Research (POF4-353)},
pid = {G:(DE-HGF)POF4-353},
typ = {PUB:(DE-HGF)32},
url = {https://pub.dzne.de/record/279481},
}