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| Home > Publications Database > Dataset: Peptidomic analysis of CSF reveals new biomarker candidates for amyotrophic lateral sclerosis |
| Home > Publications Database > Dataset: Peptidomic analysis of CSF reveals new biomarker candidates for amyotrophic lateral sclerosis |
| Dataset | DZNE-2025-00808 |
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2025
PRoteomics IDEntifications Database
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.
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