2 research outputs found
Label-Free LC–MS/MS Proteomic Analysis of Cerebrospinal Fluid Identifies Protein/Pathway Alterations and Candidate Biomarkers for Amyotrophic Lateral Sclerosis
Analysis
of the cerebrospinal fluid (CSF) proteome has proven valuable
to the study of neurodegenerative disorders. To identify new protein/pathway
alterations and candidate biomarkers for amyotrophic lateral sclerosis
(ALS), we performed comparative proteomic profiling of CSF from sporadic
ALS (sALS), healthy control (HC), and other neurological disease (OND)
subjects using label-free liquid chromatography-tandem mass spectrometry
(LC–MS/MS). A total of 1712 CSF proteins were detected and
relatively quantified by spectral counting. Levels of several proteins
with diverse biological functions were significantly altered in sALS
samples. Enrichment analysis was used to link these alterations to
biological pathways, which were predominantly related to inflammation,
neuronal activity, and extracellular matrix regulation. We then used
our CSF proteomic profiles to create a support vector machines classifier
capable of discriminating training set ALS from non-ALS (HC and OND)
samples. Four classifier proteins, WD repeat-containing protein 63,
amyloid-like protein 1, SPARC-like protein 1, and cell adhesion molecule
3, were identified by feature selection and externally validated.
The resultant classifier distinguished ALS from non-ALS samples with
83% sensitivity and 100% specificity in an independent test set. Collectively,
our results illustrate the utility of CSF proteomic profiling for
identifying ALS protein/pathway alterations and candidate disease
biomarkers
Label-Free LC–MS/MS Proteomic Analysis of Cerebrospinal Fluid Identifies Protein/Pathway Alterations and Candidate Biomarkers for Amyotrophic Lateral Sclerosis
Analysis
of the cerebrospinal fluid (CSF) proteome has proven valuable
to the study of neurodegenerative disorders. To identify new protein/pathway
alterations and candidate biomarkers for amyotrophic lateral sclerosis
(ALS), we performed comparative proteomic profiling of CSF from sporadic
ALS (sALS), healthy control (HC), and other neurological disease (OND)
subjects using label-free liquid chromatography-tandem mass spectrometry
(LC–MS/MS). A total of 1712 CSF proteins were detected and
relatively quantified by spectral counting. Levels of several proteins
with diverse biological functions were significantly altered in sALS
samples. Enrichment analysis was used to link these alterations to
biological pathways, which were predominantly related to inflammation,
neuronal activity, and extracellular matrix regulation. We then used
our CSF proteomic profiles to create a support vector machines classifier
capable of discriminating training set ALS from non-ALS (HC and OND)
samples. Four classifier proteins, WD repeat-containing protein 63,
amyloid-like protein 1, SPARC-like protein 1, and cell adhesion molecule
3, were identified by feature selection and externally validated.
The resultant classifier distinguished ALS from non-ALS samples with
83% sensitivity and 100% specificity in an independent test set. Collectively,
our results illustrate the utility of CSF proteomic profiling for
identifying ALS protein/pathway alterations and candidate disease
biomarkers