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Neurology. 2006 Apr 25;66(8):1218-22. Epub 2006 Feb 15.

Identification of potential CSF biomarkers in ALS.

Author information

  • 1Geriatric Research, Education, and Clinical Center, Bronx Veterans Affairs Medical Center, Bronx, NY, USA. giulio.pasinetti@mssm.edu

Abstract

BACKGROUND:

The clinical diagnosis of ALS is based entirely on clinical features. Identification of biomarkers for ALS would be important for diagnosis and might also provide clues to pathogenesis.

OBJECTIVE:

To determine if there is a specific protein profile in the CSF that distinguishes patients with ALS from those with purely motor peripheral neuropathy (PN) and healthy control subjects.

METHODS:

CSF obtained from patients with ALS, disease controls (patients with other neurologic disorders), and normal controls were analyzed using the surface-enhanced laser desorption/ionization time-of-flight mass spectrometry proteomics technique. Biomarker sensitivity and specificity was calculated with receiver operating characteristic curve methodology. ALS biomarkers were purified and sequence identified by mass spectrometry-directed peptide sequencing.

RESULTS:

In initial proteomic discovery studies, three protein species (4.8-, 6.7-, and 13.4-kDa) that were significantly lower in concentration in the CSF from patients with ALS (n = 36) than in normal controls (n = 21) were identified. A combination of three protein species (the "three-protein" model) correctly identified patients with ALS with 95% accuracy, 91% sensitivity, and 97% specificity from the controls. Independent validation studies using separate cohorts of ALS (n = 13), healthy control (n = 25), and PN (n = 7) subjects confirmed the ability of the three CSF protein species to separate patients with ALS from other diseases. Protein sequence analysis identified the 13.4-kDa protein species as cystatin C and the 4.8-kDa protein species as a peptic fragment of the neurosecretory protein VGF.

CONCLUSION:

Additional application of a "three-protein" biomarker model to current diagnostic criteria may provide an objective biomarker pattern to help identify patients with ALS.

PMID:
16481598
[PubMed - indexed for MEDLINE]
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