Protein patterns in cerebrospinal fluid of patients with amyotrophic lateral sclerosis: an analysis using proteomics

The use of modern mass spectroscopy methods has made proteomics a promising new tool for the clinical diagnosis of Amyotrophic Lateral Sclerosis (ALS). Advanced pattern recognition algorithms are used to associate these fingerprints with known disease states, resulting in the identification of unique protein patterns that can distinguish between healthy and affected individuals. In this study, we used a chip- or a beads based method in combination with a SELDI-MS (surface enhanced laser desorption and ionization) to find differences in the cerebrospinal fluid (CSF)- proteome of patients with ALS and patients with other neurological diseases.

CSF from 101 patients were processed using weak cationic exchange magnetic beads. Eluated peptides and proteins were spotted on gold chips. Detection was carried out after addition of sinapinic acid with a SELDI-MS. In parallel all CSF samples were spotted twice on a CM10 chip – surface. Evaluation of spectra was done using the clinprotool software.

40–70 peptide- or protein- specific peaks were detectable in all CSF samples. Similar protein and peptide patterns were seen in the measured spectra. Using the software algorithm, it was possible to differentiate between ALS positive and ALS negative patients in some cases. Nevertheless it was not possible to find a specific protein or peptide which flag the disease.

Further validation experiments have to be performed to acquire more information on the background of the normal CSF proteome. This will lead to an improvement in the normalization procedures of the data obtained after measurement of the CSF from patients with ALS. Additional algorithms have to be tested to receive more reliable information about the disease status of the patient.