Cerebrospinal fluid proteomic patterns discriminate Parkinsons disease and multiple system atrophy
Movement Disorders, 06/26/2012
Clinical Article
Ishigami N et al. – A proteomic pattern classification method can increase the accuracy of clinical diagnosis of Parkinson's disease and multiple system atrophy, especially in the early stages.
Methods- Cerebrospinal fluid was obtained from 37 patients diagnosed with Parkinson's disease, 32 patients diagnosed with multiple system atrophy, and 26 patients diagnosed with other neurological diseases as controls.
- The samples were from the first cohort and the second cohort.
- Cerebrospinal fluid peptides/proteins were purified with C8 magnetic beads, and spectra were obtained by matrix-assisted laser desorption ionization time-of-flight mass spectrometry.
- Principal component analysis and support vector machine methods are used to reduce dimension of the data and select features to classify diseases.
- Cerebrospinal fluid proteomic profiles of Parkinson's disease, multiple system atrophy, and control were differentiated from each other by principal component analysis.
- By building a support vector machine classifier, 3 groups were classified effectively with good cross-validation accuracy.
- The model accuracy was well preserved for both cases, training by the first cohort and validated by the second cohort and vice versa.
- Receiver operating characteristics proved that the peak of m/z 6250 was the most important to differentiate multiple system atrophy from Parkinson's disease, especially in the early stages of the disease.
