Verification of a Parkinson's disease protein signature in T-lymphocytes by multiple reaction monitoring.

Abstract

Diagnosis of Parkinson's disease, the second most common neurodegenerative disease, is based on the appearance of motor symptoms. A panel of protein biomarkers in the T-lymphocyte proteome was previously proposed as a Parkinson's disease signature. Here, we designed an LC-MS based method to quantitatively evaluate this protein signature by multiple reaction monitoring (MRM) in T-lymphocytes and peripheral blood mononuclear cells from a new cohort of nine patients with Parkinson's disease and nine unaffected subjects. Patients were classified using the discriminant function obtained from two-dimensional electrophoresis and protein amounts measured by MRM, thus assigning seven controls out of nine as true negatives and nine patients out of nine as true positives. A good discriminant power was obtained by selecting a subset of peptides from the protein signature, with an area under the receiver operating characteristic curve of 0.877. A similar result is achieved by evaluating all peptides of a selected panel of proteins (gelsolin, moesin, septin-6, twinfilin-2, lymphocyte-specific protein 1, vimentin, transaldolase), with an area under the curve of 0.840. Conversely, the signature was not able to classify the enrolled subjects when evaluated in whole mononuclear cells. Overall, this report shows the portability of the proposed method to a large-scale clinical validation study.

• Authors: Tiziana Alberio, Kelly McMahon, Manuela Cuccurullo, Lee A Gethings, Craig Lawless, Maurizio Zibetti, Leonardo Lopiano, Johannes P C Vissers, Mauro Fasano
• Journal: Journal of proteome research (J Proteome Res) Vol. 13 Issue 8 Pg. 3554-61 (Aug 01 2014) ISSN: 1535-3907 [Electronic] United States
• PMID: 24946097 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't, Validation Study)

Chemical References

• Biomarkers
• Cytoskeletal Proteins
• Peptides

Topics

• Amino Acid Sequence
• Area Under Curve
• Biomarkers (metabolism)
• Cytoskeletal Proteins (metabolism)
• Discriminant Analysis
• Electrophoresis, Gel, Two-Dimensional
• Humans
• Molecular Sequence Data
• Parkinson Disease (diagnosis, immunology, metabolism)
• Peptides (genetics, metabolism)
• T-Lymphocytes (metabolism)