OBJECTIVE: To find a panel of proteins in antemortem cerebrospinal fluid (CSF) that could be used to differentiate between samples from Alzheimer's disease (AD) patients and samples from healthy and neurological control subjects. METHODS: For a test cohort, antemortem CSF proteins from 34 AD and 34 non-AD patients were separated using two-dimensional gel electrophoresis. The resulting protein patterns were analyzed using the random forest multivariate statistical method. Protein spots of interest were identified using tandem time-of-flight mass spectrometry. A validation cohort consisting of CSF from 18 AD patients and 10 non-AD subjects was analyzed in a similar way. RESULTS: Using the test cohort, a panel of 23 spots was identified that could be used to differentiate AD and non-AD gels with a sensitivity of 94%, a specificity of 94%, and a predicted classification error rate of only 5.9%. These proteins are related to the transport of beta-amyloid, the inflammatory response, proteolytic inhibition, and neuronal membrane proteins. The 23 spots separately classified the validation cohort with 90% sensitivity (probable AD subjects), 83% specificity, and a predicted classification error rate of 14% in a blinded analysis. The total observed sensitivity is 93%, the total observed specificity is 90%, and the predicted classification error rate is 8.3%. INTERPRETATION: A panel of possible CSF biomarkers for AD has been identified using proteomic methods.
OBJECTIVE: To find a panel of proteins in antemortem cerebrospinal fluid (CSF) that could be used to differentiate between samples from Alzheimer's disease (AD) patients and samples from healthy and neurological control subjects. METHODS: For a test cohort, antemortem CSF proteins from 34 AD and 34 non-ADpatients were separated using two-dimensional gel electrophoresis. The resulting protein patterns were analyzed using the random forest multivariate statistical method. Protein spots of interest were identified using tandem time-of-flight mass spectrometry. A validation cohort consisting of CSF from 18 ADpatients and 10 non-AD subjects was analyzed in a similar way. RESULTS: Using the test cohort, a panel of 23 spots was identified that could be used to differentiate AD and non-AD gels with a sensitivity of 94%, a specificity of 94%, and a predicted classification error rate of only 5.9%. These proteins are related to the transport of beta-amyloid, the inflammatory response, proteolytic inhibition, and neuronal membrane proteins. The 23 spots separately classified the validation cohort with 90% sensitivity (probable AD subjects), 83% specificity, and a predicted classification error rate of 14% in a blinded analysis. The total observed sensitivity is 93%, the total observed specificity is 90%, and the predicted classification error rate is 8.3%. INTERPRETATION: A panel of possible CSF biomarkers for AD has been identified using proteomic methods.
Authors: William T Hu; Alice Chen-Plotkin; Steven E Arnold; Murray Grossman; Christopher M Clark; Leslie M Shaw; Eve Pickering; Max Kuhn; Yu Chen; Leo McCluskey; Lauren Elman; Jason Karlawish; Howard I Hurtig; Andrew Siderowf; Virginia M-Y Lee; Holly Soares; John Q Trojanowski Journal: Acta Neuropathol Date: 2010-03-16 Impact factor: 17.088
Authors: Leila Choe; Mark D'Ascenzo; Norman R Relkin; Darryl Pappin; Philip Ross; Brian Williamson; Steven Guertin; Patrick Pribil; Kelvin H Lee Journal: Proteomics Date: 2007-10 Impact factor: 3.984
Authors: Aaron M Swomley; Sarah Förster; Jierel T Keeney; Judy Triplett; Zhaoshu Zhang; Rukhsana Sultana; D Allan Butterfield Journal: Biochim Biophys Acta Date: 2013-10-09
Authors: M Moon; H Song; H J Hong; D W Nam; M-Y Cha; M S Oh; J Yu; H Ryu; I Mook-Jung Journal: Cell Death Differ Date: 2012-12-21 Impact factor: 15.828
Authors: Jing Zhang; Izabela Sokal; Elaine R Peskind; Joseph F Quinn; Joseph Jankovic; Christopher Kenney; Kathryn A Chung; Steven P Millard; John G Nutt; Thomas J Montine Journal: Am J Clin Pathol Date: 2008-04 Impact factor: 2.493