Identification and Validation of Novel Cerebrospinal Fluid Biomarkers for Staging Early Alzheimer's Disease

Ideally, disease modifying therapies for Alzheimer disease (AD) will be applied during the 'preclinical' stage (pathology present with cognition intact) before severe neuronal damage occurs, or upon recognizing very mild cognitive impairment. Developing and judiciously administering such therapies will require biomarker panels to identify early AD pathology, classify disease stage, monitor pathological progression, and predict cognitive decline. To discover such biomarkers, we measured AD-associated changes in the cerebrospinal fluid (CSF) proteome.CSF samples from individuals with mild AD (Clinical Dementia Rating [CDR] 1) (n = 24) and cognitively normal controls (CDR 0) (n = 24) were subjected to two-dimensional difference-in-gel electrophoresis. Within 119 differentially-abundant gel features, mass spectrometry (LC-MS/MS) identified 47 proteins. For validation, eleven proteins were re-evaluated by enzyme-linked immunosorbent assays (ELISA). Six of these assays (NrCAM, YKL-40, chromogranin A, carnosinase I, transthyretin, cystatin C) distinguished CDR 1 and CDR 0 groups and were subsequently applied (with tau, p-tau181 and Aβ42 ELISAs) to a larger independent cohort (n = 292) that included individuals with very mild dementia (CDR 0.5). Receiver-operating characteristic curve analyses using stepwise logistic regression yielded optimal biomarker combinations to distinguish CDR 0 from CDR>0 (tau, YKL-40, NrCAM) and CDR 1 from CDR<1 (tau, chromogranin A, carnosinase I) with areas under the curve of 0.90 (0.85-0.94 95% confidence interval [CI]) and 0.88 (0.81-0.94 CI), respectively.Four novel CSF biomarkers for AD (NrCAM, YKL-40, chromogranin A, carnosinase I) can improve the diagnostic accuracy of Aβ42 and tau. Together, these six markers describe six clinicopathological stages from cognitive normalcy to mild dementia, including stages defined by increased risk of cognitive decline. Such a panel might improve clinical trial efficiency by guiding subject enrollment and monitoring disease progression. Further studies will be required to validate this panel and evaluate its potential for distinguishing AD from other dementing conditions

Quantitative spectrally resolved imaging through a spectrograph

A grating spectrograph can be used for spectrally selective two-dimensional imaging if it is operated with a broad entrance slit. The resulting intensity distribution in its exit plane is a one-dimensional convolution of the spatial and spectral distributions of incident light. We present a dedicated deconvolution filter to reconstruct the spatial image from the spectrograph output. The algorithm is illustrated on Raman imaging of an underexpanded dry air jet. Recorded Raman images correspond to density maps convolved with the Raman spectrum of air; the latter essentially acts as a blurring function for the density map. The deconvolution filter combines the individual images recorded in the O-2 and N-2 Raman bands into a single image of relative air density. (C) 2003 Optical Society of America

Quantitative spectrally resolved imaging through a spectrograph

A grating spectrograph can be used for spectrally selective two-dimensional imaging if it is operated with a broad entrance slit. The resulting intensity distribution in its exit plane is a one-dimensional convolution of the spatial and spectral distributions of incident light. We present a dedicated deconvolution filter to reconstruct the spatial image from the spectrograph output. The algorithm is illustrated on Raman imaging of an underexpanded dry air jet. Recorded Raman images correspond to density maps convolved with the Raman spectrum of air; the latter essentially acts as a blurring function for the density map. The deconvolution filter combines the individual images recorded in the O-2 and N-2 Raman bands into a single image of relative air density. (C) 2003 Optical Society of America