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. 2014 Jun 6:9:22.
doi: 10.1186/1750-1326-9-22.

Identification of longitudinally dynamic biomarkers in Alzheimer's disease cerebrospinal fluid by targeted proteomics

Kristin R Wildsmith  1 , Stephen P Schauer, Ashley M Smith, David Arnott, Yuda Zhu, Joshua Haznedar, Surinder Kaur, W Rodney Mathews, Lee A Honigberg
Affiliations

Identification of longitudinally dynamic biomarkers in Alzheimer's disease cerebrospinal fluid by targeted proteomics

Kristin R Wildsmith et al. Mol Neurodegener. .

Abstract

Background: Alzheimer's disease (AD) is the leading cause of dementia affecting greater than 26 million people worldwide. Although cerebrospinal fluid (CSF) levels of Aβ42, tau, and p-tau181 are well established as diagnostic biomarkers of AD, there is a need for additional CSF biomarkers of neuronal function that continue to change during disease progression and could be used as pharmacodynamic measures in clinical trials. Multiple proteomic discovery experiments have reported a range of CSF biomarkers that differ between AD and control subjects. These potential biomarkers represent multiple aspects of the disease pathology. The performance of these markers has not been compared with each other, and their performance has not been evaluated longitudinally.

Results: We developed a targeted-proteomic, multiple reaction monitoring (MRM) assay for the absolute quantitation of 39 peptides corresponding to 30 proteins. We evaluated the candidate biomarkers in longitudinal CSF samples collected from aged, cognitively-normal control (n = 10), MCI (n = 5), and AD (n = 45) individuals (age > 60 years). We evaluated each biomarker for diagnostic sensitivity, longitudinal consistency, and compared with CSF Aβ42, tau, and p-tau181. Four of 28 quantifiable CSF proteins were significantly different between aged, cognitively-normal controls and AD subjects including chitinase-3-like protein 1, reproducing published results. Four CSF markers demonstrated significant longitudinal change in AD: Amyloid precursor protein, Neuronal pentraxin receptor, NrCAM and Chromogranin A. Robust correlations were observed within some subgroups of proteins including the potential disease progression markers.

Conclusion: Using a targeted proteomics approach, we confirmed previous findings for a subset of markers, defined longitudinal performance of our panel of markers, and established a flexible proteomics method for robust multiplexed analyses.

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Figures

Figure 1
Figure 1
Difference in Chitinase-3-like protein 1 (CH3L1 aka YKL-40) is comparable with the change observed for Aβ42, tau and p-tau181 in AD vs. aged cognitively-normal controls (age > 60y) (linear regression, **p = 0.001-0.01, ***p < 0.001). Control, green-circle, MCI blue-square, AD red-triangle. A. CH3L1, B. Aβ42, C. total tau, D. p-tau181.
Figure 2
Figure 2
Classical CSF biomarkers of AD are stable in established disease. Black-line mean slope. Control, green-circle, MCI blue-square, AD red-triangle. Closed symbols, decliners. A. Aβ42, B. total tau, C. p-tau181.
Figure 3
Figure 3
Estimated annual change of biomarkers in AD patients (n = 45) adjusted for age and sex. Dot, mean change. Line, 95% confidence interval.
Figure 4
Figure 4
Potential longitudinal biomarkers in established AD patients. Black-line mean slope. Control, green-circle, MCI blue-square, AD red-triangle. Closed symbols, decliners. A. Amyloid precursor protein peptide (A4_117), B. Neuronal pentraxin receptor (NPTXR), C. Chromogranin A (CMGA), D. NrCAM.
Figure 5
Figure 5
Chromogranin A (CMGA), NrCAM, and Neuronal pentraxin receptor (NPTXR) are highly correlated (A-C), NrCAM and CMGA concentrations are also correlated by ELISA (D) (Baseline for all groups, Control, green-circle, MCI blue-square, AD red-triangle).
Figure 6
Figure 6
Peptides from different regions of Amyloid Precursor Protein (APP, A4) reflect different processing products.
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