Proteomic Characterization of Cerebrospinal Fluid from Ataxia-Telangiectasia (A-T) Patients Using a LC/MS-Based Label-Free Protein Quantification Technology

Monika Dzieciatkowska, Guihong Qi, Jinsam You, Kerry G Bemis, Heather Sahm, Howard M Lederman, Thomas O Crawford, Lawrence M Gelbert, Cynthia Rothblum-Oviatt, Mu Wang, Monika Dzieciatkowska, Guihong Qi, Jinsam You, Kerry G Bemis, Heather Sahm, Howard M Lederman, Thomas O Crawford, Lawrence M Gelbert, Cynthia Rothblum-Oviatt, Mu Wang

Abstract

Cerebrospinal fluid (CSF) has been used for biomarker discovery of neurodegenerative diseases in humans since biological changes in the brain can be seen in this biofluid. Inactivation of A-T-mutated protein (ATM), a multifunctional protein kinase, is responsible for A-T, yet biochemical studies have not succeeded in conclusively identifying the molecular mechanism(s) underlying the neurodegeneration seen in A-T patients or the proteins that can be used as biomarkers for neurologic assessment of A-T or as potential therapeutic targets. In this study, we applied a high-throughput LC/MS-based label-free protein quantification technology to quantitatively characterize the proteins in CSF samples in order to identify differentially expressed proteins that can serve as potential biomarker candidates for A-T. Among 204 identified CSF proteins with high peptide-identification confidence, thirteen showed significant protein expression changes. Bioinformatic analysis revealed that these 13 proteins are either involved in neurodegenerative disorders or cancer. Future molecular and functional characterization of these proteins would provide more insights into the potential therapeutic targets for the treatment of A-T and the biomarkers that can be used to monitor or predict A-T disease progression. Clinical validation studies are required before any of these proteins can be developed into clinically useful biomarkers.

Figures

Figure 1
Figure 1
Linear Discriminant Analysis (LDA) of differentially expressed proteins in A-T. A panel of 13 differentially expressed proteins were analyzed by LDA (a function of JMP version 8 software). Expression differences of proenkephalin-A (P01210), isoform 1 of extracellular matrix protein 1 (Q16610), secretogranin-2 (P13521), isoform 1 of CD166 antigen (Q13740), and insulin-like growth factor binding protein 7 (Q16270) can clearly discriminate A-T samples (AT, ∗, 8 samples) from normal controls (0H, x, 5 samples), suggesting that these five proteins can potentially serve as a panel of biomarkers of A-T.
Figure 2
Figure 2
Pathway analysis linking five A-T biomarker candidates and ATM. Pathway studio was used to link the A-T biomarker candidates with ATM. Direct interactions are represented by solid lines, whereas indirect interactions are shown in dashed lines.
Figure 3
Figure 3
MRM analysis of A-T biomarker candidates. Relative protein expression levels were determined by averaging the area-under-the-Curve (AUC) for each selected MRM transition for each peptide shown in Table 4. For secretogranin-2 and IGFBP7, the fold-changes from both MRM peptides were also averaged. Statistical analysis was performed by ANOVA models using PROC MIXED in SAS. P < .05.

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