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Comprehensive Proteomic Profiling of Patients’ Tears Identifies Potential Biomarkers for the Traumatic Vegetative State

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Abstract

The vegetative state is a complex condition with unclear mechanisms and limited diagnostic, prognostic, and therapeutic methods. In this study, we aimed to explore the proteomic profile of tears from patients in a traumatic vegetative state and identify potential diagnostic markers using tears—a body fluid that can be collected non-invasively. Using iTRAQ quantitative proteomic technology, in the discovery phase, tear samples collected from 16 patients in a traumatic vegetative state and 16 normal individuals were analyzed. Among 1080 identified tear proteins, 57 were upregulated and 15 were downregulated in the patients compared to the controls. Bioinformatics analysis revealed that the differentially-expressed proteins were mainly involved in the wound response and immune response signaling pathways. Furthermore, we verified the levels of 7 differentially-expressed proteins in tears from 50 traumatic vegetative state patients and 50 normal controls (including the samples used in the discovery phase) using ELISA. The results showed that this 7-protein panel had a high discrimination ability for traumatic vegetative state (area under the curve = 0.999). In summary, the altered tear proteomic profile identified in this study provides a basis for potential tear protein markers for diagnosis and prognosis of the traumatic vegetative state and also provides novel insights into the mechanisms of traumatic vegetative state.

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Acknowledgements

The work was supported by the National Natural Science Foundation of China (81671198), the Grant of Shanghai Municipal Education Commission-Gaofeng Clinical Medicine (20152212), and the Shanghai Shenkang Clinical Research Plan of the Shanghai Hospital Development Center (16CR3011A).

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Correspondence to Guoyi Gao.

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Tang, Q., Zhang, C., Wu, X. et al. Comprehensive Proteomic Profiling of Patients’ Tears Identifies Potential Biomarkers for the Traumatic Vegetative State. Neurosci. Bull. 34, 626–638 (2018). https://doi.org/10.1007/s12264-018-0259-x

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  • DOI: https://doi.org/10.1007/s12264-018-0259-x

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