Proteomics and bioinformatics approaches for the identification of plasma biomarkers to detect Parkinson's disease

  • Dong W
  • Qiu C
  • Gong D
  • et al.
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Abstract

The aim of the present study was to screen for biomarkers of Parkinson's disease (PD) using proteomics and bioinformatics approaches. PD patients were divided into three groups: Those without surgery (PD1 group); those who had undergone deep brain stimulation (DBS) surgery without electrode stimulation (PD2 group); and those who had undergone DBS surgery with 1 month of electrode stimulation (PD3 group). The non-Parkinson control group (CK group) was also involved. Quantitative proteomic analysis of human sera was performed through the use of tandem mass tag markers and liquid chromatography-mass spectrometry (LC-MS)-based techniques. For the proteins with quantitative information, a systematic bioinformatics analysis was then performed, including protein annotation, functional classification, functional enrichment and cluster analysis based on functional enrichment. Of the 739 proteins identified, quantitative information was available for 644. With regard to differential expression, 18 upregulated and 21 downregulated proteins were screened in the PD1/CK comparison group; 12 upregulated and 12 downregulated proteins in the PD2/PD1 comparison group; and 16 upregulated and 19 downregulated proteins in the PD3/PD2 comparison group. Coiled-coil domain-containing protein 154 (CCDC154) and tripartite motif-containing protein 3 (TRIM3) were key proteins involved in the molecular mechanisms of PD, participating in intracellular vesicle, ubiquitin protein ligase and transition metal ion-binding activities. After DBS surgery, desert hedgehog protein (DHH) was downregulated, whereas neuropilin-2 (NRP2) was upregulated; these participated in the ensheathment of neurons and the semaphorin receptor complex, respectively. The expression level of chloride intracellular channel protein 1 (CLIC1) was increased after 1 month of electrode stimulation following DBS. By combining proteomic approaches and LC-MS methods, significant proteins including CCDC154, TRIM3, DHH, NRP2 and CLIC1 were detected with high specificity and sensitivity. These may be used as novel biomarkers for early diagnosis of PD and the future development of treatments. Copyright: © Dong et al.

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APA

Dong, W., Qiu, C., Gong, D., Jiang, X., Liu, W., Liu, W., … Zhang, W. (2019). Proteomics and bioinformatics approaches for the identification of plasma biomarkers to detect Parkinson’s disease. Experimental and Therapeutic Medicine. https://doi.org/10.3892/etm.2019.7888

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