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Identification of biomarkers for early diagnosis of Parkinson's disease by multi-omics joint analysis
Institution:1. Department of Neurosurgery, MacKay Memorial Hospital, New Taipei City, Taiwan;2. Department of Biological Science and Technology, National Chiao Tung University, Hsin-Chu City, Taiwan;3. Biomaterials Translational Research Center, China Medical University Hospital, Taichung, Taiwan;4. Center for General Education, China Medical University, Taichung, Taiwan;5. Master Program in Technology Management, China Medical University, Taichung, Taiwan;6. Department of Electronics Engineering and Institute of Electronics, National Chiao Tung University, Hsin-Chu City 30010, Taiwan
Abstract:ObjectiveThe purpose of this study is to identify the biomarkers for early diagnosis of Parkinson's disease (PD) by multi-omics joint analysis, so as to identify the biomarkers for early diagnosis of PD, and to help clinicians make early diagnosis and treatment.MethodsIn this study, mice are taken as the study subjects. The model of PD mice is established, and then lymphocyte, striatum, substantia nigra protein and proteolysis are extracted. After that, the experiments of protein imprinting and 418O labeling are carried out. Mass Spectrometry (MS) analysis technology is mainly used to study proteomics and to analyze the quantitative and qualitative situation of differential proteins in striatum, substantia nigra protein and lymphocyte. By this method, biomarkers for early diagnosis of PD are analyzed and identified.ResultsThe biomarkers of Parkinson's early onset are related to the same quantitative differential expression of lymphocyte, striatum, substantia nigra protein, lymphocyte and substantia nigra.ConclusionThis experimental method can analyze and identify the biomarkers of early diagnosis of PD, help to explore the pathophysiology and pathogenesis of PD, effectively help clinicians make timely diagnosis in advance, and improve the prevention and treatment effect of the disease.
Keywords:Multi-omics  Biomarkers  Parkinson  Differential proteins
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