Affiliations: [a] College of Life Science and Oceanography, Shenzhen Key Laboratory of Marine Biotechnology and Ecology, Shenzhen University, Shenzhen, China
| [b] Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, College of Optoelectronic Engineering, Shenzhen University, Shenzhen, China
| [c] Department of Neurology, China-Japan Union Hospital, Changchun, China
| [d] College of Computer Science and Technology, Jilin University, Changchun, China
Correspondence:
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Correspondence to: Yong Wang, College of Life Science and Oceanography, Shenzhen University, 518060, Shenzhen, China. Tel.: +86 137 983 50829; E-mail: [email protected].
Abstract: Alzheimer’s disease (AD) is a chronic neurodegenerative disorder contributing to nearly 70% of dementia cases. However, no diagnostic protein biomarkers are available in urine. In this study, we combined computational and experimental methods to identify urinary biomarkers for AD. First, by analyzing brain tissue-based gene expression data of AD, 2,754 differentially expressed genes were identified, 559 of which were predicted to encode urine-excretory proteins that might act as candidate protein biomarkers of AD. GO enrichment analyses implied that they were mainly involved in microtubule-based process, myelin sheath, and calcium ion binding, suggesting that they might be associated with AD pathogenesis. In order to verify these proteins in urine, an iTRAQ experiment was carried out to analyze urine samples from AD patients and healthy controls, and 15 proteins were detected. Based on the expression changes of these proteins, 4 proteins were chosen for further validation by ELISA experiment, and SPP1, GSN, and IGFBP7 were found to be differentially expressed in the urine of AD patients. After a literature survey, we found that they were involved in AD pathophysiology and might serve as new urine biomarkers for AD. To our knowledge, this is the first time that urine biomarkers for AD were identified by combining computational and experimental methods. Furthermore, this is the first time SPP1, GSN, and IGFBP7 have been reported as potential urine protein biomarkers for AD. Therefore, our findings might provide significant guidance for finding early biomarkers of AD in urine.
