Suppr超能文献

通过计算与实验方法相结合鉴定阿尔茨海默病的尿液生物标志物。

Urine-Based Biomarkers for Alzheimer's Disease Identified Through Coupling Computational and Experimental Methods.

机构信息

College of Life Science and Oceanography, Shenzhen Key Laboratory of Marine Biotechnology and Ecology, Shenzhen University, Shenzhen, China.

Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, College of Optoelectronic Engineering, Shenzhen University, Shenzhen, China.

出版信息

J Alzheimers Dis. 2018;65(2):421-431. doi: 10.3233/JAD-180261.

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.

摘要

阿尔茨海默病(AD)是一种慢性神经退行性疾病,导致近 70%的痴呆病例。然而,目前在尿液中尚未发现诊断用的蛋白质生物标志物。在本研究中,我们结合计算和实验方法来鉴定 AD 的尿液生物标志物。首先,通过分析 AD 患者的脑组织基因表达数据,我们鉴定出了 2754 个差异表达基因,其中 559 个被预测编码尿液分泌蛋白,这些蛋白可能作为 AD 的候选蛋白质生物标志物。GO 富集分析表明,它们主要参与微管相关过程、髓鞘和钙离子结合,表明它们可能与 AD 的发病机制有关。为了在尿液中验证这些蛋白质,我们进行了 iTRAQ 实验来分析 AD 患者和健康对照者的尿液样本,共检测到 15 种蛋白质。基于这些蛋白质的表达变化,我们选择了 4 种蛋白质通过 ELISA 实验进行进一步验证,发现 SPP1、GSN 和 IGFBP7 在 AD 患者的尿液中表达差异。经过文献调查,我们发现它们参与了 AD 的病理生理学过程,可能作为 AD 的新尿液生物标志物。据我们所知,这是首次通过结合计算和实验方法鉴定 AD 的尿液生物标志物。此外,这也是首次报道 SPP1、GSN 和 IGFBP7 可作为 AD 的潜在尿液蛋白质生物标志物。因此,我们的研究结果可能为在尿液中寻找 AD 的早期生物标志物提供重要指导。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验