Identification of Blood Biomarkers for Alzheimer's Disease Through Computational Prediction and Experimental Validation.

ABSTRACT: Background: Alzheimer's disease (AD) is the major cause of dementia in population aged over 65 years, accounting up to 70% dementia cases. However, validated peripheral biomarkers for AD diagnosis are not available up to present. In this study, we adopted a new strategy of combination of computational prediction and experimental validation to identify blood protein biomarkers for AD. Methods: First, we collected tissue-based gene expression data of AD patients and healthy controls from GEO database. Second, we analyzed these data and identified differentially expressed genes for AD. Third, we applied a blood-secretory protein prediction program on these genes and predicted AD-related proteins in blood. Finally, we collected blood samples of AD patients and healthy controls to

SUBMITTER: Yao F 

PROVIDER: S-EPMC6331438 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature