Whole Blood mRNA Expression Pattern Differentiates AD Patients and Healthy Controls Through Bioinformatics Analysis

Mengjia Zhu, Liqun Wang

Abstract


Background: Gene chip has a wide range of applications in screening disease markers.

Methods: GSE63063 dataset including 238 healthy controls and 285 patients with Alzheimer’s disease (AD) was downloaded to investigate the whole blood mRNA expression pattern. Lumi and LIMMA packages of R software were used to screening differential-expressed genes (DEGs). We functionally annotate DEGs through DAVID database. Then STRING database and Cytoscape software were used to construct protein-protein interaction models for hub genes.

Results: Our results indicated that 51 DEGs altered in AD patients compared with healthy controls. These DEGs was associated with transcription (BP), RNA binding (MF) and ribosome (CC) terms and the ribosome signaling pathway. In addition, Ribosomal protein S17 (RPS17) was identified as the top 1 in hub genes using maximal clique centrality. RPS17 mutations reduced erythrocyte production and impaired brain development. Finally, the expression levels of the three genes (NDUFA1, RPL36AL, and NDUFS5) showed a good predictive effect.

Conclusion: In conclusion, we explored the expression of genes in the AD blood and NDUFA1 may be a potential biomarker for predicting AD.


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DOI: https://doi.org/10.5296/jbls.v10i2.14491

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Copyright (c) 2019 Liqun Wang

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Journal of Biology and Life Science  ISSN 2157-6076

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