《Chinese Journal of Rehabilitation Theory and Practice》 ›› 2015, Vol. 21 ›› Issue (10): 1117-1123.

• 基础研究 •     Next Articles

Mining Alzheimer's Disease Susceptible Genes Based on Data Integration Strategy

WANG Mei-qin1, YANG Kai-bing1, JI Ran1, PANG Qing-hua1, ZHANG Da-bao1, ZHANG Min1,2   

  1. 1. Department of Bioinformatics, School of Biomedical Engineering, Capital Medical University, Beijing 100069, China; 2. Alzheimer's Disease Center, Beijing Institute for Brain Disorders, Capital Medical University, Beijing 100069, China
  • Received:1900-01-01 Revised:1900-01-01 Published:2015-10-25 Online:2015-10-25

Abstract: Objective To clarify the role of the known genes and new discovered genes, which were important to the pathogenesis of Alzheimer's disease (AD), in order to provide targets for clinical prevention, diagnosis and treatment. Methods In order to predict AD susceptible genes, the website databases (OMIM, AlzGene) and a variety of pathogenic gene prediction tools such as Endeavour, Gene Prospector, GLAD4U and ProphNet were used to make biological analysis. Results Disease-causing genes were directly obtained from the OMIM and Alzgene databases, and related genes were collected by 4 kinds of tools (select gene whose frequency was 3 or more). The data were shared and a list of 25 genes was gotten. These genes were CALHM1、 ABCA7、 A2M、 CLU、 SORL1、 HFE、 CD2AP、 APP、 ACE、 PICALM、 APOE、 NOS3、 MS4A6A、 PLD3、 CR1、 ADAM10、 MS4A4E、 BLMH、 PSEN1、 CD33、 PSEN2、 MPO、 APBB2、 BIN1 and PLAU. Conclusion CALHM1, ABCA7, A2M and CLU, etc., have a certain correlation with AD, which provide theoretical basis for further research of AD genics and clinical treatment.

Key words: Alzheimer's disease, database resource, susceptible gene, gene prediction tool