Mining diabetes cardiomyopathy expression profile chip based on bioinformatics
SHI Lei1 LI Wanpeng2 AN Junyu1 LIU Yi1 WU Peng1 WU Wenyu3 CAO Yunshan2 HUANG Yan2
1.Graduate School, Gansu University of Chinese Medicine, Gansu Province, Lanzhou 730000, China;
2.the Second Department of Cardiology, Gansu Provincial Hospital, Gansu Province, Lanzhou 730000, China;
3.Graduate School, Ningxia Medical University, Ningxia Hui Autonomous Region, Yinchuan 750004, China
Abstract：Objective To explore differentially expressed genes and their function related to diabetic cardiomyopathy (DC) based on bioinformatics technology. Methods The gene expression profile data set GSE4547 was analyzed using bioinformatics methods. Results The original chip data was mined and 79 differentially expressed genes were screened. Based on gene ontology functional annotation and related pathway analysis, as well as the construction of differentially coexpressed genes protein-protein interaction and module analysis, 10 key genes of Hk2, Col1a2, Col1a1, Col3a1, Slc2a1, Cpt1a, Slc2a4, Cd36, Ucp3 and Pdk4 were finally obtained as the key genes of Streptozozin induced DC. Conclusion The 10 key genes eventually obtained may become potential therapeutic targets for the treatment of DC in the future, and provide a new perspective and guidance for the exploration of functional changes of DC related genes and signaling pathways in the future.
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2019, Vol. 16 
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