X-Q Wang1, X-M Wang, T-F Zhou, L-Q Dong. 1. Department of Pediatric Cardiology, Sichuan University, Sichuan, People's Republic of China.
Abstract
BACKGROUND: Asthma is a disease resulting from a complex interaction of multiple genetic and environmental factors. More than 200 asthma candidate genes have been identified in the past decades by using genetic association studies, positional cloning and knockout mouse approaches. AIM: This study was to identify differentially expressed genes and provide direction for medicine design related to pediatric allergic asthma with DNA microarray. MATERIALS AND METHODS: The gene expression profile of pediatric allergic asthma GSE18965 was downloaded from Gene Expression Omnibus database which includes 16 samples, 7 normal and 9 pediatric allergic asthma samples. The differentially expressed genes between normal and disease samples were identified by using R language. The co-expression coefficient was calculated among the differentially expressed genes to construct co-expression networks with String Software. Software DAVID and FuncAssociate were used to analyze the functions of genes in the co-expression networks. RESULTS: A total of 133 genes were identified as differentially expressed genes between normal and disease samples, and 8 related small medicine molecules were also obtained (penbutolol, felbinac, iodixanol, josamycin, oxolamine, 3-nitropropionic acid, scriptaid, and sanguinarine) from database CMAP. The differentially expressed genes were enriched in several biological processes, in which viral transcription and lysosome were the most significant GO term of up- or down-regulated genes. CONCLUSIONS: Our present findings shed new light on the molecular mechanism of allergic asthma and provide three small molecular medicines (3-nitropropionic acid, scriptaid, and sanguinarine) which have the potential to use in clinic for treatment of allergic asthma in future.
BACKGROUND: Asthma is a disease resulting from a complex interaction of multiple genetic and environmental factors. More than 200 asthma candidate genes have been identified in the past decades by using genetic association studies, positional cloning and knockout mouse approaches. AIM: This study was to identify differentially expressed genes and provide direction for medicine design related to pediatric allergic asthma with DNA microarray. MATERIALS AND METHODS: The gene expression profile of pediatric allergic asthma GSE18965 was downloaded from Gene Expression Omnibus database which includes 16 samples, 7 normal and 9 pediatric allergic asthma samples. The differentially expressed genes between normal and disease samples were identified by using R language. The co-expression coefficient was calculated among the differentially expressed genes to construct co-expression networks with String Software. Software DAVID and FuncAssociate were used to analyze the functions of genes in the co-expression networks. RESULTS: A total of 133 genes were identified as differentially expressed genes between normal and disease samples, and 8 related small medicine molecules were also obtained (penbutolol, felbinac, iodixanol, josamycin, oxolamine, 3-nitropropionic acid, scriptaid, and sanguinarine) from database CMAP. The differentially expressed genes were enriched in several biological processes, in which viral transcription and lysosome were the most significant GO term of up- or down-regulated genes. CONCLUSIONS: Our present findings shed new light on the molecular mechanism of allergic asthma and provide three small molecular medicines (3-nitropropionic acid, scriptaid, and sanguinarine) which have the potential to use in clinic for treatment of allergic asthma in future.