Yong-Liang Chu1,2, Yi-Qi Jiang3,2, Si-Long Sun3,2, Bao-Lin Zheng4, Wan-Sheng Xiong5, Wen-Jie Li1, Xiu-Min Chen1, Mao-Jie Wang1, Qing-Chun Huang1, Run-Yue Huang1,3,6. 1. Department of Rheumatology, The Second Affiliated Hospital, Guangzhou University of Chinese Medicine (Guangdong Provincial Hospital of Chinese Medicine), Guangzhou, Guangdong, China. 2. These authors contributed equally to this article. 3. Beijing Genomics Institute-Shenzhen, Shenzhen, Guangdong, China. 4. Department of Rheumatology, Foshan Hospital of Traditional Chinese Medicine, Foshan, Guangdong, China. 5. Department of Rheumatology, Beijing University of Chinese Medicine Shenzhen Hospital, Shenzhen, Guangdong, China. 6. Guangdong Provincial Key Laboratory of Clinical Research on Traditional Chinese Medicine Syndrome, Guangzhou, Guangdong, China.
Abstract
OBJECTIVE: This study was designed to determine the differential profiles of long non-coding RNAs (lncRNAs) between rheumatoid arthritis (RA) and gouty arthritis (GA), which may lead to the discovery of specific biomarkers for RA diagnosis and treatment in the future. METHODS: The profiles of lncRNAs were determined by Agilent microarray. Bioinformatics analyses, including Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, of the large dataset obtained from microarray experiments were performed. RESULTS: A total of 765 lncRNAs and 2,808 mRNAs were significantly and differentially expressed in RA samples as compared to GA samples. Moreover, of 2,808 differentially expressed mRNAs, 178 upregulated mRNAs and 21 downregulated mRNAs were identified to be strongly correlated with lncRNAs examined in this study. Bioinformatics analyses revealed the tumor-like phenotype of synovial cells in RA and the involvement of immune system process in GA. In addition, this study demonstrated the significantly different molecular origins of two Chinese Medicine syndrome patterns of RA patients -- blood stasis and non-blood stasis. CONCLUSIONS: Our study showed for the first time the differentially expressed lncRNA profiles in synovial tissues between RA and GA and between two clinical phenotypes of RA patients differentiated by Chinese Medicine. This study helps achieving personalized medicine in RA. Larger-scale studies are required to validate the data presented.
OBJECTIVE: This study was designed to determine the differential profiles of long non-coding RNAs (lncRNAs) between rheumatoid arthritis (RA) and gouty arthritis (GA), which may lead to the discovery of specific biomarkers for RA diagnosis and treatment in the future. METHODS: The profiles of lncRNAs were determined by Agilent microarray. Bioinformatics analyses, including Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, of the large dataset obtained from microarray experiments were performed. RESULTS: A total of 765 lncRNAs and 2,808 mRNAs were significantly and differentially expressed in RA samples as compared to GA samples. Moreover, of 2,808 differentially expressed mRNAs, 178 upregulated mRNAs and 21 downregulated mRNAs were identified to be strongly correlated with lncRNAs examined in this study. Bioinformatics analyses revealed the tumor-like phenotype of synovial cells in RA and the involvement of immune system process in GA. In addition, this study demonstrated the significantly different molecular origins of two Chinese Medicine syndrome patterns of RA patients -- blood stasis and non-blood stasis. CONCLUSIONS: Our study showed for the first time the differentially expressed lncRNA profiles in synovial tissues between RA and GA and between two clinical phenotypes of RA patients differentiated by Chinese Medicine. This study helps achieving personalized medicine in RA. Larger-scale studies are required to validate the data presented.