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.