Aims

Osteoarthritis (OA) is a prevalent joint disorder with inflammatory response and cartilage deterioration as its main features. Dihydrocaffeic acid (DHCA), a bioactive component extracted from natural plant (gynura bicolor), has demonstrated anti-inflammatory properties in various diseases. We aimed to explore the chondroprotective effect of DHCA on OA and its potential mechanism.

Objectives. The aim of this study was to provide a comprehensive understanding of alterations in messenger RNAs (mRNAs), long noncoding RNAs (lncRNAs), and circular RNAs (circRNAs) in cartilage affected by osteoarthritis (OA). Methods. The expression profiles of mRNAs, lncRNAs, and circRNAs in OA cartilage were assessed using whole-transcriptome sequencing. Bioinformatics analyses included prediction and reannotation of novel lncRNAs and circRNAs, their classification, and their placement into subgroups. Gene ontology and pathway analysis were performed to identify differentially expressed genes (DEGs), differentially expressed lncRNAs (DELs), and differentially expressed circRNAs (DECs). We focused on the overlap of DEGs and targets of DELs previously identified in seven high-throughput studies. The top ten DELs were verified by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) in articular chondrocytes, both in vitro and in vivo. Results. In total, 739 mRNAs, 1152 lncRNAs, and 42 circRNAs were found to be differentially expressed in OA cartilage tissue. Among these, we identified 18 overlapping DEGs and targets of DELs, and the top ten DELs were screened by expression profile analysis as candidate OA-related genes. WISP2, ATF3, and CHI3L1 were significantly increased in both normal versus OA tissues and normal versus interleukin (IL)-1β-induced OA-like cell models, while ADAM12, PRELP, and ASPN were shown to be significantly decreased. Among the identified DELs, we observed higher expression of ENST00000453554 and MSTRG.99593.3, and lower expression of MSTRG.44186.2 and NONHSAT186094.1 in normal versus OA cells and tissues. Conclusion. This study revealed expression patterns of coding and noncoding RNAs in OA cartilage, which added sets of genes and noncoding RNAs to the list of candidate diagnostic biomarkers and therapeutic agents for OA patients. Cite this article: H. Li, H. H. Yang, Z. G. Sun, H. B. Tang, J. K. Min. Whole-transcriptome sequencing of knee joint cartilage from osteoarthritis patients. Bone Joint Res 2019;8:290–303. DOI: 10.1302/2046-3758.87.BJR-2018-0297.R1

Objectives

The aim of this study was to identify key pathological genes in osteoarthritis (OA).