Abstract:

Objective To explore the potential pathogenesis-related long non-coding RNA (lncRNA) in gouty arthritis (GA) and the correlation with inflammatory factors. Methods GA microarray data were obtained from the Gene Expression Omnibus(GEO) database, and key lncRNA was identified and intersected by multiple machine learning methods. mRNAs co-expressed with lncRNAs were performed GO enrichment analysis. Kyoto encyclopedia of genes and genomes (KEGG) signaling pathway analysis was accomplished. The expression of key lncRNAs in GA patients was verified using quantitative real-time polymerase chain reaction(qRT-PCR) and the correlation between lncRNA and inflammatory factor levels was analyzed. The diagnostic value of LINC01465 expression levels in GA patients was analyzed by receiver operator characteristic(ROC) curves. Results One key lncRNA(LINC01465) was identified. GO enrichment analysis showed that the genes co-expressed with LINC01465 were enriched in RNA splicing, oxidative phosphorylation, reduced nicotinamide adenine dinucleotide (NADH ) dehydrogenase activity and other functions. KEGG signaling pathway analysis presented that it was mainly enriched in metabolic and inflammatory pathways such as nicotinate and nicotinamide metabolism, phosphoinositide 3-kinase(PI3K)-Akt, tumor necrosis factor signaling pathway. The qRT-PCR results exhibited that LINC01465 expression was upregulated in the patients with GA and was proportional to the expression of hematocrit, C-reactive protein and interleukin-6. The area under the receiver operator characteristic curve(AUC) was 0.86. Conclusions LINC01465 could be a potential diagnostic and therapeutic target for GA.

Key words: Gouty arthritis, LINC01465, Machine learning, Signaling pathway