Expression patterns of eight RNA-modified regulators correlating with immune infiltrates during the progression of osteoarthritis.

Abstract

RNA modifications in eukaryotic cells have emerged as an exciting but under-explored area in recent years and are considered to be associated with many human diseases. While several studies have been published relating to m6A in osteoarthritis (OA), we only have limited knowledge of other kinds of RNA modifications. Our study investigated eight RNA modifiers' specific roles in OA including A-to-I, APA, m5C, m6A, m7G, mcm5s2U, Nm and Ψ together with their relationship with immune infiltration. RNA modification patterns in OA samples were identified based on eight-type RNA modifiers and their correlation with the degree of immune infiltration was also methodically investigated. Receiver operating characteristic curves (ROC) and qRT-PCR was performed to confirm the abnormal expression of hub genes. The RNA modification score (Rmscore) was generated by the applications of principal component analysis (PCA) algorithm in order to quantify RNA modification modes in individual OA patients. We identified 21 differentially-expressed RNA modification related genes between OA and healthy samples. For example, CFI, CBLL1 and ALKBH8 were expressed at high levels in OA (P<0.001), while RPUSD4, PUS1, NUDT21, FBL and WDR4 were expressed at low levels (P<0.001). Two candidate RNA modification regulators (WDR4 and CFI) were screened out utilizing a random forest machine learning model. We then identified two distinctive RNA modification modes in OA which were found to display distinctive biological features. High Rmscore, characterized by increased immune cell infiltration, indicated an inflamed phenotype. Our study was the first to systematically reveal the crosstalk and dysregulations eight-type of RNA modifications in OA. Assessing individuals' RNA modification patterns will be conductive to enhance our understanding of the properties of immune infiltration, provide novel diagnostic and prognostic biomarkers, and guide more effective immunotherapy strategies in the future.