Abstract
This work aims to analyze and construct a novel competing endogenous RNA (ceRNA) network in ankylosing spondylitis (AS) with bone bridge formation, lncRNA. Using RNA sequencing and bioinformatics, we analyzed expression profiles of long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and mRNAs in whole blood cells from 5 AS patients and 3 healthy individuals. Next, we verified the expression levels of candidate lncRNAs in 97 samples using the ΔΔCt value of real-time quantitative polymerase chain reaction (qRT-PCR). We used multivariate logistic regression analysis to screen lncRNAs and clinical indicators for use in the prediction model. Both SPSS 24.0 and R software were used for data analysis and prediction model construction. The results showed that compared with the normal controls, 205 long noncoding RNAs (lncRNAs), 961 microRNAs (miRNAs), and 200 mRNAs (DEmRNAs) were differentially expressed in the AS patients. We identified lncRNA 122K13.12 and lncRNA 326C3.7 among 205 lncRNAs differentially expressed between AS patients and healthy humans. Then, we noted that 30 miRNAs and five mRNAs formed a ceRNA network together with these two lncRNAs. These ceRNA networks might regulate the tumor necrosis factor (TNF) signaling pathway in AS development. In addition, the expression level of lncRNA 122K13.12 and lncRNA 326C3.7 correlated with various structural damage indicators in AS. Specifically, the lncRNA 326C3.7 expression level was an independent risk factor in bone bridge formation [area under the ROC curve (AUC) = 0.739 (0.609–0.870) and p = 0.003], and the best Youden Index was 0.405 (sensitivity = 0.800 and specificity = 0.605). Moreover, we constructed a lncRNA-based nomogram that could effectively predict bone bridge formation [AUC = 0.870 (0.780–0.959) and p < 0.001, and the best Youden Index was 0.637 (sensitivity = 0.900 and specificity = 0.737)]. In conclusion, we uncovered a unique ceRNA signaling network in AS with bone bridge formation and identified novel biomarkers and prediction models with the potential for clinical applications.
Highlights
Ankylosing spondylitis (AS) is one of the primary subtypes of spondyloarthritis (SpA), and its diagnosis is still based on the modified New York 1984 criteria (Linden et al, 1984)
Functional analysis showed that DElncRNA had 542 enriched GO terms, and coexpressed genes were enriched in 6733 GO terms that encompassed a variety of biological processes, including some of the essential terms such as response to a mechanical stimulus (GO:0009612), fat cell differentiation (GO:0045600), osteoblast differentiation (GO:0001649), and proliferation (GO:0033687)
Combined with functional analysis results related to bone formation in ankylosing spondylitis (AS) pathology and consistent expression of long noncoding RNAs (lncRNAs), we further selected two DElncRNAs that met the criteria to verify: ENSG00000254910 and ENSG00000278238
Summary
Ankylosing spondylitis (AS) is one of the primary subtypes of spondyloarthritis (SpA), and its diagnosis is still based on the modified New York 1984 criteria (Linden et al, 1984). New bone formation was produced via inflammatorydependent pathways (Poddubnyy and Sieper, 2017). This is because it is still difficult to detect bone bridges in advance at the early stages because of the lack of accurate and predictable biomarkers. Some previous studies have illustrated that lncRNAs were engaged in ceRNA networks in many diseases (Zhao et al, 2021). These lncRNAs might act as competing endogenous RNAs (ceRNAs) by competitively binding to miRNAs through their miRNA response elements, regulating the expression levels of miRNA-target mRNAs (Ju et al, 2020). The status quo that the ceRNA network is associated with bone bridge formation has not been investigated
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