Background: The pathogenesis and diagnosis of Ankylosing Spondylitis (AS) has remained uncertain due to several reasons, including the lack of studies on the local and systemic immune response in AS. To construct a clinical diagnostic model, this study identified the micro RNA-messenger RNA (miRNA-mRNA) interaction network and immune cell infiltration-related hub genes associated with AS. Materials and Methods: Total RNA was extracted and purified from the interspinous ligament tissue samples of three patients with AS and three patients without AS; miRNA and mRNA microarrays were constructed using the extracted RNA. Bioinformatic tools were used to construct an miRNA-mRNA network, identify hub genes, and analyze immune infiltration associated with AS. Next, we collected the blood samples and clinical characteristics of 359 patients (197 with AS and 162 without AS). On the basis of the clinical characteristics and results of the routine blood tests, we selected immune-related cells whose numbers were significantly different in patients with AS and patients without AS. Univariate and multivariate logistic regression analysis was performed to construct a nomogram. Immunohistochemistry staining analysis was utilized to verify the differentially expression of LYN in AS and controls. Results: A total of 225 differentially expressed miRNAs (DE miRNAs) and 406 differentially expressed mRNAs (DE mRNAs) were identified from the microarray. We selected 15 DE miRNAs and 38 DE mRNAs to construct a miRNA-mRNA network. The expression of LYN, an immune-related gene, correlated with the counts of monocytes, neutrophils, and dendritic cells. Based on the independent predictive factors of sex, age, and counts of monocytes, neutrophils, and white blood cells, a nomogram was established. Receiver operating characteristic (ROC) analysis was performed to evaluate the nomogram, with a C-index of 0.835 and AUC of 0.855. Conclusion: LYN, an immune-related hub gene, correlated with immune cell infiltration in patients with AS. In addition, the counts of monocytes and neutrophils were the independent diagnostic factors for AS. If verified in future studies, a diagnostic model based on these findings may be used to predict AS effectively.

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