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Rheumatoid arthritis (RA) and osteoarthritis (OA) are two most common rheumatic diseases in the world. Although there are standard methods for the diagnosis of both RA and OA, the differentials in some cases are poor. With deepening research, the role of autophagy in maintaining cell homeostasis and thus enabling cells adapt to external environments has become increasingly prominent. Both RA and OA, two diseases with inherent differences in pathogenesis, gradually show differences in autophagy levels. Our study therefore aims to further understand differences in pathogenesis of RA and OA through in-depth studies of autophagy in RA and OA. We also define appropriate autophagy-related markers as recognition indicators. Differences in autophagy levels between RA and OA were found based on analysis of the Kyoto Encyclopedia of Genes and Genomes (KEGG) and single-sample gene set enrichment (ssGSEA). These differences were mainly caused by 134 differentially expressed genes (DEGs). In two autophagy-related genes, CXCR4 and SERPINA1, there existed significant statistical difference between RA and OA. An autophagy related index (ARI) was thus successfully constructed based on CXCR4 and SERPINA by binary logistic regression of the generalized linear regression (GLR) algorithm. Pearson analysis indicated that the expression of CXCR4, SERPINA1, and ARI were closely correlated with autophagy scores and immune infiltration. Moreover, ARI showed high disease identification through receiver operating characteristic (ROC) analysis (AUCtesting cohort = 0.956, AUCtraining cohort = 0.867). These results were then verified in GSE12021 independent cohort. In conclusion, ARI associated with autophagy and immune infiltration was successfully constructed for accurately identifying OA and RA. The index, thus, has great potential in clinical applications.