{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T14:33:23Z","timestamp":1780410803404,"version":"3.54.1"},"reference-count":53,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2024,7,11]],"date-time":"2024-07-11T00:00:00Z","timestamp":1720656000000},"content-version":"vor","delay-in-days":10,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Immunity Inflam &amp;amp; Disease"],"published-print":{"date-parts":[[2024,7]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Osteomyelitis (OM) is recognized as a significant challenge in orthopedics due to its complex immune and inflammatory responses. The prognosis heavily depends on timely diagnosis, accurate classification, and assessment of severity. Thus, the identification of diagnostic and classification\u2010related genes from an immunological standpoint is crucial for the early detection and tailored treatment of OM.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Transcriptomic data for OM was sourced from the Gene Expression Omnibus\u00a0(GEO) database, leading to the identification of autophagy\u2010 and immune\u2010related differentially expressed genes (AIR\u2010DEGs) through differential expression analysis. Diagnostic and classification models were subsequently developed. The CIBERSORT algorithm was utilized to examine immune cell infiltration in OM, and the relationship between OM clusters and various immune cells was explored. Key AIR\u2010DEGs were further validated through the creation of OM animal models.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Analysis of the transcriptomic data revealed three AIR\u2010DEGs that played a significant role in immune responses and pathways. Nomogram and receiver operating characteristic curve analyses were performed, demonstrating excellent diagnostic capability for differentiating between OM patients and healthy individuals, with an area under the curve\u00a0of 0.814. An unsupervised clustering analysis discerned two unique patterns of autophagy\u2010 and immune\u2010related genes,\u00a0as well as gene patterns. Further exploration into immune infiltration exhibited notable variances across different subtypes, especially between OM cluster 1 and gene cluster A, highlighting their potential role in mitigating inflammatory responses by regulating immune activities. Moreover, the mRNA and protein expression levels of three AIR\u2010DEGs in the animal model were aligned with those in the training and validation data sets.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>From an immunological perspective, a diagnostic model was successfully developed, and two distinct clustering patterns were identified. These contributions offer a significant resource for the early detection and personalized immunotherapy of patients with OM.<\/jats:p><\/jats:sec>","DOI":"10.1002\/iid3.1339","type":"journal-article","created":{"date-parts":[[2024,7,11]],"date-time":"2024-07-11T14:59:50Z","timestamp":1720709990000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Integrative gene expression analysis and animal model reveal immune\u2010 and autophagy\u2010related biomarkers in osteomyelitis"],"prefix":"10.1002","volume":"12","author":[{"given":"Xiangwen","family":"Shi","sequence":"first","affiliation":[{"name":"Kunming Medical University  Kunming China"},{"name":"Laboratory of Yunnan Traumatology and Orthopedics Clinical Medical Center Yunnan Orthopedics and Sports Rehabilitation Clinical Medical Research Center  Kunming China"},{"name":"Department of Orthopedic Surgery 920th Hospital of Joint Logistics Support Force of PLA  Kunming 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