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This research aimed to explore the disease pathogenesis and improve the diagnosis and treatment of pSS by mining inflammation-associated biomarkers.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Five pSS-related datasets were retrieved from the Gene Expression Omnibus (GEO) database. Inflammation-associated biomarkers were determined by the least absolute shrinkage and selection operator (LASSO) and support vector machines recursive feature elimination (SVM-RFE). Single sample gene set enrichment analysis (ssGSEA) was implemented to profile the infiltration levels of immune cells. Real-time quantitative PCR (RT-qPCR) verified the expression of biomarkers in clinical samples.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Four genes (LY6E, EIF2AK2, IL15, and CXCL10) were screened as inflammation-associated biomarkers in pSS, the predictive performance of which were determined among three pSS-related datasets (AUC\u2009&gt;\u20090.7). Functional enrichment results suggested that the biomarkers were involved in immune and inflammation-related pathways. Immune infiltration analysis revealed that biomarkers were notably connected with type 2\u00a0T helper cells, regulatory T cells which were significantly expressed between pSS and control. TESTOSTERONE and CYCLOSPORINE were predicted to take effect by targeting CXCL10 and IL15 in pSS, respectively.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>\n                      Four inflammation-associated biomarkers (LY6E, EIF2AK2, IL15, and CXCL10) were explored, and the underlying regulatory mechanisms and targeted drugs associated with these biomarkers were preliminarily investigated according to a series of bioinformatics methods based on the online datasets of pSS, which provided a reference for understanding the pathogenesis of pSS.\n                      <jats:table-wrap>\n                        <jats:table>\n                          <jats:tbody>\n                            <jats:tr>\n                              <jats:td align=\"left\" colspan=\"2\">\n                                Key Points\u2022\n                                <jats:italic>Inflammation-associated biomarkers (LY6E, EIF2AK2, IL15, and CXCL10) were firstly identified in Sj\u00f6gren\u2019s syndrome based on LASSO and SVM-RFE analyses.<\/jats:italic>\n                                \u2022\n                                <jats:italic>CXCL10, EIF2AK2 and LY6E were prominently positively correlated with immature B cells, while IL15 were significantly negatively correlated with memory B cells in Sj\u00f6gren\u2019s syndrome.<\/jats:italic>\n                                \u2022\n                                <jats:italic>LY6E, EIF2AK2, IL15, and CXCL10 were significantly more highly expressed in clinical Sj\u00f6gren\u2019s syndrome samples compared to healthy control samples, which was consistent with the analysis results of the GEO database.<\/jats:italic>\n                                \u2022\n                                <jats:italic>LY6E, EIF2AK2, IL15, and CXCL10 might be used as the biomarkers for the treatment and diagnosis of Sj\u00f6gren\u2019s syndrome.<\/jats:italic>\n                              <\/jats:td>\n                            <\/jats:tr>\n                          <\/jats:tbody>\n                        <\/jats:table>\n                      <\/jats:table-wrap>\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s10067-024-06901-y","type":"journal-article","created":{"date-parts":[[2024,2,20]],"date-time":"2024-02-20T11:02:06Z","timestamp":1708426926000},"page":"1335-1352","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Identification and verification of inflammatory biomarkers for primary Sj\u00f6gren\u2019s syndrome"],"prefix":"10.1007","volume":"43","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3387-2177","authenticated-orcid":false,"given":"Xiaodan","family":"Liu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haojie","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiao","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaodan","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yinji","family":"Jin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ying","family":"Han","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhihui","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,2,20]]},"reference":[{"key":"6901_CR1","doi-asserted-by":"publisher","first-page":"e3821","DOI":"10.1136\/bmj.e3821","volume":"344","author":"M Ramos-Casals","year":"2012","unstructured":"Ramos-Casals M, Brito-Zeron P, Siso-Almirall A, Bosch X (2012) Primary Sjogren syndrome. 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