{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T13:21:25Z","timestamp":1783948885520,"version":"3.55.0"},"reference-count":45,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,3,2]],"date-time":"2026-03-02T00:00:00Z","timestamp":1772409600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100019446","name":"Medical and Health Science and Technology Development Project of Shandong Province","doi-asserted-by":"publisher","award":["202109011085"],"award-info":[{"award-number":["202109011085"]}],"id":[{"id":"10.13039\/501100019446","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Physiol."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Atherosclerosis, a chronic inflammatory arterial disease, involves complex interactions among diverse immune cells. Although single-cell RNA sequencing (scRNA-seq) has revealed cellular heterogeneity within atherosclerotic lesions, the diversity of neutrophils and their crucial genes in atherogenesis remain elusive.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We integrated scRNA-seq data from six human atherosclerotic samples, comprising 47,604 single cells.The Harmony algorithm was applied for dimensionality reduction and batch effect correction, resulting in the identification of 16 distinct cell subtypes. High-resolution weighted gene co-expression network (hdWGCNA) analysis was performed to construct a gene co-expression network specifically within the neutrophil subtype. Characteristic genes were selected using Lasso regression. Immune infiltration analysis, gene set enrichment analysis (GSEA), and gene set variation analysis (GSVA) were conducted to investigate the biological functions and potential regulatory mechanisms of the key genes. An atherosclerosis animal model was employed to validate the expression levels of the key genes in carotid artery tissues. In addition, transcriptional regulatory network analysis and correlation analysis between key genes and atherosclerosis-related regulatory genes were carried out. Drug prediction was performed using the Connectivity Map (CMap) database.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A total of 16 cell subtypes were identified following batch effect correction. Annotation results revealed a increased proportion of neutrophils in atherosclerotic arteries compared to healthy controls. WGCNA analysis of neutrophil subtypes unveiled four key genes: CSTB, CHST15, RNASE1 and ATP2B1, which were validated as promising candidate biomarkers in independent cohorts (AUC &amp;gt;0.85). Preliminary validation in the animal model showed that the expression levels of the four genes were elevated in diseased carotid artery tissues compared to normal controls. Immune infiltration analysis demonstrated significant correlations between the key genes and the infiltration levels of multiple immune cell types. GSEA and GSVA showed that these genes were primarily enriched in pathways associated with inflammatory response, ferroptosis, and atherosclerosis-related signaling pathways. Transcriptional regulation analysis predicted potential transcription factors, and correlation analysis revealed significant associations between the key genes and known atherosclerosis-related regulatory genes. CMap analysis predicted several small-molecule compounds with potential therapeutic effects.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>Our findings uncover the previously unrecognized heterogeneity of neutrophils in atherosclerosis and identify four key genes as promising diagnostic markers and therapeutic targets. These findings provide new insights into the pathogenesis of atherosclerosis and provide a theoretical basis for developing targeted therapies against this devastating disease.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fphys.2026.1704443","type":"journal-article","created":{"date-parts":[[2026,3,2]],"date-time":"2026-03-02T05:21:07Z","timestamp":1772428867000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Single-cell transcriptomics reveals heterogeneous neutrophil populations and diagnostic biomarkers in atherosclerosis"],"prefix":"10.3389","volume":"17","author":[{"given":"Ping","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Nuclear Medicine, The 960th Hospital of the PLA","place":["Jinan, Shandong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiang","family":"Fu","sequence":"additional","affiliation":[{"name":"Medical Service Department, The 960th Hospital of the PLA","place":["Jinan, Shandong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuefeng","family":"Cai","sequence":"additional","affiliation":[{"name":"College of Liberal Arts and Sciences, University of Illinois Urbana-Champaign","place":["Champaign, IL, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiaxin","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine, The 960th Hospital of the PLA","place":["Jinan, Shandong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhenzhen","family":"Cui","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine, The 960th Hospital of the PLA","place":["Jinan, Shandong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiyu","family":"Sun","sequence":"additional","affiliation":[{"name":"Jinzhou Medical University Graduate Training Base (The 960th Hospital of the PLA)","place":["Jinan, Shandong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Quanli","family":"Qiu","sequence":"additional","affiliation":[{"name":"Jinzhou Medical University Graduate Training Base (The 960th Hospital of the PLA)","place":["Jinan, Shandong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaowen","family":"Ma","sequence":"additional","affiliation":[{"name":"Department of Pharmacy, The 960th Hospital of the PLA","place":["Jinan, Shandong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Min","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine, The 960th Hospital of the PLA","place":["Jinan, Shandong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,3,2]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"1083","DOI":"10.1038\/nmeth.4463","article-title":"SCENIC: single-cell regulatory network inference and clustering","volume":"14","author":"Aibar","year":"2017","journal-title":"Nat. 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