{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T20:46:49Z","timestamp":1782852409383,"version":"3.54.5"},"reference-count":39,"publisher":"SAGE Publications","issue":"2","license":[{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"Xianning Central Hospital","award":["2025XYA001"],"award-info":[{"award-number":["2025XYA001"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Science Progress"],"published-print":{"date-parts":[[2026,4]]},"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study aimed to identify immune-related hub genes shared between acute myocardial infarction (AMI) and metabolic syndrome (MetS), and to construct and validate a blood-based gene diagnostic signature for AMI, with the hypothesis that this signature may be informative for AMI risk assessment in MetS patients.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Two AMI datasets (GSE66360, GSE61145) and one MetS dataset (GSE98895) were obtained from the Gene Expression Omnibus (GEO) database. Based on the GSE66360 dataset, 285 AMI-related common genes were identified as the intersection between 1409 differentially expressed genes (DEGs) and 304 module genes, identified via Limma and weighted gene co-expression network analysis (WGCNA), respectively. Subsequently, the intersection of these 285 AMI-related common genes and 1446 MetS-related DEGs yielded 40 genes that were primarily associated with immunoregulation, as revealed by functional enrichment analysis. After constructing a protein-protein interaction (PPI) network, 30 node genes were selected and ranked according to node degree. Six candidate hub genes (THBD, MMP9, IRAK3, CXCL16, NLRP3, and JDP2) identified via machine learning were used to establish a diagnostic model and evaluate its diagnostic value.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We revealed that the six candidate genes demonstrated strong diagnostic value for AMI (AUC ranging from 0.86 to 0.94, with 95% confidence intervals [CIs]). Moreover, a diagnostic nomogram constructed from these genes allows for visual quantification of AMI probability. Immune cell infiltration analysis revealed dysregulation across multiple immune cell subsets in AMI. These six immune-based hub genes have been identified as potential diagnostic biomarkers for AMI, with hypothesized relevance in MetS patients.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>These findings provide a hypothesis-generating resource for understanding inflammatory links between MetS and AMI, though clinical utility for risk stratification in MetS patients requires further prospective validation.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/00368504261448304","type":"journal-article","created":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T00:19:48Z","timestamp":1777421988000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Identification of immune-related genes shared between acute myocardial infarction and metabolic syndrome and construction of a diagnostic signature for acute myocardial infarction"],"prefix":"10.1177","volume":"109","author":[{"given":"Ni","family":"Feng","sequence":"first","affiliation":[{"name":"The First Affiliated Hospital of Hubei University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meiguo","family":"Feng","sequence":"additional","affiliation":[{"name":"The First Affiliated Hospital of Hubei University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian","family":"Ruan","sequence":"additional","affiliation":[{"name":"The First Affiliated Hospital of Hubei University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cai","family":"Zhou","sequence":"additional","affiliation":[{"name":"The First Affiliated Hospital of Hubei University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoying","family":"Song","sequence":"additional","affiliation":[{"name":"The First Affiliated Hospital of Hubei University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Chen","sequence":"additional","affiliation":[{"name":"The First Affiliated Hospital of Hubei University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-5989-619X","authenticated-orcid":false,"given":"Shuai","family":"Hou","sequence":"additional","affiliation":[{"name":"The First Affiliated Hospital of Hubei University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,4,28]]},"reference":[{"key":"e_1_3_6_2_2","first-page":"e153","article-title":"Heart disease and stroke statistics-2022 update: a report from the american heart association","volume":"8","author":"Tsao CW","year":"2022","unstructured":"Tsao CW, Aday AW, Almarzooq ZI, et al. 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