{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,26]],"date-time":"2026-01-26T17:35:26Z","timestamp":1769448926897,"version":"3.49.0"},"reference-count":27,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,1,26]],"date-time":"2026-01-26T00:00:00Z","timestamp":1769385600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Microbiol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Predicting progression to active tuberculosis (TB) is a critical unmet need, as current immunological tests only detect infection but cannot discriminate those who will develop active disease. A reliable prognostic biomarker could enable targeted preventive therapy and transform TB control strategies.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      We performed deep plasma proteomics using data-independent acquisition mass spectrometry on a prospective cohort of 60 TB-exposed students in Jiangsu Province, China, comprising 40 individuals with\n                      <jats:italic>Mycobacterium tuberculosis<\/jats:italic>\n                      infection and 20 uninfected controls.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Over 2\u202fyears of follow-up, 21 of the 40 infected participants progressed to active disease, and a LASSO-Cox model with internal cross-validation for tuning the regularization parameter (\n                      <jats:italic>\u03bb<\/jats:italic>\n                      ) was used to develop a prognostic signature from baseline plasma samples. A 33-protein signature predicted progression to active TB with high discriminatory performance in this cohort (AUC\u202f=\u202f0.992, 95% CI 0.977\u20131.0). This signature revealed a distinct pre-symptomatic state in progressors, defined by a pro-thrombotic shift in the coagulation cascade and profound disruption of actin cytoskeleton dynamics. The proteomic alterations were detectable up to 2\u202fyears before clinical diagnosis, providing a potential window for intervention. Functional network analysis identified key hub proteins including ACTR3, ACTN1, and MYH9 (actin remodeling) and F2 (coagulation).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>We identified a plasma protein signature that accurately predicts progression from latent to active tuberculosis, linking disease onset to dysregulation of the actin cytoskeleton and coagulation. This biomarker provides a basis for precision preventive therapy and identifies novel host-directed therapeutic targets.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fmicb.2025.1746190","type":"journal-article","created":{"date-parts":[[2026,1,26]],"date-time":"2026-01-26T07:09:21Z","timestamp":1769411361000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A plasma proteomic signature of the actin-coagulation axis accurately predicts progression to active tuberculosis"],"prefix":"10.3389","volume":"16","author":[{"given":"Peng","family":"Lu","sequence":"first","affiliation":[{"name":"Department of Chronic Communicable Disease, Jiangsu Provincial Center for Disease Control and Prevention","place":["Nanjing, China"]},{"name":"Key Laboratory of Public Health Safety and Emergency Prevention and Control Technology of Higher Education Institutions in Jiangsu Province, Department of Epidemiology, School of Public Health, Nanjing Medical University","place":["Nanjing, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weiwei","family":"Gao","sequence":"additional","affiliation":[{"name":"Department of Tuberculosis, The Second Hospital of Nanjing, Nanjing University of Chinese Medicine","place":["Nanjing, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoyan","family":"Ding","sequence":"additional","affiliation":[{"name":"Department of Chronic Communicable Disease, Jiangsu Provincial Center for Disease Control and Prevention","place":["Nanjing, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingjing","family":"Pan","sequence":"additional","affiliation":[{"name":"Department of Chronic Communicable Disease, Jiangsu Provincial Center for Disease Control and Prevention","place":["Nanjing, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hui","family":"Ding","sequence":"additional","affiliation":[{"name":"Department of Chronic Communicable Disease, Jiangsu Provincial Center for Disease Control and Prevention","place":["Nanjing, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiao","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Chronic Communicable Disease, Jiangsu Provincial Center for Disease Control and Prevention","place":["Nanjing, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Limei","family":"Zhu","sequence":"additional","affiliation":[{"name":"Department of Chronic Communicable Disease, Jiangsu Provincial Center for Disease Control and Prevention","place":["Nanjing, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiang","family":"Huo","sequence":"additional","affiliation":[{"name":"Department of Chronic Communicable Disease, Jiangsu 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