{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T15:58:46Z","timestamp":1785427126175,"version":"3.56.0"},"reference-count":36,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T00:00:00Z","timestamp":1775174400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62102104 and 62202115"],"award-info":[{"award-number":["62102104 and 62202115"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"award":["62102104 and 62202115"],"award-info":[{"award-number":["62102104 and 62202115"]}],"id":[{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Genes"],"abstract":"<jats:p>Background: In complex biological processes, there exists a tipping point (pre-disease state) when the system undergoes a sudden and dramatic shift to a contrasting state. Accurate detection of the pre-disease state is critical for preventive medicine. However, precise detection of the pre-disease state proves challenging due to the clinical single-sample problem. Methods: To address this challenge, in this study, we introduce a novel single-sample pre-disease state detection method based on the change in local network enrichment level. Results: We validated the proposed method on five independent real datasets, including one influenza virus infection time-course dataset and four tumor datasets. Experimental results confirmed that the proposed method can accurately identify the pre-disease state prior to overt disease onset. Further analysis verified key genes identified by the proposed method in pre-disease state are associated with viral infection and immune dysregulation for the influenza dataset, and tumor metastasis for the tumor datasets. Conclusions: These results demonstrate that this method is a robust and biologically interpretable tool for single-sample pre-disease state detection, with great potential for clinical translation in individualized preventive medicine.<\/jats:p>","DOI":"10.3390\/genes17040425","type":"journal-article","created":{"date-parts":[[2026,4,6]],"date-time":"2026-04-06T03:11:28Z","timestamp":1775445088000},"page":"425","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Detecting the Pre-Disease State of Single Sample Through the Change in Local Network Enrichment Level"],"prefix":"10.3390","volume":"17","author":[{"given":"Zhenshen","family":"Bao","sequence":"first","affiliation":[{"name":"School of Information Engineering, Taizhou University, Taizhou 225300, China"},{"name":"State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ying","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1678-5960","authenticated-orcid":false,"given":"Zhiyu","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Rehabilitation and Physical Education, Nanjing Normal University of Special Education, Nanjing 210038, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9196-7027","authenticated-orcid":false,"given":"Xianbin","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer and Big Data Science, Jiujiang University, Jiujiang 332000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4088-4117","authenticated-orcid":false,"given":"Yunfei","family":"Bai","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,4,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"342","DOI":"10.1038\/srep00342","article-title":"Detecting early-warning signals for sudden deterioration of complex diseases by dynamical network biomarkers","volume":"2","author":"Chen","year":"2012","journal-title":"Sci. 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