ORIGINAL RESEARCH article
Front. Med.
Sec. Intensive Care Medicine and Anesthesiology
Volume 12 - 2025 | doi: 10.3389/fmed.2025.1521827
This article is part of the Research TopicSepsis Awareness Month 2024View all 3 articles
AI-Driven Discovery of Minimal Sepsis Biomarkers for Disease Detection and Progression: Precision Medicine Across Diverse Populations
Provisionally accepted
Zhengjun Zhang1*
Qiyuan Su2
Jingtao Huang3
Yunlong Zhang3Zhou Liu3Zhihua Lv3Chunming Zhang1Chengxiu Ling2Hanwen Su3*
LIying Zhan3*- 1University of Wisconsin-Madison, Madison, United States
- 2Xi'an Jiaotong-Liverpool University, Suzhou, Jiangsu Province, China
- 3Renmin Hospital of Wuhan University, Wuhan, Hubei Province, China
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Background: Sepsis biomarker research over the past 30 years has been plagued by the use of wrong animal models and inappropriate patient selections, leading to the failure of translating findings into precision medicine. Thousands of sepsis-related gene biomarkers have been published, but this excess hinders medical advancement because 1) an overwhelming number of genes make targeted drug development and precision medicine unfeasible; 2) many biomarkers lack cross-cohort validation, rendering them clinically unhelpful. Our goal is to identify a highly informative, single-digit set of sepsis biomarkers to advance precision medicine.Methods: We conducted large-scale research on heterogeneous populations, including patients with sepsis, severe sepsis, and septic shocks, and collected plasma samples from 32 sepsis patients and 18 healthy controls at Renmin Hospital of Wuhan University, China. RNA was isolated using the HYCEZMBIO Serum/Plasma RNA Kit, and RT-qPCR was performed on the Roche Light Cycler 480 platform. An AI-based max-logistic competing classifier was applied across eleven cohorts with thousands of samples, using both self-designed and public datasets to identify the most critical sepsis biomarkers.Results: Our analysis highlights CKAP4, FCAR, and RNF4 as key genetic drivers in sepsis-related variations. In whole blood, NONO is crucial for immune response, while in plasma, PLEKHO1 and BMP6 reveal further genetic heterogeneities. Pediatric patients also exhibit significant contributions from RNASE2 and OGFOD3. These genes form the most effective miniature set of biomarkers.Conclusion: Achieving 99.42% accuracy across cohorts, this miniature set outperforms larger published gene sets. These findings provide critical insights for personalized risk assessment, targeted drug development, and tailored treatments for both adult and pediatric sepsis patients
Keywords: Gene interaction, biomarkers, AI, Disease detection, progression
Received: 03 Nov 2024; Accepted: 30 May 2025.
Copyright: © 2025 Zhang, Su, Huang, Zhang, Liu, Lv, Zhang, Ling, Su and Zhan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Zhengjun Zhang, University of Wisconsin-Madison, Madison, United States
Hanwen Su, Renmin Hospital of Wuhan University, Wuhan, 430060, Hubei Province, China
LIying Zhan, Renmin Hospital of Wuhan University, Wuhan, 430060, Hubei Province, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.