Decoding monocyte heterogeneity in sepsis: a single-cell apoptotic signature for immune stratification and guiding precision therapy

作者：Wenjuan Duan, Qi Chen, Wei Li, Haiying Zhou, Xiaorong Deng, Yan Zhang · 发表于：Frontiers in Pharmacology · 年份：2025 · DOI：10.3389/fphar.2025.1675887 · 被引用次数：3 · 研究领域：Sepsis Diagnosis and Treatment、Neutrophil, Myeloperoxidase and Oxidative Mechanisms、Immune Response and Inflammation

Background: The effectiveness of immunomodulatory therapies in sepsis is often hampered by profound and patient-specific immune heterogeneity. Classical monocytes play a central role in the progression toward sepsis-induced immunoparalysis, with their apoptotic rate serving as a sensitive marker of immune dysfunction. Traditional bulk transcriptomic approaches fail to resolve this complexity. Here, we harness single-cell RNA sequencing to delineate the apoptotic landscape of classical monocytes and identify robust molecular biomarkers for immunological stratification and targeted intervention. Methods: We integrated single-cell and bulk transcriptomic data from four independent cohorts. A machine learning pipeline incorporating SVM, RF, XGB, and GLM algorithms was used to identify hub genes associated with monocyte apoptosis. A diagnostic nomogram was constructed based on the selected gene signature and validated across external datasets. Clinical relevance was confirmed through Western blot analysis of purified monocytes from sepsis patients and healthy controls. Results: A four-gene signature (G0S2, GZMA, ITM2A, PAG1) emerged as a specific apoptotic fingerprint of classical monocytes. The diagnostic model based on these signature genes demonstrated excellent discriminatory performance, effectively stratifying patients into high-risk and low-risk groups (AUC >0.8 across multiple validation cohorts), with each risk group exhibiting distinctly different immune states. High-ris...