Randomized trial identifies distinct neutrophil subsets in sepsis, suggesting new treatment opportunities.
Rationale Sepsis is a state of life-threatening organ dysfunction in the setting of infection. It is biologically heterogeneous, as evidenced by whole blood transcriptomic analyses that reveal distinct molecular subtypes based on gene expression. At the cellular level, sepsis is primarily mediated by neutrophils, a leukocyte population increasingly recognized as heterogeneous across several domains. We sought to further characterize neutrophil heterogeneity by identifying neutrophil subsets in critically ill patients with severe sepsis based on multidimensional mass cytometry analysis. Methods We generated time series mass cytometry (CyTOF) data from whole blood samples taken from 17 patients with sepsis admitted to an intensive care unit who were enrolled in a randomized controlled trial of high-dose vitamin C. We analyzed these data using unsupervised machine learning techniques to identify distinct neutrophil subtypes. We characterized the resulting subtypes and described their changes over time. Results We analyzed approximately 1.5 million cytometry events gated as neutrophils. We identified five clusters that reveal complex heterogeneity across multiple neutrophil markers of maturation and activation including olfactomedin-4 (OLFM4), CD177, glucose transporter 1 (GLUT1), CD16, and lipocalin-2. The two dominant clusters differed primarily in the abundance of OLFM4, a neutrophil granule protein. Between Day 1 and Day 7, there was an increased proportion of neutrophils in the dominant OLFM4-expressing cluster, a difference primarily driven by increased abundance of OLFM4 in the placebo group, but not the vitamin C group. Conclusions Our findings point to complex multidimensional heterogeneity among neutrophils in sepsis, thereby extending the current concept of neutrophil heterogeneity with new data from critically ill patients with sepsis derived from mass cytometry. Variation in the temporal differences in cluster proportions between treatment arms may suggest opportunities for precision sepsis treatment.
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Lima et al. (2026) studied this question.
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