Immune Cell Profiling in Clinical Sepsis: Insights from scRNA-seq Meta-Analysis of publicly available datasets 4438

Abstract Description Sepsis is a life-threatening condition caused by an extreme immune response to infection, often resulting in organ dysfunction and death. Clinical variability, influenced by pathogens, infection sites, and genetic differences in immune responses, complicates the identification of universal biomarkers and treatments. Additionally, the availability and quality of single-cell RNA sequencing (scRNA-seq) datasets for sepsis are limited, often lacking appropriate control groups. To address these gaps, this study analyzed publicly available scRNA-seq data from peripheral blood mononuclear cells of septic (S) patients and patients with cardiogenic shock (SC) as controls. A robust pipeline was developed, combining quality control in R with large-scale data integration in Python using Scanpy and Scanorama. Nine immune cell clusters (macrophages, monocytes, dendritic cells, B cells, NK cells, mucosa-associated T, naïve T, CD4+ T, and CD8+ T cells) were present in both groups. However, reduced proportions of T cells expressing CD4, ADRB2, CD8A, EOMES, CD28, CD69, and GATA3 were found in the S compared to CS, suggesting their role in immune paralysis. Pathway enrichment analysis identified unique pathways implicated in sepsis pathology, including macrophage migration inhibitory factor, CD99, annexins, resistin, and selectin P ligand. Targeting these pathways could provide a means to refine inflammatory responses and restore immune balance in sepsis. Funding Sources Author Marina Ninkov was supported by The American Association of Immunologists through an Intersect Fellowship for Computational Scientists and Immunologists. Topic Categories Computational and Systems Immunology (COMP)