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Updated: Jun 19, 2025

A Data-Driven Approach to Quantifying Immune States in Sepsis
Published on: February 7, 2025
Summary data-based Mendelian randomization and single-cell RNA sequencing analyses identify immune associations with
Yongsan Yang1,2, Lei Dong3, Yanguo Li4
1Intensive Care Unit and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.
Abstract:
Sepsis is one of the major challenges in intensive care units, characterized by the complexity of the host immune status. To gain a deeper understanding of the pathogenesis of sepsis, it is crucial to study the phenotypic changes in immune cells and their underlying molecular mechanisms. We conducted Summary data-based Mendelian randomization analysis by integrating genome-wide association studies data for sepsis with expression quantitative trait locus data, revealing a significant decrease in the expression levels of 17 biomarkers in sepsis patients. Furthermore, based on single-cell RNA sequencing data, we elucidated potential molecular mechanisms at single-cell resolution and identified that LGALS9 inhibition in sepsis patients leads to the activation and differentiation of monocyte and T-cell subtypes. These findings are expected to assist researchers in gaining a more in-depth understanding of the immune dysregulation in sepsis.
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