Summary Data-based Mendelian Randomization and Single-cell RNA Sequencing Analyses Identify Immune Associations with Low-level LGALS9 in Sepsis

Overview

Journal J Cell Mol Med

Specialties Cell Biology
Molecular Biology

Date 2024 Jul 23

PMID 39044269

Authors

Yongsan Yang

Lei Dong

Yanguo Li

Ye Huang

Xiaoxi Zeng

Affiliations

Soon will be listed here.

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.

Citing Articles

Summary data-based Mendelian randomization and single-cell RNA sequencing analyses identify immune associations with low-level LGALS9 in sepsis.

Yang Y, Dong L, Li Y, Huang Y, Zeng X J Cell Mol Med. 2024; 28(14):e18559.

PMID: 39044269 PMC: 11265992. DOI: 10.1111/jcmm.18559.

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