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

被引:1
作者
Yang, Yongsan [1 ,2 ]
Dong, Lei [3 ]
Li, Yanguo [4 ]
Huang, Ye [5 ]
Zeng, Xiaoxi [2 ,6 ]
机构
[1] Sichuan Univ, West China Hosp, West China Biomed Big Data Ctr, Intens Care Unit, Chengdu, Peoples R China
[2] Sichuan Univ, Medx Ctr Informat, Chengdu, Peoples R China
[3] Chinese Acad Sci, Inst Biophys, Ctr Big Data Res Hlth, Key Lab RNA Biol, Beijing, Peoples R China
[4] Ningbo Univ, Inst Drug Discovery Technol, Ningbo, Peoples R China
[5] China Acad Chinese Med Sci, Xiyuan Hosp, Dept Emergency Med, Beijing, Peoples R China
[6] Sichuan Univ, West China Hosp, West China Biomed Big Data Ctr, Chengdu, Peoples R China
关键词
LGALS9; monocytes; single-cell RNA-seq; Summary data-based Mendelian randomization; T cells; STEADY-STATE; MONOCYTES; FATE; DYNAMICS; EQTL;
D O I
10.1111/jcmm.18559
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
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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页数:11
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