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

Author:

Yang Yongsan12,Dong Lei3,Li Yanguo4,Huang Ye5,Zeng Xiaoxi26ORCID

Affiliation:

1. Intensive Care Unit and West China Biomedical Big Data Center West China Hospital, Sichuan University Chengdu China

2. Med‐X Center for Informatics Sichuan University Chengdu China

3. Key Laboratory of RNA Biology, Center for Big Data Research in Health, Institute of Biophysics, Chinese Academy of Sciences Beijing China

4. Institute of Drug Discovery Technology, Ningbo University Ningbo China

5. Department of Emergency Medicine Xiyuan Hospital of China Academy of Chinese Medical Sciences Beijing China

6. West China Biomedical Big Data Center West China Hospital, Sichuan University Chengdu China

Abstract

AbstractSepsis 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.

Funder

National Key Research and Development Program of China

Chengdu Municipal Science and Technology Program

Sichuan Province Science and Technology Support Program

Publisher

Wiley

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