Summary data-based Mendelian randomization and single-cell RNA sequencing analyses identify immune associations with low-level LGALS9 in sepsis.
Yongsan YangLei DongYanguo LiYe HuangXiaoxi ZengPublished in: Journal of cellular and molecular medicine (2024)
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.
Keyphrases
- single cell
- intensive care unit
- septic shock
- acute kidney injury
- rna seq
- end stage renal disease
- electronic health record
- big data
- ejection fraction
- newly diagnosed
- chronic kidney disease
- poor prognosis
- high throughput
- peritoneal dialysis
- prognostic factors
- gene expression
- dna methylation
- genome wide association
- optical coherence tomography
- data analysis
- long non coding rna
- genome wide
- mass spectrometry
- high resolution
- patient reported
- artificial intelligence
- single molecule