Cargando…
LPIN1 Is a Regulatory Factor Associated With Immune Response and Inflammation in Sepsis
OBJECTIVES: Sepsis is a clinical disease that is typically treated in the intensive care unit, and the complex pathophysiology under this disease has not been thoroughly understood. While ferroptosis is involved in inflammation and infection, its effect in sepsis is still unknown. The study aimed to...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8865371/ https://www.ncbi.nlm.nih.gov/pubmed/35222395 http://dx.doi.org/10.3389/fimmu.2022.820164 |
Sumario: | OBJECTIVES: Sepsis is a clinical disease that is typically treated in the intensive care unit, and the complex pathophysiology under this disease has not been thoroughly understood. While ferroptosis is involved in inflammation and infection, its effect in sepsis is still unknown. The study aimed to identify ferroptosis-related genes in sepsis, providing translational potential therapeutic targets. METHODS: The dataset GSE65682 was used to download the sample source from the Gene Expression Omnibus (GEO) database. Consensus weighted gene co-expression network analysis (WGCNA) was performed to find suspected modules of sepsis. The differentially expressed genes (DEGs) most significantly associated with mortality were intersected with those altered by lipopolysaccharide (LPS) treatment and were further analyzed for the identification of main pathways of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The related pathway markers were further verified by qPCR. RESULTS: A total of 802 blood samples with sepsis were included for WGCNA, which identified 21 modules. Intersected with ferroptosis databases and LPS treatment groups, we identified two ferroptosis-related genes: PEBP1 and LPIN1. Only LPIN1 contributes to a poor outcome. Then, 205 DEGs were further identified according to the high or low LPIN1 expression. Among them, we constructed a gene regulatory network with several transcriptional factors using the NetworkAnalyst online tool and identified that these genes mostly correlate with inflammation and immune response. The immune infiltration analysis showed that lower expression of LPIN1 was related to macrophage infiltration and could be an independent predictor factor of the survival status in sepsis patients. Meanwhile, the multivariate Cox analysis showed that LPIN1 had a significant correlation with survival that was further verified by in vitro and in vivo experiments. CONCLUSION: In conclusion, LPIN1 could become a reliable biomarker for patient survival in sepsis, which is associated with immune and inflammation status. |
---|