Integrated lipidomic and transcriptomic analysis reveals clarithromycin-induced alteration of glycerophospholipid metabolism in the cerebral cortex of mice

Wang, Xiaojie; Wang, Liang; Luo, Mingyi; Bu, Qian; Liu, Chunqi; Jiang, Linhong; Xu, Rui; Wang, Shaomin; Zhang, Haoluo; Zhang, Jiamei; Wan, Xuemei; Li, Hongchun; Wang, Yonghai; Liu, Bin; Zhao, Ying; Chen, Yuanyuan; Dai, Yanping; Li, Min; Wang, Hongbo; Tian, Jingwei; Zhao, Yinglan; Cen, Xiaobo

doi:10.1007/s10565-021-09646-5

Cited by 4 publications

(1 citation statement)

References 80 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…CHPT1 is a key enzyme that participates in the synthesis of glycerophospholipids, catalyzing phosphatidylcholine synthesis and regulating choline metabolism ( Wang et al., 2021 ). Metabolomics analysis demonstrated that serum concentrations of glycerophospholipids and the glycerophospholipid were significantly altered in sepsis ( Wang et al., 2021 ).…”

Section: Discussionmentioning

confidence: 99%

Classification of subtypes and identification of dysregulated genes in sepsis

Tong,

Ding,

Liu

et al. 2023

Front. Cell. Infect. Microbiol.

View full text Add to dashboard Cite

BackgroundSepsis is a clinical syndrome with high mortality. Subtype identification in sepsis is meaningful for improving the diagnosis and treatment of patients. The purpose of this research was to identify subtypes of sepsis using RNA-seq datasets and further explore key genes that were deregulated during the development of sepsis.MethodsThe datasets GSE95233 and GSE13904 were obtained from the Gene Expression Omnibus database. Differential analysis of the gene expression matrix was performed between sepsis patients and healthy controls. Intersection analysis of differentially expressed genes was applied to identify common differentially expressed genes for enrichment analysis and gene set variation analysis. Obvious differential pathways between sepsis patients and healthy controls were identified, as were developmental stages during sepsis. Then, key dysregulated genes were revealed by short time-series analysis and the least absolute shrinkage and selection operator model. In addition, the MCPcounter package was used to assess infiltrating immunocytes. Finally, the dysregulated genes identified were verified using 69 clinical samples.ResultsA total of 898 common differentially expressed genes were obtained, which were chiefly related to increased metabolic responses and decreased immune responses. The two differential pathways (angiogenesis and myc targets v2) were screened on the basis of gene set variation analysis scores. Four subgroups were identified according to median expression of angiogenesis and myc target v2 genes: normal, myc target v2, mixed-quiescent, and angiogenesis. The genes CHPT1, CPEB4, DNAJC3, MAFG, NARF, SNX3, S100A9, S100A12, and METTL9 were recognized as being progressively dysregulated in sepsis. Furthermore, most types of immune cells showed low infiltration in sepsis patients and had a significant correlation with the key genes. Importantly, all nine key genes were highly expressed in sepsis patients.ConclusionThis study revealed novel insight into sepsis subtypes and identified nine dysregulated genes associated with immune status in the development of sepsis. This study provides potential molecular targets for the diagnosis and treatment of sepsis.

show abstract

Section: Discussionmentioning

confidence: 99%