Dataset Information

Exosomal hsa_circRNA_104484 and hsa_circRNA_104670 may serve as potential novel biomarkers and therapeutic targets for sepsis.

ABSTRACT: In order to explore the role of exosomal circRNAs in the occurrence and development of sepsis, we looked for potential diagnostic markers to accurately identify sepsis and to lay a molecular basis for precise treatment. Ultracentrifugation was used to extract exosomes from the serum of patients with sepsis and healthy individuals. Then, changes in circRNA expression in exosomes were studied by circRNA microarray analysis. Gene ontology (GO) analysis and Kyoto City Encyclopaedia of Genes and Genomes (KEGG) pathway analysis were used to annotate the biological functions and pathways of genes, and a circRNA-miRNA-mRNA regulatory network was constructed. In the microarray analysis, 132 circRNAs were significantly differentially expressed, including 80 and 52 that were upregulated and downregulated, respectively. RT-qPCR verified the results of microarray analysis: hsa_circRNA_104484 and hsa_circRNA_104670 were upregulated in sepsis serum exosomes. ROC analysis showed that hsa_circRNA_104484 and hsa_circRNA_104670 in serum exosomes have the potential to be used as diagnostic markers for sepsis. The circRNA-miRNA-mRNA network predicted the potential regulatory pathways of differentially expressed circRNAs. There are differences in the expression of circRNA in serum exosomes between patients with sepsis and healthy individuals, which may be involved in the occurrence and development of the disease. Among them, elevations in hsa_circRNA_104484 and hsa_circRNA_104670 could be used as novel diagnostic biomarkers and molecular therapeutic targets.

SUBMITTER: Tian C

PROVIDER: S-EPMC8266806 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Sepsis is a diagnostic and therapeutic challenge and is associated with morbidity and a high risk of death. Metabolomic and lipidomic profiling in sepsis can identify alterations in metabolism and might provide useful insights into the dysregulated host response to infection, but investigations in dogs are limited. We aimed to use untargeted metabolomics and lipidomics to characterize metabolic pathways in dogs with sepsis to identify therapeutic targets and potential diagnostic and prognostic biomarkers. In this prospective observational cohort study, we examined the plasma metabolomes and lipidomes of 20 healthy control dogs and compared them with those of 21 client-owned dogs with sepsis. Patient data including signalment, physical exam findings, clinicopathologic data and clinical outcome were recorded. Metabolites were identified using an untargeted mass spectrometry approach and pathway analysis identified multiple enriched metabolic pathways including pyruvaldehyde degradation; ketone body metabolism; the glucose-alanine cycle; vitamin-K metabolism; arginine and betaine metabolism; the biosynthesis of various amino acid classes including the aromatic amino acids; branched chain amino acids; and metabolism of glutamine/glutamate and the glycerophospholipid phosphatidylethanolamine. Metabolites were identified with high discriminant abilities between groups which could serve as potential biomarkers of sepsis including 13,14-Dihydro-15-keto Prostaglandin A2; 12(13)-DiHOME (12,13-dihydroxy-9Z-octadecenoic acid); and 9-HpODE (9-Hydroxyoctadecadienoic acid). Metabolites with higher abundance in samples from nonsurvivors than survivors included 3-(2-hydroxyethyl) indole, indoxyl sulfate and xanthurenic acid. Untargeted lipidomic profiling revealed multiple sphingomyelin species (SM(d34:0)+H; SM(d36:0)+H; SM(d34:0)+HCOO; and SM(d34:1D3)+HCOO); lysophosphatidylcholine molecules (LPC(18:2)+H) and lipophosphoserine molecules (LPS(20:4)+H) that were discriminating for dogs with sepsis. These biomarkers could aid in the diagnosis of dogs with sepsis, provide prognostic information, or act as potential therapeutic targets.

Dataset Information

Exosomal hsa_circRNA_104484 and hsa_circRNA_104670 may serve as potential novel biomarkers and therapeutic targets for sepsis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets