Dataset Information

The metabolic analysis in human aortic tissues of aortic dissection.

ABSTRACT:

Background

The metabolic profile of human aortic tissues is of great importance. Among the analytical platforms utilized in metabolomics, LC-MS provides broad metabolome coverage. The non-targeted metabolomics can comprehensively detect the entire metabolome of an organism and find the metabolic characteristics that have significant changes in the experimental group and the control group and elucidate the metabolic pathway concerning the recognized metabolites. Employing non-targeted metabolomics is helpful to develop biomarkers for disease diagnosis and disease pathology research; for instance, Aortic aneurysm (AA) and Aortic dissection (AD).

Aim

This study sought to describe the non-targeted analysis of 18 aortic tissue samples, comparing between AA and AD.

Material & methods

Our experimental flow included dividing the samples into (AA, nine samples) and (AD, nine samples), SCIEX quadrupole timeofflight tandem mass spectrometer (TripleTOF) 6600+ mass spectrometer data refinement, MetDNA database analysis, and pathway analysis. We performed an initial validation by setting quality control parameters to evaluate the stability of the analysis system during the computer operation. We then used the repeatability of the control samples to examine the stability of the instrument during the entire analysis process to ensure the reliability of the results.

Results

Our study found 138 novel metabolites involved in galactose metabolism.

Discussion

138 novel metabolites found in this study will be further studied in the future.

Conclusion

Our study found 138 novel metabolites between AA and AD, which will provide viable clinical data for future studies aimed to implement galactose markers in aortic tissue analysis.

SUBMITTER: Zhang K

PROVIDER: S-EPMC9459286 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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Publications

The metabolic analysis in human aortic tissues of aortic dissection.

Zhang Kefeng K Pan Xudong X Zheng Jun J Liu Yongmin Y Sun Lizhong L

Journal of clinical laboratory analysis 20220726 9

<h4>Background</h4>The metabolic profile of human aortic tissues is of great importance. Among the analytical platforms utilized in metabolomics, LC-MS provides broad metabolome coverage. The non-targeted metabolomics can comprehensively detect the entire metabolome of an organism and find the metabolic characteristics that have significant changes in the experimental group and the control group and elucidate the metabolic pathway concerning the recognized metabolites. Employing non-targeted met ...[more]

PMID: 35881684

Similar Datasets

Project description:BackgroundAortic dissection (AD) poses a great threat to the life of patients; however, there is currently no documentation of a clear pathogenic mechanism of this disease. In recent years, β-aminopropionitrile (BAPN)-induced AD in rodents has been widely used in basic research, which provides a good platform for exploring the pathogenesis of AD and drug modification. This study aimed to identify molecular markers and pathways for the diagnosis and treatment of AD by comparing a murine AD model and human AD transcriptome through a bioinformatics analysis.MethodsWe constructed a BAPN-induced mice model and performed high-throughput sequencing analysis. The GSE147026 dataset of patients was obtained from the Gene Expression Omnibus database. We performed a subsequent bioinformatics analysis of human AD and the murine AD model using R software. The DESeq software package was used to analyze the differentially expressed genes (DEGs). Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to analyze the enrichment pathways. Protein-protein interaction network construction and hub gene selection were based on STRING software analysis. Stepwise identification of potential drugs was performed online, while hub genes were validated immunohistochemically.ResultsWe compared the murine AD model and human AD transcriptome and found that both differentially expressed 463 genes. The cytokine-cytokine receptor interaction, tuberculosis, and phagosome pathways were significantly enriched. CDC20, CCNB2, and CCNB1 may be associated with AD development. Protein-drug interactions were also identified.ConclusionsThis study is the first to reveal transcriptional changes in a murine BAPN-induced AD model versus human AD transcriptome. Furthermore, we identified the important hub genes, related pathways, and potential drugs by analyzing the overlapping DEGs between human AD and the murine AD model. Our results provide a basis for the further identification of potential molecular markers for diagnosing and treating AD.

Dataset Information

The metabolic analysis in human aortic tissues of aortic dissection.

Background

Aim

Material & methods

Results

Discussion

Conclusion

Publications

The metabolic analysis in human aortic tissues of aortic dissection.

Similar Datasets

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