CMap analysis identifies Atractyloside as a potential drug candidate for type 2 diabetes based on integration of metabolomics and transcriptomics

Abstract

Background This research aimed at exploring the mechanisms of alterations of metabolites and pathways in T2D from the perspective of metabolomics and transcriptomics, as well as uncovering novel drug candidate for T2D treatment. Methods Metabolites in human plasma from 42 T2D patients and 45 non‐diabetic volunteers were detected by liquid chromatography‐mass spectrometer (LC‐MS). Microarray dataset of the transcriptome was obtained from Gene Expression Omnibus (GEO) database. Kyoto Encyclopedia of Genes and Genomes (KEGG) database was used to conduct pathway enrichment analysis. Connectivity Map (CMap) was employed to select potential drugs for T2D therapy. In vivo assay was performed to verify above findings. The protein expression levels of ME1 , ME2 and MDH1 were detected by Western blot to determine the status of NAD/NADH cofactor system. Results In our study, differentially expressed metabolites were selected out between healthy samples and T2D samples with selection criteria P value < .05, |Fold Change| > 2, including N‐acetylglutamate and Malate. Genes set enrichment analysis (GSEA) revealed that 34 pathways were significantly enriched in T2D. Based on CMap analysis and animal experiments, Atractyloside was identified as a potential novel drug for T2D treatment via targeting ME1 , ME2 and MDH1 and regulating the NAD/NADH cofactor system. Conclusion The present research revealed differentially expressed metabolites and genes, as well as significantly altered pathways in T2D via an integration of metabolomics, transcriptomics and CMap analysis. It was also demonstrated that comprehensive analysis based on metabolomics and transcriptomics was an effective approach for identification and verification of metabolic biomarkers and alternated pathways.

Pyroptosis-related lncRNAs are potential biomarkers for predicting prognoses and immune responses in patients with UCEC

“…The two-dimensional and three-dimensional structures of the drugs were taken from PubChem. 101 , 102 …”

Screening for Potential Therapeutic Agents for Non-Small Cell Lung Cancer by Targeting Ferroptosis

“…Drug repurposing, that is, a novel drug development strategy to discover new drug indications based on drugs already on the market or in the clinical research stage, can mitigate a variety of costs including time, manpower, and material resources ( Parvathaneni et al, 2019 ). Application of the CMap database can reveal drug–gene associations and identify possible therapeutic effects of compounds ( Shi et al, 2016 ; Li H. et al, 2020 ). Based on gene chip technology and the CMap database for drug repositioning, we identified the potential candidate lead compound FFA to induce ferroptosis in NSCLC cells and cure this disease.…”

Artificial Intelligence-Assisted Bioinformatics, Microneedle, and Diabetic Wound Healing: A “New Deal” of an Old Drug

“…17 Some researchers use Cmap to empower new deals of old drugs, such as disulfiram for diabetic angiopathy (DA) 18 and atractyloside for type 2 diabetes. 19 However, there is little research on diabetic wounds based on this dataset. Through the various AI-assisted bioinformatics approaches, including GSE144441, Cmap dataset, and molecular docking test, the therapeutic potential of TSA and hub gene HDAC4 in diabetic wounds is excavated.…”