Metformin strongly affects transcriptome of peripheral blood cells in healthy individuals

Ustinova, Monta; Silamiķelis, Ivars; Kalniņa, Ineta; Ansone, Laura; Rovīte, Vita; Elbere, Ilze; Radoviča-Spalviņa, Ilze; Fridmanis, Dāvids; Aladyeva, Ekaterina; Konrāde, Ilze; Pīrāgs, Valdis; Kloviņš, Jānis

doi:10.1371/journal.pone.0224835

Cited by 20 publications

(20 citation statements)

References 52 publications

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“…Interestingly, CEACAM1 is a mediator of insulin clearance in the liver [53] and IRS1 is playing a key role in glucose homeostasis [54], though no reports were linking their activity with metformin efficacy so far. In our previous studies, we have already reported the contribution of IgA, the most abundant intestinal antibody shaping the gut microbiome composition, in metformin action [27], and here we suggest a potential implication of IgA in microbiome-mediated metformin response [55]. Together these genes showed notable patient segregation in metformin response groups also when visualized in CPM-based heat map, therefore they may be considered as candidates for further studies of biomarkers for metformin response.…”

Section: Plos Onesupporting

confidence: 70%

“… Log 2 FC, log 2 fold change; FDR, false discovery rate. † Genes showing significant differential expression due to the administration of metformin also in healthy individuals [ 27 ]. …”

Section: Resultsmentioning

confidence: 99%

“…Comparison of gene expression profiles between metformin responders and non-responders after the use of metformin for three months (M3m) showed differential expression of 15 genes (12 up-regulated, 3 down-regulated), including 5 mitochondrial genes, which may be associated with mechanisms underlying variable efficacy of the drug (Table 5) (Fig 2D). https://doi.org/10.1371/journal.pone.0237400.g001 † Genes showing significant differential expression due to the administration of metformin also in healthy individuals [27].…”

Section: Determining Genes Involved In Differential Metformin Responsmentioning

confidence: 99%

“…The main objective of the study was to assess the systemic effect of metformin in T2DM patients and reveal potential biomarkers for accurate prediction of its therapeutic efficacy. We have previously reported direct evidence of the effects of metformin on the immediate and strong transcriptome changes in whole-blood samples of healthy subjects, though we considered the diabetic state as a significant confounding factor, therefore the study was continued in a well-characterized, prospective T2DM patient cohort with prolonged observational time, providing much wider applicability of the study results [27]. We believe that our strategy will promote the development of biomarker-based approaches for monitoring treatment outcomes and early identification of metformin responders, moving towards precision medicine.…”

Section: Introductionmentioning

confidence: 99%

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Whole-blood transcriptome profiling reveals signatures of metformin and its therapeutic response

et al. 2020

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Metformin, a biguanide agent, is the first-line treatment for type 2 diabetes mellitus due to its glucose-lowering effect. Despite its wide application in the treatment of multiple health conditions, the glycemic response to metformin is highly variable, emphasizing the need for reliable biomarkers. We chose the RNA-Seq-based comparative transcriptomics approach to evaluate the systemic effect of metformin and highlight potential predictive biomarkers of metformin response in drug-naïve volunteers with type 2 diabetes in vivo. The longitudinal blood-derived transcriptome analysis revealed metformin-induced differential expression of novel and previously described genes involved in cholesterol homeostasis (SLC46A1 and LRP1), cancer development (CYP1B1, STAB1, CCR2, TMEM176B), and immune responses (CD14, CD163) after administration of metformin for three months. We demonstrate for the first time a transcriptome-based molecular discrimination between metformin responders (delta HbA1c � 1% or 12.6 mmol/mol) and non-responders (delta HbA1c < 1% or 12.6 mmol/mol), that is determined by expression levels of 56 genes, explaining 13.9% of the variance in the therapeutic efficacy of the drug. Moreover, we found a significant upregulation of IRS2 gene (log 2 FC 0.89) in responders compared to non-responders before the use of metformin. Finally, we provide evidence for the mitochondrial respiratory complex I as one of the factors related to the high variability of the therapeutic response to metformin in patients with type 2 diabetes mellitus.

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Section: Plos Onesupporting

confidence: 70%

“… Log 2 FC, log 2 fold change; FDR, false discovery rate. † Genes showing significant differential expression due to the administration of metformin also in healthy individuals [ 27 ]. …”

Section: Resultsmentioning

confidence: 99%

Section: Determining Genes Involved In Differential Metformin Responsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Whole-blood transcriptome profiling reveals signatures of metformin and its therapeutic response

et al. 2020

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“…Ustinova et al showed the differential expression genes (DEGs) induced by metformin in healthy individuals. The DEGs were involved in the intestinal immune network for cytokine-cytokine receptor interaction and IgA production pathways (Ustinova et al, 2019). Extensive research has been conducted to explore the re-purpose of current clinic drugs.…”

Section: Rna-seq In Identification Of Drug-target Genes and Drug Re-pmentioning

confidence: 99%

High-Throughput Transcriptome Profiling in Drug and Biomarker Discovery

et al. 2020

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The development of new drugs is multidisciplinary and systematic work. High-throughput techniques based on "-omics" have driven the discovery of biomarkers in diseases and therapeutic targets of drugs. A transcriptome is the complete set of all RNAs transcribed by certain tissues or cells at a specific stage of development or physiological condition. Transcriptome research can demonstrate gene functions and structures from the whole level and reveal the molecular mechanism of specific biological processes in diseases. Currently, gene expression microarray and high-throughput RNA-sequencing have been widely used in biological, medical, clinical, and drug research. The former has been applied in drug screening and biomarker detection of drugs due to its high throughput, fast detection speed, simple analysis, and relatively low price. With the further development of detection technology and the improvement of analytical methods, the detection flux of RNAseq is much higher but the price is lower, hence it has powerful advantages in detecting biomarkers and drug discovery. Compared with the traditional RNA-seq, scRNA-seq has higher accuracy and efficiency, especially the single-cell level of gene expression pattern analysis can provide more information for drug and biomarker discovery. Therefore, (sc) RNA-seq has broader application prospects, especially in the field of drug discovery. In this overview, we will review the application of these technologies in drug, especially in natural drug and biomarker discovery and development. Emerging applications of scRNA-seq and the third generation RNA-sequencing tools are also discussed.

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Metformin induces tolerogenicity of dendritic cells by promoting metabolic reprogramming

Liu,

Yu,

et al. 2023

Cell. Mol. Life Sci.

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Dendritic cells (DCs) can mediate immune responses or immune tolerance depending on their immunophenotype and functional status. Remodeling of DCs’ immune functions can develop proper therapeutic regimens for different immune-mediated diseases. In the immunopathology of autoimmune diseases (ADs), activated DCs notably promote effector T-cell polarization and exacerbate the disease. Recent evidence indicates that metformin can attenuate the clinical symptoms of ADs due to its anti-inflammatory properties. Whether and how the therapeutic effects of metformin on ADs are associated with DCs remain unknown. In this study, metformin was added to a culture system of LPS-induced DC maturation. The results revealed that metformin shifted DC into a tolerant phenotype, resulting in reduced surface expression of MHC-II, costimulatory molecules and CCR7, decreased levels of proinflammatory cytokines (TNF-α and IFN-γ), increased level of IL-10, upregulated immunomodulatory molecules (ICOSL and PD-L) and an enhanced capacity to promote regulatory T-cell (Treg) differentiation. Further results demonstrated that the anti-inflammatory effects of metformin in vivo were closely related to remodeling the immunophenotype of DCs. Mechanistically, metformin could mediate the metabolic reprogramming of DCs through FoxO3a signaling pathways, including disturbing the balance of fatty acid synthesis (FAS) and fatty acid oxidation (FAO), increasing glycolysis but inhibiting the tricarboxylic acid cycle (TAC) and pentose phosphate pathway (PPP), which resulted in the accumulation of fatty acids (FAs) and lactic acid, as well as low anabolism in DCs. Our findings indicated that metformin could induce tolerance in DCs by reprogramming their metabolic patterns and play anti-inflammatory roles in vitro and in vivo.

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Metformin strongly affects transcriptome of peripheral blood cells in healthy individuals

Cited by 20 publications

References 52 publications

Whole-blood transcriptome profiling reveals signatures of metformin and its therapeutic response

Whole-blood transcriptome profiling reveals signatures of metformin and its therapeutic response

High-Throughput Transcriptome Profiling in Drug and Biomarker Discovery

Metformin induces tolerogenicity of dendritic cells by promoting metabolic reprogramming

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