Metformin-induced alterations in peripheral blood cell trancriptome of healthy individuals
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA565158 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR10103400.fastq.gz | Fastqsanger.gz | |||
| SRR10103401.fastq.gz | Fastqsanger.gz | |||
| SRR10103402.fastq.gz | Fastqsanger.gz | |||
| SRR10103403.fastq.gz | Fastqsanger.gz | |||
| SRR10103404.fastq.gz | Fastqsanger.gz |
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Project description:Metformin is a commonly used antihyperglycaemic agent for the treatment of type 2 diabetes. Nevertheless, the exact mechanisms of action, underlying the various therapeutic effects of metformin, remain elusive. The goal of this study was to evaluate the alterations in longitudinal whole-blood transcriptome profiles of healthy individuals after a one-week metformin intervention in order to identify the novel molecular targets and further prompt the discovery of predictive biomarkers of metformin response. Next generation sequencing-based transcriptome analysis revealed four clusters of functionally related genes with a subject-specific differential expression even after a single dose of metformin: ribosomal genes and their pseudogenes (e.g., RNA5-8SN1, RNA5-8SN5, RNY4P10), small nuclear RNAs (e.g., SNORA20, SCARNA5, SNORA80E), genes relevant to insulin production (HNF1B, HNF1A, HNF4A, GCK, INS, NEUROD1, PAX4, PDX1, ABCC8, KCNJ11) and cholesterol homeostasis (APOB, LDLR, PCSK9). After accounting for subject-specific expression, the enrichment of pathways associated with immune responses, such as intestinal immune network for IgA production and cytokine-cytokine receptor interaction were observed for the majority of the cohort. The results of the study reveal for the first time a strong inter-individual variation of the metformin effect on the transcriptional regulation, that goes in line with well-known variability of the therapeutic response to the drug.
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Project description:Optimal treatment for nonalcoholic steatohepatitis (NASH) has not yet been established, particularly for individuals without diabetes. We examined the effects of metformin, commonly used to treat patients with type 2 diabetes, on liver pathology in a non-diabetic NASH mouse model. Eight-week-old C57BL/6 mice were fed a methionine- and choline-deficient (MCD) + high fat (HF) diet with or without 0.1% metformin for 8 weeks.
2012-02-21 | E-GEOD-35961 | biostudies-arrayexpress
Project description:Metformin is a commonly used antihyperglycaemic agent for the treatment of type 2 diabetes mellitus. Nevertheless, the exact mechanisms of action, underlying the various therapeutic effects of metformin, remain elusive. The goal of this study was to evaluate the alterations in longitudinal whole-blood transcriptome profiles of healthy individuals after a one-week metformin intervention in order to identify the novel molecular targets and further prompt the discovery of predictive biomarkers of metformin response. Next generation sequencing-based transcriptome analysis revealed metformin-induced differential expression of genes involved in intestinal immune network for IgA production and cytokine-cytokine receptor interaction pathways. Significantly elevated faecal sIgA levels during administration of metformin, and its correlation with the expression of genes associated with immune response (CXCR4, HLA-DQA1, MAP3K14, TNFRSF21, CCL4, ACVR1B, PF4, EPOR, CXCL8) supports a novel hypothesis of strong association between metformin and intestinal immune system, and for the first time provide evidence for altered RNA expression as a contributing mechanism of metformin's action. In addition to universal effects, 4 clusters of functionally related genes with a subject-specific differential expression were distinguished, including genes relevant to insulin production (HNF1B, HNF1A, HNF4A, GCK, INS, NEUROD1, PAX4, PDX1, ABCC8, KCNJ11) and cholesterol homeostasis (APOB, LDLR, PCSK9). This inter-individual variation of the metformin effect on the transcriptional regulation goes in line with well-known variability of the therapeutic response to the drug.
| S-EPMC6839856 | biostudies-literature
Project description:Aims: Metformin is a widely used, primary drug of choice to treat individuals with type 2 diabetes (T2D). Clinically, inter-individual variability of drug response is of significant concern. The targets and precise mechanisms of action for metformin is still under interrogation. In the present study, a whole transcriptome analysis was performed with an intent to identify predictive biomarkers of metformin response in T2D individuals. Methods: Twenty drug naïve individuals with T2D and ten healthy controls were enrolled. T2D individuals were administrated with metformin monotherapy and were defined as responders and non-responders based on the changes in their glycated haemoglobin (HbA1c) over a period of three months. Poly(A) RNA Seq was performed using Ion Torrent Proton platform and differentially expressed genes were identified from the transcriptome profiles. The gene prioritization, enrichment analysis, drug-gene interactions, disease gene association analysis were performed using various tools and databases. A correlation analysis was also performed between gene expression and change in HbA1c levels after 3 months of metformin therapy. Results: The expression analysis highlighted differentially expressed genes in metformin responders, non-responders and healthy individuals. The gene prioritization and enrichment analysis highlighted potential targets for predicting metformin response (n=35) as well as T2D disease (n=14). The drug-gene interactions did not show any direct association with diabetes drugs. However, the expression of GDF15, TWISTNB and RPL36A genes showed maximum correlation with change in HbA1c levels after 3 months of metformin therapy. The disease gene association analysis highlighted rs113805659 in MAGI2 gene to be linked with T2D in African Americans. Conclusion: The results of the present study provide evidence for the perturbed transcriptome and pathways associated with metformin drug response in T2D individuals.
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Project description:The biguanide metformin has been shown to not only reduce circulating glucose levels but also suppress in vitro and in vivo growth of prostate cancer. However, the mechanisms underlying the anti-tumor effects of metformin in advanced prostate cancers are not fully understood. The goal of the present study was to define the signaling pathways regulated by metformin in androgen-receptor (AR) positive, castration-resistant prostate cancers. Our group used RNA sequencing (RNA-seq) to examine genes regulated by metformin within the C4-2 human prostate cancer cell line. Western blot analysis and quantitative RT-PCR were used to confirm alterations in gene expression and further explore regulation of protein expression by metformin. Data from the RNA-seq analysis revealed that metformin alters the expression of genes products involved in metabolic pathways, the spliceosome, RNA transport, and protein processing within the endoplasmic reticulum. Gene products involved in ErbB, insulin, mTOR, TGF-, MAPK, and Wnt signaling pathways are also regulated by metformin. A subset of metformin-regulated gene products were genes known to be direct transcriptional targets of p53 or AR. Together, our results suggest metformin regulates multiple pathways linked to tumor growth and progression within advanced prostate cancer cells.
2022-02-10 | GSE196343 | GEO
Project description:Substantial effort is currently devoted to identifying cancer-associated alterations using genomics. Here, we show that standard blood collection procedures rapidly change the transcriptional and post-transcriptional landscapes of hematopoietic cells, resulting in biased activation of specific biological pathways, up-regulation of pseudogenes, antisense RNAs, and unannotated coding isoforms, and RNA surveillance inhibition. Affected genes include common mutational targets and thousands of other genes participating in processes such as chromatin modification, RNA splicing, T and B cell activation, and NF-κB signaling. The majority of published leukemic transcriptomes exhibit signals of this incubation-induced dysregulation, explaining up to 40% of differences in gene expression and alternative splicing between leukemias and reference normal transcriptomes. The effects of sample processing are particularly evident in pan-cancer analyses. We provide biomarkers that detect prolonged incubation of individual samples, and show that keeping blood on ice markedly reduces changes to the transcriptome. In addition to highlighting the potentially confounding effects of technical artifacts in cancer genomics data, our study emphasizes the need to survey the diversity of normal as well as neoplastic cells when characterizing tumors. This study is complemented by GSE61410: transcriptomic profiling of bone marrow cells from healthy individuals. Peripheral blood mononuclear cells (PBMCs) were isolated from four healthy individuals, following an ex vivo incubation of variable length at either room temperature or on ice. RNA transcriptomes were measured using the Illumina HiSeq.
2014-10-27 | E-GEOD-58335 | biostudies-arrayexpress
Project description:Substantial effort is currently devoted to identifying cancer-associated alterations using genomics. Here, we show that standard blood collection procedures rapidly change the transcriptional and post-transcriptional landscapes of hematopoietic cells, resulting in biased activation of specific biological pathways, up-regulation of pseudogenes, antisense RNAs, and unannotated coding isoforms, and RNA surveillance inhibition. Affected genes include common mutational targets and thousands of other genes participating in processes such as chromatin modification, RNA splicing, T and B cell activation, and NF-κB signaling. The majority of published leukemic transcriptomes exhibit signals of this incubation-induced dysregulation, explaining up to 40% of differences in gene expression and alternative splicing between leukemias and reference normal transcriptomes. The effects of sample processing are particularly evident in pan-cancer analyses. We provide biomarkers that detect prolonged incubation of individual samples, and show that keeping blood on ice markedly reduces changes to the transcriptome. In addition to highlighting the potentially confounding effects of technical artifacts in cancer genomics data, our study emphasizes the need to survey the diversity of normal as well as neoplastic cells when characterizing tumors. This study is complemented by GSE61410: transcriptomic profiling of bone marrow cells from healthy individuals.
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Project description:Optimal treatment for nonalcoholic steatohepatitis (NASH) has not yet been established, particularly for individuals without diabetes. We examined the effects of metformin, commonly used to treat patients with type 2 diabetes, on liver pathology in a non-diabetic NASH mouse model.
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