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

ABSTRACT: 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 (log2FC 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.

SUBMITTER: Ustinova M

PROVIDER: S-EPMC7418999 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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

Ustinova Monta M Ansone Laura L Silamikelis Ivars I Rovite Vita V Elbere Ilze I Silamikele Laila L Kalnina Ineta I Fridmanis Davids D Sokolovska Jelizaveta J Konrade Ilze I Pirags Valdis V Klovins Janis J

PloS one 20200811 8

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 voluntee ...[more]

PMID: 32780768

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Project description:BackgroundTo understand how Plasmodium falciparum malaria is controlled, it is essential to elucidate the transcriptomic responses of the human host in naturally-exposed populations. Various individual studies of the human transcriptomic responses to naturally transmitted P. falciparum infections have been reported with varying results. Multicohort gene expression analysis by aggregating data from diverse populations into a single analysis will increase the reproducibility and reliability of the results.MethodsIn this study, discovery cohorts GSE1124-GPL96, GSE34404, GSE117613, and validation cohort GSE35858 were obtained from the Gene Expression Omnibus. A meta-analysis using data from the multicohort studies was performed to identify the differentially expressed genes (DEGs) between malaria-infected and noninfected individuals using the MetaIntegrator R package. Subsequently, the protein-protein interaction (PPI) networks of the DEGs were constructed using Cytoscape software. Significant modules were selected, and the hub genes were identified using the CytoHubba and MCODE plug-ins. Multicohort WGCNA was conducted to find a correlation between modules and malaria infection. Furthermore, the immune cell profile of the peripheral blood in different groups was identified using ssGSEA.ResultsThese analyses reveal that neutrophil activation, neutrophil-mediated immunity, and neutrophil degranulation are involved in the human response to natural malaria infection. However, neutrophil cell enrichment and activation were not significantly different between mild malaria and severe malaria groups. Malaria infection also downregulates host genes in ribosome synthesis and protein translation and upregulates host cell division-related genes. Furthermore, immune cell profiling analysis shows that activated dendritic cells and type 2 T helper cells are upregulated, while activated B cells, immature B cells, and monocytes are downregulated in the malaria-infected patients relative to the noninfected individuals. Significantly higher enrichment of activated dendritic cell-related genes and significantly lower enrichment of monocyte-related genes are also observed in the peripheral blood of the severe malaria group than in the mild malaria group.ConclusionThese results reveal important molecular signatures of host responses to malaria infections, providing some bases for developing malaria control strategies and protective vaccines.

Project description:Macrophages are mononuclear phagocytes that constitute a first line of defense against pathogens. While lethal to many microbes, they are the primary host cells of Leishmania spp. parasites, the obligate intracellular pathogens that cause leishmaniasis. We conducted transcriptomic profiling of two Leishmania species and the human macrophage over the course of intracellular infection by using high-throughput RNA sequencing to characterize the global gene expression changes and reprogramming events that underlie the interactions between the pathogen and its host. A systematic exclusion of the generic effects of large-particle phagocytosis revealed a vigorous, parasite-specific response of the human macrophage early in the infection that was greatly tempered at later time points. An analogous temporal expression pattern was observed with the parasite, suggesting that much of the reprogramming that occurs as parasites transform into intracellular forms generally stabilizes shortly after entry. Following that, the parasite establishes an intracellular niche within macrophages, with minimal communication between the parasite and the host cell later during the infection. No significant difference was observed between parasite species transcriptomes or in the transcriptional response of macrophages infected with each species. Our comparative analysis of gene expression changes that occur as mouse and human macrophages are infected by Leishmania spp. points toward a general signature of the Leishmania-macrophage infectome. Little is known about the transcriptional changes that occur within mammalian cells harboring intracellular pathogens. This study characterizes the gene expression signatures of Leishmania spp. parasites and the coordinated response of infected human macrophages as the pathogen enters and persists within them. After accounting for the generic effects of large-particle phagocytosis, we observed a parasite-specific response of the human macrophages early in infection that was reduced at later time points. A similar expression pattern was observed in the parasites. Our analyses provide specific insights into the interplay between human macrophages and Leishmania parasites and constitute an important general resource for the study of how pathogens evade host defenses and modulate the functions of the cell to survive intracellularly.

Project description:BACKGROUND:Treatment protocols for nasopharyngeal carcinoma (NPC) developed in the past decade have significantly improved patient survival. In most NPC patients, however, the disease is diagnosed at late stages, and for some patients treatment response is less than optimal. This investigation has two aims: to identify a blood-based gene-expression signature that differentiates NPC from other medical conditions and from controls and to identify a biomarker signature that correlates with NPC treatment response. METHODS:RNA was isolated from peripheral whole blood samples (2 x 10 ml) collected from NPC patients/controls (EDTA vacutainer). Gene expression patterns from 99 samples (66 NPC; 33 controls) were assessed using the Affymetrix array. We also collected expression data from 447 patients with other cancers (201 patients) and non-cancer conditions (246 patients). Multivariate logistic regression analysis was used to obtain biomarker signatures differentiating NPC samples from controls and other diseases. Differences were also analysed within a subset (n=28) of a pre-intervention case cohort of patients whom we followed post-treatment. RESULTS:A blood-based gene expression signature composed of three genes - LDLRAP1, PHF20, and LUC7L3 - is able to differentiate NPC from various other diseases and from unaffected controls with significant accuracy (area under the receiver operating characteristic curve of over 0.90). By subdividing our NPC cohort according to the degree of patient response to treatment we have been able to identify a blood gene signature that may be able to guide the selection of treatment. CONCLUSION:We have identified a blood-based gene signature that accurately distinguished NPC patients from controls and from patients with other diseases. The genes in the signature, LDLRAP1, PHF20, and LUC7L3, are known to be involved in carcinoma of the head and neck, tumour-associated antigens, and/or cellular signalling. We have also identified blood-based biomarkers that are (potentially) able to predict those patients who are more likely to respond to treatment for NPC. These findings have significant clinical implications for optimizing NPC therapy.

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

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

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