Genomic Characterization of Metformin Hepatic Response

Disinfection by-products of metformin in the environment: A systematic toxicity evaluation on gut-liver-brain axis homeostasis and establishment of a detection method based on NiFe-LDOs/N-BC composite

Metformin, a first-line drug used to treat type 2 diabetes, is not metabolised in the body and discharged into the environment in the form of prototype drugs. Compounds C (C4H6ClN3) and Y (C4H6ClN5) are the main disinfection byproducts of metformin in urban sewage treatment; however, their potential toxicity is unclear. In this study, absorption, distribution, metabolism, elimination, and toxicity (ADMET) prediction indicated that compounds C and Y had potential hepatotoxicity and could cross the blood-brain-barrier. Toxicity verification tests indicated a sex difference in the acute toxicity of compound C, with an LD50 value of 253.269 mg kg-1 for male mice and 728.908 mg kg-1 for female mice. The subacute toxicity of compounds C and Y was evaluated to study the toxicity mechanism via the gut-liver-brain axis, which indicated that they could cause damage to the liver and brain, change the composition of the gut microbiota, and disturb the levels of metabolites in mice. Neuron-like magnetic N-doped biochar (NiFe-LDOs/N-BC) was synthesised using hydrothermal and calcination methods, and the optimised d-MSPE-HPLC-UV method was proven to be applicable for the trace detection of compound C in real water samples. The simultaneous presentation of toxicity evaluation and trace detection of compound C is intended to make the monitoring system for compound C more comprehensive.

Harnessing Pharmacomultiomics for Precision Medicine in Diabetes: A Comprehensive Review

Type 2 diabetes (T2D) is the fastest-growing non-communicable disease worldwide, accounting for around 90% of all diabetes cases and imposing a significant health burden globally. Due to its phenotypic heterogeneity and composite genetic underpinnings, T2D requires a precision medicine approach personalized to individual molecular profiles, thereby shifting away from the traditional "one-size-fits-all" medical methods. This review advocates for a thorough pharmacomultiomics approach to enhance precision medicine for T2D. It emphasizes personalized treatment strategies that enhance treatment efficacy while minimizing adverse effects by integrating data from genomics, proteomics, metabolomics, transcriptomics, microbiomics, and epigenomics. We summarize key findings on candidate genes impacting diabetic medication responses and explore the potential of pharmacometabolomics in predicting drug efficacy. The role of pharmacoproteomics in prognosis and discovering new therapeutic targets is discussed, along with transcriptomics' contribution to understanding T2D pathophysiology. Additionally, pharmacomicrobiomics is explored to understand gut microbiota interactions with antidiabetic drugs. Emerging evidence on utilizing epigenomic profiles in improving drug efficacy and personalized treatment is also reviewed, illustrating their implications in personalized medicine. In this paper, we discuss the integration of these layers of omics data, examining recently developed paradigms that leverage complex data to deepen our understanding of diabetes. Such integrative approaches advance precision medicine strategies to tackle the disease by better understanding its complex biology.

Navigating stem cell culture: insights, techniques, challenges, and prospects

Stem cell research holds huge promise for regenerative medicine and disease modeling, making the understanding and optimization of stem cell culture a critical aspect of advancing these therapeutic applications. This comprehensive review provides an in-depth overview of stem cell culture, including general information, contemporary techniques, encountered problems, and future perspectives. The article begins by explaining the fundamental characteristics of various stem cell types, elucidating the importance of proper culture conditions in maintaining pluripotency or lineage commitment. A detailed exploration of established culture techniques sheds light on the evolving landscape of stem cell culture methodologies. Common challenges such as genetic stability, heterogeneity, and differentiation efficiency are thoroughly discussed, with insights into cutting-edge strategies and technologies aimed at addressing these hurdles. Moreover, the article delves into the impact of substrate materials, culture media components, and biophysical cues on stem cell behavior, emphasizing the intricate interplay between the microenvironment and cell fate decisions. As stem cell research advances, ethical considerations and regulatory frameworks become increasingly important, prompting a critical examination of these aspects in the context of culture practices. Lastly, the article explores emerging perspectives, including the integration of artificial intelligence and machine learning in optimizing culture conditions, and the potential applications of stem cell-derived products in personalized medicine. This comprehensive overview aims to serve as a valuable resource for researchers and clinicians, fostering a deeper understanding of stem cell culture and its key role in advancing regenerative medicine and biomedical research.

AMPK, a key molecule regulating aging-related myocardial ischemia-reperfusion injury

Aging leads to the threat of more diseases to the biological anatomical structure and the decline of disease resistance, increasing the incidence and mortality of myocardial ischemia-reperfusion injury (MI/RI). Moreover, MI/RI promotes damage to an aging heart. Notably, 5'-adenosine monophosphate-activated protein kinase (AMPK) regulates cellular energy metabolism, stress response, and protein metabolism, participates in aging-related signaling pathways, and plays an essential role in ischemia-reperfusion (I/R) injury diseases. This study aims to introduce the aging theory, summarize the interaction between aging and MI/RI, and describe the crosstalk of AMPK in aging and MI/RI. We show how AMPK can offer protective effects against age-related stressors, lifestyle factors such as alcohol consumption and smoking, and hypertension. We also review some of the clinical prospects for the development of interventions that harness the effect of AMPK to treat MI/RI and other age-related cardiovascular diseases.

Genome-Wide Association Study Identifies Pharmacogenomic Variants Associated With Metformin Glycemic Response in African American Patients With Type 2 Diabetes

OBJECTIVE

Metformin is the most common treatment for type 2 diabetes (T2D). However, there have been no pharmacogenomic studies for T2D in which a population of color was used in the discovery analysis. This study sought to identify genomic variants associated with metformin response in African American patients with diabetes.

RESEARCH DESIGN AND METHODS

Patients in the discovery set were adult, African American participants from the Diabetes Multi-omic Investigation of Drug Response (DIAMOND), a cohort study of patients with T2D from a health system serving southeast Michigan. DIAMOND participants had genome-wide genotype data and longitudinal electronic records of laboratory results and medication fills. The genome-wide discovery analysis identified polymorphisms correlated to changes in glycated hemoglobin (HbA1c) levels among individuals on metformin monotherapy. Lead associations were assessed for replication in an independent cohort of African American participants from Kaiser Permanente Northern California (KPNC) and in European American participants from DIAMOND.

RESULTS

The discovery set consisted of 447 African American participants, whereas the replication sets included 353 African American KPNC participants and 466 European American DIAMOND participants. The primary analysis identified a variant, rs143276236, in the gene ARFGEF3, which met the threshold for genome-wide significance, replicated in KPNC African Americans, and was still significant in the meta-analysis (P = 1.17 × 10-9). None of the significant discovery variants replicated in European Americans DIAMOND participants.

CONCLUSIONS

We identified a novel and biologically plausible genetic variant associated with a change in HbA1c levels among African American patients on metformin monotherapy. These results highlight the importance of diversity in pharmacogenomic studies.

Effect of Metformin Versus Placebo on New Primary Cancers in Canadian Cancer Trials Group MA.32: A Secondary Analysis of a Phase III Randomized Double-Blind Trial in Early Breast Cancer

Clinical trials frequently include multiple end points that mature at different times. The initial report, typically based on the primary end point, may be published when key planned coprimary or secondary analyses are not yet available. Clinical trial updates provide an opportunity to disseminate additional results from studies, published in JCO or elsewhere, for which the primary end point has already been reported.Metformin has been associated with lower cancer risk in epidemiologic and preclinical research. In the MA.32 randomized adjuvant breast cancer trial, metformin (v placebo) did not affect invasive disease-free or overall survival. Here, we report metformin effects on the risk of new cancer. Between 2010 and 2013, 3,649 patients with breast cancer younger than 75 years without diabetes with high-risk T1-3, N0-3 M0 breast cancer (any estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2) were randomly assigned to metformin 850 mg orally twice a day or placebo twice a day for 5 years. New primary invasive cancers (outside the ipsilateral breast) developing as a first event were identified. Time to events was described by the competing risks method; two-sided likelihood ratio tests adjusting for age, BMI, smoking, and alcohol intake were used to compare metformin versus placebo arms. A total of 184 patients developed new invasive cancers: 102 metformin and 82 placebo, hazard ratio (HR), 1.25; 95% CI, 0.94 to 1.68; P = .13. These included 48 contralateral invasive breast cancers (27 metformin v 21 placebo), HR, 1.29; 95% CI, 0.72 to 2.27; P = .40 and 136 new nonbreast primary cancers (75 metformin v 61 placebo), HR, 1.24; 95% CI, 0.88 to 1.74; P = .21. Metformin did not reduce the risk of new cancer development in these nondiabetic patients with breast cancer.

DNA damage-induced stalling of transcription drives aging through gene expression imbalance

Age-related changes in gene expression have long been examined to understand the biology of aging. The hallmarks of aging are biological processes known to be associated with aging, but whether there is a unifying driver of these attributes, is not well understood. With the advent of technology over the last few years, it is quite clear that aging leads to global decline in transcription. In this Perspective, we highlight a new study in Nature Genetics that aimed to determine why global transcription rate reduces with age and how this phenomenon is the driver that interconnects multiple hallmarks of aging. This study recognizes that age-related accumulation of DNA damage, particularly transcription-blocking lesions, stalls RNA polymerase. This phenomenon affects longer genes leading to a gradual loss of transcription and skewing the transcriptome. In order to design a successful aging intervention, future work will be needed to test how some promising therapies in pre-clinical trials target affect transcriptional rate.

Aging is associated with a systemic length-associated transcriptome imbalance

Aging is among the most important risk factors for morbidity and mortality. To contribute toward a molecular understanding of aging, we analyzed age-resolved transcriptomic data from multiple studies. Here, we show that transcript length alone explains most transcriptional changes observed with aging in mice and humans. We present three lines of evidence supporting the biological importance of the uncovered transcriptome imbalance. First, in vertebrates the length association primarily displays a lower relative abundance of long transcripts in aging. Second, eight antiaging interventions of the Interventions Testing Program of the National Institute on Aging can counter this length association. Third, we find that in humans and mice the genes with the longest transcripts enrich for genes reported to extend lifespan, whereas those with the shortest transcripts enrich for genes reported to shorten lifespan. Our study opens fundamental questions on aging and the organization of transcriptomes.

Metformin Treatment Modulates Long Non-Coding RNA Isoforms Expression in Human Cells

Long noncoding RNAs (lncRNAs) undergo splicing and have multiple transcribed isoforms. Nevertheless, for lncRNAs, as well as for mRNA, measurements of expression are routinely performed only at the gene level. Metformin is the first-line oral therapy for type 2 diabetes mellitus and other metabolic diseases. However, its mechanism of action remains not thoroughly explained. Transcriptomic analyses using metformin in different cell types reveal that only protein-coding genes are considered. We aimed to characterize lncRNA isoforms that were differentially affected by metformin treatment on multiple human cell types (three cancer, two non-cancer) and to provide insights into the lncRNA regulation by this drug. We selected six series to perform a differential expression (DE) isoform analysis. We also inferred the biological roles for lncRNA DE isoforms using in silico tools. We found the same isoform of an lncRNA (AC016831.6-205) highly expressed in all six metformin series, which has a second exon putatively coding for a peptide with relevance to the drug action. Moreover, the other two lncRNA isoforms (ZBED5-AS1-207 and AC125807.2-201) may also behave as cis-regulatory elements to the expression of transcripts in their vicinity. Our results strongly reinforce the importance of considering DE isoforms of lncRNA for understanding metformin mechanisms at the molecular level.

A resource for integrated genomic analysis of the human liver

In this study, we generated whole-transcriptome RNA-Seq from n = 192 genotyped liver samples and used these data with existing data from the GTEx Project (RNA-Seq) and previous liver eQTL (microarray) studies to create an enhanced transcriptomic sequence resource in the human liver. Analyses of genotype-expression associations show pronounced enrichment of associations with genes of drug response. The associations are primarily consistent across the two RNA-Seq datasets, with some modest variation, indicating the importance of obtaining multiple datasets to produce a robust resource. We further used an empirical Bayesian model to compare eQTL patterns in liver and an additional 20 GTEx tissues, finding that MHC genes, and especially class II genes, are enriched for liver-specific eQTL patterns. To illustrate the utility of the resource to augment GWAS analysis with small sample sizes, we developed a novel meta-analysis technique to combine several liver eQTL data sources. We also illustrate its application using a transcriptome-enhanced re-analysis of a study of neutropenia in pancreatic cancer patients. The associations of genotype with liver expression, including splice variation and its genetic associations, are made available in a searchable genome browser.

Integrated or Independent Actions of Metformin in Target Tissues Underlying Its Current Use and New Possible Applications in the Endocrine and Metabolic Disorder Area

Metformin is considered the first-choice drug for type 2 diabetes treatment. Actually, pleiotropic effects of metformin have been recognized, and there is evidence that this drug may have a favorable impact on health beyond its glucose-lowering activity. In summary, despite its long history, metformin is still an attractive research opportunity in the field of endocrine and metabolic diseases, age-related diseases, and cancer. To this end, its mode of action in distinct cell types is still in dispute. The aim of this work was to review the current knowledge and recent findings on the molecular mechanisms underlying the pharmacological effects of metformin in the field of metabolic and endocrine pathologies, including some endocrine tumors. Metformin is believed to act through multiple pathways that can be interconnected or work independently. Moreover, metformin effects on target tissues may be either direct or indirect, which means secondary to the actions on other tissues and consequent alterations at systemic level. Finally, as to the direct actions of metformin at cellular level, the intracellular milieu cooperates to cause differential responses to the drug between distinct cell types, despite the primary molecular targets may be the same within cells. Cellular bioenergetics can be regarded as the primary target of metformin action. Metformin can perturb the cytosolic and mitochondrial NAD/NADH ratio and the ATP/AMP ratio within cells, thus affecting enzymatic activities and metabolic and signaling pathways which depend on redox- and energy balance. In this context, the possible link between pyruvate metabolism and metformin actions is extensively discussed.

DDX10 and BYSL as the potential targets of chondrosarcoma and glioma

To provide reliable molecular markers and effective therapeutic targets for chondrosarcoma and glioma.Gene Set Enrichment (GSE) 29745 and GSE48420 were downloaded from the Gene Expression Omnibus (GEO) database. Differently expressed genes (DEGs) were identified by the GEO2R. We annotated the function of common DEGs through Digital Audio/Video Interactive Decoder (DAVID) and Metascape. Protein-protein interaction network construction was performed through STRING. Hub genes were identified by the two different algorithms (MCC, EPC). DDX10 and BYSL were key factors in embryo implantation and development, and plays a role in a variety of cancers. The role of the DDX10 and BYSL on the glioma derived from the chondrosarcoma would be explored by the clinical samples.A total of 1442 DEGs were identified. The variations in DEGs were mainly enriched in vasculature development, cell motion, blood vessel development, cell migration, regulation of cell proliferation, regulation of cell proliferation, wound healing, biological adhesion, growth factor binding, identical pathways in cancer, and p53 signaling pathway. Dead-box helicase 10 (DDX10), Bystin-like (BYSL), and WD repeat domain 12 (WDR12) were identified as the hub genes, and the three hub genes were up-regulated in the chondrosarcoma. Chondrosarcoma patients with high expression levels of DDX10 (Logrank P = .0052; HR (high) = 1.8; n (high) = 131, 50%), and BYSL (P = 6.5e-05; HR (high) = 2.3; n (high) = 131, 50%) had poorer overall survival times than those with low expression levels.DDX10 and BYSL genes may provide reliable molecular markers and effective therapeutic targets for chondrosarcoma and glioma.

Metformin Actions on the Liver: Protection Mechanisms Emerging in Hepatocytes and Immune Cells against NASH-Related HCC

Nonalcoholic fatty liver disease (NAFLD) is strongly linked to the global epidemic of obesity and type 2 diabetes mellitus (T2DM). Notably, NAFLD can progress from the mildest form of simple steatosis to nonalcoholic steatohepatitis (NASH) that increases the risk for hepatocellular carcinoma (HCC), which is a malignancy with a dismal prognosis and rising incidence in the United States and other developed counties, possibly due to the epidemic of NAFLD. Metformin, the first-line drug for T2DM, has been suggested to reduce risks for several types of cancers including HCC and protect against NASH-related HCC, as revealed by epidemical studies on humans and preclinical studies on animal models. This review focuses on the pathogenesis of NASH-related HCC and the mechanisms by which metformin inhibits the initiation and progression of NASH-related HCC. Since the functional role of immune cells in liver homeostasis and pathogenesis is increasingly appreciated in developing anti-cancer therapies on liver malignancies, we discuss both the traditional targets of metformin in hepatocytes and the recently defined effects of metformin on immune cells.

Inhibition of mitochondrial function by metformin increases glucose uptake, glycolysis and GDF-15 release from intestinal cells

Even though metformin is widely used to treat type2 diabetes, reducing glycaemia and body weight, the mechanisms of action are still elusive. Recent studies have identified the gastrointestinal tract as an important site of action. Here we used intestinal organoids to explore the effects of metformin on intestinal cell physiology. Bulk RNA-sequencing analysis identified changes in hexose metabolism pathways, particularly glycolytic genes. Metformin increased expression of Slc2a1 (GLUT1), decreased expression of Slc2a2 (GLUT2) and Slc5a1 (SGLT1) whilst increasing GLUT-dependent glucose uptake and glycolytic rate as observed by live cell imaging of genetically encoded metabolite sensors and measurement of oxygen consumption and extracellular acidification rates. Metformin caused mitochondrial dysfunction and metformin's effects on 2D-cultures were phenocopied by treatment with rotenone and antimycin-A, including upregulation of GDF15 expression, previously linked to metformin dependent weight loss. Gene expression changes elicited by metformin were replicated in 3D apical-out organoids and distal small intestines of metformin treated mice. We conclude that metformin affects glucose uptake, glycolysis and GDF-15 secretion, likely downstream of the observed mitochondrial dysfunction. This may explain the effects of metformin on intestinal glucose utilisation and food balance.

Restoration of mRNA Expression of Solute Carrier Proteins in Liver of Diet-Induced Obese Mice by Metformin

Metformin (MET), the most common medicine for type 2 diabetes (T2DM), improves insulin sensitivity by targeting the liver, intestine and other organs. Its impact on expression of the solute carrier (Slc) transporter genes have not been reported in the mechanism of insulin sensitization. In this study, we examined Slc gene expression in the liver and colon of diet-induced obese (DIO) mice treated with MET by transcriptomic analysis. There were 939 differentially expressed genes (DEGs) in the liver of DIO mice vs lean mice, which included 34 Slc genes. MET altered 489 DEGs in the liver of DIO mice, in which 23 were Slc genes. Expression of 20 MET-responsive Slc DEGs was confirmed by qRT-PCR, in which 15 Slc genes were altered in DIO mice and their expressions were restored by MET, including Slc2a10, Slc2a13, Slc5a9, Slc6a14, Slc7a9, Slc9a2, Slc9a3, Slc13a2, Slc15a2, Slc26a3, Slc34a2, Slc37a1, Slc44a4, Slc51b and Slc52a3. While, there were only 97 DEGs in the colon of DIO mice with 5 Slc genes, whose expression was not restored by MET. The data suggest that more genes were altered in the liver over the colon by the high fat diet (HFD). There were 20 Slc genes with alteration confirmed in the liver of DIO mice and 15 of them were restored by MET, which was associated with improvement of insulin sensitivity and obesity. The restoration may improve the uptake of glucose, amino acids, mannose, fructose, 1,5-anhydro-D-glucitol and bumetanide in hepatocytes of the liver of DIO mice. The study provides new insight into the mechanism of metformin action in insulin sensitization and obesity.

Epigenetics of Hepatic Insulin Resistance

Insulin resistance (IR) is largely recognized as a unifying feature that underlies metabolic dysfunction. Both lifestyle and genetic factors contribute to IR. Work from recent years has demonstrated that the epigenome may constitute an interface where different signals may converge to promote IR gene expression programs. Here, we review the current knowledge of the role of epigenetics in hepatic IR, focusing on the roles of DNA methylation and histone post-translational modifications. We discuss the broad epigenetic changes observed in the insulin resistant liver and its associated pathophysiological states and leverage on the wealth of 'omics' studies performed to discuss efforts in pinpointing specific loci that are disrupted by these changes. We envision that future studies, with increased genomic resolution and larger cohorts, will further the identification of biomarkers of early onset hepatic IR and assist the development of targeted interventions. Furthermore, there is growing evidence to suggest that persistent epigenetic marks may be acquired over prolonged exposure to disease or deleterious exposures, highlighting the need for preventative medicine and long-term lifestyle adjustments to avoid irreversible or long-term alterations in gene expression.

Genomic characterization of the adolescent idiopathic scoliosis-associated transcriptome and regulome

Adolescent idiopathic scoliosis (AIS), a sideways curvature of the spine, is the most common pediatric musculoskeletal disorder, affecting ~3% of the population worldwide. However, its genetic bases and tissues of origin remain largely unknown. Several genome-wide association studies (GWAS) have implicated nucleotide variants in non-coding sequences that control genes with important roles in cartilage, muscle, bone, connective tissue and intervertebral disks (IVDs) as drivers of AIS susceptibility. Here, we set out to define the expression of AIS-associated genes and active regulatory elements by performing RNA-seq and chromatin immunoprecipitation-sequencing against H3 lysine 27 acetylation in these tissues in mouse and human. Our study highlights genetic pathways involving AIS-associated loci that regulate chondrogenesis, IVD development and connective tissue maintenance and homeostasis. In addition, we identify thousands of putative AIS-associated regulatory elements which may orchestrate tissue-specific expression in musculoskeletal tissues of the spine. Quantification of enhancer activity of several candidate regulatory elements from our study identifies three functional enhancers carrying AIS-associated GWAS SNPs at the ADGRG6 and BNC2 loci. Our findings provide a novel genome-wide catalog of AIS-relevant genes and regulatory elements and aid in the identification of novel targets for AIS causality and treatment.

Epigenetic markers associated with metformin response and intolerance in drug-naïve patients with type 2 diabetes

Metformin is the first-line pharmacotherapy for managing type 2 diabetes (T2D). However, many patients with T2D do not respond to or tolerate metformin well. Currently, there are no phenotypes that successfully predict glycemic response to, or tolerance of, metformin. We explored whether blood-based epigenetic markers could discriminate metformin response and tolerance by analyzing genome-wide DNA methylation in drug-naïve patients with T2D at the time of their diagnosis. DNA methylation of 11 and 4 sites differed between glycemic responders/nonresponders and metformin-tolerant/intolerant patients, respectively, in discovery and replication cohorts. Greater methylation at these sites associated with a higher risk of not responding to or not tolerating metformin with odds ratios between 1.43 and 3.09 per 1-SD methylation increase. Methylation risk scores (MRSs) of the 11 identified sites differed between glycemic responders and nonresponders with areas under the curve (AUCs) of 0.80 to 0.98. MRSs of the 4 sites associated with future metformin intolerance generated AUCs of 0.85 to 0.93. Some of these blood-based methylation markers mirrored the epigenetic pattern in adipose tissue, a key tissue in diabetes pathogenesis, and genes to which these markers were annotated to had biological functions in hepatocytes that altered metformin-related phenotypes. Overall, we could discriminate between glycemic responders/nonresponders and participants tolerant/intolerant to metformin at diagnosis by measuring blood-based epigenetic markers in drug-naïve patients with T2D. This epigenetics-based tool may be further developed to help patients with T2D receive optimal therapy.

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

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.

Noncoding SNPs associated with increased GDF15 levels located in a metformin-activated enhancer region upstream of GDF15

Aim: GDF15 levels are a biomarker for metformin use. We performed the functional annotation of noncoding genome-wide association study (GWAS) SNPs for GDF15 levels and the Genotype-Tissue Expression (GTEx)-expression quantitative trait loci (eQTLs) for GDF15 expression within metformin-activated enhancers around GDF15. Materials & methods: These enhancers were identified using chromatin immunoprecipitation followed by sequencing data for active (H3K27ac) and silenced (H3K27me3) histone marks on human hepatocytes treated with metformin, Encyclopedia of DNA Elements data and cis-regulatory elements assignment tools. Results: The GWAS lead SNP rs888663, the SNP rs62122429 associated with GDF15 levels in the Outcome Reduction with Initial Glargine Intervention trial, and the GTEx-expression quantitative trait locus rs4808791 for GDF15 expression in whole blood are located in a metformin-activated enhancer upstream of GDF15 and tightly linked in Europeans and East Asians. Conclusion: Noncoding variation within a metformin-activated enhancer may increase GDF15 expression and help to predict GDF15 levels.

Metformin: Sentinel of the Epigenetic Landscapes That Underlie Cell Fate and Identity

The biguanide metformin is the first drug to be tested as a gerotherapeutic in the clinical trial TAME (Targeting Aging with Metformin). The current consensus is that metformin exerts indirect pleiotropy on core metabolic hallmarks of aging, such as the insulin/insulin-like growth factor 1 and AMP-activated protein kinase/mammalian Target Of Rapamycin signaling pathways, downstream of its primary inhibitory effect on mitochondrial respiratory complex I. Alternatively, but not mutually exclusive, metformin can exert regulatory effects on components of the biologic machinery of aging itself such as chromatin-modifying enzymes. An integrative metabolo-epigenetic outlook supports a new model whereby metformin operates as a guardian of cell identity, capable of retarding cellular aging by preventing the loss of the information-theoretic nature of the epigenome. The ultimate anti-aging mechanism of metformin might involve the global preservation of the epigenome architecture, thereby ensuring cell fate commitment and phenotypic outcomes despite the challenging effects of aging noise. Metformin might therefore inspire the development of new gerotherapeutics capable of preserving the epigenome architecture for cell identity. Such gerotherapeutics should replicate the ability of metformin to halt the erosion of the epigenetic landscape, mitigate the loss of cell fate commitment, delay stochastic/environmental DNA methylation drifts, and alleviate cellular senescence. Yet, it remains a challenge to confirm if regulatory changes in higher-order genomic organizers can connect the capacity of metformin to dynamically regulate the three-dimensional nature of epigenetic landscapes with the 4th dimension, the aging time.

Metformin regulates TRPM6, a potential explanation for magnesium imbalance in type 2 diabetes patients

Metformin therapy is associated with lower serum magnesium (Mg²⁺) levels in type 2 diabetes patients. The TRPM6 channel determines the fine-tuning of Mg²⁺ (re)absorption in intestine and kidney. Therefore, we aimed to investigate the short- and long-term effects of metformin on TRPM6. Patch clamp recordings and biotinylation assays were performed upon 1 h of incubation with metformin in TRPM6-transfected HEK293 cells. Additionally, 24 h of treatment of mDCT15 kidney and hCaco-2 colon cells with metformin was applied to measure the effects on endogenous TRPM6 expression by quantitative real-time PCR. To assess Mg²⁺ absorption, ²⁵Mg²⁺ uptake measurements were performed using inductively coupled plasma mass spectrometry. Short-term effects of metformin significantly increased TRPM6 activity and its cell surface trafficking. In contrast, long-term effects significantly decreased TRPM6 mRNA expression and ²⁵Mg²⁺ uptake. Metformin lowered TRPM6 mRNA levels independently of insulin- and AMPK-mediated pathways. Moreover, in type 2 diabetes patients, metformin therapy was associated with lower plasma Mg²⁺ concentrations and fractional excretion of Mg²⁺. Thereby, short-term metformin treatment increases TRPM6 activity explained by enhanced cell surface expression. Conversely, long-term metformin treatment results in downregulation of TRPM6 gene expression in intestine and kidney cells. This long-term effect translated in an inverse correlation between metformin and plasma Mg²⁺ concentration in type 2 diabetes patients.

Weighting approaches for a genetic risk score and an oxidative stress score for predicting the incidence of obesity

BACKGROUND

We aimed to predict the incidence of obesity in a Korean population using a genetic risk score (GRS) constructed with obesity-related single nucleotide polymorphisms (SNPs) along with an oxidative stress score (OSS).

METHODS

A total of 9460 Korean subjects and 356 974 SNPs were included. The GRS was constructed using three significant obesity-related SNP loci, and the OSS was calculated with three reliable oxidative stress biomarkers.

RESULTS

The GRS showed a more significant association with increased obesity (OR = 2.879) than did individual SNPs after adjusting for age and sex. Three oxidative stress biomarkers, including malondialdehyde, oxidized low-density lipoprotein, and 8-epi-prostaglandin F_2α , showed significantly high levels in the obese group. The OSS, which was the sum of each oxidative stress biomarker score, showed a markedly high association with the incidence of obesity, with an OR of 3.213. Based on the results of the regression tests and a receiver-operating characteristic (ROC) curve analysis, we found that HOMA-IR, high-sensitivity C-reactive protein (hs-CRP), the GRS, and the OSS were the most relevant factors for the increased risk of obesity and were significantly associated with the incidence of obesity. The area under the ROC curve was improved when the GRS was added to the model (from 74.2% to 75.1%).

CONCLUSIONS

We first identified that subjects with an obesity GRS and a high OSS might have a higher risk of obesity. Our findings and weighting approaches were effective in predicting the incidence of obesity; furthermore, the GRS is a relevant factor that significantly predicts the risk of obesity.

A New Liver Expression Quantitative Trait Locus Map From 1,183 Individuals Provides Evidence for Novel Expression Quantitative Trait Loci of Drug Response, Metabolic, and Sex-Biased Phenotypes

Expression quantitative trait locus (eQTL) studies in human liver are crucial for elucidating how genetic variation influences variability in disease risk and therapeutic outcomes and may help guide strategies to obtain maximal efficacy and safety of clinical interventions. Associations between expression microarray and genome-wide genotype data from four human liver eQTL studies (n = 1,183) were analyzed. More than 2.3 million cis-eQTLs for 15,668 genes were identified. When eQTLs were filtered against a list of 1,496 drug response genes, 187,829 cis-eQTLs for 1,191 genes were identified. Additionally, 1,683 sex-biased cis-eQTLs were identified, as well as 49 and 73 cis-eQTLs that colocalized with genome-wide association study signals for blood metabolite or lipid levels, respectively. Translational relevance of these results is evidenced by linking DPYD eQTLs to differences in safety of chemotherapy, linking the sex-biased regulation of PCSK9 expression to anti-lipid therapy, and identifying the G-protein coupled receptor GPR180 as a novel drug target for hypertriglyceridemia.

Identification and Massively Parallel Characterization of Regulatory Elements Driving Neural Induction

Epigenomic regulation and lineage-specific gene expression act in concert to drive cellular differentiation, but the temporal interplay between these processes is largely unknown. Using neural induction from human pluripotent stem cells (hPSCs) as a paradigm, we interrogated these dynamics by performing RNA sequencing (RNA-seq), chromatin immunoprecipitation sequencing (ChIP-seq), and assay for transposase accessible chromatin using sequencing (ATAC-seq) at seven time points during early neural differentiation. We found that changes in DNA accessibility precede H3K27ac, which is followed by gene expression changes. Using massively parallel reporter assays (MPRAs) to test the activity of 2,464 candidate regulatory sequences at all seven time points, we show that many of these sequences have temporal activity patterns that correlate with their respective cell-endogenous gene expression and chromatin changes. A prioritization method incorporating all genomic and MPRA data further identified key transcription factors involved in driving neural fate. These results provide a comprehensive resource of genes and regulatory elements that orchestrate neural induction and illuminate temporal frameworks during differentiation.

The C Allele of ATM rs11212617 Associates With Higher Pathological Complete Remission Rate in Breast Cancer Patients Treated With Neoadjuvant Metformin

Background: The minor allele (C) of the single-nucleotide polymorphism (SNP) rs11212617, located near the ataxia telangiectasia mutated (ATM) gene, has been associated with an increased likelihood of treatment success with metformin in type 2 diabetes. We herein investigated whether the same SNP would predict clinical response to neoadjuvant metformin in women with early breast cancer (BC). Methods: DNA was collected from 79 patients included in the intention-to-treat population of the METTEN study, a phase 2 clinical trial of HER2-positive BC patients randomized to receive either metformin combined with anthracycline/taxane-based chemotherapy and trastuzumab or equivalent regimen without metformin, before surgery. SNP rs11212617 genotyping was assessed using allelic discrimination by quantitative polymerase chain reaction. Results: Logistic regression analyses revealed a significant relationship between the rs11212617 genotype and the ability of treatment arms to achieve a pathological complete response (pCR) in patients (odds ratio [OR]_{genotype×arm} = 10.33, 95% confidence interval [CI]: 1.29-82.89, p = 0.028). In the metformin-containing arm, patients bearing the rs11212617 C allele had a significantly higher probability of pCR (OR _A/C,C/C = 7.94, 95%CI: 1.60-39.42, p = 0.011). Conversely, no association was found between rs11212617 and clinical response in the reference arm (OR _A/C,C/C = 0.77, 95%CI: 0.20-2.92, p = 0.700). After controlling for tumor size and hormone receptor status, the rs11212617 C allele remained a significant predictor of pCR solely in the metformin-containing arm. Conclusions: If reproducible, the rs11212617 C allele might warrant consideration as a predictive clinical biomarker to inform the personalized use of metformin in BC patients. Trial Registration: EU Clinical Trials Register, EudraCT number 2011-000490-30. Registered 28 February 2011, https://www.clinicaltrialsregister.eu/ctr-search/trial/2011-000490-30/ES.

Pharmacogenetics of type 2 diabetes mellitus, the route toward tailored medicine

Type 2 diabetes mellitus (T2DM) is a chronic disease that has reached the levels of a global epidemic. In order to achieve optimal glucose control, it is often necessary to rely on combination therapy of multiple drugs or insulin because uncontrolled glucose levels result in T2DM progression and enhanced risk of complications and mortality. Several antihyperglycemic agents have been developed over time, and T2DM pharmacotherapy should be prescribed based on suitability for the individual patient's characteristics. Pharmacogenetics is the branch of genetics that investigates how our genome influences individual responses to drugs, therapeutic outcomes, and incidence of adverse effects. In this review, we evaluated the pharmacogenetic evidences currently available in the literature, and we identified the top informative genetic variants associated with response to the most common anti-diabetic drugs: metformin, DPP-4 inhibitors/GLP1R agonists, thiazolidinediones, and sulfonylureas/meglitinides. Overall, we found 40 polymorphisms for each drug class in a total of 71 loci, and we examined the possibility of encouraging genetic screening of these variants/loci in order to critically implement decision-making about the therapeutic approach through precision medicine strategies. It is possible then to anticipate that when the clinical practice will take advantage of the genetic information of the diabetic patients, this will provide a useful resource for the prevention of T2DM progression, enabling the identification of the precise drug that is most likely to be effective and safe for each patient and the reduction of the economic impact on a global scale.

Pharmacogenetics of Antidiabetic Drugs

Pharmacogenetic studies of antidiabetic drugs have so far focused largely on response to metformin, which is the first-line therapy for treatment of type 2 diabetes (T2D). The first studies of metformin pharmacogenetics were focused on candidate genes that were implicated in metformin pharmacokinetics and transport. Since 2011, genome-wide association studies have been conducted in large cohorts of individuals with T2D identifying genes that are associated with glycemic response to metformin. There have been fewer pharmacogenetic studies of other antidiabetic drugs, and those have been largely limited to candidate gene studies with small sample sizes. Understanding the pharmacogenetics of antidiabetes medications is important for the integration of genetic screening into therapeutic decision making, and to achieve the goal of "precision medicine" for patients with T2D. In this chapter, we provide a review of the pharmacogenetics investigations of metformin and other antidiabetes medications. In addition, we highlight the importance of collaborative efforts with large sample size and representation from multiple ethnic groups in pharmacogenetics studies.

CRISPR/Cas9 therapeutics for liver diseases

The development of innovative genome editing techniques in recent years has revolutionized the field of biomedicine. Among the novel approaches, the clustered regularly interspaced short palindromic repeat/CRISPR-associated protein (CRISPR/Cas9) technology has become the most popular, in part due to its matchless ability to carry out gene editing at the target site with great precision. With considerable successes in animal and preclinical studies, CRISPR/Cas9-mediated gene editing has paved the way for its use in human trials, including patients with a variety of liver diseases. Gene editing is a logical therapeutic approach for liver diseases because many metabolic and acquired disorders are caused by mutations within a single gene. In this review, we provide an overview on current and emerging therapeutic strategies for the treatment of liver diseases using the CRISPR/Cas9 technology.

Precision medicine in diabetes: an opportunity for clinical translation

Metabolic disorders present a public health challenge of staggering proportions. In diabetes, there is an urgent need to better understand disease heterogeneity, clinical trajectories, and related comorbidities. A pressing and timely question is whether we are ready for precision medicine in diabetes. Some biological insights that have emerged during the last decade have already been used to direct clinical decision making, especially in monogenic forms of diabetes. However, much work is necessary to integrate high-dimensional explorations into complex disease architectures, less penetrant biological alterations, and broader phenotypes, such as type 2 diabetes. In addition, for precision medicine to take hold in diabetes, reproducibility, interpretability, and actionability remain key guiding objectives. In this review, we examine how mounting data sets generated during the last decade to understand biological variability are now inspiring new venues to clarify diabetes nosology and ultimately translate findings into more effective prevention and treatment strategies.

Towards natural mimetics of metformin and rapamycin

Aging is now at the forefront of major challenges faced globally, creating an immediate need for safe, widescale interventions to reduce the burden of chronic disease and extend human healthspan. Metformin and rapamycin are two FDA-approved mTOR inhibitors proposed for this purpose, exhibiting significant anti-cancer and anti-aging properties beyond their current clinical applications. However, each faces issues with approval for off-label, prophylactic use due to adverse effects. Here, we initiate an effort to identify nutraceuticals-safer, naturally-occurring compounds-that mimic the anti-aging effects of metformin and rapamycin without adverse effects. We applied several bioinformatic approaches and deep learning methods to the Library of Integrated Network-based Cellular Signatures (LINCS) dataset to map the gene- and pathway-level signatures of metformin and rapamycin and screen for matches among over 800 natural compounds. We then predicted the safety of each compound with an ensemble of deep neural network classifiers. The analysis revealed many novel candidate metformin and rapamycin mimetics, including allantoin and ginsenoside (metformin), epigallocatechin gallate and isoliquiritigenin (rapamycin), and withaferin A (both). Four relatively unexplored compounds also scored well with rapamycin. This work revealed promising candidates for future experimental validation while demonstrating the applications of powerful screening methods for this and similar endeavors.

Diabetes medication associates with DNA methylation of metformin transporter genes in the human liver

BACKGROUND

Given that metformin is the most common pharmacological therapy for type 2 diabetes, understanding the function of this drug is of great importance. Hepatic metformin transporters are responsible for the pharmacologic action of metformin. However, epigenetics in genes encoding metformin transporters has not been fully elucidated. We examined the DNA methylation of these genes in the liver of subjects with type 2 diabetes and tested whether epigenetic alterations associate with diabetes medication, i.e., metformin or insulin plus metformin treatment.

RESULTS

DNA methylation in OCT1 encoded by SLC22A1, OCT3 encoded by SLC22A3, and MATE1 encoded by SLC47A1 was assessed in the human liver. Lower average and promoter DNA methylation of SLC22A1, SLC22A3, and SLC47A1 was found in diabetic subjects receiving just metformin, compared to those who took insulin plus metformin or no diabetes medication. Moreover, diabetic subjects receiving just metformin had a similar DNA methylation pattern in these genes compared to non-diabetic subjects. Notably, DNA methylation was also associated with gene expression, glucose levels, and body mass index, i.e., higher SLC22A3 methylation was related to lower SLC22A3 expression and to insulin plus metformin treatment, higher fasting glucose levels and higher body mass index. Importantly, metformin treatment did also directly decrease DNA methylation of SLC22A1 in hepatocytes cultured in vitro.

CONCLUSIONS

Our study supports that metformin decreases DNA methylation of metformin transporter genes in the human liver. Moreover, higher methylation levels in these genes associate with hyperglycaemia and obesity.

Use antibiotics in cell culture with caution: genome-wide identification of antibiotic-induced changes in gene expression and regulation

Standard cell culture guidelines often use media supplemented with antibiotics to prevent cell contamination. However, relatively little is known about the effect of antibiotic use in cell culture on gene expression and the extent to which this treatment could confound results. To comprehensively characterize the effect of antibiotic treatment on gene expression, we performed RNA-seq and ChIP-seq for H3K27ac on HepG2 cells, a human liver cell line commonly used for pharmacokinetic, metabolism and genomic studies, cultured in media supplemented with penicillin-streptomycin (PenStrep) or vehicle control. We identified 209 PenStrep-responsive genes, including transcription factors such as ATF3 that are likely to alter the regulation of other genes. Pathway analyses found a significant enrichment for "xenobiotic metabolism signaling" and "PXR/RXR activation" pathways. Our H3K27ac ChIP-seq identified 9,514 peaks that are PenStrep responsive. These peaks were enriched near genes that function in cell differentiation, tRNA modification, nuclease activity and protein dephosphorylation. Our results suggest that PenStrep treatment can significantly alter gene expression and regulation in a common liver cell type such as HepG2, advocating that antibiotic treatment should be taken into account when carrying out genetic, genomic or other biological assays in cultured cells.

CRISPR/Cas9: at the cutting edge of hepatology

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 genome engineering has revolutionised biomedical science and we are standing on the cusp of medical transformation. The therapeutic potential of this technology is tremendous, however, its translation to the clinic will be challenging. In this article, we review recent progress using this genome editing technology and explore its potential uses in studying and treating diseases of the liver. We discuss the development of new research tools and animal models as well as potential clinical applications, strategies and challenges.

Pharmacogenetics in the treatment of pre-eclampsia: current findings, challenges and perspectives

Pre-eclampsia (PE) is defined as pregnancy-induced hypertension and proteinuria, and is a major cause of maternal and perinatal morbidity and mortality. A large subgroup of pregnant women with PE is nonresponsive to antihypertensive drugs, including methyldopa, nifedipine and hydralazine. Pharmacogenomics may help to guide the individualized therapy for this nonresponsive subgroup. However, just a few pharmacogenetic studies examined the effects of genetic polymorphisms on response to antihypertensive drugs in PE, and the criteria of responsiveness used to define responsive or nonresponsive subgroups to antihypertensive therapy should be replicated by others. We review these gene–drugs interactions, novel approaches to pharmacogenomics research and potential novel drugs for PE therapy. Finally, we discuss the challenges and perspectives of pharmacogenetics in the treatment of PE.