Common variants near ATM are associated with glycemic response to metformin in type 2 diabetes

Drug-induced hypoglycaemia in type 2 diabetes

INTRODUCTION

Hypoglycaemia is a side effect caused by some therapies for type 2 diabetes, which can cause physical, social and psychological harm. Hypoglycaemia also prevents attainment of treatment goals and satisfactory glycaemic control.

AREAS COVERED

The risk of hypoglycaemia associated with commonly prescribed therapies, including metformin, sulphonylureas, dipeptidyl peptidase-4 enzyme (DPP-4) inhibitors, glucagon-like peptide-1 (GLP-1) agonists and thiazolidinediones, is reviewed in this paper (insulin-induced hypoglycaemia is not included). Other medications that are frequently co-prescribed in type 2 diabetes are also discussed, including anti-hypertensive drugs, antibiotics and fibrates, along with various important patient-related risk factors.

EXPERT OPINION

Hypoglycaemia is a common and potentially dangerous side effect of some medications used for type 2 diabetes. The risk of hypoglycaemia should always be considered when selecting and implementing a therapy, with a focus on the individual. Future research into new therapies should measure the frequency of hypoglycaemia prospectively and accurately. Hypoglycaemia has been shown to be a potentially life-threatening metabolic stress; therefore therapies that effectively manage diabetes without the risk of hypoglycaemia are likely to be favoured in the future.

Targeting metabolism for cancer treatment and prevention: metformin, an old drug with multi-faceted effects

Understanding the complexity of cancer and of the underlying regulatory networks provides a new paradigm that tackles cancer development and treatment through a system biology approach, contemporarily acting on various intersecting pathways. Cancer cell metabolism is an old pathogenetic issue that has recently gained new interest as target for therapeutic approaches. More than 70 years ago, Warburg discovered that malignant cells generally have altered metabolism with high rates of glucose uptake and increased glycolysis, even under aerobic condition. Observational studies have provided evidence that impaired metabolism, obesity, hyperglycemia and hyperinsulinemia may have a role in cancer development, progression and prognosis, and actually diabetic and obese patients have increased cancer risk. On the other hand, caloric restriction has been shown to prolong life span and reduce cancer incidence in several animal models, having an impact on different metabolic pathways. Metformin, an antidiabetic drug widely used for over 40 years, mimics caloric restriction acting on cell metabolism at multiple levels, reducing all energy-consuming processes in the cells, including cell proliferation. By overviewing molecular mechanisms of action, epidemiological evidences, experimental data in tumor models and early clinical study results, this review provides information supporting the promising use of metformin in cancer prevention and treatment.

'Omics'-driven discoveries in prevention and treatment of type 2 diabetes

Eur J Clin Invest 2012; 42 (6): 579-588 ABSTRACT: Glucose-based methods are currently gold standards for identifying individuals at risk of type 2 diabetes. Obviously, these methods only consider one of many pathologies of impaired glucose metabolism and they all suffer from a poor specificity as type 2 diabetes risk assessment tools. Recently, however, panels of multiple biomarkers reflecting several pre-diabetic pathologies have been developed. Their specificity and potentials for future risk stratification are discussed. As a multifactorial disorder type 2 diabetes calls for a multifactorial treatment approach targeting multiple but modifiable vascular risk factors. The same holds for pre-diabetic states and prevention hereof. In addition, type 2 diabetes and pre-diabetes show major heterogeneity between affected individuals in pathology, risk of organ damages, progression rate and responsiveness to treatment or prevention. Despite the heterogeneity and uniqueness of type 2 diabetes and pre-diabetes most affected individuals are currently offered interventions as if they all have the same disease or risk of disease and will respond similarly. The complex origin and course of type 2 diabetes combined with uniformity and non-specificity of current interventions may explain the high rate of treatment failures and the relative poor prognosis of many diabetes patients. Given this situation, the present review also explores the perspectives of selected examples within applied genomics and metagenomics for improving patient care by facilitating interventions tailored to specific subpopulations.

Genetic and environmental factors associated with type 2 diabetes and diabetic vascular complications

Faced with a global epidemic of type 2 diabetes (T2D), it is critical that researchers improve our understanding of the pathogenesis of T2D and related vascular complications. These findings may ultimately lead to novel treatment options for disease prevention or delaying progression. Two major paradigms jointly underlie the development of T2D and related coronary artery disease, diabetic nephropathy, and diabetic retinopathy. These paradigms include the genetic risk variants and behavioral/environmental factors. This article systematically reviews the literature supporting genetic determinants in the pathogenesis of T2D and diabetic vasculopathy, and the functional implications of these gene variants on the regulation of beta-cell function and glucose homeostasis. We update the discovery of diabetes and diabetic vasculopathy risk variants, and describe the genetic technologies that have uncovered them. Also, genomic linkage between obesity and T2D is discussed. There is a complementary role for behavioral and environmental factors modulating the genetic susceptibility and diabetes risk. Epidemiological and clinical data demonstrating the effects of behavioral and novel environmental exposures on disease expression are reviewed. Finally, a succinct overview of recent landmark clinical trials addressing glycemic control and its impact on rates of vascular complications is presented. It is expected that novel strategies to exploit the gene- and exposure-related underpinnings of T2D will soon result.

LDGIdb: a database of gene interactions inferred from long-range strong linkage disequilibrium between pairs of SNPs

Background

Complex human diseases may be associated with many gene interactions. Gene interactions take several different forms and it is difficult to identify all of the interactions that are potentially associated with human diseases. One approach that may fill this knowledge gap is to infer previously unknown gene interactions via identification of non-physical linkages between different mutations (or single nucleotide polymorphisms, SNPs) to avoid hitchhiking effect or lack of recombination. Strong non-physical SNP linkages are considered to be an indication of biological (gene) interactions. These interactions can be physical protein interactions, regulatory interactions, functional compensation/antagonization or many other forms of interactions. Previous studies have shown that mutations in different genes can be linked to the same disorders. Therefore, non-physical SNP linkages, coupled with knowledge of SNP-disease associations may shed more light on the role of gene interactions in human disorders. A user-friendly web resource that integrates information about non-physical SNP linkages, gene annotations, SNP information, and SNP-disease associations may thus be a good reference for biomedical research.

Findings

Here we extracted the SNPs located within the promoter or exonic regions of protein-coding genes from the HapMap database to construct a database named the Linkage-Disequilibrium-based Gene Interaction database (LDGIdb). The database stores 646,203 potential human gene interactions, which are potential interactions inferred from SNP pairs that are subject to long-range strong linkage disequilibrium (LD), or non-physical linkages. To minimize the possibility of hitchhiking, SNP pairs inferred to be non-physically linked were required to be located in different chromosomes or in different LD blocks of the same chromosomes. According to the genomic locations of the involved SNPs (i.e., promoter, untranslated region (UTR) and coding region (CDS)), the SNP linkages inferred were categorized into promoter-promoter, promoter-UTR, promoter-CDS, CDS-CDS, CDS-UTR and UTR-UTR linkages. For the CDS-related linkages, the coding SNPs were further classified into nonsynonymous and synonymous variations, which represent potential gene interactions at the protein and RNA level, respectively. The LDGIdb also incorporates human disease-association databases such as Genome-Wide Association Studies (GWAS) and Online Mendelian Inheritance in Man (OMIM), so that the user can search for potential disease-associated SNP linkages. The inferred SNP linkages are also classified in the context of population stratification to provide a resource for investigating potential population-specific gene interactions.

Conclusion

The LDGIdb is a user-friendly resource that integrates non-physical SNP linkages and SNP-disease associations for studies of gene interactions in human diseases. With the help of the LDGIdb, it is plausible to infer population-specific SNP linkages for more focused studies, an avenue that is potentially important for pharmacogenetics. Moreover, by referring to disease-association information such as the GWAS data, the LDGIdb may help identify previously uncharacterized disease-associated gene interactions and potentially lead to new discoveries in studies of human diseases.

Keywords

Gene interaction, SNP, Linkage disequilibrium, Systems biology, Bioinformatics

Metformin in obesity, cancer and aging: addressing controversies

Metformin, an oral anti-diabetic drug, is being considered increasingly for treatment and prevention of cancer, obesity as well as for the extension of healthy lifespan. Gradually accumulating discrepancies about its effect on cancer and obesity can be explained by the shortage of randomized clinical trials, differences between control groups (reference points), gender- and age-associated effects and pharmacogenetic factors. Studies of the potential antiaging effects of antidiabetic biguanides, such as metformin, are still experimental for obvious reasons and their results are currently ambiguous. Here we discuss whether the discrepancies in different studies are merely methodological or inherently related to individual differences in responsiveness to the drug.

Stratifying type 2 diabetes cases by BMI identifies genetic risk variants in LAMA1 and enrichment for risk variants in lean compared to obese cases

Common diseases such as type 2 diabetes are phenotypically heterogeneous. Obesity is a major risk factor for type 2 diabetes, but patients vary appreciably in body mass index. We hypothesized that the genetic predisposition to the disease may be different in lean (BMI<25 Kg/m²) compared to obese cases (BMI≥30 Kg/m²). We performed two case-control genome-wide studies using two accepted cut-offs for defining individuals as overweight or obese. We used 2,112 lean type 2 diabetes cases (BMI<25 kg/m²) or 4,123 obese cases (BMI≥30 kg/m²), and 54,412 un-stratified controls. Replication was performed in 2,881 lean cases or 8,702 obese cases, and 18,957 un-stratified controls. To assess the effects of known signals, we tested the individual and combined effects of SNPs representing 36 type 2 diabetes loci. After combining data from discovery and replication datasets, we identified two signals not previously reported in Europeans. A variant (rs8090011) in the LAMA1 gene was associated with type 2 diabetes in lean cases (P = 8.4×10⁻⁹, OR = 1.13 [95% CI 1.09-1.18]), and this association was stronger than that in obese cases (P = 0.04, OR = 1.03 [95% CI 1.00-1.06]). A variant in HMG20A--previously identified in South Asians but not Europeans--was associated with type 2 diabetes in obese cases (P = 1.3×10⁻⁸, OR = 1.11 [95% CI 1.07-1.15]), although this association was not significantly stronger than that in lean cases (P = 0.02, OR = 1.09 [95% CI 1.02-1.17]). For 36 known type 2 diabetes loci, 29 had a larger odds ratio in the lean compared to obese (binomial P = 0.0002). In the lean analysis, we observed a weighted per-risk allele OR = 1.13 [95% CI 1.10-1.17], P = 3.2×10⁻¹⁴. This was larger than the same model fitted in the obese analysis where the OR = 1.06 [95% CI 1.05-1.08], P = 2.2×10⁻¹⁶. This study provides evidence that stratification of type 2 diabetes cases by BMI may help identify additional risk variants and that lean cases may have a stronger genetic predisposition to type 2 diabetes.

Metformin and the ATM DNA damage response (DDR): accelerating the onset of stress-induced senescence to boost protection against cancer

By activating the ataxia telangiectasia mutated (ATM)-mediated DNA Damage Response (DDR), the AMPK agonist metformin might sensitize cells against further damage, thus mimicking the precancerous stimulus that induces an intrinsic barrier against carcinogenesis. Herein, we present the new hypothesis that metformin might function as a tissue sweeper of pre-malignant cells before they gain stem cell/tumor initiating properties. Because enhanced glycolysis (the Warburg effect) plays a causal role in the gain of stem-like properties of tumor-initiating cells by protecting them from the pro-senescent effects of mitochondrial respiration-induced oxidative stress, metformin's ability to disrupt the glycolytic metabotype may generate a cellular phenotype that is metabolically protected against immortalization. The bioenergetic crisis imposed by metformin, which may involve enhanced mitochondrial biogenesis and oxidative stress, can lower the threshold for cellular senescence by pre-activating an ATM-dependent pseudo-DDR. This allows an accelerated onset of cellular senescence in response to additional oncogenic stresses. By pushing cancer cells to use oxidative phosphorylation instead of glycolysis, metformin can rescue cell surface major histocompatibility complex class I (MHC-I) expression that is downregulated by oncogenic transformation, a crucial adaptation of tumor cells to avoid the adaptive immune response by cytotoxic T-lymphocytes (CTLs). Aside from restoration of tumor immunosurveillance at the cell-autonomous level, metformin can activate a senescence-associated secretory phenotype (SASP) to reinforce senescence growth arrest, which might trigger an immune-mediated clearance of the senescent cells in a non-cell-autonomous manner. By diminishing the probability of escape from the senescence anti-tumor barrier, the net effect of metformin should be a significant decrease in the accumulation of dysfunctional, pre-malignant cells in tissues, including those with the ability to initiate tumors. As life-long or late-life removal of senescent cells has been shown to prevent or delay the onset or progression of age-related disorders, the tissue sweeper function of metformin may inhibit the malignant/metastatic progression of pre-malignant/senescent tumor cells and increase the human lifespan.

AMPK: a nutrient and energy sensor that maintains energy homeostasis

AMP-activated protein kinase (AMPK) is a crucial cellular energy sensor. Once activated by falling energy status, it promotes ATP production by increasing the activity or expression of proteins involved in catabolism while conserving ATP by switching off biosynthetic pathways. AMPK also regulates metabolic energy balance at the whole-body level. For example, it mediates the effects of agents acting on the hypothalamus that promote feeding and entrains circadian rhythms of metabolism and feeding behaviour. Finally, recent studies reveal that AMPK conserves ATP levels through the regulation of processes other than metabolism, such as the cell cycle and neuronal membrane excitability.

Integrative genomics strategies to elucidate the complexity of drug response

Pharmacogenomic investigation from both genome-wide association studies and experiments focused on candidate loci involved in drug mechanism and metabolism has yielded a substantial and increasing list of robust genetic effects on drug therapy in humans. At the same time, reasonably comprehensive molecular data such as gene expression, proteomic and metabolomic data are now available for collections of hundreds to thousands of individuals. If these data are structured in a statistically robust and computationally tractable way, such as a network model, they can aid in the analysis of new pharmacogenomics studies by suggesting novel hypotheses for the regulation of genes involved in drug metabolism and response. Similarly, hypotheses taken from these same models can direct genome-wide association studies by focusing the genome-wide association studies analysis on a number of specific hypotheses informed by the relationships customarily seen between a gene's expression or protein activity and genetic variation at a particular locus. Network models based on other sorts of systematic biological data such as cell-based surveys of drug effect on gene expression and mining of literature and electronic medical records for associations between clinical and molecular phenotypes also promise similar utility. Although surely primitive in comparison with what will be developed, these model-based approaches to leveraging the increasing volume of data generated in the course of patient care and medical research nevertheless suggest a huge opportunity to improve our understanding of biological systems involved in pharmacogenomics and apply them to questions of medical relevance.

Genetic predisposition to type 2 diabetes is associated with impaired insulin secretion but does not modify insulin resistance or secretion in response to an intervention to lower dietary saturated fat

Genome-wide association studies have identified SNPs reproducibly associated with type 2 diabetes (T2D). We examined the effect of genetic predisposition to T2D on insulin sensitivity and secretion using detailed phenotyping in overweight individuals with no diagnosis of T2D. Furthermore, we investigated whether this genetic predisposition modifies the responses in beta-cell function and insulin sensitivity to a 24-week dietary intervention. We genotyped 25 T2D-associated SNPs in 377 white participants from the RISCK study. Participants underwent an IVGTT prior to and following a dietary intervention that aimed to lower saturated fat intake by replacement with monounsaturated fat or carbohydrate. We composed a genetic predisposition score (T2D-GPS) by summing the T2D risk-increasing alleles of the 25 SNPs and tested for association with insulin secretion and sensitivity at baseline, and with the change in response to the dietary intervention. At baseline, a higher T2D-GPS was associated with lower acute insulin secretion (AIRg 4% lower/risk allele, P = 0.006) and lower insulin secretion for a given level of insulin sensitivity, assessed by the disposition index (DI 5% lower/risk allele, P = 0.002), but not with insulin sensitivity (Si). T2D-GPS did not modify changes in insulin secretion, insulin sensitivity or the disposition index in response to the dietary interventions to lower saturated fat. Participants genetically predisposed to T2D have an impaired ability to compensate for peripheral insulin resistance with insulin secretion at baseline, but this does not modify the response to a reduction in dietary saturated fat through iso-energetic replacement with carbohydrate or monounsaturated fat.

Metformin and cancer therapy

PURPOSE OF REVIEW

To focus on the potential role of metformin, a widely used antidiabetic drug, in cancer treatment.

RECENT FINDINGS

Epidemiological, preclinical and cellular studies have shown in the last 6 years that metformin exerts antitumoral properties. Here, we review the very last findings concerning metformin action in cancer. The results of the first clinical trials as well as the combined action of metformin and chemotherapeutics agents in vitro and in vivo will be discussed. Recent studies show that metformin could also regulate inflammation and, therefore, may play a role in tumor microenvironment. Finally, we will present the latest publications concerning the molecular mechanisms implicated in metformin action, especially the AMP-activated kinase-independent pathways.

SUMMARY

The numerous in-vitro and in-vivo studies warrant the ongoing clinical trials, which should definitively help us to determine if metformin could be used in cancer therapy.

Five years of GWAS discovery

The past five years have seen many scientific and biological discoveries made through the experimental design of genome-wide association studies (GWASs). These studies were aimed at detecting variants at genomic loci that are associated with complex traits in the population and, in particular, at detecting associations between common single-nucleotide polymorphisms (SNPs) and common diseases such as heart disease, diabetes, auto-immune diseases, and psychiatric disorders. We start by giving a number of quotes from scientists and journalists about perceived problems with GWASs. We will then briefly give the history of GWASs and focus on the discoveries made through this experimental design, what those discoveries tell us and do not tell us about the genetics and biology of complex traits, and what immediate utility has come out of these studies. Rather than giving an exhaustive review of all reported findings for all diseases and other complex traits, we focus on the results for auto-immune diseases and metabolic diseases. We return to the perceived failure or disappointment about GWASs in the concluding section.

Cellular and molecular mechanisms of metformin: an overview

Considerable efforts have been made since the 1950s to better understand the cellular and molecular mechanisms of action of metformin, a potent antihyperglycaemic agent now recommended as the first-line oral therapy for T2D (Type 2 diabetes). The main effect of this drug from the biguanide family is to acutely decrease hepatic glucose production, mostly through a mild and transient inhibition of the mitochondrial respiratory chain complex I. In addition, the resulting decrease in hepatic energy status activates AMPK (AMP-activated protein kinase), a cellular metabolic sensor, providing a generally accepted mechanism for the action of metformin on hepatic gluconeogenesis. The demonstration that respiratory chain complex I, but not AMPK, is the primary target of metformin was recently strengthened by showing that the metabolic effect of the drug is preserved in liver-specific AMPK-deficient mice. Beyond its effect on glucose metabolism, metformin has been reported to restore ovarian function in PCOS (polycystic ovary syndrome), reduce fatty liver, and to lower microvascular and macrovascular complications associated with T2D. Its use has also recently been suggested as an adjuvant treatment for cancer or gestational diabetes and for the prevention in pre-diabetic populations. These emerging new therapeutic areas for metformin will be reviewed together with recent findings from pharmacogenetic studies linking genetic variations to drug response, a promising new step towards personalized medicine in the treatment of T2D.

Pharmacogenetics in type 2 diabetes: potential implications for clinical practice

Pharmacogenetic research aims to study how genetic variation may influence drug efficacy and/or toxicity; pharmacogenomics expands this quest to the entire genome. Pharmacogenetic findings may help to uncover new drug targets, illuminate pathophysiology, clarify disease heterogeneity, aid in the fine-mapping of genetic associations, and contribute to personalized treatment. In diabetes, there is precedent for the successful application of pharmacogenetic concepts to monogenic forms of the disease, such as maturity onset diabetes of the young or neonatal diabetes. Whether similar insights will be produced for the common form of type 2 diabetes remains to be seen. With recent advances in genetic approaches, the successive application of candidate gene studies, large-scale genotyping studies and genome-wide association studies has begun to generate suggestive results that may lead to changes in clinical practice. However, many potential barriers to the translation of pharmacogenetic discoveries to the clinical management of diabetes still remain. Here, we offer a contemporary overview of the field in its current state, identify potential obstacles, and highlight future directions.

The ATM protein kinase and cellular redox signaling: beyond the DNA damage response

The ataxia-telangiectasia mutated (ATM) protein kinase is best known for its role in the DNA damage response, but recent findings suggest that it also functions as a redox sensor that controls the levels of reactive oxygen species in human cells. Here, we review evidence supporting the conclusion that ATM can be directly activated by oxidation, as well as various observations from ATM-deficient patients and mouse models that point to the importance of ATM in oxidative stress responses. We also discuss the roles of this kinase in regulating mitochondrial function and metabolic control through its action on tumor suppressor p53, AMP-activated protein kinase (AMPK), mammalian target of rapamycin (mTOR) and hypoxia-inducible factor 1 (HIF1), and how the regulation of these enzymes may be affected in ATM-deficient patients and in cancer cells.

Pharmacogenomics of oral antidiabetic medications: current data and pharmacoepigenomic perspective

Type 2 diabetes mellitus (T2DM) is an increasingly prevalent disease. Several classes of drugs are currently available to treat T2DM patients; however, clinical response to these drugs often exhibits significant variation among individuals. For the oral antidiabetic drug classes of sulfonylureas, nonsulfonylurea insulin secretagogs, biguanides and thiazolidinediones, pharmacogenomic evidence has accumulated demonstrating an association between specific gene polymorphisms and interindividual variability in their therapeutic and adverse reaction effects. These polymorphisms are in genes of molecules involved in metabolism, transport and therapeutic mechanisms of the aforementioned drugs. Overall, it appears that pharmacogenomics has the potential to improve the management of T2DM and help clinicians in the effective prescribing of oral antidiabetic medications. Although pharmacogenomics can explain some of the heterogeneity in dose requirements, response and incidence of adverse effects of drugs between individuals, it is now clearly understood that much of the diversity in drug effects cannot be solely explained by studying the genomic diversity. Epigenomics, the field that focuses on nongenomic modifications that influence gene expression, may expand the scope of pharmacogenomics towards optimization of drug therapy. Therefore, pharmacoepigenomics, the combined analysis of genetic variations and epigenetic modifications, holds promise for the realization of personalized medicine. Although pharmacoepigenomics has so far been evaluated mainly in cancer pharmacotherapy, studies on epigenomic modifications during T2DM development provide useful data on the potential of pharmacoepigenomics to elucidate the mechanisms underlying interindividual response to oral antidiabetic treatment. In summary, the present article focuses on available data from pharmacogenomic studies of oral antidiabetic drugs and also provides an overview of T2DM epigenomic research, which has the potential to boost the development of pharmacoepigenomics in antidiabetic treatment.

Do genome-wide association scans have potential for translation?

The success of genome-wide association studies (GWAS) in identifying replicating associations has greatly contributed to understanding of the genetic aetiology of complex diseases. This review discusses and provides examples of the potential of GWAS findings to be translated into clinical practice, i.e., diagnosis, prediction, prognosis, novel treatments and response to treatment of common diseases. The biological insights afforded by newly-identified robust associations represent the largest, albeit indirect, translational contribution of GWAS.

A common 5'-UTR variant in MATE2-K is associated with poor response to metformin

Multidrug and toxin extrusion 2 (MATE2-K (SLC47A2)), a polyspecific organic cation exporter, facilitates the renal elimination of the antidiabetes drug metformin. In this study, we characterized genetic variants of MATE2-K, determined their association with metformin response, and elucidated their impact by means of a comparative protein structure model. Four nonsynonymous variants and four variants in the MATE2-K basal promoter region were identified from ethnically diverse populations. Two nonsynonymous variants-c.485C>T and c.1177G>A-were shown to be associated with significantly lower metformin uptake and reduction in protein expression levels. MATE2-K basal promoter haplotypes containing the most common variant, g.-130G>A (>26% allele frequency), were associated with a significant increase in luciferase activities and reduced binding to the transcriptional repressor myeloid zinc finger 1 (MZF-1). Patients with diabetes who were homozygous for g.-130A had a significantly poorer response to metformin treatment, assessed as relative change in glycated hemoglobin (HbA1c) (-0.027 (-0.076, 0.033)), as compared with carriers of the reference allele, g.-130G (-0.15 (-0.17, -0.13)) (P=0.002). Our study showed that MATE2-K plays a role in the antidiabetes response to metformin.

Genetics and genomics of radiotherapy toxicity: towards prediction

Radiotherapy is involved in many curative treatments of cancer; millions of survivors live with the consequences of treatment, and toxicity in a minority limits the radiation doses that can be safely prescribed to the majority. Radiogenomics is the whole genome application of radiogenetics, which studies the influence of genetic variation on radiation response. Work in the area focuses on uncovering the underlying genetic causes of individual variation in sensitivity to radiation, which is important for effective, safe treatment. In this review, we highlight recent advances in radiotherapy and discuss results from four genome-wide studies of radiotoxicity.

Pharmacogenetics: past, present and future

The subject area of pharmacogenetics, also known as pharmacogenomics, has a long history. Research in this area has led to fundamental discoveries, which have helped our understanding of the reasons why individuals differ in the way they handle drugs, and ultimately in the way they respond to drugs, either in terms of efficacy or toxicity. However, not much of this knowledge has been translated into clinical practice, most drug-gene associations that have some evidence of clinical validity have not progressed to clinical settings. Advances in genomics since 2000, including the ready availability of data on the variability of the human genome, have provided us with unprecedented opportunities to understand variability in drug responses, and the opportunity to incorporate this into patient care. This is only likely to occur with a systematic approach that evaluates and overcomes the different translational gaps in taking a biomarker from discovery to clinical practice. In this article, I explore the history of pharmacogenetics, appraise the current state of research in this area, and finish off with suggestions for progressing in the field in the future.

Signal transduction by mitochondrial oxidants

The production of mitochondrial reactive oxygen species occurs as a consequence of aerobic metabolism. Mitochondrial oxidants are increasingly viewed less as byproducts of metabolism and more as important signaling molecules. Here, I review several notable examples, including the cellular response to hypoxia, aspects of innate immunity, the regulation of autophagy, and stem cell self-renewal capacity, where evidence suggests an important regulatory role for mitochondrial oxidants.

AMP-activated protein kinase: also regulated by ADP?

AMPK is a ubiquitous sensor of cellular energy status in eukaryotic cells. It is activated by stresses causing ATP depletion and, once activated, maintains energy homeostasis by phosphorylating targets that activate catabolism and inhibit energy-consuming processes. Evidence derived from non-mammalian orthologs suggests that its ancestral role was in the response to starvation for a carbon source. We review recent findings showing that AMPK is activated by ADP as well as AMP, and discuss the mechanism by which binding of these nucleotides prevent its dephosphorylation and inactivation. We also discuss the role of the carbohydrate-binding module on the β subunit and the mechanisms by which it is activated by drugs and xenobiotics such as metformin and resveratrol.

The BATTLE to personalize lung cancer prevention through reverse migration

Agents can enter clinical development for cancer prevention either initially or after previous development for a different indication, such as arthritis, with both approaches consuming many years of development before an agent is fully evaluated for cancer prevention. We propose the following, third approach: reverse migration, that is, importing agents, targets, and study designs to personalize interventions and concepts developed in advanced cancer to the setting of cancer prevention. Importing these "ready-made" features from therapy will allow reverse migration to streamline preventive agent development. We recently reported the Biomarker-integrated Approaches of Targeted Therapy for Lung Cancer Elimination (BATTLE) trial of personalized lung cancer therapy and now propose the reverse migration development of personalized lung cancer prevention based on the BATTLE model.

Type 2 diabetes and obesity: genomics and the clinic

Type 2 diabetes (T2D) and obesity represent major challenges for global public health. They are at the forefront of international efforts to identify the genetic variation contributing to complex disease susceptibility, and recent years have seen considerable success in identifying common risk-variants. Given the clinical impact of molecular diagnostics in rarer monogenic forms of these diseases, expectations have been high that genetic discoveries will transform the prospects for risk stratification, development of novel therapeutics and personalised medicine. However, so far, clinical translation has been limited. Difficulties in defining the alleles and transcripts mediating association effects have frustrated efforts to gain early biological insights, whilst the fact that variants identified account for only a modest proportion of observed familiarity has limited their value in guiding treatment of individual patients. Ongoing efforts to track causal variants through fine-mapping and to illuminate the biological mechanisms through which they act, as well as sequence-based discovery of lower-frequency alleles (of potentially larger effect), should provide welcome acceleration in the capacity for clinical translation. This review will summarise recent advances in identifying risk alleles for T2D and obesity, and existing contributions to understanding disease pathology. It will consider the progress made in translating genetic knowledge into clinical utility, the challenges remaining, and the realistic potential for further progress.

Genetics of type 2 diabetes: the GWAS era and future perspectives [Review]

Genome-wide association studies (GWAS) have facilitated a substantial and rapid rise in the number of confirmed genetic susceptibility variants for type 2 diabetes (T2D). Approximately 40 variants have been identified so far, many of which were discovered through GWAS. This success has led to widespread hope that the findings will translate into improved clinical care for the increasing numbers of patients with diabetes. Potential areas or clinical translation include risk prediction and subsequent disease prevention, pharmacogenetics, and the development of novel therapeutics. However, the genetic loci so far identified account for only a small fraction (approximately 10%) of the overall heritable risk for T2D. Uncovering the missing heritability is essential to the progress of T2D genetic studies and to the translation of genetic information into clinical practice.