Effects of SLC22A1 Polymorphisms on Metformin-Induced Reductions in Adiposity and Metformin Pharmacokinetics in Obese Children With Insulin Resistance

Precision medicine to identify, prevent, and treat pediatric obesity

Pediatric obesity is a growing health concern that has many secondary adverse health implications. Personalized medicine is a tool that can be used to optimize diagnosis and treatments of many diseases. In this review, we will focus on three areas related to the genetics of pediatric obesity: (i) genetic causes predisposing to pediatric obesity, (ii) pharmacogenomics that may predict weight gain associated with pharmacotherapy, and (iii) pharmacogenomics of anti-obesity pharmacotherapy. This narrative review evaluates genetic cause of pediatric obesity and how genetic findings can be used to optimize pharmacotherapy to minimize weight gain and optimize obesity treatment in pediatric patients. Pediatric obesity has many genetic causes including genomic obesity syndromes and monogenic obesity disorders. Several genetic etiologies of obesity have current or emerging targeted genetic therapies. Pharmacogenomic (PGx) targets associated with pharmacotherapy-induced weight gain have been identified for antipsychotic, antiepileptic, antidepressant therapies, and steroids, yet to date no clinical guidelines exist for application use of PGx to tailor pharmacotherapy to avoid weight gain. As legislation evolves for genetic testing coverage and technology advances, this will decrease cost and expand access to genetic testing. This will result in identification of potential genetic causes of obesity and genes that predispose to pharmacotherapy-induced weight gain. Advances in precision medicine can ultimately lead to development of clinical practice guidelines on how to apply genetic findings to optimize pharmacotherapy to treat genetic targets of obesity and avoid weight gain as an adverse event associated with pharmacotherapy.

The Impact of Paediatric Obesity on Drug Pharmacokinetics: A Virtual Clinical Trials Case Study with Amlodipine

The incidence of paediatric obesity continues to rise worldwide and contributes to a range of diseases including cardiovascular disease. Obesity in children has been shown to impact upon the plasma concentrations of various compounds, including amlodipine. Nonetheless, information on the influence of obesity on amlodipine pharmacokinetics and the need for dose adjustment has not been studied previously. This study applied the physiologically based pharmacokinetic modelling and established a paediatric obesity population to assess the impact of obesity on amlodipine pharmacokinetics in children and explore the possible dose adjustments required to reach the same plasma concentration as non-obese paediatrics. The difference in predicted maximum concentration (Cmax) and area under the curve (AUC) were significant between children with and without obesity across the age group 2 to 18 years old when a fixed-dose regimen was used. On the contrary, a weight-based dose regimen showed no difference in Cmax between obese and non-obese from 2 to 9 years old. Thus, when a fixed-dose regimen is to be administered, a 1.25- to 1.5-fold increase in dose is required in obese children to achieve the same Cmax concentration as non-obese children, specifically for children aged 5 years and above.

Precision medicine of obesity as an integral part of type 2 diabetes management - past, present, and future

Obesity is a complex and heterogeneous condition that leads to various metabolic complications, including type 2 diabetes. Unfortunately, for some, treatment options to date for obesity are insufficient, with many people not reaching sustained weight loss or having improvements in metabolic health. In this Review, we discuss advances in the genetics of obesity from the past decade-with emphasis on developments from the past 5 years-with a focus on metabolic consequences, and their potential implications for precision management of the disease. We also provide an overview of the potential role of genetics in guiding weight loss strategies. Finally, we propose a vision for the future of precision obesity management that includes developing an obesity-centred multidisease management algorithm that targets both obesity and its comorbidities. However, further collaborative efforts and research are necessary to fully realise its potential and improve metabolic health outcomes.

Assessment of the nlmixr R package for population pharmacokinetic modeling: A metformin case study

AIM

nlmixr offers first-order conditional estimation (FOCE), FOCE with interaction (FOCEi) and stochastic approximation estimation-maximisation (SAEM) to fit nonlinear mixed-effect models (NLMEM). We modelled metformin's pharmacokinetic data using nlmixr and investigated SAEM and FOCEi's performance with respect to bias and precision of parameter estimates, and robustness to initial estimates.

METHOD

Compartmental models were fitted. The final model was determined based on the objective function value and inspection of goodness-of-fit plots. The bias and precision of parameter estimates were compared between SAEM and FOCEi using stochastic simulations and estimations. For robustness, parameters were re-estimated as the initial estimates were perturbed 100 times and resultant changes evaluated.

RESULTS

The absorption kinetics of metformin depend significantly on food status. Under the fasted state, the first-order absorption into the central compartment was preceded by zero-order infusion into the depot compartment, whereas for the fed state, the absorption into the depot was instantaneous followed by first-order absorption from depot into the central compartment. The means of relative mean estimation error (rMEE) ( ME E SAEM ME E FOCEi ) and rRMSE ( RMS E SAEM RMS E FOCEi ) were 0.48 and 0.35, respectively. All parameter estimates given by SAEM appeared to be narrowly distributed and were close to the true value used for simulation. In contrast, the distribution of estimates from FOCEi were skewed and more biased. When initial estimates were perturbed, FOCEi estimates were more biased and imprecise.

DISCUSSION

nlmixr is reliable for NLMEM. SAEM was superior to FOCEi in terms of bias and precision, and more robust against initial estimate perturbations.

Research Progress of Population Pharmacokinetic of Metformin

Metformin is commonly used as first-line treatment for T2DM (type2 diabetes mellitus). Owing to the high pharmacokinetic (PK) variability, several population pharmacokinetic (PPK) models have been developed for metformin to explore potential covariates that affect its pharmacokinetic variation. This comprehensive review summarized the published PPK studies of metformin, aimed to summarize PPK models of metformin. Most studies described metformin pharmacokinetics as a 2-compartment (2-CMT) model with 4 study describing its pharmacokinetics as 1-compartment (1-CMT). Studies on metformin PPK have shown that obesity, creatinine clearance (CL_Cr), gene polymorphism, degree of renal function damage, and pathological conditions all have a certain impact on the PK parameters of metformin. It is particularly important to formulate individualized dosing regimens. For future PPK studies of metformin, we believe that more attention should be paid to special populations.

Physiologically Based Pharmacokinetic Modeling of Metformin in Children and Adolescents with Obesity

Childhood obesity continues to rise in the United States, and with it the off-label use of metformin for weight loss. The influence of age and obesity on the drug's disposition and exposure has not previously been studied using a mechanistic framework. Here, an adult physiologically based pharmacokinetic (PBPK) model of metformin was scaled to pediatric populations without obesity, with overweight / obesity, and with severe obesity; a published virtual population of children and adolescents with obesity was leveraged during model evaluation. When the pediatric model was simulated in groups 10 - 18 y of age, oral clearance (CL/F) following 1,000 mg of metformin was higher (∼1200 mL/min) in those with obesity and severe obesity compared to the groups without and with overweight (∼1000 mL/min). In addition, simulated AUC in older children and adolescents with obesity and severe obesity was comparable to that in adults with a similar dose-exposure relationship. Overall, simulations using the pediatric PBPK model support the use of adult doses of metformin in older children and adolescents with obesity. Moreover, the virtual population of children and adolescents with obesity offers a valuable tool to facilitate development of pediatric PBPK models for studying populations with obesity and, in turn, contribute information to inform drug labeling in this special population. This article is protected by copyright. All rights reserved.

Pharmacogenomics of Medication-Induced Weight Gain and Antiobesity Medications

Obesity is a chronic, multifactorial disease associated with a large number of comorbidities. The clinical management of obesity involves a stepwise integrated approach, beginning with behavioral and lifestyle modification, followed by antiobesity medications, endobariatric procedures, and bariatric surgery. Weight gain and subsequent obesity are common side effects of medications, such as prednisone or antipsychotics. In this era of precision medicine, it is essential to identify patients at the highest risk of weight gain as a result of medication use. Pharmacogenomics could play an important role in obesity management by optimizing use of antiobesity medications as well as minimizing adverse weight gain. This review aims to provide a comprehensive analysis of the current literature on the role of pharmacogenomics in obesity and medication-induced weight gain. In summary, there are more robust studies of medication associated with weight gain and pharmacogenomics, and more studies are needed to understand the role of pharmacogenomics in antiobesity medications.

Dosing Common Medications in Hospitalized Pediatric Patients with Obesity: A Review

Medication management in children and adolescents with obesity is challenging because both developmental and pathophysiological changes may impact drug disposition and response. Evidence to date indicates an effect of obesity on drug disposition for certain drugs used in this population. This work identified published studies evaluating drug dosing, pharmacokinetics (PK), and effect in pediatric patients with obesity, focusing on 70 common medications used in a pediatric network of 42 US medical centers. A PubMed search revealed 33 studies providing PK and/or effectiveness data for 23% (16 of 70) of medications, 44% of which have just one study and can be considered exploratory. This work appraising 4 decades of literature shows several promising approaches: greater use of PK models applied to prospective clinical studies, dosing recommendations derived from both PK and safety, and multiyear effectiveness data on drugs for chronic conditions (e.g., asthma). Most studies make dose recommendations but are weakened by retrospective study design, small study populations, and no controls or historic controls. Dosing decisions continue to rely on extrapolating knowledge, including targeting systemic drug exposure typically achieved in adults. Optimal weight-based dosing strategies vary by drug and warrant prospective, controlled studies incorporating PK and modeling and simulation to complement clinical assessment.

Cell free DNA biology and its involvement in breast carcinogenesis

Liquid biopsy represents a procedure for minimally invasive analysis of non-solid tissue, blood and other body fluids. It comprises a set of analytes that includes circulating tumor cells (CTCs) and circulating free DNA (cfDNA), RNA, long noncoding RNA (lncRNA) and micro RNA (miRNA), as well as extracellular vesicles. These novel analytes represent an alternative tool to complement diagnosis and monitor and predict response to treatment of the tumoral process and may be used for other disease processes such viral and parasitic infection. This review focuses on the biologic and molecular characteristics of cfDNA in general and the molecular changes (mutational and epigenetic) proven useful in oncologic practice for diagnosis, monitoring and treatment of breast cancer specifically.

Drug Dose Selection in Pediatric Obesity: Available Information for the Most Commonly Prescribed Drugs to Children

Obesity rates continue to rise in children, and little guidance exists regarding the need for adjustment away from total body weight-based doses for those prescribing drugs to this population of children. A majority of drugs prescribed to children with obesity result in either sub-therapeutic or supra-therapeutic concentrations, placing these children at risk for treatment failure and drug toxicities. In this review, we highlight available obesity-specific pharmacokinetic and dosing information for the most frequently prescribed drugs to children in the inpatient and outpatient clinical settings. We also comment on available dosing recommendations for drugs prescribed to treat common pediatric obesity-related comorbidities. This review highlights that there is no safe or proven 'rule of thumb,' for dosing drugs for children with obesity, and a striking lack of pharmacokinetic data to support the creation of dosing guidelines for children with obesity for the most commonly prescribed drugs. It is important that those prescribing for children with obesity are aware of these gaps in knowledge and of potential drug treatment failure or adverse events related to drug toxicity as a result of these knowledge gaps. Until more data are available, we recommend close monitoring of drug response and adverse events in children with obesity receiving commonly prescribed drugs.

Common Variants in 22 Genes Regulate Response to Metformin Intervention in Children with Obesity: A Pharmacogenetic Study of a Randomized Controlled Trial

Metformin is a first-line oral antidiabetic agent that has shown additional effects in treating obesity and metabolic syndrome. Inter-individual variability in metformin response could be partially explained by the genetic component. Here, we aimed to test whether common genetic variants can predict the response to metformin intervention in obese children. The study was a multicenter and double-blind randomized controlled trial that was stratified according to sex and pubertal status in 160 children with obesity. Children were randomly assigned to receive either metformin (1g/d) or placebo for six months after meeting the defined inclusion criteria. We conducted a post hoc genotyping study in 124 individuals (59 placebo, 65 treated) comprising finally 231 genetic variants in candidate genes. We provide evidence for 28 common variants as promising pharmacogenetics regulators of metformin response in terms of a wide range of anthropometric and biochemical outcomes, including body mass index (BMI) Z-score, and glucose, lipid, and inflammatory traits. Although no association remained statistically significant after multiple-test correction, our findings support previously reported variants in metformin transporters or targets as well as identify novel and promising loci, such as the ADYC3 and the BDNF genes, with plausible biological relation to the metformin's action mechanism. Trial Registration: Registered on the European Clinical Trials Database (EudraCT, ID: 2010-023061-21) on 14 November 2011 (URL: https://www.clinicaltrialsregister.eu/ctr-search/trial/2010-023061-21/ES).

Clinical and genetic predictors of diabetes drug's response

Diabetes is a major health problem worldwide. Glycemic control is the main goal in the management of type 2 diabetes. While many anti-diabetic drugs and guidelines are available, almost half of diabetic patients do not reach their treatment goal and develop complications. The glucose-lowering response to anti-diabetic drug differs significantly between individuals. Relatively little is known about the factors that might underlie this response. The identification of predictors of response to anti-diabetic drugs is essential for treatment personalization. Unfortunately, the evidence on predictors of drugs response in type 2 diabetes is scarce. Only a few trials were designed for specific groups of patients (e.g. patients with renal impairment or older patients), while subgroup analyses of larger trials are frequently unreported. Physicians need help in picking the drug which provides the maximal benefit, with minimal side effects, in the right dose, for a specific patient, using an omics-based approach besides the phenotypic characteristics.

Time-dependent therapeutic roles of nitazoxanide on high-fat diet/streptozotocin-induced diabetes in rats: effects on hepatic peroxisome proliferator-activated receptor-gamma receptors

Targeting peroxisome proliferator-activated receptor-gamma (PPAR-γ) is an approved strategy in facing insulin resistance (IR) for diabetes mellitus (DM) type 2. The PPAR-γ modulators display improvements in the insulin-sensitizing and adverse effects of the traditional thiazolidinediones. Nitazoxanide (NTZ) is proposed as a PPAR-γ receptor ligand with agonistic post-transcriptional effects. Currently, NTZ antidiabetic activities versus pioglitazone (PIO) in a high-fat diet/streptozotocin rat model of type 2 diabetes was explored. Diabetic adult male Wistar rats were treated orally with either PIO (2.7 mg·kg^-1·day^-1) or NTZ (200 mg·kg^-1·day^-1) for 14, 21, and 28 days. Body masses, fasting blood glucose, IR, lipid profiles, and liver and kidney functions of rats were assayed. Hepatic glucose metabolism and PPAR-γ protein expression levels as well as hepatic, pancreatic, muscular, and renal histopathology were evaluated. Significant time-dependent euglycemic and insulin-sensitizing effects with preservation of liver and kidney functions were offered by NTZ. Higher hepatic levels of glucose-6-phosphatase and glucose-6-phosphate dehydrogenase enzymes and PPAR-γ protein expressions were acquired by NTZ and PIO, respectively. NTZ could be considered an oral therapeutic strategy for DM type 2. Further systematic NTZ/PPAR-γ receptor subtype molecular activations are recommended. Simultaneous use of NTZ with other approved antidiabetics should be explored.