Clinical Utility and Economic Impact of CYP2D6 Genotyping

Genophenotypic Factors and Pharmacogenomics in Adverse Drug Reactions

Adverse drug reactions (ADRs) rank as one of the top 10 leading causes of death and illness in developed countries. ADRs show differential features depending upon genotype, age, sex, race, pathology, drug category, route of administration, and drug–drug interactions. Pharmacogenomics (PGx) provides the physician effective clues for optimizing drug efficacy and safety in major problems of health such as cardiovascular disease and associated disorders, cancer and brain disorders. Important aspects to be considered are also the impact of immunopharmacogenomics in cutaneous ADRs as well as the influence of genomic factors associated with COVID-19 and vaccination strategies. Major limitations for the routine use of PGx procedures for ADRs prevention are the lack of education and training in physicians and pharmacists, poor characterization of drug-related PGx, unspecific biomarkers of drug efficacy and toxicity, cost-effectiveness, administrative problems in health organizations, and insufficient regulation for the generalized use of PGx in the clinical setting. The implementation of PGx requires: (i) education of physicians and all other parties involved in the use and benefits of PGx; (ii) prospective studies to demonstrate the benefits of PGx genotyping; (iii) standardization of PGx procedures and development of clinical guidelines; (iv) NGS and microarrays to cover genes with high PGx potential; and (v) new regulations for PGx-related drug development and PGx drug labelling.

Clinical Relevance of CYP2D6 Polymorphisms in Patients of an Austrian Medical Practice: A Family Practice-Based Observational Study

BACKGROUND

Around 20-30% of all prescribed drugs are estimated to be metabolised by the cytochrome P450 (CYP) 2D6 enzyme. In a medical practice, it is usually not known whether a patient is a poor, intermediate, normal or ultra-rapid metaboliser for CYP2D6-metabolised drugs.

OBJECTIVE

This study aims to explore the clinical relevance and the extent of hazardous prescriptions by analysing the metaboliser status of patients already taking such drugs.

METHODS

This is a family practice-based observational study performed in a rural practice for general and family medicine in Lower Austria providing care for approximately 2100 patients annually. In 287 consecutive patients, who had taken or were taking a drug metabolised by CYP2D6 during the last 3 years, the metaboliser status was analysed.

RESULTS

The genetic analysis of 287 patients resulted in 51.22% normal metabolisers, 38.68% intermediate metabolisers, 6.27% poor metabolisers and 3.83% ultra-rapid metabolisers. In 50 cases (poor metaboliser, intermediate metaboliser and ultra-rapid metaboliser, i.e. 17.42% of all tested patients taking a CYP2D6-specific drug), an altered gene function was identified, for which clinical guideline annotations, drug label annotations, or clinical annotations are available. Allele and genotype frequencies were in accordance with data from other European studies.

CONCLUSIONS

In 17.42% of all patients already taking a drug metabolised by CYP2D6, knowledge of the genetically defined metaboliser status would have been of immediate clinical relevance before prescribing the drug. CLINICALTRIALS.

GOV IDENTIFIER

NCT03859622.

A systematic meta-review of predictors of antidepressant treatment outcome in major depressive disorder

INTRODUCTION

The heterogeneity of symptoms and complex etiology of depression pose a significant challenge to the personalization of treatment. Meanwhile, the current application of generic treatment approaches to patients with vastly differing biological and clinical profiles is far from optimal. Here, we conduct a meta-review to identify predictors of response to antidepressant therapy in order to select robust input features for machine learning models of treatment response. These machine learning models will allow us to learn associations between patient features and treatment response which have predictive value at the individual patient level; this learning can be optimized by selecting high-quality input features for the model. While current research is difficult to directly apply to the clinic, machine learning models built using knowledge gleaned from current research may become useful clinical tools.

METHODS

The EMBASE and MEDLINE/PubMed online databases were searched from January 1996 to August 2017, using a combination of MeSH terms and keywords to identify relevant literature reviews. We identified a total of 1909 articles, wherein 199 articles met our inclusion criteria.

RESULTS

An array of genetic, immune, endocrine, neuroimaging, sociodemographic, and symptom-based predictors of treatment response were extracted, varying widely in clinical utility.

LIMITATIONS

Due to heterogeneous sample sizes, effect sizes, publication biases, and methodological disparities across reviews, we could not accurately assess the strength and directionality of every predictor.

CONCLUSION

Notwithstanding our cautious interpretation of the results, we have identified a multitude of predictors that can be used to formulate a priori hypotheses regarding the input features for a computational model. We highlight the importance of large-scale research initiatives and clinically accessible biomarkers, as well as the need for replication studies of current findings. In addition, we provide recommendations for future improvement and standardization of research efforts in this field.

Abundance of Cytochromes in Hepatic Extracellular Vesicles Is Altered by Drugs Related With Drug-Induced Liver Injury

Drug‐induced liver injury (DILI) is a serious worldwide health problem that accounts for more than 50% of acute liver failure. There is a great interest in clinical diagnosis and pharmaceutical industry to elucidate underlying molecular mechanisms and find noninvasive biomarkers for this pathology. Cell‐secreted extracellular vesicles (EVs) have provided a new biological source to identify low disease invasive markers. Despite the intense research developed on these vesicles, there is currently a gap on their patho‐physiological effects. Here, we study EVs secreted by primary rat hepatocytes challenged with galactatosamine (GalN), acetaminophen, or diclofenac as DILI in vitromodels. Proteomics analysis of these EVs revealed an increase in enzymes already associated with liver damage, such as catecholamine‐methyl transferase and arginase 1. An increase in translation‐related proteins and a decrease in regulators of apoptosis were also observed. In addition, we show the presence of enzymatic activity of P450 cytochrome 2d1 in EVs. The activity specifically is decreased in EVs secreted by hepatocytes after acetaminophen treatment and increased in EVs derived from GalN‐treated hepatocytes. By using in vivo preclinical models, we demonstrate the presence of this cytochrome activity in circulation under normal conditions and an increased activity after GalN‐induced injury. Conclusion: Hepatocyte‐secreted EVs carry active xenobiotic‐metabolizing enzymes that might be relevant in extracellular metabolism of drugs and be associated with DILI. (Hepatology Communications 2018;0:00‐00)

The Role of Genetic Polymorphisms in Chronic Pain Patients

It is estimated that the total annual financial cost for pain management in the U.S. exceeds 100 billion dollars. However, when indirect costs are included, such as functional disability and reduction in working hours, the cost can reach more than 300 billion dollars. In chronic pain patients, the role of pharmacogenetics is determined by genetic effects on various pain types, as well as the genetic effect on drug safety and efficacy. In this review article, we discuss genetic polymorphisms present in different types of chronic pain, such as fibromyalgia, low back pain, migraine, painful peripheral diabetic neuropathy and trigeminal neuralgia. Furthermore, we discuss the role of CYP450 enzymes involved in metabolism of drugs, which have been used for treatment of chronic pain (amitriptyline, duloxetine, opioids, etc.). We also discuss how pharmacogenetics can be applied towards improving drug efficacy, shortening the time required to achieve therapeutic outcomes, reducing risks of side effects, and reducing medical costs and reliance upon polypharmacy.

Association between cytochrome P450 2D6 polymorphisms and body fluid methamphetamine concentrations in Japanese forensic autopsy cases

Methamphetamine (MA) is an illicit stimulant that affects the central nervous system. Cytochrome P450 2D6 (CYP2D6) plays an important role in MA metabolism. Numerous allelic variants confer substantial variation in CYP2D6 activity among individuals. In the present study, we examined the frequencies of CYP2D6 alleles, including CYP2D6*1, *2, *4, *5, *10, *14A, *14B, *18, and *36, and multiplication, in 82 forensic autopsy cases of MA abusers and 567 autopsy cases in which MA was not detected (controls). Ultrarapid metabolizer (UM), extensive metabolizer (EM), intermediate metabolizer (IM), and poor metabolizer (PM) phenotypes were predicted from CYP2D6 genotypes. Of MA abusers, 64 subjects were predicted to be EM, 17 were IM, and 1 was UM. No MA abuser had the predicted PM phenotype. No significant differences in CYP2D6 phenotype frequencies were found between MA abusers and controls. MA and amphetamine (AMP) concentrations were measured in the right heart blood, left heart blood, peripheral external iliac blood, urine, pericardial fluid, and bone marrow of MA abusers. MA concentrations in urine and bone marrow were significantly higher in IM than in EM. AMP concentration was not associated with CYP2D6 phenotype in any body fluid. These results suggest that the MA concentration in body fluids is influenced by CYP2D6 phenotypes in the Japanese population.

Pharmacogenetics: a general review on progress to date

BACKGROUND

Pharmacogenetics is not a new subject area but its relevance to drug prescribing has become clearer in recent years due to developments in gene cloning and DNA genotyping and sequencing.

SOURCES OF DATA

There is a very extensive published literature concerned with a variety of different genes and drugs.

AREAS OF AGREEMENT

There is general agreement that pharmacogenetic testing is essential for the safe use of drugs such as the thiopurines and abacavir.

AREAS OF CONTROVERSY

Whether pharmacogenetic testing should be applied more widely including to the prescription of certain drugs such as warfarin and clopidogrel where the overall benefit is less clear remains controversial.

GROWING POINTS

Personal genotype information is increasingly being made available directly to the consumer. This is likely to increase demand for personalized prescription and mean that prescribers need to take pharmacogenetic information into account. Projects such as 100 000 genomes are providing complete genome sequences that can form part of a patient medical record. This information will be of great value in personalized prescribing.

AREAS TIMELY FOR DEVELOPING RESEARCH

Development of new drugs targeting particular genetic risk factors for disease. These could be prescribed to those with an at risk genotype.

Avoidable drug-gene conflicts and polypharmacy interactions in patients participating in a personalized medicine program

AIM

Determine the ability of a pharmacogenetic service, PRIMER, to identify drug-gene (DGI) and drug-drug interactions (DDI) in patients across multiple conditions. PRIMER consists of patient selection criteria, a gene panel and actionable guidance for DGIs and DDIs.

RESULTS

The average patient was prescribed 12 medications. PRIMER identified significant DGIs in 73% of patients tested, with 43% having more than one DGI. DDIs were found in 87% of patients. The most common actionable DGIs were for opioid, psychotropic and cardiovascular medications.

CONCLUSION

The pairing of patient selection criteria, a multigene panel with evidence-based interpretation and review of DDIs maximizes the patients tested who have actionable benefit and alerts physicians to potentially critical adjustments needed for the patient's medication regimen.