Deciphering single-cell gene expression variability and its role in drug response

The effectiveness of drug treatments is profoundly influenced by individual responses, which are shaped by gene expression variability, particularly within pharmacogenes. Leveraging single-cell RNA sequencing (scRNA-seq) data, our study explores the extent of expression variability among pharmacogenes in a wide array of cell types across eight different human tissues, shedding light on their impact on drug responses. Our findings broaden the established link between variability in pharmacogene expression and drug efficacy to encompass variability at the cellular level. Moreover, we unveil a promising approach to enhance drug efficacy prediction. This is achieved by leveraging a combination of cross-cell and cross-individual pharmacogene expression variation measurements. Our study opens avenues for more precise forecasting of drug performance, facilitating tailored and more effective treatments in the future.

DNA Profiling in Human Identification: From Past to Present

Forensic DNA typing has been widely accepted in the courts all over the world. This is because DNA profiling is a very powerful tool to identify individuals on the basis of their unique genetic makeup. DNA evidence is capable of not only identifying the presence of specific biospecimens in a crime scene, but it is also used to exonerate suspects who are innocent of a crime. Technological advancements in DNA profiling, including the development of validated kits and statistical methods have made this tool to be more precise in forensic investigations. Therefore, validated combined DNA index system (CODIS) short tandem repeats (STRs) kits which require very small amount of DNA, coupled with real-time polymerase chain reaction (PCR) and the statistical strengths are used routinely to identify human remains, establish paternity or to match suspected crime scene biospecimens. The road to modern DNA profiling has been long, and it has taken scientists decades of work and fine tuning to develop highly accurate testing and analyses that are used today. This review will discuss the various DNA polymorphisms and their utility in human identity testing.

PSnpBind-ML: predicting the effect of binding site mutations on protein-ligand binding affinity

Protein mutations, especially those which occur in the binding site, play an important role in inter-individual drug response and may alter binding affinity and thus impact the drug's efficacy and side effects. Unfortunately, large-scale experimental screening of ligand-binding against protein variants is still time-consuming and expensive. Alternatively, in silico approaches can play a role in guiding those experiments. Methods ranging from computationally cheaper machine learning (ML) to the more expensive molecular dynamics have been applied to accurately predict the mutation effects. However, these effects have been mostly studied on limited and small datasets, while ideally a large dataset of binding affinity changes due to binding site mutations is needed. In this work, we used the PSnpBind database with six hundred thousand docking experiments to train a machine learning model predicting protein-ligand binding affinity for both wild-type proteins and their variants with a single-point mutation in the binding site. A numerical representation of the protein, binding site, mutation, and ligand information was encoded using 256 features, half of them were manually selected based on domain knowledge. A machine learning approach composed of two regression models is proposed, the first predicting wild-type protein-ligand binding affinity while the second predicting the mutated protein-ligand binding affinity. The best performing models reported an RMSE value within 0.5 [Formula: see text] 0.6 kcal/mol^-1 on an independent test set with an R² value of 0.87 [Formula: see text] 0.90. We report an improvement in the prediction performance compared to several reported models developed for protein-ligand binding affinity prediction. The obtained models can be used as a complementary method in early-stage drug discovery. They can be applied to rapidly obtain a better overview of the ligand binding affinity changes across protein variants carried by people in the population and narrow down the search space where more time-demanding methods can be used to identify potential leads that achieve a better affinity for all protein variants.

Population Pharmacokinetics, Exposure-Safety, and Probability of Target Attainment Analyses for Isavuconazole in Japanese Patients With Deep-Seated Mycoses

Isavuconazonium sulfate is the water-soluble prodrug of the novel, broad-spectrum, triazole antifungal agent isavuconazole. Its pharmacokinetics (PK) and exposure-response relationship have been well investigated, but not in a Japanese patient population. The objectives of this analysis were to (1) develop a population PK model for Japanese patients with deep-seated mycoses and healthy subjects, and to identify significant covariates; (2) determine the probability of PK-pharmacodynamic (PK-PD) target attainment in Japanese patients by a clinical dosing regimen; and (3) evaluate the exposure-safety relationship of isavuconazole in Japanese patients. Data from 2 phase 1 studies and 1 phase 3 study in Japanese patients were pooled to develop the population PK model using NONMEM. The PK of isavuconazole in Japanese patients was best described as a 2-compartment model with a Weibull absorption function and first-order elimination. The identified covariates on clearance were creatinine clearance and lean body mass. The probability of target attainment showed that >90% of simulated Japanese patients would achieve the PK-PD target, an exposure index corresponding to 50% survival of nonneutropenic infected mice, with minimal inhibitory concentration values of ≤1 mg/L according to Clinical and Laboratory Standards Institute methodology and of ≤2 mg/L according to European Committee on Antimicrobial Susceptibility Testing methodology by the clinical dosing regimen. No apparent relationships were found for any of the exposure parameters of isavuconazole with any assessed safety end points in Japanese patients. Taken together, the clinical dosing regimen is appropriate for the treatment of Japanese patients with deep-seated mycoses.

A p53 transcriptional signature in primary and metastatic cancers derived using machine learning

The tumor suppressor gene, TP53, has the highest rate of mutation among all genes in human cancer. This transcription factor plays an essential role in the regulation of many cellular processes. Mutations in TP53 result in loss of wild-type p53 function in a dominant negative manner. Although TP53 is a well-studied gene, the transcriptome modifications caused by the mutations in this gene have not yet been explored in a pan-cancer study using both primary and metastatic samples. In this work, we used a random forest model to stratify tumor samples based on TP53 mutational status and detected a p53 transcriptional signature. We hypothesize that the existence of this transcriptional signature is due to the loss of wild-type p53 function and is universal across primary and metastatic tumors as well as different tumor types. Additionally, we showed that the algorithm successfully detected this signature in samples with apparent silent mutations that affect correct mRNA splicing. Furthermore, we observed that most of the highly ranked genes contributing to the classification extracted from the random forest have known associations with p53 within the literature. We suggest that other genes found in this list including GPSM2, OR4N2, CTSL2, SPERT, and RPE65 protein coding genes have yet undiscovered linkages to p53 function. Our analysis of time on different therapies also revealed that this signature is more effective than the recorded TP53 status in detecting patients who can benefit from platinum therapies and taxanes. Our findings delineate a p53 transcriptional signature, expand the knowledge of p53 biology and further identify genes important in p53 related pathways.

PSnpBind: a database of mutated binding site protein-ligand complexes constructed using a multithreaded virtual screening workflow

A key concept in drug design is how natural variants, especially the ones occurring in the binding site of drug targets, affect the inter-individual drug response and efficacy by altering binding affinity. These effects have been studied on very limited and small datasets while, ideally, a large dataset of binding affinity changes due to binding site single-nucleotide polymorphisms (SNPs) is needed for evaluation. However, to the best of our knowledge, such a dataset does not exist. Thus, a reference dataset of ligands binding affinities to proteins with all their reported binding sites' variants was constructed using a molecular docking approach. Having a large database of protein-ligand complexes covering a wide range of binding pocket mutations and a large small molecules' landscape is of great importance for several types of studies. For example, developing machine learning algorithms to predict protein-ligand affinity or a SNP effect on it requires an extensive amount of data. In this work, we present PSnpBind: A large database of 0.6 million mutated binding site protein-ligand complexes constructed using a multithreaded virtual screening workflow. It provides a web interface to explore and visualize the protein-ligand complexes and a REST API to programmatically access the different aspects of the database contents. PSnpBind is open source and freely available at https://psnpbind.org .

Pharmacokinetics, Safety, and Tolerability of Single and Multiple Doses of Isavuconazonium Sulfate in Healthy Adult Japanese Subjects

Isavuconazonium sulfate is the water‐soluble prodrug of the novel, broad‐spectrum, triazole antifungal agent isavuconazole. This was a first‐in‐Japanese study assessing the pharmacokinetics, safety, and tolerability of isavuconazonium sulfate. The study was conducted in 2 parts: part 1 (single ascending dose; 100‐, 200‐, and 400‐mg equivalent of isavuconazole oral or intravenous administration); and part 2 (multiple doses for 16 days; 200‐mg equivalent of isavuconazole oral or intravenous administration; once‐daily administration with a loading regimen every 8 hours for the first 48 hours). A total of 60 and 16 subjects were randomized in part 1 and part 2, respectively. Observed clearance was lower in this study compared to what was previously reported in predominantly White populations and similar to clearance in non‐Japanese Asian populations. The range of the plasma isavuconazole concentration in this study was within the range of the pivotal phase 3 study, with no relationship between isavuconazole exposure and either efficacy or safety. There were no serious adverse events, and all reported treatment‐emergent adverse events were of mild intensity. This study confirmed that isavuconazonium sulfate was safe and well tolerated in healthy adult Japanese subjects.

Sources of Interindividual Variability

The efficacy, safety, and tolerability of drugs are dependent on numerous factors that influence their disposition. A dose that is efficacious and safe for one individual may result in sub-therapeutic or toxic blood concentrations in others. A significant source of this variability in drug response is drug metabolism, where differences in presystemic and systemic biotransformation efficiency result in variable degrees of systemic exposure (e.g., AUC, C_max, and/or C_min) following administration of a fixed dose.Interindividual differences in drug biotransformation have been studied extensively. It is recognized that both intrinsic factors (e.g., genetics, age, sex, and disease states) and extrinsic factors (e.g., diet , chemical exposures from the environment, and the microbiome) play a significant role. For drug-metabolizing enzymes, genetic variation can result in the complete absence or enhanced expression of a functional enzyme. In addition, upregulation and downregulation of gene expression, in response to an altered cellular environment, can achieve the same range of metabolic function (phenotype), but often in a less predictable and time-dependent manner. Understanding the mechanistic basis for variability in drug disposition and response is essential if we are to move beyond the era of empirical, trial-and-error dose selection and into an age of personalized medicine that will improve outcomes in maintaining health and treating disease.

Integration of pharmacogenomics and theranostics with nanotechnology as quality by design (QbD) approach for formulation development of novel dosage forms for effective drug therapy

To cater to medication needs in the future healthcare system, we need to shift from the conventional system of drug delivery to modern molecular signature-based drug delivery systems. The current drug therapies are either less effective, ineffective, or produce numerous adverse reactions. One scientific principle or discipline cannot adequately address all the problems, so we need an innovative application of the current scientific principles. Here we are proposing a novel concept of nanoformulation based on pharmacogenomics and theranostics for personalized error-free and targeted therapeutic agent delivery. The addition of more knowledge about the human genome opens the new way to study disease-gene, gene-drug, and drug-effect interactions, which is the basis of future medicines. Pharmacogenomics provides information about the disease etiology, role in genes in disease pathophysiology, disease biomarkers, drug targets, drug effects, and the fate of drugs inside the body. Theranostics approach utilizes the above information in diagnosis, treatment, and monitoring of the disease on a real-time basis. Personalized dosage forms can be formulated into a nanoformulation that provides a better therapeutic effect and minimizes adverse drug reactions. The therapeutic system needs to be shifted from the principle of one drug fits all to one drug unique population. In the present manuscript, we tried to conceptualize a modern therapeutic system by combining the three approaches viz. pharmacogenomics, theranostics, and nanotechnology applied in the area of formulation development to produce a multifunctional single tiny entity.

RS7435335 located in the UGT2B7 gene may be a possible genetic marker for the clinical response and prognosis of breast cancer patients receiving neoadjuvant chemotherapy

OBJECTIVE

To evaluate the predictive efficacy and prognostic value of rs7435335 located in the UGT2B7 gene as a genetic marker in breast cancer patients receiving neoadjuvant chemotherapy (NAC).

METHODS

A total of 190 patients with breast cancer treated with NAC were enrolled to detect the rs7435335 SNP by sequenom. Miller-Payne grades were used to evaluate the treatment efficacy. The association between rs7435335 and chemotherapy efficacy and prognosis was analyzed.

RESULTS

Altogether, 42 cases (22.1%) achieved pathologic complete response (pCR). The results of the univariate analysis showed that rs7435335 had no statistically significant difference with pCR and Miller-Payne grades (P > 0.05). When grouping was done in accordance with the ER status, the pCR and Miller-Payne grades significantly associated with rs7435335 ( P < 0.05) only in the ER-negative group. Multivariate logistic regression analysis suggested that rs7435335 in the ER-negative group was an independent predictor of pCR ( P < 0.05). Survival analysis showed that the disease-free survival (DFS) time in patients with GA genotype was longer than that of GG genotype, and rs7435335 predicted the DFS in the ER-negative group.

CONCLUSION

The UGT2B7 rs7435335 is associated with the NAC efficacy and prognosis. Patients with GA genotype have better efficacy and prognosis. Rs7435335 was found to be a possible gene marker for pCR and prognosis in ER-negative patients who received NAC.

Revolution of Alzheimer Precision Neurology. Passageway of Systems Biology and Neurophysiology

The Precision Neurology development process implements systems theory with system biology and neurophysiology in a parallel, bidirectional research path: a combined hypothesis-driven investigation of systems dysfunction within distinct molecular, cellular, and large-scale neural network systems in both animal models as well as through tests for the usefulness of these candidate dynamic systems biomarkers in different diseases and subgroups at different stages of pathophysiological progression. This translational research path is paralleled by an "omics"-based, hypothesis-free, exploratory research pathway, which will collect multimodal data from progressing asymptomatic, preclinical, and clinical neurodegenerative disease (ND) populations, within the wide continuous biological and clinical spectrum of ND, applying high-throughput and high-content technologies combined with powerful computational and statistical modeling tools, aimed at identifying novel dysfunctional systems and predictive marker signatures associated with ND. The goals are to identify common biological denominators or differentiating classifiers across the continuum of ND during detectable stages of pathophysiological progression, characterize systems-based intermediate endophenotypes, validate multi-modal novel diagnostic systems biomarkers, and advance clinical intervention trial designs by utilizing systems-based intermediate endophenotypes and candidate surrogate markers. Achieving these goals is key to the ultimate development of early and effective individualized treatment of ND, such as Alzheimer's disease. The Alzheimer Precision Medicine Initiative (APMI) and cohort program (APMI-CP), as well as the Paris based core of the Sorbonne University Clinical Research Group "Alzheimer Precision Medicine" (GRC-APM) were recently launched to facilitate the passageway from conventional clinical diagnostic and drug development toward breakthrough innovation based on the investigation of the comprehensive biological nature of aging individuals. The APMI movement is gaining momentum to systematically apply both systems neurophysiology and systems biology in exploratory translational neuroscience research on ND.

Pharmacogenetics: An Important Part of Drug Development with A Focus on Its Application

Since the human genome project in 2003, the view of personalized medicine to improve diagnosis and cure diseases at the molecular level became more real. Sequencing the human genome brought some benefits in medicine such as early detection of diseases with a genetic predisposition, treating patients with rare diseases, the design of gene therapy and the understanding of pharmacogenetics in the metabolism of drugs. This review explains the concepts of pharmacogenetics, polymorphisms, mutations, variations, and alleles, and how this information has helped us better understand the metabolism of drugs. Multiple resources are presented to promote reducing the gap between scientists, physicians, and patients in understanding the use and benefits of pharmacogenetics. Some of the most common clinical examples of genetic variants and how pharmacogenetics was used to determine treatment options for patients having these variants were discussed. Finally, we evaluated some of the challenges of implementing pharmacogenetics in a clinical setting and proposed actions to be taken to make pharmacogenetics a standard diagnostic tool in personalized medicine.

Defining baseline epigenetic landscapes in the rat liver

Aim

Characterization of the hepatic epigenome following exposure to chemicals and therapeutic drugs provides novel insights into toxicological and pharmacological mechanisms, however appreciation of genome-wide inter- and intra-strain baseline epigenetic variation, particularly in under-characterized species such as the rat is limited.

Material & methods

To enhance the utility of epigenomic endpoints safety assessment, we map both DNA modifications (5-methyl-cytosine and 5-hydroxymethyl-cytosine) and enhancer related chromatin marks (H3K4me1 and H3K27ac) across multiple male and female rat livers for two important outbred laboratory rat strains (Sprague–Dawley and Wistar).

Results & conclusion

Integration of DNA modification, enhancer chromatin marks and gene expression profiles reveals clear gender-specific chromatin states at genes which exhibit gender-specific transcription. Taken together this work provides a valuable baseline liver epigenome resource for rat strains that are commonly used in chemical and pharmaceutical safety assessment.

A Synopsis of the "Influence of Epigenetics, Genetics, and Immunology" Session Part A at the 35th Annual Society of Toxicologic Pathology Symposium

The overarching theme of the 2016 Society of Toxicology Pathology's Annual Symposium was "The Basis and Relevance of Variation in Toxicologic Responses." Session 4 focused on genetic variation as a potential source for variability in toxicologic responses within nonclinical toxicity studies and further explored how knowledge of genetic traits might enable targeted prospective and retrospective studies in drug development and human health risk assessment. In this session, the influence of both genetic sequence variation and epigenetic modifications on toxicologic responses and their implications for understanding risk were explored. In this overview, the presentations in this session will be summarized, with a goal of exploring the ramifications of genetic and epigenetic variability within and across species for toxicity studies and disseminating information regarding novel tools to harness this variability to advance understanding of toxicologic responses across populations.

Minimum information required for a DMET experiment reporting

AIM

To provide pharmacogenomics reporting guidelines, the information and tools required for reporting to public omic databases.

MATERIAL & METHODS

For effective DMET data interpretation, sharing, interoperability, reproducibility and reporting, we propose the Minimum Information required for a DMET Experiment (MIDE) reporting.

RESULTS

MIDE provides reporting guidelines and describes the information required for reporting, data storage and data sharing in the form of XML.

CONCLUSION

The MIDE guidelines will benefit the scientific community with pharmacogenomics experiments, including reporting pharmacogenomics data from other technology platforms, with the tools that will ease and automate the generation of such reports using the standardized MIDE XML schema, facilitating the sharing, dissemination, reanalysis of datasets through accessible and transparent pharmacogenomics data reporting.

The integration and interpretation of pharmacogenomics - a comparative study between the United States of America and Europe: towards better health care

The study of pharmacogenomics has, by harnessing sequence information from human genomes, the potential to lead to novel approaches in drug discovery, an individualized application of drug therapy, and new insights into disease prevention. For this potential to be realized results need to be interpreted to the prescriber into a format which dictates an action. This mini review briefly describes the history, the regulatory environment, opinions towards, and implementation, integration and interpretation of pharmacogenomics in the United States of America and Europe. The article discusses also how interpretation of pharmacogenomics could move forward to better implementation in health care.

Roles of CYP2C19 Gene Polymorphisms in Susceptibility to POAG and Individual Differences in Drug Treatment Response

Background

The aim of this study was to investigate the roles of cytochrome P450 2C19 (CYP2C19) polymorphisms in primary open-angle glaucoma (POAG) susceptibility and individual responses to drug treatment.

Material/Methods

This case-control study consisted of 93 cases with POAG and 125 controls. Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) was used to analyze CYP2C19 single-nucleotide polymorphisms (SNPs). After timolol treatment, patients were classified into side effect (SE) group and non-side effect (NSE) group. According to drug treatment responses, patients were divided into 3 groups: excellent group (Ex) (IOP ≥8 mm Hg); utility group (Ut) (5 <IOP ≤8 mm Hg), and ineffective group (In) (IOP ≤5 mm Hg). Data analysis was performed using SPSS software.

Results

We found no statistical differences in the alleles and genotypes frequencies of CYP2C19 between the case group and the control group (both P>0.05). Frequencies of extensive metabolizer phenotype and poor metabolizer phenotype or poor metabolizer phenotype and intermediate metabolizer phenotype were significantly different between the SE group and NSE group (both P<0.05). The distribution of intermediate metabolizer phenotype and extensive metabolizer phenotype were significantly different among Ex group, Ut group, and In group (all P<0.05).

Conclusions

We found no evidence that CYP2C19 polymorphisms are associated with susceptibility to POAG. However, different CYP2C19 metabolizer phenotypes were identified and observed to have important effects on the individual differences in drug treatment response.

Dilemmas of the causality assessment tools in the diagnosis of adverse drug reactions

Importance: Basic essence of Pharmacovigilance is prevention of ADRs and its precise diagnosis is crucially a primary step, which still remains a challenge among clinicians. Objective: This study is undertaken with the objective to scrutinize and offer a notion of commonly used as well as recently developed methods of causality assessment tools for the diagnosis of adverse drug reactions and discuss their pros and cons. Evidence review: Overall 49 studies were recognized for all assessment methods with five major decisive factors of causality evaluation, all the information regarding reasons allocating causality, the advantages and limitations of the appraisal methods were extracted and scrutinized. Findings: From epidemiological information a past prospect is designed and subsequent possibility merged this background information with a clue in the individual case to crop up with an approximation of causation. Expert judgment is typically based on the decisive factor on which algorithms are based, nevertheless in imprecise manner. The probabilistic methods use the similar principle; however connect probabilities to each measure. Such approaches are quite skeptical and liable to generate cloudy causation results. Causation is quite intricate to ascertain than correlation in Pharmacovigilance due to numerous inherent shortcomings in causality assessment tools. Conclusions and relevance: We suggest that there is a need to develop a high quality assessment tool which can meticulously establish suitable diagnostic criteria for ADRs with universal acceptance to improvise the fundamental aspect of drug safety and evade the impending ADRs with the motive to convert Pharmacovigilance into a state of art.

The promise of psychiatric pharmacogenomics

Clinicians already face "personalized" medicine every day while experiencing the great variation in toxicities and drug efficacy among individual patients. Pharmacogenetics studies are the platform for discovering the DNA determinants of variability in drug response and tolerability. Research now focuses on the genome after its beginning with analyses of single genes. Therapeutic outcomes from several psychotropic drugs have been weakly linked to specific genetic variants without independent replication. Drug side effects show stronger associations to genetic variants, including human leukocyte antigen loci with carbamazepine-induced dermatologic outcome and MC4R with atypical antipsychotic weight gain. Clinical implementation has proven challenging, with barriers including a lack of replicable prospective evidence for clinical utility required for altering medical care. More recent studies show promising approaches for reducing these barriers to routine incorporation of pharmacogenetics data into clinical care.

Perceptions and Attitudes About Genetic Counseling Among Residents of a Midwestern Rural Area

Relatively few investigations of the public's perceptions and attitudes about genetic counseling exist, and most are limited to individuals at-risk for a specific disease. In this study 203 individuals from a Midwest rural area completed an anonymous survey assessing their familiarity with genetic counseling; perceptions of genetic counseling purpose, scope, and practice; attitudes toward genetic counseling/counselors; and willingness to use genetic counseling services. Although very few respondents were familiar with genetic counseling, most reported accurate perceptions and positive attitudes; mean ratings, however, showed less endorsement of trust in information provided by genetic counselors and less agreement that genetic counseling aligns with their values. Logistic regression indicated reported willingness to use genetic counseling services increased if respondents: had completed some college; rated their familiarity with genetic counseling as high; agreed with the statements: genetic counseling may be useful to someone with cancer in their family, genetic counseling is in line with my values, and genetic counselors advise women to get abortions when there is a problem; and disagreed with the statements: genetic counseling is only useful to a small group of people with rare diseases, and genetic counselors must receive a lot of special training. Additional findings, practice implications, and research recommendations are presented.

Integrating in silico prediction methods, molecular docking, and molecular dynamics simulation to predict the impact of ALK missense mutations in structural perspective

Over the past decade, advancements in next generation sequencing technology have placed personalized genomic medicine upon horizon. Understanding the likelihood of disease causing mutations in complex diseases as pathogenic or neutral remains as a major task and even impossible in the structural context because of its time consuming and expensive experiments. Among the various diseases causing mutations, single nucleotide polymorphisms (SNPs) play a vital role in defining individual's susceptibility to disease and drug response. Understanding the genotype-phenotype relationship through SNPs is the first and most important step in drug research and development. Detailed understanding of the effect of SNPs on patient drug response is a key factor in the establishment of personalized medicine. In this paper, we represent a computational pipeline in anaplastic lymphoma kinase (ALK) for SNP-centred study by the application of in silico prediction methods, molecular docking, and molecular dynamics simulation approaches. Combination of computational methods provides a way in understanding the impact of deleterious mutations in altering the protein drug targets and eventually leading to variable patient's drug response. We hope this rapid and cost effective pipeline will also serve as a bridge to connect the clinicians and in silico resources in tailoring treatments to the patients' specific genotype.

Epigenetic primer for diagnostic applications: a window into personalized medicine

Epigenetic testing, primarily in the form of DNA methylation analysis, is currently being used in healthcare settings to help identify and manage disease conditions and to develop and select drugs that specifically target epigenetic machinery. Yet, the clinical application of epigenetic analysis is still in its infancy. With a number of large-scale national and international epigenomic consortia projects in progress to identify tissue-specific epigenomes in normal and disease conditions, we are now poised for a new era of understanding disease processes based upon genetic changes that do not involve alterations to the DNA sequence. The developing epigenetic knowledge base will significantly advance the practice of personalized medicine and precision therapeutics. In this article, we provide a primer on the fundamentals of epigenetics with an emphasis on DNA methylation and review the prospective uses of epigenetic testing in advancing healthcare.

Sources of interindividual variability

The efficacy, safety, and tolerability of drugs are dependent on numerous factors that influence their disposition. A dose that is efficacious and safe for one individual may result in sub-therapeutic or toxic blood concentrations in other individuals. A major source of this variability in drug response is drug metabolism, where differences in pre-systemic and systemic biotransformation efficiency result in variable degrees of systemic exposure (e.g., AUC, C max, and/or C min) following administration of a fixed dose.Interindividual differences in drug biotransformation have been studied extensively. It is well recognized that both intrinsic (such as genetics, age, sex, and disease states) and extrinsic (such as diet, chemical exposures from the environment, and even sunlight) factors play a significant role. For the family of cytochrome P450 enzymes, the most critical of the drug metabolizing enzymes, genetic variation can result in the complete absence or enhanced expression of a functional enzyme. In addition, up- and down-regulation of gene expression, in response to an altered cellular environment, can achieve the same range of metabolic function (phenotype), but often in a less reliably predictable and time-dependent manner. Understanding the mechanistic basis for drug disposition and response variability is essential if we are to move beyond the era of empirical, trial-and-error dose selection and into an age of personalized medicine that brings with it true improvements in health outcomes in the therapeutic treatment of disease.

Progressing the utilisation of pharmacogenetics and pharmacogenomics into clinical care

Understanding human genetic variation and how it impacts on gene function is a major focus in genomic-based research. Translation of this knowledge into clinical care is exemplified by pharmacogenetics/pharmacogenomics. The identification of particular gene variants that might influence drug uptake, metabolism, distribution or excretion promises a more effective personalised medicine approach in choosing the right drug or its dose for any particular individual. Adverse drug responses can then be avoided or mitigated. An understanding of germline or acquired (somatic) DNA mutations can also be used to identify drugs that are more likely to be therapeutically beneficial. This represents an area of growing interest in the treatment of cancer.

Comparative epidemiology of hospital-acquired adverse drug reactions in adults and children and their impact on cost and hospital stay--a systematic review

PURPOSE

To study and analyze the comparative impact of hospital-acquired adverse drug reactions (ADRs) in adult and pediatric patients in terms of the economic implications, (length of) hospital stay, and salient features in relation to the incidence rate, severity, morbidity, mortality, and preventability of the ADRs.

METHODS

A systematic search to identify and retrieve relevant articles/studies in the PubMed, Medline, Scopus, MEDPAR, and Cochrane databases and by the Google search engine was performed for the study period 2000 to April 2013. In total, 51 studies were identified on patients hospitalized for ADRs, and these were included in the study. The incidence rate of ADRs, their severity, mortality, morbidity, preventability, cost, and association with extended hospital stay due to ADRs were extracted and scrutinized.

RESULTS

Hospital-acquired ADRs are more widely studied in adults than in children, and the incidence rate is higher in the former. However, a wide variation in the incidence rate worldwide is observed in both groups. Irrespective of the ages of patients, ADRs are among the most frequent causes of morbidity and mortality. Interestingly, preventable ADRs are more frequently observed in patients at the younger and older ends of the age spectrum. Hospital-acquired ADRs place an immense economic burden on healthcare systems, with the overall cost for a hospitalized patient with an ADR reported to be $2,401 per patient, which is equivalent to a 19.86 % additional increase in the total cost of care and an increase in average length of hospital stay of 8.25 %.

CONCLUSION

Based on the findings of this review, we suggest that excellent assertive measures of pharmacovigilance with the aim to diminish the incidence rate of hospital-acquired ADRs and support the development of interventions are needed to promote vital facets of drug safety with an overall objective to avert potential ADRs.

Pharmacogenetic Biomarkers as Tools for Pharmacoepidemiology of Severe Adverse Drug Reactions

Preclinical Research

The development of new genomic technologies has led to an exponential increase in the number of biomarkers for drug safety and efficacy. Pharmacogenomics has the potential to impact clinically relevant outcomes in drug dosing, efficacy, toxicity, and prediction of adverse drug reactions (ADRs). Genotype‐based prescribing is anticipated to improve the overall efficacy rates and minimize ADRs, making personalized medicine a reality. Genome‐wide association studies have been increasingly applied to pharmacogenetics. Severe ADRs are a major issue for drug therapy because they can cause serious disorders and can be life threatening. For severe ADRs, significant associations have been reported for drug‐induced liver injury, statin‐induced myopathy, increased risk of hemorrhagic complications of anticoagulant use, drug‐induced torsade de pointes, drug‐induced long QT, and severe cutaneous ADRs. This review summarizes the current position concerning the clinical and pharmacoepidemiological relevance of pharmacogenetic biomarkers in ADR prediction and prevention, with an emphasis on genetic risk factors and biomarkers for three specific severe ADRs.

Omics and drug response

A new generation of technologies commonly named omics permits assessment of the entirety of the components of biological systems and produces an explosion of data and a major shift in our concepts of disease. These technologies will likely shape the future of health care. One aspect of these advances is that the data generated document the uniqueness of each human being in regard to disease risk and treatment response. These developments have reemphasized the concept of personalized medicine. Here we review the impact of omics technologies on one key aspect of personalized medicine: the individual drug response. We describe how knowledge of different omics may affect treatment decisions, namely drug choice and drug dose, and how it can be used to improve clinical outcomes.

Mitochondrial bioenergetics and drug-induced toxicity in a panel of mouse embryonic fibroblasts with mitochondrial DNA single nucleotide polymorphisms

Mitochondrial DNA (mtDNA) variations including single nucleotide polymorphisms (SNPs) have been proposed to be involved in idiosyncratic drug reactions. However, current in vitro and in vivo models lack the genetic diversity seen in the human population. Our hypothesis is that different cell strains with distinct mtDNA SNPs may have different mitochondrial bioenergetic profiles and may therefore vary in their response to drug-induced toxicity. Therefore, we used an in vitro system composed of four strains of mouse embryonic fibroblasts (MEFs) with mtDNA polymorphisms. We sequenced mtDNA from embryonic fibroblasts isolated from four mouse strains, C57BL/6J, MOLF/EiJ, CZECHII/EiJ and PERA/EiJ, with the latter two being sequenced for the first time. The bioenergetic profile of the four strains of MEFs was investigated at both passages 3 and 10. Our results showed that there were clear differences among the four strains of MEFs at both passages, with CZECHII/EiJ having a lower mitochondrial robustness when compared to C57BL/6J, followed by MOLF/EiJ and PERA/EiJ. Seven drugs known to impair mitochondrial function were tested for their effect on the ATP content of the four strains of MEFs in both glucose- and galactose-containing media. Our results showed that there were strain-dependent differences in the response to some of the drugs. We propose that this model is a useful starting point to study compounds that may cause mitochondrial off-target toxicity in early stages of drug development, thus decreasing the number of experimental animals used.

Pharmacogenetically driven treatments for alcoholism: are we there yet?

Pharmacogenetic analyses of treatments for alcohol dependence attempt to predict treatment response and side-effect risk for specific medications. We review the literature on pharmacogenetics relevant to alcohol dependence treatment, and describe state-of-the-art methods of pharmacogenetic research in this area. Two main pharmacogenetic study designs predominate: challenge studies and treatment-trial analyses. Medications studied include US FDA-approved naltrexone and acamprosate, both indicated for treating alcohol dependence, as well as several investigational (and off-label) treatments such as sertraline, olanzapine and ondansetron. The best-studied functional genetic variant relevant to alcoholism treatment is rs1799971, a single-nucleotide polymorphism in exon 1 of the OPRM1 gene that encodes the μ-opioid receptor. Evidence from clinical trials suggests that the presence of the variant G allele of rs1799971 may predict better treatment response to opioid receptor antagonists such as naltrexone. Evidence from clinical trials also suggests that several medications interact pharmacogenetically with variation in genes that encode proteins involved in dopaminergic and serotonergic neurotransmission. Variation in the DRD4 gene, which encodes the dopamine D(4) receptor, may predict better response to naltrexone and olanzapine. A polymorphism in the serotonin transporter gene SLC6A4 promoter region appears related to differential treatment response to sertraline depending on the subject's age of onset of alcoholism. Genetic variation in SLC6A4 may also be associated with better treatment response to ondansetron. Initial pharmacogenetic efforts in alcohol research have identified functional variants with potential clinical utility, but more research is needed to further elucidate the mechanism of these pharmacogenetic interactions and their moderators in order to translate them into clinical practice.

Bioinformatics and variability in drug response: a protein structural perspective

Marketed drugs frequently perform worse in clinical practice than in the clinical trials on which their approval is based. Many therapeutic compounds are ineffective for a large subpopulation of patients to whom they are prescribed; worse, a significant fraction of patients experience adverse effects more severe than anticipated. The unacceptable risk-benefit profile for many drugs mandates a paradigm shift towards personalized medicine. However, prior to adoption of patient-specific approaches, it is useful to understand the molecular details underlying variable drug response among diverse patient populations. Over the past decade, progress in structural genomics led to an explosion of available three-dimensional structures of drug target proteins while efforts in pharmacogenetics offered insights into polymorphisms correlated with differential therapeutic outcomes. Together these advances provide the opportunity to examine how altered protein structures arising from genetic differences affect protein-drug interactions and, ultimately, drug response. In this review, we first summarize structural characteristics of protein targets and common mechanisms of drug interactions. Next, we describe the impact of coding mutations on protein structures and drug response. Finally, we highlight tools for analysing protein structures and protein-drug interactions and discuss their application for understanding altered drug responses associated with protein structural variants.

Genetic polymorphisms affecting drug metabolism: recent advances and clinical aspects

Though current knowledge of pharmacogenetic factors relevant to drug metabolism is fairly comprehensive and this should facilitate translation to the clinic, there are a number of gaps in knowledge. Recent studies using both conventional and novel approaches have added to our knowledge of pharmacogenetics of drug metabolism. Genome-wide association studies have provided new insights into the major contribution of cytochromes P450 to response to therapeutic agents such as coumarin anticoagulants and clopidogrel as well as to caffeine and nicotine. Recent advances in understanding of factors affecting gene expression, both regulation by transcription factors and by microRNA and epigenetic factors, have added to understanding of variation in expression of genes such as CYP3A4 and CYP2E1. The implementation of testing for pharmacogenetic polymorphisms in prescription of selected anticancer drugs and cardiovascular agents is considered in detail, with current controversies and barriers to implementation of pharmacogenetic testing assessed. Though genotyping for thiopurine methyltransferase is now common prior to prescription of thiopurines, genotyping for other pharmacogenetic polymorphisms prior to drug prescription remains uncommon. However, it seems likely that it will become more widespread as both increased evidence that certain pharmacogenetic tests are valuable and cost-effective and more accessible genotyping methods become available.

Allopurinol pharmacogenetics: assessment of potential clinical usefulness

Use of pharmacogenetics to inform treatment decisions remains a priority for clinicians, patients and public health agencies. We previously developed a framework for systematically assessing whether pharmacogenetic test information would likely bring value to clinical decision-making and enjoy practical uptake. We applied this tool to allopurinol to determine potential usefulness of HLA genetic information in assessing risk for allopurinol-induced severe cutaneous adverse reactions. We quantified allopurinol use data and the magnitude of adverse event signals using US FDA databases, reviewed reported cases of allopurinol-associated severe cutaneous adverse reactions to assess whether clinical subtypes of patients could be identified, performed pooled analyses of associations between HLA variation and allopurinol-induced severe cutaneous adverse reactions and described considerations in clinical implementation of allopurinol pharmacogenetics.

DNA amplification techniques in pharmacogenomics

The variable predisposition of patients, both to disease susceptibility and drug response, is well established. It is largely attributed to genetic, as well as epigenetic variations between individuals, which may be inherited or acquired. The most common variation in the human genome is the SNP, which occurs throughout the genome, both within coding and noncoding regions. Characterization of SNPs in the context of both inherited and acquired conditions, such as cancer, are a main focus of many genotyping procedures. The demand for identifying (diagnosing) targeted SNPs or other variations, as well as the application of genome-wide screens, is continuously directing the development of new technologies. In general, most methods require a DNA amplification step to provide the amounts of DNA needed for the SNP detection step. In addition, DNA amplification is an important step when investigating other types of genomic information, for instance when addressing repeat, deletion, copy number variation or epigenetic regulation by DNA methylation. Besides the widely used PCR technique, there are several alternative approaches for genomic DNA amplification suitable for supporting the detection of genomic variation. In this article, we describe and evaluate a number of techniques, and discuss possible future prospects of DNA amplification in the fields of pharmacogenetics and pharmacogenomics.

Role of the cytochrome P450 enzyme system in veterinary pharmacokinetics: where are we now? Where are we going?

Drug metabolism is a core determinant of the dose-effectiveness-toxicity relationship of many compounds. It is also critical to the human food safety assessment of drug residues in the edible tissues of food-producing animals. This article describes the current state of knowledge regarding the role of the cytochrome P450 superfamily of enzymes in determining the metabolic profile of compounds administered to companion animals (e.g., dog and cat) and to food-producing animal species (e.g., cattle, swine, chickens). In turn, this knowledge reflects the collection of insights derived from the recognized population variability observed in human drug metabolism, our general understanding of the kinetics of various drug-metabolism pathways, emerging tools that enable the role of pharmacogenetics to be studied and the characterization of drug metabolism in individual veterinary species. Ultimately, by increasing our insights with regard to factors that can influence drug metabolism, our knowledge of metabolic pathways, sources of within- and between-species variability in pharmacokinetics and the development of in silico models that can be used to predict pharmacokinetic profiles from these diverse sources of information. We will improve our ability to generate the population inferences needed to insure the target animal safety, product effectiveness and the human food safety of veterinary pharmaceuticals.

Genetic susceptibility to renal scar formation after urinary tract infection: a systematic review and meta-analysis of candidate gene polymorphisms

Identifying patients who may develop renal scarring after urinary tract infections (UTI) remains challenging, as clinical determinants explain only a portion of individual risk. An additional factor that likely affects risk is individual genetic variability. We searched for peer-reviewed articles from 1980 to December 2009 in electronic databases that reported results showing an association between gene polymorphims and renal scaring after UTI. Two independent researchers screened articles using predetermined criteria. Studies were assessed for methodological quality using an aggregate scoring system. The 18 studies ultimately included in the review had investigated 16 polymorphisms in nine genes in association with renal scarring formation after UTI. Based on the predetermined criteria for assessing the quality of the studies, 12 studies (67%) were identified as being of poor quality design. A meta-analysis of cumulative studies showed on association between renal scarring formation after UTI and the angiotensin converting enzyme insertion/deletion polymorphism [ACE I/D; recessive model for D allele; odds ratio (OR) 1.73, 95% confidence interval (CI) 1.09-2.74, P = 0.02] or transforming growth factor (TGF)-β1 c.-509 T > C polymorphism (dominant model for T allele; OR 2.24, 95% CI 1.34-3.76, P = 0.002). However, heterogeneity among studies was large, indicating a strong difference that cannot only be explained by differences in study design. The studies reviewed in this article support a modest involvement of the vasomotor and inflammatory genes in the development of renal scarring after UTIs. This review also shows that only few possible candidate genes have been investigated for an association with renal scarring, raising the hypothesis that some gene polymorphisms may exert their effects through an interaction with as yet uninvestigated factors that may be related to geographic and/or socio-economic differences.

Impact of UGT2B7 His268Tyr polymorphism on the outcome of adjuvant epirubicin treatment in breast cancer

INTRODUCTION

Epirubicin is a common adjuvant treatment for breast cancer. It is mainly eliminated after glucuronidation through uridine diphosphate-glucuronosyltransferase 2B7 (UGT2B7). The present study aimed to describe the impact of the UGT2B7(His268Tyr) polymorphism on invasive disease-free survival in breast cancer patients after epirubicin treatment.

METHODS

This is a pharmacogenetic study based on samples collected from 745 breast cancer patients of the Austrian Tumor of breast tissue: Incidence, Genetics, and Environmental Risk factors (TIGER) cohort who did not present metastases at baseline. This cohort included 205 women with epirubicin-based combination chemotherapy, 113 patients having received chemotherapy without epirubicin and 427 patients having received no chemotherapy at all. Of the epirubicin-treated subgroup, 120 were subsequently treated with tamoxifen. For all women UGT2B7(His268Tyr) was genotyped. Invasive disease-free survival was assessed using Kaplan-Meier and Cox's proportional hazard regression analysis.

RESULTS

Among the 205 epirubicin-treated patients, carriers of two UGT2B7(268Tyr) alleles had a mean invasive disease-free survival of 8.6 (95% confidence interval (CI) 7.9 to 9.3) years as compared to 7.5 (95% CI 6.9 to 8.0) years in carriers of at least one UGT2B7(268His) allele (adjusted hazard ratio (HR) = 2.64 (95% CI 1.22 to 5.71); P = 0.014). In addition, the impact of the UGT2B7(His268Tyr) polymorphism became even more pronounced in patients subsequently treated with tamoxifen (adjusted HR = 5.22 (95% CI 1.67 to 26.04); P = 0.015) whereas no such difference in invasive disease-free survival was observed in patients not receiving epirubicin.

CONCLUSIONS

Breast cancer patients carrying the UGT2B7(268Tyr/Tyr) genotype may benefit most from adjuvant epirubicin-based chemotherapy. These results warrant confirmation in further studies.

CYP3A5 genotype does not influence everolimus in vitro metabolism and clinical pharmacokinetics in renal transplant recipients

BACKGROUND

CYP3A5 genotyping might be useful to guide tacrolimus and sirolimus dosing. The aim of this study was to assess the influence of CYP3A5 polymorphism on everolimus metabolism and pharmacokinetics.

METHODS

We investigated the effect of CYP3A5 6986A>G polymorphism (CYP3A5*1/*3 alleles) on the pharmacokinetics of everolimus in 28 renal transplant patients and on its in vitro hepatic metabolism using a bank of genotyped human liver microsomes (n=49). We further evaluated in vitro the contribution of CYP3A4, CYP3A5, and CYP2C8 to everolimus hepatic metabolism using recombinant enzymes.

RESULTS

We found no association between CYP3A5 polymorphism and everolimus pharmacokinetics in renal transplant patients. On the other hand, no effect of CYP3A5 polymorphism was observed on the intrinsic clearance of everolimus by human liver microsomes, whereas that of tacrolimus (positive control) was 1.5-fold higher in microsomes carrying the CYP3A5*1 allele than in noncarriers. In vitro data showed that CYP3A4 is a better catalyst of everolimus metabolism than CYP3A5, whereas the opposite was observed for tacrolimus.

CONCLUSIONS

This study provides direct and indirect evidence that CYP3A5 genotyping cannot help improve everolimus therapy.