Genetics of Population Differences in Drug Response

Genetic ancestry in population pharmacogenomics unravels distinct geographical patterns related to drug toxicity

Genetic ancestry plays a major role in pharmacogenomics, and a deeper understanding of the genetic diversity among individuals holds immerse promise for reshaping personalized medicine. In this pivotal study, we have conducted a large-scale genomic analysis of 1,136 pharmacogenomic variants employing machine learning algorithms on 3,714 individuals from publicly available datasets to assess the risk proximity of experiencing drug-related adverse events. Our findings indicate that Admixed Americans and Europeans have demonstrated a higher risk of experiencing drug toxicity, whereas individuals with East Asian ancestry and, to a lesser extent, Oceanians displayed a lower risk proximity. Polygenic risk scores for drug-gene interactions did not necessarily follow similar assumptions, reflecting distinct genetic patterns and population-specific differences that vary depending on the drug class. Overall, our results provide evidence that genetic ancestry is a pivotal factor in population pharmacogenomics and should be further exploited to strengthen even more personalized drug therapy.

Pharmacogenomics: A Genetic Approach to Drug Development and Therapy

The majority of the well-known pharmacogenomics research used in the medical sciences contributes to our understanding of medication interactions. It has a significant impact on treatment and drug development. The broad use of pharmacogenomics is required for the progress of therapy. The main focus is on how genes and an intricate gene system affect the body's reaction to medications. Novel biomarkers that help identify a patient group that is more or less likely to respond to a certain medication have been discovered as a result of recent developments in the field of clinical therapeutics. It aims to improve customized therapy by giving the appropriate drug at the right dose at the right time and making sure that the right prescriptions are issued. A combination of genetic, environmental, and patient variables that impact the pharmacokinetics and/or pharmacodynamics of medications results in interindividual variance in drug response. Drug development, illness susceptibility, and treatment efficacy are all impacted by pharmacogenomics. The purpose of this work is to give a review that might serve as a foundation for the creation of new pharmacogenomics applications, techniques, or strategies.

Comparing variants related to chronic diseases from genome-wide association study (GWAS) and the cancer genome atlas (TCGA)

BACKGROUND

Several genome-wide association studies (GWAS) have been performed to identify variants related to chronic diseases. Somatic variants in cancer tissues are associated with cancer development and prognosis. Expression quantitative trait loci (eQTL) and methylation QTL (mQTL) analyses were performed on chronic disease-related variants in TCGA dataset.

METHODS

MuTect2 calling variants for 33 cancers from TCGA and 296 GWAS variants provided by LocusZoom were used. At least one mutation was found in TCGA 22 cancers and LocusZoom 23 studies. Differentially expressed genes (DEGs) and differentially methylated regions (DMRs) from the three cancers (TCGA-COAD, TCGA-STAD, and TCGA-UCEC). Variants were mapped to the world map using population locations of the 1000 Genomes Project (1GP) populations. Decision tree analysis was performed on the discovered features and survival analysis was performed according to the cluster.

RESULTS

Based on the DEGs and DMRs with clinical data, the decision tree model classified seven and three nodes in TCGA-COAD and TCGA-STAD, respectively. A total of 11 variants were commonly detected from TCGA and LocusZoom, and eight variants were selected from the 1GP variants, and the distribution patterns were visualized on the world map.

CONCLUSIONS

Variants related to tumors and chronic diseases were selected, and their geological regional 1GP-based proportions are presented. The variant distribution patterns could provide clues for regional clinical trial designs and personalized medicine.

Assessing pharmacogenomic literacy in China through validation of the Chinese version of the Minnesota Assessment of Pharmacogenomic Literacy

Pharmacogenomics (PGx) implementation into clinical care is rapidly increasing in China. However, the extent to which the public understands PGx testing and important knowledge domains requiring patient education or counseling remains unclear. To address this, we created and validated the Chinese version of the Minnesota Assessment of Pharmacogenomic Literacy (MAPL-CTM ). The MAPL-C was developed by translating the English MAPL to Chinese following cross-cultural translation guidelines. An online survey validated the MAPL-C and assessed Chinese individuals' PGx literacy. Validation analyses were performed and associations of PGx literacy with participants' characteristics were quantified. Of 959 high-quality responses, the majority of respondents were Han Chinese (96.3%), men (54.5%), aged 18-29 years (70.9%), residing in China (97.3%), and had received college or higher education (95.0%). Out of 15 starting items developed to query specific predefined knowledge domains, two uninformative items were excluded, resulting in a 13-item MAPL-C. Chinese participants' MAPL-C performance was best explained by a three-factor model, encompassing PGx concepts and function, testing limitations, and privacy. Higher MAPL-C performance was associated with younger age, higher education, and previous genetic testing experience. Correct response rates for questions related to testing limitations were lower than those in other domains. The creation and validation of the MAPL-C fills a gap in determining PGx knowledge among Chinese speakers, quantifying PGx literacy within a Chinese cohort, and identifying response patterns and knowledge gaps. The MAPL-C can be useful in clinical practice to guide patient counseling, assess PGx education interventions, and quantify PGx knowledge in relation to outcomes in research studies involving Chinese participants.

Rational design of an N-terminal cysteine-containing tetrapeptide that inhibits tyrosinase and evaluation of its mechanism of action

There has been a resurgence of interest in bioactive peptides as therapeutic agents. This is particularly interesting for tyrosinase, which can be inhibited by thiol-containing peptides. This work demonstrates that an N-terminal cysteine-containing tetrapeptide can be rationally designed to inhibit tyrosinase activity in vitro and in cells. The tetrapeptide cysteine (C), arginine (R), asparagine (N) and leucine (L) or CRNL is a potent inhibitor of tyrosinase activity with an IC50 value of 39.62 ± 6.21 μM, which is comparable to currently used tyrosinase inhibitors. Through structure-activity studies and computational modeling, we demonstrate the peptide interacts with the enzyme via electrostatic (R with E322), hydrogen bonding (N with N260) and hydrophobic (L with V248) intermolecular interactions and that a combination of these is required for potent activity. Moreover, copper chelating activity might be one of the mechanisms of tyrosinase inhibition by CRNL. Kinetic studies show that tetrapeptide is a competitive inhibitor with two-step irreversible inhibition. In addition, CRNL had no toxicity and could reduce melanin levels in the murine melanoma cell line (B16F1). Overall, CRNL is a very promising candidate for hyperpigmentation treatment.

Population Pharmacogenomics in Croatia: Evaluating the PGx Allele Frequency and the Impact of Treatment Efficiency

BACKGROUND

Adverse drug reactions (ADRs) are a significant cause of mortality, and pharmacogenomics (PGx) offers the potential to optimize therapeutic efficacy while minimizing ADRs. However, there is a lack of data on the Croatian population, highlighting the need for investigating the most common alleles, genotypes, and phenotypes to establish national guidelines for drug use.

METHODS

A single-center retrospective cross-sectional study was performed to examine the allele, genotype, and phenotype frequencies of drug-metabolizing enzymes, receptors, and other proteins in a random sample of 522 patients from Croatia using a 28-gene PGx panel.

RESULTS

Allele frequencies, genotypes, and phenotypes for the investigated genes were determined. No statistically significant differences were found between the Croatian and European populations for most analyzed genes. The most common genotypes observed in the patients resulted in normal metabolism rates. However, some genes showed higher frequencies of altered metabolism rates.

CONCLUSIONS

This study provides insights into the allele, genotype, and phenotype frequencies of drug-metabolizing enzymes, receptors, and other associated proteins in the Croatian population. The findings contribute to optimizing drug use guidelines, potentially reducing ADRs, and improving therapeutic efficacy. Further research is needed to tailor population-specific interventions based on these findings and their long-term benefits.

Race, Ethnicity, and Pharmacogenomic Variation in the United States and the United Kingdom

The relevance of race and ethnicity to genetics and medicine has long been a matter of debate. An emerging consensus holds that race and ethnicity are social constructs and thus poor proxies for genetic diversity. The goal of this study was to evaluate the relationship between race, ethnicity, and clinically relevant pharmacogenomic variation in cosmopolitan populations. We studied racially and ethnically diverse cohorts of 65,120 participants from the United States All of Us Research Program (All of Us) and 31,396 participants from the United Kingdom Biobank (UKB). Genome-wide patterns of pharmacogenomic variation-6311 drug response-associated variants for All of Us and 5966 variants for UKB-were analyzed with machine learning classifiers to predict participants' self-identified race and ethnicity. Pharmacogenomic variation predicts race/ethnicity with averages of 92.1% accuracy for All of Us and 94.3% accuracy for UKB. Group-specific prediction accuracies range from 99.0% for the White group in UKB to 92.9% for the Hispanic group in All of Us. Prediction accuracies are substantially lower for individuals who identified with more than one group in All of Us (16.7%) or as Mixed in UKB (70.7%). There are numerous individual pharmacogenomic variants with large allele frequency differences between race/ethnicity groups in both cohorts. Frequency differences for toxicity-associated variants predict hundreds of adverse drug reactions per 1000 treated participants for minority groups in All of Us. Our results indicate that race and ethnicity can be used to stratify pharmacogenomic risk in the US and UK populations and should not be discounted when making treatment decisions. We resolve the contradiction between the results reported here and the orthodoxy of race and ethnicity as non-genetic, social constructs by emphasizing the distinction between global and local patterns of human genetic diversity, and we stress the current and future limitations of race and ethnicity as proxies for pharmacogenomic variation.

Differences in Plasma Cannabidiol Concentrations in Women and Men: A Randomized, Placebo-Controlled, Crossover Study

The potential therapeutic benefits of cannabidiol (CBD) require further study. Here, we report a triple-blind (participant, investigator, and outcome assessor) placebo-controlled crossover study in which 62 hypertensive volunteers were randomly assigned to receive the recently developed DehydraTECH2.0 CBD formulation or a placebo. This is the first study to have been conducted using the DehydraTECH2.0 CBD formulation over a 12-week study duration. The new formulation's long-term effects on CBD concentrations in plasma and urine, as well as its metabolites 7-hydroxy-CBD and 7-carboxy-CBD, were analyzed. The results of the plasma concentration ratio for CBD/7-OH-CBD in the third timepoint (after 5 weeks of use) were significantly higher than in the second timepoint (after 2.5 weeks of use; p = 0.043). In the same timepoints in the urine, a significantly higher concentration of 7-COOH-CBD was observed p < 0.001. Differences in CBD concentration were found between men and women. Plasma levels of CBD were still detectable 50 days after the last consumption of the CBD preparations. Significantly higher plasma CBD concentrations occurred in females compared to males, which was potentially related to greater adipose tissue. More research is needed to optimize CBD doses to consider the differential therapeutic benefits in men and women.

Trial of a Novel Oral Cannabinoid Formulation in Patients with Hypertension: A Double-Blind, Placebo-Controlled Pharmacogenetic Study

Cannabidiol (CBD) is a non-psychoactive cannabinoid, and available evidence suggests potential efficacy in the treatment of many disorders. DehydraTECH™2.0 CBD is a patented capsule formulation that improves the bioabsorption of CBD. We sought to compare the effects of CBD and DehydraTECH™2.0 CBD based on polymorphisms in CYP P450 genes and investigate the effects of a single CBD dose on blood pressure. In a randomized and double-blinded order, 12 females and 12 males with reported hypertension were given either placebo capsules or DehydraTECH™2.0 CBD (300 mg of CBD, each). Blood pressure and heart rate were measured during 3 h, and blood and urine samples were collected. In the first 20 min following the dose, there was a greater reduction in diastolic blood pressure (p = 0.025) and mean arterial pressure MAP (p = 0.056) with DehydraTECH™2.0 CBD, which was probably due to its greater CBD bioavailability. In the CYP2C9*2*3 enzyme, subjects with the poor metabolizer (PM) phenotype had higher plasma CBD concentrations. Both CYP2C19*2 (p = 0.037) and CYP2C19*17 (p = 0.022) were negatively associated with urinary CBD levels (beta = -0.489 for CYP2C19*2 and beta = -0.494 for CYP2C19*17). Further research is required to establish the impact of CYP P450 enzymes and the identification of metabolizer phenotype for the optimization of CBD formulations.

Advancing workforce diversity by leveraging the Clinical and Translational Science Awards (CTSA) program

Clinical trials continue to disproportionately underrepresent people of color. Increasing representation of diverse backgrounds among clinical research personnel has the potential to yield greater representation in clinical trials and more efficacious medical interventions by addressing medical mistrust. In 2019, North Carolina Central University (NCCU), a Historically Black College and University with a more than 80% underrepresented student population, established the Clinical Research Sciences Program with support from the Clinical and Translational Science Awards (CTSA) program at neighboring Duke University. This program was designed to increase exposure of students from diverse educational, racial, and ethnic backgrounds to the field of clinical research, with a special focus on health equity education. In the first year, the program graduated 11 students from the two-semester certificate program, eight of whom now hold positions as clinical research professionals. This article describes how leveraging the CTSA program helped NCCU build a framework for producing a highly trained, competent, and diverse workforce in clinical research responsive to the call for increased diversity in clinical trial participation.

Proteome-wide Mendelian randomization in global biobank meta-analysis reveals multi-ancestry drug targets for common diseases

Proteome-wide Mendelian randomization (MR) shows value in prioritizing drug targets in Europeans but with limited evidence in other ancestries. Here, we present a multi-ancestry proteome-wide MR analysis based on cross-population data from the Global Biobank Meta-analysis Initiative (GBMI). We estimated the putative causal effects of 1,545 proteins on eight diseases in African (32,658) and European (1,219,993) ancestries and identified 45 and 7 protein-disease pairs with MR and genetic colocalization evidence in the two ancestries, respectively. A multi-ancestry MR comparison identified two protein-disease pairs with MR evidence in both ancestries and seven pairs with specific effects in the two ancestries separately. Integrating these MR signals with clinical trial evidence, we prioritized 16 pairs for investigation in future drug trials. Our results highlight the value of proteome-wide MR in informing the generalizability of drug targets for disease prevention across ancestries and illustrate the value of meta-analysis of biobanks in drug development.

Comprehensive Assessment of Indian Variations in the Druggable Kinome Landscape Highlights Distinct Insights at the Sequence, Structure and Pharmacogenomic Stratum

India confines more than 17% of the world’s population and has a diverse genetic makeup with several clinically relevant rare mutations belonging to many sub-group which are undervalued in global sequencing datasets like the 1000 Genome data (1KG) containing limited samples for Indian ethnicity. Such databases are critical for the pharmaceutical and drug development industry where diversity plays a crucial role in identifying genetic disposition towards adverse drug reactions. A qualitative and comparative sequence and structural study utilizing variant information present in the recently published, largest curated Indian genome database (IndiGen) and the 1000 Genome data was performed for variants belonging to the kinase coding genes, the second most targeted group of drug targets. The sequence-level analysis identified similarities and differences among different populations based on the nsSNVs and amino acid exchange frequencies whereas a comparative structural analysis of IndiGen variants was performed with pathogenic variants reported in UniProtKB Humsavar data. The influence of these variations on structural features of the protein, such as structural stability, solvent accessibility, hydrophobicity, and the hydrogen-bond network was investigated. In-silico screening of the known drugs to these Indian variation-containing proteins reveals critical differences imparted in the strength of binding due to the variations present in the Indian population. In conclusion, this study constitutes a comprehensive investigation into the understanding of common variations present in the second largest population in the world and investigating its implications in the sequence, structural and pharmacogenomic landscape. The preliminary investigation reported in this paper, supporting the screening and detection of ADRs specific to the Indian population could aid in the development of techniques for pre-clinical and post-market screening of drug-related adverse events in the Indian population.

Genetic Ancestry Inference for Pharmacogenomics

Genetic ancestry inference can be used to stratify patient cohorts and to model pharmacogenomic variation within and between populations. We provide a detailed guide to genetic ancestry inference using genome-wide genetic variant datasets, with an emphasis on two widely used techniques: principal components analysis (PCA) and ADMIXTURE analysis. PCA can be used for patient stratification and categorical ancestry inference, whereas ADMIXTURE is used to characterize genetic ancestry as a continuous variable. Visualization methods are critical for the interpretation of genetic ancestry inference methods, and we provide instructions for how the results of PCA and ADMIXTURE can be effectively visualized.

Translational Pharmacogenomics: Discovery, Evidence Synthesis and Delivery of Race-Conscious Medicine

Response to medications, the principal treatment modality for acute and chronic diseases, is highly variable, with 40-70% of patients exhibiting lack of efficacy or adverse drug reactions. With ~ 15-30% of this variability explained by genetic variants, pharmacogenomics has become a valuable tool in our armamentarium for optimizing treatments and is poised to play an increasing role in clinical care. This review presents the progress made toward elucidating genetic underpinnings of drug response including discovery of race/ancestry-specific pharmacogenetic variants and discusses the current evidence and evidence framework for actionability. The review is framed in the context of changing demographics and evolving views related to race and ancestry. Finally, it highlights the vital role played by cohort studies in elucidating genetic differences in drug response across race and ancestry and the informal collaborations that have enabled the field to bridge the "bench to bedside" translational gap.

Allele frequencies of single nucleotide polymorphisms of clinically important drug-metabolizing enzymes CYP2C9, CYP2C19, and CYP3A4 in a Thai population

Prior knowledge of allele frequencies of cytochrome P450 polymorphisms in a population is crucial for the revision and optimization of existing medication choices and doses. In the current study, the frequency of the CYP2C9*2, CYP2C9*3, CYP2C19*2, CYP2C19*3, CYP2C19*6, CYP2C19*17, and CYP3A4 (rs4646437) alleles in a Thai population across different regions of Thailand was examined. Tests for polymorphisms of CYP2C9 and CYP3A4 were performed using TaqMan SNP genotyping assay and CYP2C19 was performed using two different methods; TaqMan SNP genotyping assay and Luminex x Tag V3. The blood samples were collected from 1205 unrelated healthy individuals across different regions within Thailand. Polymorphisms of CYP2C9 and CYP2C19 were transformed into phenotypes, which included normal metabolizer (NM), intermediate metabolizer (IM), poor metabolizer (PM), and rapid metabolizers (RM). The CYP2C9 allele frequencies among the Thai population were 0.08% and 5.27% for the CYP2C9*2 and CYP2C9*3 alleles, respectively. The CYP2C19 allele frequencies among the Thai population were 25.60%, 2.50%, 0.10%, and 1.80% for the CYP2C19*2, CYP2C19*3, CYP2C19*6, and CYP2C19*17 alleles, respectively. The allele frequency of the CYP3A4 (rs4646437) variant allele was 28.50% in the Thai population. The frequency of the CYP2C9*3 allele was significantly lower among the Northern Thai population (P < 0.001). The frequency of the CYP2C19*17 allele was significantly higher in the Southern Thai population (P < 0.001). Our results may provide an understanding of the ethnic differences in drug responses and support for the utilization of pharmacogenomics testing in clinical practice.

Clinical laboratory reference values in adults in Kisumu County, Western Kenya; hematology, chemistry and CD4

BACKGROUND

Clinical laboratory reference intervals (RIs) are essential for diagnosing and managing patients in routine clinical care as well as establishing eligibility criteria and defining adverse events in clinical trials, but may vary by age, gender, genetics, nutrition and geographic location. It is, therefore, critical to establish region-specific reference values in order to inform clinical decision-making.

METHODS

We analyzed data from a prospective observational HIV incidence cohort study in Kombewa, Kenya. Study participants were healthy males and females, aged 18-35 years, without HIV. Median and 95% reference values (2.5th percentile to 97.5th percentile) were calculated for laboratory parameters including hematology, chemistry studies, and CD4 T cell count. Standard Deviation Ratios (SDR) and Bias Ratios (BR) are presented as measures of effect magnitude. Findings were compared with those from the United States and other Kenyan studies.

RESULTS

A total of 299 participants were analyzed with a median age of 24 years (interquartile range: 21-28). Ratio of males to females was 0.9:1. Hemoglobin range (2.5th-97.5th percentiles) was 12.0-17.9 g/dL and 9.5-15.3 g/dL in men and women respectively. In the cohort, MCV range was 59-95fL, WBC 3.7-9.2×103/μL, and platelet 154-401×103/μL. Chemistry values were higher in males; the creatinine RI was 59-103 μmol/L in males vs. 46-76 μmol/L in females (BRUL>.3); and the alanine transferase range was 8.8-45.3 U/L in males vs. 7.5-36.8 U/L in females (SDR>.3). The overall CD4 T cell count RI was 491-1381 cells/μL. Some parameters including hemoglobin, neutrophil, creatinine and ALT varied with that from prior studies in Kenya and the US.

CONCLUSION

This study not only provides clinical reference intervals for a population in Kisumu County but also highlights the variations in comparable settings, accentuating the requirement for region-specific reference values to improve patient care, scientific validity, and quality of clinical trials in Africa.

Molecular Mechanism of Action of Repurposed Drugs and Traditional Chinese Medicine Used for the Treatment of Patients Infected With COVID-19: A Systematic Scoping Review

Background: The emergence of COVID-19 as a pandemic has resulted in the need for urgent development of vaccines and drugs and the conduction of clinical trials to fight the outbreak. Because of the time constraints associated with the development of vaccines and effective drugs, drug repurposing and other alternative treatment methods have been used to treat patients that have been infected by the SARS-CoV-2 virus and have acquired COVID-19. Objective: The objective of this systematic scoping review is to provide an overview of the molecular mechanism of action of repurposed drugs or alternative treatment medicines used to attenuate COVID-19 disease. Method: The research articles or gray literature, including theses, government reports, and official news online, were identified from four databases and one search engine. The full content of a total of 160 articles that fulfilled our inclusion criteria was analyzed and information about six drugs (ritonavir, lopinavir, oseltamivir, remdesivir, favipiravir, and chloroquine) and four Traditional Chinese Medicines (Shuang Huang Lian Kou Fu Ye, TCM combination of Bu Huan Jin Zheng Qi San and Da Yuan Yin, Xue Bi Jing Injection, and Qing Fei Pai Du Tang) was extracted. Results: All of the repurposed drugs and complementary medicine that have been used for the treatment of COVID-19 depend on the ability of the drug to inhibit the proliferation of the SARS-CoV-2 virus by binding to enzyme active sites, viral chain termination, or triggering of the molecular pathway, whereas Traditional Chinese Medicine plays a pivotal role in triggering the inflammation pathway, such as the neuraminidase blocker, to fight the SARS-CoV-2 virus.

Genetic profiles of 103,106 individuals in the Taiwan Biobank provide insights into the health and history of Han Chinese

Personalized medical care focuses on prediction of disease risk and response to medications. To build the risk models, access to both large-scale genomic resources and human genetic studies is required. The Taiwan Biobank (TWB) has generated high-coverage, whole-genome sequencing data from 1492 individuals and genome-wide SNP data from 103,106 individuals of Han Chinese ancestry using custom SNP arrays. Principal components analysis of the genotyping data showed that the full range of Han Chinese genetic variation was found in the cohort. The arrays also include thousands of known functional variants, allowing for simultaneous ascertainment of Mendelian disease-causing mutations and variants that affect drug metabolism. We found that 21.2% of the population are mutation carriers of autosomal recessive diseases, 3.1% have mutations in cancer-predisposing genes, and 87.3% carry variants that affect drug response. We highlight how TWB data provide insight into both population history and disease burden, while showing how widespread genetic testing can be used to improve clinical care.

Identification of ancestry proportions in admixed groups across the Americas using clinical pharmacogenomic SNP panels

We evaluated the performance of three PGx panels to estimate biogeographical ancestry: the DMET panel, and the VIP and Preemptive PGx panels described in the literature. Our analysis indicate that the three panels capture quite well the individual variation in admixture proportions observed in recently admixed populations throughout the Americas, with the Preemptive PGx and DMET panels performing better than the VIP panel. We show that these panels provide reliable information about biogeographic ancestry and can be used to guide the implementation of PGx clinical decision-support (CDS) tools. We also report that using these panels it is possible to control for the effects of population stratification in association studies in recently admixed populations, as exemplified with a warfarin dosing GWA study in a sample from Brazil.

Study of Adverse Effect Profile of Zoledronic Acid Infusion Among Patients with Cancer: A Retrospective Analysis

Background: Zoledronic acid (ZA) is widely used in the management of cancer-related bone events. It, however, might be associated with serious adverse effects. Objectives: To evaluate ZA adverse effects and changes in biochemical parameters related to ZA toxicities among patients with cancer. Methods: Ninety-eight oncology patients, who were prescribed ZA intravenous (IV) infusion, were interviewed to assess whether they experienced ZA related symptoms, including acute events and serious adverse effects. ZA’s effects on the serum levels of different biochemical parameters were retrospectively assessed by checking patients’ electronic medical records. Results: The most commonly reported adverse effects were: myalgia (48%), bone pain (36.7%), influenza-like symptoms (34.7%), headache (31.6%), and pyrexia (22.45%) with decreasing frequency of such adverse effects upon repeated infusions. Serious side effects including jaw osteonecrosis, cardiac, and renal problems were not reported. A small, but statistically significant reduction in serum calcium, creatinine, and total protein levels was observed upon comparing levels before and after the first IV infusion of ZA (P ≤ 0.031). No significant change was recorded with other serum electrolytes including phosphorus, sodium, potassium, and magnesium as well as urea levels (P ≥ 0.271). No significant difference was determined in terms of final serum levels of all parameters in comparison to pre-treatment (P ≥ 0.059), except for potassium, where a significant reduction was observed (P = 0.003). Notably, the mean values of all parameters were within the normal range. Conclusions: ZA acute events resolved with symptomatic treatment and reduced with repeated IV infusions. ZA appears as a safe treatment modality for skeletal-related events among patients with cancer and the reported adverse effects should not affect patients’ compliance.

Population structure and pharmacogenomic risk stratification in the United States

BACKGROUND

Pharmacogenomic (PGx) variants mediate how individuals respond to medication, and response differences among racial/ethnic groups have been attributed to patterns of PGx diversity. We hypothesized that genetic ancestry (GA) would provide higher resolution for stratifying PGx risk, since it serves as a more reliable surrogate for genetic diversity than self-identified race/ethnicity (SIRE), which includes a substantial social component. We analyzed a cohort of 8628 individuals from the United States (US), for whom we had both SIRE information and whole genome genotypes, with a focus on the three largest SIRE groups in the US: White, Black (African-American), and Hispanic (Latino). Our approach to the question of PGx risk stratification entailed the integration of two distinct methodologies: population genetics and evidence-based medicine. This integrated approach allowed us to consider the clinical implications for the observed patterns of PGx variation found within and between population groups.

RESULTS

Whole genome genotypes were used to characterize individuals' continental ancestry fractions-European, African, and Native American-and individuals were grouped according to their GA profiles. SIRE and GA groups were found to be highly concordant. Continental ancestry predicts individuals' SIRE with > 96% accuracy, and accordingly, GA provides only a marginal increase in resolution for PGx risk stratification. In light of the concordance between SIRE and GA, taken together with the fact that information on SIRE is readily available to clinicians, we evaluated PGx variation between SIRE groups to explore the potential clinical utility of race and ethnicity. PGx variants are highly diverged compared to the genomic background; 82 variants show significant frequency differences among SIRE groups, and genome-wide patterns of PGx variation are almost entirely concordant with SIRE. The vast majority of PGx variation is found within rather than between groups, a well-established fact for almost all genetic variants, which is often taken to argue against the clinical utility of population stratification. Nevertheless, analysis of highly differentiated PGx variants illustrates how SIRE partitions PGx variation based on groups' characteristic ancestry patterns. These cases underscore the extent to which SIRE carries clinically valuable information for stratifying PGx risk among populations, albeit with less utility for predicting individual-level PGx alleles (genotypes), supporting the concept of population pharmacogenomics.

CONCLUSIONS

Perhaps most interestingly, we show that individuals who identify as Black or Hispanic stand to gain far more from the consideration of race/ethnicity in treatment decisions than individuals from the majority White population.

Responsiveness to i.v. immunoglobulin therapy in patients with toxic epidermal necrolysis: A novel pharmaco-immunogenetic concept

Toxic epidermal necrolysis (TEN) represents a rare drug-induced autoimmune reaction with delayed-type hypersensitivity that initiates the process of developing massive keratinocyte apoptosis, dominantly in the dermoepidermal junction. Although the etiopathophysiology has not yet been fully elucidated, the binding of Fas ligand (FasL, CD95L) to the Fas receptor (CD95) was shown to play a key role in the induction of apoptosis in this syndrome. The knowledge of the role of immunoglobulin G (IgG) in inhibition of Fas-mediated apoptosis contributed to the introduction of i.v. Ig (IVIg) in the therapy of TEN patients. Despite great enthusiasm for this therapy at the end of the 1990s, subsequent studies in various populations and meta-analyses could not unequivocally confirm the efficacy of the IVIg-based treatment concept. Today, therefore, we are faced with the dilemmas of how to adjust therapy of TEN patients most effectively, which patients could benefit from IVIg therapy and what dose of the preparation should be administrated. The ground-breaking question is: do the host genetic profiles influence the responsiveness and side-effects of IVIg therapy in TEN patients? Based on recent pharmacological, immunological and genetic findings, we suggest that the variability of IVIg therapy outcomes in TEN patients may be related to functional variants in Fas, FasL and Fc-γ receptor genes. This novel concept could lead to improved quality of care for patients with TEN, facilitating personalized therapy to reduce mortality.

Costing Methods as a Means to Measure the Costs of Pharmacogenomics Testing

Clinical implementation of pharmacogenomics and personalized medicine interventions relies on addressing important financial aspects of the delivery of genetic testing to the patients, be it from public or private providers. Details on how to determine the cost items of the genetic testing are often limited. The goal of this study is to present a costing methodology in order to estimate and measure the costs as far as the technical process of pharmacogenomics testing is concerned. Moreover, an overall cost mindset strategy based on the selective genotyping workflow to guide specialized laboratories of interest effectively is provided. We particularly accounted for the resources consumed within the laboratory premises such as cost of reagents for DNA isolation, cost of consumables, cost of personnel, while costs associated with patient recruitment, blood sample collection and maintenance, administration costs in the hospital, and costs of blood sample shipment were not taken into consideration. Our article presents the first-time detailed information on a costing framework for pharmacogenomic testing that could be employed to laboratories involved in routine clinical implementation of pharmacogenomics.

Not your average joint: Towards precision medicine in psoriatic arthritis

Precision medicine, propelled by advances in multi-omics methods and analytics, aims to revolutionize patient care by using clinically-actionable molecular markers to guide diagnostic and therapeutic decisions. We describe the applications of precision medicine in risk stratification, drug selection, and treatment response prediction in psoriatic arthritis, for which targeted, personalized approaches are steadily emerging.

Pharmacogenomic genotypes define genetic ancestry in patients and enable population-specific genomic implementation

The importance of genetic ancestry characterization is increasing in genomic implementation efforts, and clinical pharmacogenomic guidelines are being published that include population-specific recommendations. Our aim was to test the ability of focused clinical pharmacogenomic SNP panels to estimate individual genetic ancestry (IGA) and implement population-specific pharmacogenomic clinical decision-support (CDS) tools. Principle components and STRUCTURE were utilized to assess differences in genetic composition and estimate IGA among 1572 individuals from 1000 Genomes, two independent cohorts of Caucasians and African Americans (AAs), plus a real-world validation population of patients undergoing pharmacogenomic genotyping. We found that clinical pharmacogenomic SNP panels accurately estimate IGA compared to genome-wide genotyping and identify AAs with ≥70 African ancestry (sensitivity >82%, specificity >80%, PPV >95%, NPV >47%). We also validated a new AA-specific warfarin dosing algorithm for patients with ≥70% African ancestry and implemented it at our institution as a novel CDS tool. Consideration of IGA to develop an institutional CDS tool was accomplished to enable population-specific pharmacogenomic guidance at the point-of-care. These capabilities were immediately applied for guidance of warfarin dosing in AAs versus Caucasians, but also provide a real-world model that can be extended to other populations and drugs as actionable genomic evidence accumulates.

Heterogeneity in the distribution of 159 drug-response related SNPs in world populations and their genetic relatedness

Interethnic variability in drug response arises from genetic differences associated with drug metabolism, action and transport. These genetic variations can affect drug efficacy as well as cause adverse drug reactions (ADRs). We retrieved drug-response related single nucleotide polymorphism (SNP) associated data from databases and analyzed to elucidate population specific distribution of 159 drug-response related SNPs in twenty six populations belonging to five super-populations (African, Admixed Americans, East Asian, European and South Asian). Significant interpopulation differences exist in the minor (variant) allele frequencies (MAFs), linkage disequilibrium (LD) and haplotype distributions among these populations. 65 of the drug-response related alleles, which are considered as minor (variant) in global population, are present as the major alleles (frequency ≥0.5) in at least one or more populations. Populations that belong to the same super-population have similar distribution pattern for majority of the variant alleles. These drug response related variant allele frequencies and their pairwise LD measure (r²) can clearly distinguish the populations in a way that correspond to the known evolutionary history of human and current geographic distributions, while D' cannot. The data presented here may aid in identifying drugs that are more appropriate and/or require pharmacogenetic testing in these populations. Our findings emphasize on the importance of distinct, ethnicity-specific clinical guidelines, especially for the African populations, to avoid ADRs and ensure effective drug treatment.

Towards precision medicine: interrogating the human genome to identify drug pathways associated with potentially functional, population-differentiated polymorphisms

Drug response variations amongst different individuals/populations are influenced by several factors including allele frequency differences of single nucleotide polymorphisms (SNPs) that functionally affect drug-response genes. Here, we aim to identify drugs that potentially exhibit population differences in response using SNP data mining and analytics. Ninety-one pairwise-comparisons of >22,000,000 SNPs from the 1000 Genomes Project, across 14 different populations, were performed to identify ‘population-differentiated’ SNPs (pdSNPs). Potentially-functional pdSNPs (pf-pdSNPs) were then selected, mapped into genes, and integrated with drug–gene databases to identify ‘population-differentiated’ drugs enriched with genes carrying pf-pdSNPs. 1191 clinically-approved drugs were found to be significantly enriched (Z > 2.58) with genes carrying SNPs that were differentiated in one or more population-pair comparisons. Thirteen drugs were found to be enriched with such differentiated genes across all 91 population-pairs. Notably, 82% of drugs, which were previously reported in the literature to exhibit population differences in response were also found by this method to contain a significant enrichment of population specific differentiated SNPs. Furthermore, drugs with genetic testing labels, or those suspected to cause adverse reactions, contained a significantly larger number (P < 0.01) of population-pairs with enriched pf-pdSNPs compared with those without these labels. This pioneering effort at harnessing big-data pharmacogenomics to identify ‘population differentiated’ drugs could help to facilitate data-driven decision-making for a more personalized medicine.

EFFICACY AND SAFETY OF IGLARLIXI IN HISPANICS AND NON-HISPANIC WHITES WITH TYPE 2 DIABETES

Objective: Type 2 diabetes (T2D) is more common in Hispanic than non-Hispanic white (NHW) populations worldwide, and ethnicity, among other factors, may affect response to therapy. The efficacy and safety of insulin glargine 100 units/mL (iGlar) and the fixed-ratio combination of iGlar and the glucagon-like peptide 1 receptor agonist lixisenatide (iGlarLixi) was assessed in Hispanic and NHW patients with T2D from 25 countries. Methods: In this post hoc analysis, data from two 30-week randomized controlled trials comparing iGlar and iGlarLixi in patients with T2D uncontrolled on basal insulin ± oral antidiabetes drugs (OADs; LixiLan-L: NCT02058160) or uncontrolled on metformin ± OADs (LixiLan-O: NCT02058147) were evaluated. Results: Of the 1,512 patients included across trials, 301 were Hispanic and 1,211 NHW. Compared with iGlar, iGlarLixi resulted in greater reductions in glycated hemoglobin (A1C) and 2-hour postprandial glucose and a higher proportion of patients at target A1C <7.0% (<53 mmol/mol), regardless of ethnicity. Among NHWs from the LixiLan-L trial, documented symptomatic hypoglycemia (plasma glucose ≤70 mg/dL) rates were higher with iGlar compared with iGlarLixi (P = .06), whereas this trend was reversed among Hispanics (P = .07). Nevertheless, in both trials, a greater proportion of patients taking iGlarLixi than iGlar reached the composite efficacy endpoints of target A1C without hypoglycemia and target A1C without weight gain, regardless of ethnicity. Conclusion: These results indicate that iGlarLixi is a viable therapeutic option for both Hispanic and NHW patients with T2D, as it is efficacious without a significant increase in hypoglycemia, irrespective of ethnicity. Abbreviations: A1C = glycated hemoglobin; BMI = body mass index; FPG = fasting plasma glucose; FRC = fixed-ratio combination; GLP-1 RA = glucagon-like peptide 1 receptor agonist; HDL-C = high-density-lipoprotein cholesterol; iGlar = insulin glargine; iGlarLixi = insulin glargine + lixisenatide; LDL-C = low-density-lipoprotein cholesterol; NHW = non-Hispanic white; OAD = oral antidiabetes drug; PPG = postprandial glucose; T2D = type 2 diabetes.

Population Pharmacogenomics for Precision Public Health in Colombia

While genomic approaches to precision medicine hold great promise, they remain prohibitively expensive for developing countries. The precision public health paradigm, whereby healthcare decisions are made at the level of populations as opposed to individuals, provides one way for the genomics revolution to directly impact health outcomes in the developing world. Genomic approaches to precision public health require a deep understanding of local population genomics, which is still missing for many developing countries. We are investigating the population genomics of genetic variants that mediate drug response in an effort to inform healthcare decisions in Colombia. Our work focuses on two neighboring populations with distinct ancestry profiles: Antioquia and Chocó. Antioquia has primarily European genetic ancestry followed by Native American and African components, whereas Chocó shows mainly African ancestry with lower levels of Native American and European admixture. We performed a survey of the global distribution of pharmacogenomic variants followed by a more focused study of pharmacogenomic allele frequency differences between the two Colombian populations. Worldwide, we found pharmacogenomic variants to have both unusually high minor allele frequencies and high levels of population differentiation. A number of these pharmacogenomic variants also show anomalous effect allele frequencies within and between the two Colombian populations, and these differences were found to be associated with their distinct genetic ancestry profiles. For example, the C allele of the single nucleotide polymorphism (SNP) rs4149056 [Solute Carrier Organic Anion Transporter Family Member 1B1 (SLCO1B1)^∗5], which is associated with an increased risk of toxicity to a commonly prescribed statin, is found at relatively high frequency in Antioquia and is associated with European ancestry. In addition to pharmacogenomic alleles related to increased toxicity risk, we also have evidence that alleles related to dosage and metabolism have large frequency differences between the two populations, which are associated with their specific ancestries. Using these findings, we have developed and validated an inexpensive allele-specific PCR assay to test for the presence of such population-enriched pharmacogenomic SNPs in Colombia. These results serve as an example of how population-centered approaches to pharmacogenomics can help to realize the promise of precision medicine in resource-limited settings.

Genetic polymorphisms of organic cation transporters 1 (OCT1) and responses to metformin therapy in individuals with type 2 diabetes mellitus: a systematic review protocol

BACKGROUND

Metformin is one of the most commonly used drugs for type 2 diabetes mellitus (T2DM). Despite its efficacy and safety, metformin is frequently associated with highly variable glycemic responses, which is hypothesized to be the result of genetic variations in its transport by organic cation transporters (OCTs). This systematic review aims to highlight and summarize the overall effects of OCT1 polymorphisms on therapeutic responses to metformin and to evaluate their potential role in terms of interethnic differences with metformin responses.

METHODS/DESIGN

We will systematically review observational studies reporting on the genetic association between OCT1 polymorphisms and metformin responses in T2DM patients. A comprehensive search strategy formulated with the help of a librarian will be used to search MEDLINE via PubMed, Embase, and CINAHL for relevant studies published between January 1990 and July 2017. Two review authors will independently screen titles and abstracts in duplicate, extract data, and assess the risk of bias with discrepancies resolved by discussion or arbitration of a third review author. Mined data will be grouped according to OCT1 polymorphisms, and their effects on therapeutic responses to metformin will be narratively synthesized. If sufficient numbers of homogeneous studies are scored, meta-analyses will be performed to obtain pooled effect estimates. Funnel plots analysis and Egger's test will be used to assess publication bias. This study will be reported according to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines.

DISCUSSION

This review will summarize the genetic effects of OCT1 polymorphisms associated with variabilities in glycemic responses to metformin. The findings of this study could help to develop genetic tests that could predict a person's response to metformin treatment and create personalized drugs with greater efficacy and safety.

SYSTEMATIC REVIEW REGISTRATION

Registration number: PROSPERO, CRD42017079978.

Genetic polymorphisms of organic cation transporter 1 (OCT1) and responses to metformin therapy in individuals with type 2 diabetes: A systematic review

BACKGROUND

Metformin is one of the most commonly used drugs for the treatment of type 2 diabetes mellitus (T2DM). Despite its widespread use, there are considerable interindividual variations in metformin response, with about 35% of patients failing to achieve initial glycemic control. These variabilities that reflect phenotypic differences in drug disposition and action may indeed be due to polymorphisms in genes that regulate pharmacokinetics and pharmacodynamics of metformin. Moreover, interethnic differences in drug responses in some cases correspond to substantial differences in the frequencies of the associated pharmacogenomics risk allele.

AIM

This study aims to highlight and summarize the overall effects of organic cation transporter 1(OCT1) polymorphisms on therapeutic responses to metformin and to evaluate the potential role of such polymorphisms in interethnic differences in metformin therapy.

METHODS

We conducted a systematic review according to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. We searched for PubMed/MEDLINE, Embase, and CINAHL, relevant studies reporting the effects of OCT1 polymorphisms on metformin therapy in T2DM individuals. Data were extracted on study design, population characteristics, relevant polymorphisms, measure of genetic association, and outcomes. The presence of gastrointestinal side effects, glycated hemoglobin A1 (HbA1c) levels, fasting plasma glucose (FPG), and postprandial plasma glucose (PPG) concentrations after treatment with metformin were chosen as measures of the metformin responses. This systematic review protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO).

RESULTS

According to the data extracted, a total of 34 OCT1 polymorphisms were identified in 10 ethnic groups. Significant differences in the frequencies of common alleles were observed among these groups. Met408Val (rs628031) variant was the most extensively explored with metformin responses. Although some genotypes and alleles have been associated with deleterious effects on metformin response, others indeed, exhibited positive effects.

CONCLUSION

Genetic effects of OCT1 polymorphisms on metformin responses were population specific. Further investigations in other populations are required to set ethnicity-specific reference for metformin responses and to obtain a solid basis to design personalized therapeutic approaches for T2DM treatment.