The genetic basis of variability in drug responses

MALDI-TOF MS-based SNP assay used to determine the appropriate antidepression for Chinese patients

Medicine remains the preferred primary treatment for depression, although some patients show remarkable individual variations in achieving satisfactory clinical outcomes during medication. Genetic polymorphisms cause approximately 40 % of individual differences in treatment response. Therefore, this study aimed to develop a technique to identify single nucleotide polymorphisms (SNPs) associated with the metabolism, effectiveness, and side effects of antidepressant medications in Chinese patients. Bibliometrics was used to search literature related to "depression" and "SNP" in Web of Science. The obtained SNP information was screened using the PharmGKB database. By designing and optimizing primers and conducting a compound amplification system, a method was established based on MALDI-TOF MS to detect polymorphisms associated with the antidepressant drugs, including sertraline, fluoxetine, citalopram, escitalopram, venlafaxine, fluvoxamine, paroxetine, and mirtazapine. The accuracy and sensitivity of the established method were verified by Sanger sequencing. A total of 10,043 articles were screened from the database, and 46 SNPs with a mutation frequency of >1 % in Asian populations and annotated with relevant clinical drugs were extracted from the PharmGKB database. This method was compared with the results of Sanger sequencing, and the accuracy of the detection results was 100 %. The MALDI-TOF MS-based SNP assay developed in this study can be a fast, convenient and effective way for patients to find the right medication for themselves. Moreover, we found that this SNP assay holds the promise of being a potential reference tool for assessing individualised differences in drug efficacy, not only for screening the causes of poor antidepressant efficacy in patients after taking medication, but also for advising physicians to understand individualised differences in drug efficacy.

Enhancing wound healing through deep reinforcement learning for optimal therapeutics

Finding the optimal treatment strategy to accelerate wound healing is of utmost importance, but it presents a formidable challenge owing to the intrinsic nonlinear nature of the process. We propose an adaptive closed-loop control framework that incorporates deep learning, optimal control and reinforcement learning to accelerate wound healing. By adaptively learning a linear representation of nonlinear wound healing dynamics using deep learning and interactively training a deep reinforcement learning agent for tracking the optimal signal derived from this representation without the need for intricate mathematical modelling, our approach has not only successfully reduced the wound healing time by 45.56% compared to the one without any treatment, but also demonstrates the advantages of offering a safer and more economical treatment strategy. The proposed methodology showcases a significant potential for expediting wound healing by effectively integrating perception, predictive modelling and optimal adaptive control, eliminating the need for intricate mathematical models.

Structure-activity relationships andz interindividual variability of drug responses: pharmacogenomics with antimicrobial drugs as a paradigm

Adverse drug reactions represent a major health burden because they cause notable patient morbidity and mortality. From this viewpoint, several strategies have been developed to prevent or reduce adverse drug reactions. One such strategy is the use of pharmacogenomics. Interindividual variability in drug response and adverse effects is mainly attributable to genetic variation in enzymes such as sulfotransferases and cytochrome P450s. The current narrative review discusses the relationship between the structure and activity of drugs. Specifically, the activity of drugs can be increased and/or their adverse effects can be reduced by altering specific positions in their structures.

Clinical outcomes of chemotherapy in cancer patients with different ethnicities

BACKGROUND

Choosing the most effective chemotherapeutic agent with safest side effect profile is a common challenge in cancer treatment. Although there are standardized chemotherapy protocols in place, protocol changes made after extensive clinical trials demonstrate significant improvement in the efficacy and tolerability of certain drugs. The pharmacokinetics, pharmacodynamics, and tolerance of anti-cancer medications are all highly individualized. A driving force behind these differences lies within a person's genetic makeup.

RECENT FINDINGS

Pharmacogenomics, the study of how an individual's genes impact the processing and action of a drug, can optimize drug responsiveness and reduce toxicities by creating a customized medication regimen. However, these differences are rarely considered in the initial determination of standardized chemotherapeutic protocols and treatment algorithms. Because pharmacoethnicity is influenced by both genetic and nongenetic variables, clinical data highlighting disparities in the frequency of polymorphisms between different ethnicities is steadily growing.  Recent data suggests that ethnic variations in the expression of allelic variants may result in different pharmacokinetic properties of the anti-cancer medication. In this article, the clinical outcomes of various chemotherapy classes in patients of different ethnicities were reviewed.

CONCLUSION

Genetic and nongenetic variables contribute to the interindividual variability in response to chemotherapeutic drugs. Considering pharmacoethnicity in the initial determination of standard chemotherapeutic protocols and treatment algorithms can lead to better clinical outcomes of patients of different ethnicities.

Can Kidney Organoid Xenografts Accelerate Therapeutic Development for Genetic Kidney Disorders?

A number of genetic kidney diseases can now be replicated experimentally, using kidney organoids generated from human pluripotent stem cells. This methodology holds great potential for drug discovery. Under in vitro conditions, however, kidney organoids remain developmentally immature, develop scarce vasculature, and may contain undesired off-target cell types. Those critical deficiencies limit their potential as disease-modeling tools. Orthotopic transplantation under the kidney capsule improves the anatomic maturity and vascularization of kidney organoids, while reducing off-target cell content. The improvements can translate into more accurate representations of disease phenotypes and mechanisms in vivo . Recent studies using kidney organoid xenografts highlighted the unique potential of this novel methodology for elucidating molecular mechanisms driving monogenic kidney disorders and for the development ofnovel pharmacotherapies.

Algorithmic lifestyle optimization

OBJECTIVE

A hallmark of personalized medicine and nutrition is to identify effective treatment plans at the individual level. Lifestyle interventions (LIs), from diet to exercise, can have a significant effect over time, especially in the case of food intolerances and allergies. The large set of candidate interventions, make it difficult to evaluate which intervention plan would be more favorable for any given individual. In this study, we aimed to develop a method for rapid identification of favorable LIs for a given individual.

MATERIALS AND METHODS

We have developed a method, algorithmic lifestyle optimization (ALO), for rapid identification of effective LIs. At its core, a group testing algorithm identifies the effectiveness of each intervention efficiently, within the context of its pertinent group.

RESULTS

Evaluations on synthetic and real data show that ALO is robust to noise, data size, and data heterogeneity. Compared to the standard of practice techniques, such as the standard elimination diet (SED), it identifies the effective LIs 58.9%-68.4% faster when used to discover an individual's food intolerances and allergies to 19-56 foods.

DISCUSSION

ALO achieves its superior performance by: (1) grouping multiple LIs together optimally from prior statistics, and (2) adapting the groupings of LIs from the individual's subsequent responses. Future extensions to ALO should enable incorporating nutritional constraints.

CONCLUSION

ALO provides a new approach for the discovery of effective interventions in nutrition and medicine, leading to better intervention plans faster and with less inconvenience to the patient compared to SED.

Integrating pharmacogenomics into clinical trials of hearing disorders

In 2019, the U.S. Food and Drug Administration issued guidance to increase the efficiency of drug development and support precision medicine, including tailoring treatments to those patients who will benefit based on genetic variation even in the absence of a documented mechanism of action. Although multiple advancements have been made in the field of pharmacogenetics (PGx) for other disease conditions, there are no approved PGx guidelines in the treatment of hearing disorders. In studies of noise-induced hearing loss (NIHL), some progress has been made in the last several years associating genomic loci with susceptibility to noise damage. However, the power of such studies is limited as the underlying physiological responses may vary considerably among the patient populations. Here, we have summarized previous animal studies to argue that NIHL subtyping is a promising strategy to increase the granularity of audiological assessments. By coupling this enhanced phenotyping capability with genetic association studies, we suggest that drug efficacy will be better predicted, increasing the likelihood of success in clinical trials when populations are stratified based on genetic variation or designed with multidrug combinations to reach a broader segment of individuals suffering or at risk from NIHL.

Pharmacogenomics polygenic risk score for drug response prediction using PRS-PGx methods

Polygenic risk scores (PRS) have been successfully developed for the prediction of human diseases and complex traits in the past years. For drug response prediction in randomized clinical trials, a common practice is to apply PRS built from a disease genome-wide association study (GWAS) directly to a corresponding pharmacogenomics (PGx) setting. Here, we show that such an approach relies on stringent assumptions about the prognostic and predictive effects of the selected genetic variants. We propose a shift from disease PRS to PGx PRS approaches by simultaneously modeling both the prognostic and predictive effects and further make this shift possible by developing a series of PRS-PGx methods, including a novel Bayesian regression approach (PRS-PGx-Bayes). Simulation studies show that PRS-PGx methods generally outperform the disease PRS methods and PRS-PGx-Bayes is superior to all other PRS-PGx methods. We further apply the PRS-PGx methods to PGx GWAS data from a large cardiovascular randomized clinical trial (IMPROVE-IT) to predict treatment related LDL cholesterol reduction. The results demonstrate substantial improvement of PRS-PGx-Bayes in both prediction accuracy and the capability of capturing the treatment-specific predictive effects while compared with the disease PRS approaches.

To try to predict an individual’s drug response using genetic data, most studies have used traditional polygenic risk score (PRS) methods. Here, the authors develop a pharmacogenomics-specific PRS method, which can improve drug response prediction and patient stratification in pharmacogenomics studies.

Molecular Variants in Genes related to the Response to Ocular Hypotensive Drugs in an Afro-Colombian Population

Aims:

This study aimed to conduct an exploratory analysis of the pharmacogenomic variants involved in ocular hypotensive drugs to understand the individual differential response in an Afro-descendant population.

Background:

Glaucoma is the leading cause of irreversible blindness worldwide. The pharmacologic treatment available consists of lowering intraocular pressure by administering topical drugs. In Asian and Caucasian people, pharmacogenomic variants associated with the efficacy of these treatments have been identified. However, in Afro-descendant populations, there is a profound gap in this knowledge.

Objective:

This study identified the pharmacogenomic variants related to ocular hypotensive efficacy treatment in Afro-descendant individuals from the Archipelago of San Andres and Providence, Colombia.

Methods:

An analysis of whole-exome sequencings (WES), functional annotation, and clinical significance was performed for pharmacogenomic variants reported in PharmGKB databases; in turn, an in silico available prediction analysis was carried out for the novel variants.

Results:

We identified six out of 18 non-synonymous variants with a clinical annotation in PharmGKB. Five were classified as level three evidence for the hypotensive drugs; rs1801252 and rs1801253 in the ADRB1 gene and rs1042714 in the ADRB2 gene. These pharmacogenomic variants have been involved in a lack of efficacy of topical beta-blockers and higher systolic and diastolic pressure under treatment with ophthalmic timolol drug. The rs1045642 in the ABCB1 gene was associated with greater efficacy of treatments with latanoprost drug. Also, we found the haplotypes *17 for CYP2D6 and *10 for CYP2C19; both related to reducing the enzyme activity to timolol drug metabolization. In addition, we observed 50 novel potentially actionable variants; 36 synonymous, two insertion variants that caused frameshift mutations, and 12 non-synonymous, where five were predicted to be pathogenic based on several pathogenicity predictions.

Conclusion:

Our results suggested that the pharmacogenomic variants were found to decrease the ocular hypotensive efficacy treatment in a Colombian Afro-descendant population and revealed a significant proportion of novel variants with a potential to influence drug response.

Association of cytochromes P450 3A4*22 and 3A5*3 genotypes and polymorphism with response to simvastatin in hypercholesterolemia patients

BACKGROUNDS

Inter-individual variability in response to statin was mainly due to genetic differences. This study aimed to investigate the association of CYP3A4*22 (rs35599367), CYP3A5*3 (rs776746) single nucleotide polymorphism (SNP) with response to simvastatin in hypercholesterolemia patients conducted at King Abdulaziz University hospital (KAUH) in Jeddah, Saudi Arabia.

PATIENTS AND METHODS

A total of 274 participants were registered in the current study. Hypercholesterolemic patients taking simvastatin 20 mg (n = 148) and control subjects (n = 126) were tested for rs35599367 and rs776746 genotypes using Custom Taqman ® Assay Probes. Response to simvastatin in these patients was assessed by determination of low density lipoprotein (LDL-C), total cholesterol (TC) and by measuring statin plasma levels using Liquid Chromatography-Mass Spectrometry (LC-MS).

RESULTS

None of the participants carried a homozygous CYP3A4*22 mutant genotype, while 12 (4.4%) individuals had a heterozygous genotype and 262 (95.6%) had a wild homozygous genotype. The CYP3A5*3 allele was detected in the homozygous mutant form in 16 (5.8%) individuals, while 74 (27.0%) individuals carried the heterozygous genotype and 184 (67.2%) carried the wildtype homozygous genotype. Of the patient group, 15 (11%) were classified as intermediate metabolizers (IMs) and 133 (89%) as extensive metabolizers (EMs). Plasma simvastatin concentrations for the combined CYP3A4/5 genotypes were significantly (P<0.05) higher in the IMs group than in the EMs group. TC and plasma LDL-C levels were also significantly (P<0.05) higher in IMs than in EMs.

CONCLUSION

The present study showed associations between CYP3A4*22 (rs35599367) and CYP3A5*3 (rs776746) SNP combination genotypes with response to statins in hypercholesterolemia. Patients who had either a mutant homozygous allele for CYP3A5*3 or mutant homozygous and heterozygous alleles for CYP3A4*22 showed increased response to lower TC and LDL-C levels.

Quantitative Proteomics in Translational Absorption, Distribution, Metabolism, and Excretion and Precision Medicine

A reliable translation of in vitro and preclinical data on drug absorption, distribution, metabolism, and excretion (ADME) to humans is important for safe and effective drug development. Precision medicine that is expected to provide the right clinical dose for the right patient at the right time requires a comprehensive understanding of population factors affecting drug disposition and response. Characterization of drug-metabolizing enzymes and transporters for the protein abundance and their interindividual as well as differential tissue and cross-species variabilities is important for translational ADME and precision medicine. This review first provides a brief overview of quantitative proteomics principles including liquid chromatography-tandem mass spectrometry tools, data acquisition approaches, proteomics sample preparation techniques, and quality controls for ensuring rigor and reproducibility in protein quantification data. Then, potential applications of quantitative proteomics in the translation of in vitro and preclinical data as well as prediction of interindividual variability are discussed in detail with tabulated examples. The applications of quantitative proteomics data in physiologically based pharmacokinetic modeling for ADME prediction are discussed with representative case examples. Finally, various considerations for reliable quantitative proteomics analysis for translational ADME and precision medicine and the future directions are discussed. SIGNIFICANCE STATEMENT: Quantitative proteomics analysis of drug-metabolizing enzymes and transporters in humans and preclinical species provides key physiological information that assists in the translation of in vitro and preclinical data to humans. This review provides the principles and applications of quantitative proteomics in characterizing in vitro, ex vivo, and preclinical models for translational research and interindividual variability prediction. Integration of these data into physiologically based pharmacokinetic modeling is proving to be critical for safe, effective, timely, and cost-effective drug development.

Pharmacogenomic landscape of Indian population using whole genomes

Ethnic differences in pharmacogenomic (PGx) variants have been well documented in literature and could significantly impact variability in response and adverse events to therapeutics. India is a large country with diverse ethnic populations of distinct genetic architecture. India's national genome sequencing initiative (IndiGen) provides a unique opportunity to explore the landscape of PGx variants using population-scale whole genome sequences. We have analyzed the IndiGen variation dataset (N = 1029 genomes) along with global population scale databases to map the most prevalent clinically actionable and potentially deleterious PGx variants among Indians. Differential frequencies for the known and novel variants were studied and interaction of the disrupted PGx genes affecting drug responses were analyzed by performing a pathway analysis. We have highlighted significant differences in the allele frequencies of clinically actionable PGx variants in Indians when compared to the global populations. We identified 134 mostly common (allele frequency [AF] > 0.1) potentially deleterious PGx variants that could alter or inhibit the function of 102 pharmacogenes in Indians. We also estimate that on, an average, each Indian individual carried eight PGx variants (single nucleotide variants) that have a direct impact on the choice of treatment or drug dosing. We have also highlighted clinically actionable PGx variants and genes for which preemptive genotyping is most recommended for the Indian population. The study has put forward the most comprehensive PGx landscape of the Indian population from whole genomes that could enable optimized drug selection and genotype-guided prescriptions for improved therapeutic outcomes and minimizing adverse events.

Pharmacogenetics of Drugs Used in the Treatment of Cancers

Pharmacogenomics is based on the understanding of the individual differences in drug use, the response to drug therapy (efficacy and toxicity), and the mechanisms underlying variable drug responses. The identification of DNA variants which markedly contribute to inter-individual variations in drug responses would improve the efficacy of treatments and decrease the rate of the adverse side effects of drugs. This review focuses only on the impact of polymorphisms within drug-metabolizing enzymes on drug responses. Anticancer drugs usually have a very narrow therapeutic index; therefore, it is very important to use appropriate doses in order to achieve the maximum benefits without putting the patient at risk of life-threatening toxicities. However, the adjustment of the appropriate dose is not so easy, due to the inheritance of specific polymorphisms in the genes encoding the target proteins and drug-metabolizing enzymes. This review presents just a few examples of such polymorphisms and their impact on the response to therapy.

Explorative Analysis of Treatment Outcomes of Levofloxacin- and Moxifloxacin-Based Regimens and Outcome Predictors in Ethiopian MDR-TB Patients: A Prospective Observational Cohort Study

Purpose/Background

Although Ethiopia is among the thirty high multi-drug resistant tuberculosis (MDR-TB) burden countries in the world, comparative therapeutic efficacy of moxifloxacin and levofloxacin has not been explored, particularly in MDR-TB patients. We therefore aimed to prospectively compare clinical outcomes and determine potential predictors of the outcomes among patients on moxifloxacin or levofloxacin-based MDR-TB drug regimens.

Methods

We analyzed clinical parameters and laboratory data of eighty MDR-TB patients on moxifloxacin- or levofloxacin-based regimens. The clinical outcomes were compared using the Kaplan–Meier survival functions and the outcome definitions of the 2013 World Health Organization. Monthly sputum culture conversions and a molecular line probe assay results were also assessed. Observed outcomes and patient-related variables between the two groups were compared using chi-square, Wilcoxon Rank and Fisher exact tests. We also determined the potential predictors influencing treatment outcomes of moxifloxacin and levofloxacin using Cox proportional hazard model.

Results

The levofloxacin-based treatment group had a lower failure rate and adverse drug events as well as better treatment success than the moxifloxacin-based group. Overall treatment success was 65%. Disaggregating the data revealed that 53.8% were cured, 11.2% completed treatment, 10.0% died, 11.2% failed, and 13.8% were lost-to-follow-up. The line probe assay result showed that 11.3% of the clinical isolates were resistant to fluoroquinolones and 3.8% were resistant to both fluoroquinolones and injectable anti-TB agents. Treatment regimen type, culture conversion rate, alcohol use, cavity lesion, serum levels of creatinine and alanine aminotransferase were independent predictors of treatment outcome.

Conclusion

The levofloxacin-based regimen group has a better overall treatment success than the moxifloxacin-based group among MDR-TB patients. Clinical parameters and substance use history of the patients influenced treatment outcomes. We recommend further broader clinical studies to substantiate our findings as an input to review MDR-TB treatment guidelines.

The Use of Drosophila to Understand Psychostimulant Responses

The addictive properties of psychostimulants such as cocaine, amphetamine, methamphetamine, and methylphenidate are based on their ability to increase dopaminergic neurotransmission in the reward system. While cocaine and methamphetamine are predominately used recreationally, amphetamine and methylphenidate also work as effective therapeutics to treat symptoms of disorders including attention deficit and hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). Although both the addictive properties of psychostimulant drugs and their therapeutic efficacy are influenced by genetic variation, very few genes that regulate these processes in humans have been identified. This is largely due to population heterogeneity which entails a requirement for large samples. Drosophila melanogaster exhibits similar psychostimulant responses to humans, a high degree of gene conservation, and allow performance of behavioral assays in a large population. Additionally, amphetamine and methylphenidate reduce impairments in fly models of ADHD-like behavior. Therefore, Drosophila represents an ideal translational model organism to tackle the genetic components underlying the effects of psychostimulants. Here, we break down the many assays that reliably quantify the effects of cocaine, amphetamine, methamphetamine, and methylphenidate in Drosophila. We also discuss how Drosophila is an efficient and cost-effective model organism for identifying novel candidate genes and molecular mechanisms involved in the behavioral responses to psychostimulant drugs.

NR3C2 genotype is associated with response to spironolactone in diastolic heart failure patients from the Aldo-DHF trial

STUDY OBJECTIVE

This study aimed to determine if variants in NR3C2, which codes the target protein of spironolactone, or CYP11B2, which is involved in aldosterone synthesis, were associated with spironolactone response, focused on the primary end point of diastolic function (E/e'), in Aldosterone Receptor Blockade in Diastolic Heart Failure (Aldo-DHF) participants.

DESIGN

Post-hoc genetic analysis.

DATA SOURCE

Data and samples were derived from the multi-center, randomized, double-blind, placebo-controlled Aldo-DHF trial.

PATIENTS

Aldo-DHF participants treated with spironolactone (n = 184) or placebo (n = 178) were included.

INTERVENTION

Participants were genotyped for NR3C2 rs5522, NR3C2 rs2070951 and CYP11B2 rs1799998 via pyrosequencing.

MEASUREMENTS

In the placebo and spironolactone arms, separate multivariable linear regression analyses were performed for change in E/e' with each single nucleotide polymorphism (SNP), adjusted for age, sex, and baseline E/e'. To discern potential mechanisms of a genotype effect, associated SNPs were further examined for their association with change in blood pressure, circulating procollagen type III N-terminal peptide (PIIINP), and left atrial area.

MAIN RESULTS

Carriers of the rs5522 G allele in the placebo arm had a greater increase in E/e' over the 12-month course of the trial compared to noncarriers (β = 1.10; 95% confidence interval [CI]: 0.05-2.16; p = 0.04). No corresponding E/e' worsening by rs5522 genotype was observed in the spironolactone arm. None of the other genotypes were associated with change in E/e'. Compared to noncarriers, rs5522 G carriers also had a greater increase in left atrial area with placebo (β = 0.83; 95% CI: 0.17-1.48; p = 0.01) and a greater reduction in diastolic blood pressure with spironolactone (β = -3.56; 95% CI: -6.73 to -0.39; p = 0.03). Serum PIIINP levels were similar across rs5522 genotypes.

CONCLUSIONS

Our results suggest that spironolactone attenuates progression of diastolic dysfunction associated with the NR3C2 rs5522 G allele. Validation of our findings is needed.

Development of Robust Quantitative Structure-Activity Relationship Models for CYP2C9, CYP2D6, and CYP3A4 Catalysis and Inhibition

Cytochrome P450 enzymes are responsible for the metabolism of >75% of marketed drugs, making it essential to identify the contributions of individual cytochromes P450 to the total clearance of a new candidate drug. Overreliance on one cytochrome P450 for clearance levies a high risk of drug-drug interactions; and considering that several human cytochrome P450 enzymes are polymorphic, it can also lead to highly variable pharmacokinetics in the clinic. Thus, it would be advantageous to understand the likelihood of new chemical entities to interact with the major cytochrome P450 enzymes at an early stage in the drug discovery process. Typical screening assays using human liver microsomes do not provide sufficient information to distinguish the specific cytochromes P450 responsible for clearance. In this regard, we experimentally assessed the metabolic stability of ∼5000 compounds for the three most prominent xenobiotic metabolizing human cytochromes P450, i.e., CYP2C9, CYP2D6, and CYP3A4, and used the data sets to develop quantitative structure-activity relationship models for the prediction of high-clearance substrates for these enzymes. Screening library included the NCATS Pharmaceutical Collection, comprising clinically approved low-molecular-weight compounds, and an annotated library consisting of drug-like compounds. To identify inhibitors, the library was screened against a luminescence-based cytochrome P450 inhibition assay; and through crossreferencing hits from the two assays, we were able to distinguish substrates and inhibitors of these enzymes. The best substrate and inhibitor models (balanced accuracies ∼0.7), as well as the data used to develop these models, have been made publicly available (https://opendata.ncats.nih.gov/adme) to advance drug discovery across all research groups. SIGNIFICANCE STATEMENT: In drug discovery and development, drug candidates with indiscriminate cytochrome P450 metabolic profiles are considered advantageous, since they provide less risk of potential issues with cytochrome P450 polymorphisms and drug-drug interactions. This study developed robust substrate and inhibitor quantitative structure-activity relationship models for the three major xenobiotic metabolizing cytochromes P450, i.e., CYP2C9, CYP2D6, and CYP3A4. The use of these models early in drug discovery will enable project teams to strategize or pivot when necessary, thereby accelerating drug discovery research.

Glutathione S-transferase M1 and T1 genes deletion polymorphisms and blood pressure control among treated essential hypertensive patients in Burkina Faso

OBJECTIVE

Glutathione S-transferases have been associated with experimental resistance to some drugs. The present study investigated the factors associated with blood pressure control in patients with essential hypertension, especially the role of GSTT1 and GSTM1 genes polymorphisms. This cross-sectional study in Burkina Faso consisted of 200 patients with essential hypertension and under treatment.

RESULTS

In the present study, 57.5% (115/200) of patients had their hypertension under control. No statistically significant difference was found between controlled and uncontrolled groups for anthropometric and biochemical parameters as well as for GSTT1 or GSTM1 gene polymorphisms (all p > 0.05). Current alcohol consumption (OR = 3.04; CI 1.88-6.13; p < 0.001), Physical inactivity (OR = 3.07; CI 1.71-5.49; p < 0.001), severe hypertension before any treatment (Grade III [OR = 3.79; CI 2.00-7.17; p < 0.001]) and heart damage (OR = 3, 14; CI 1.59-6.02; p < 0.001) were statistically more frequent in uncontrolled essential hypertensive patients than controlled hypertensive patients.

Pharmacogenetic Associations Between Atazanavir/UGT1A1*28 and Efavirenz/rs3745274 (CYP2B6) Account for Specific Adverse Reactions in Chilean Patients Undergoing Antiretroviral Therapy

Background: Efavirenz (EFV), a non-nucleoside reverse transcriptase inhibitor, and atazanavir (ATV), a protease inhibitor, are drugs widely used in antiretroviral therapy (ART) for people living with HIV. These drugs have shown high interindividual variability in adverse drug reactions (ADRs). UGT1A1*28 and CYP2B6 c.516G>T have been proposed to be related with higher toxicity by ATV and EFV, respectively. Objective: To study the association between genetic polymorphisms and ADRs related to EFV or ATV in patients living with HIV treated at a public hospital in Chile. Methods: Epidemiologic, case-control, retrospective, observational study in 67 adult patients under EFV or ATV treatment was conducted, in the San Juan de Dios Hospital. Data were obtained from patients' medical records. Genotype analyses were performed using rtPCR for rs887829 (indirect identification of UGT1A1*28 allele) and rs3745274 (CYP2B6 c.516G>T), with TaqMan® probes. The association analyses were performed with univariate logistic regression between genetic variants using three inheritance models (codominant, recessive, and dominant). Results: In ATV-treated patients, hyperbilirubinemia (total bilirubin >1.2 mg/dl) had the main incidence (61.11%), and moderate and severe hyperbilirubinemia (total bilirubin >1.9 mg/dl) were statistically associated with UGT1A1*28 in recessive and codominant inheritance models (OR = 16.33, p = 0.028 and OR = 10.82, p = 0.036, respectively). On the other hand, in EFV-treated patients adverse reactions associated with CNS toxicity reached 34.21%. In this respect, nightmares showed significant association with CYP2B6 c.516G>T, in codominant and recessive inheritance models (OR = 12.00, p = 0.031 and OR = 7.14, p = 0.042, respectively). Grouped CNS ADRs (nightmares, insomnia, anxiety, and suicide attempt) also showed a statistically significant association with CYP2B6 c.516G > T in the codominant and recessive models (OR = 30.00, p = 0.011 and OR = 14.99, p = 0.021, respectively). Conclusion: Our findings suggest that after treatment with ATV or EFV, UGT1A1*28 and CYP2B6 c.516G>T influence the appearance of moderate-to-severe hyperbilirubinemia and CNS toxicity, respectively. However, larger prospective studies will be necessary to validate these associations in our population. Without a doubt, improving adherence in patients living with HIV is a critical issue to the success of therapy. Hence, validating and applying international pharmacogenetic recommendations in Latin American countries would improve the precision of ART: a fundamental aspect to achieve the 95-95-95 treatment target proposed by UNAIDS.

Influence of low-dose aspirin, resistance exercise, and sex on human skeletal muscle PGE2 /COX pathway activity

Prostaglandin (PG) E2  has been linked to increased inflammation and attenuated resistance exercise adaptations in skeletal muscle. Nonaspirin cyclooxygenase (COX) inhibitors have been shown to reduce these effects. This study examined the effect of low-dose aspirin on skeletal muscle COX production of PGE2 at rest and following resistance exercise. Skeletal muscle (vastus lateralis) biopsies were taken from six individuals (4 M/2 W) before and 3.5 hr after a single bout of resistance exercise for ex vivo PGE2 production under control and low (10 μM)- or standard (100 μM)-dose aspirin conditions. Sex-specific effects of aspirin were also examined by combining the current findings with our previous similar ex vivo skeletal muscle investigations (n = 20, 10 M/10 W). Low-dose aspirin inhibited skeletal muscle PGE2 production (p < 0.05). This inhibition was similar to standard-dose aspirin (p > 0.05) and was not influenced by resistance exercise (p > 0.05) (overall effect: -18 ± 5%). Men and women had similar uninhibited skeletal muscle PGE2 production at rest (men: 1.97 ± 0.33, women: 1.96 ± 0.29 pg/mg wet weight/min; p > 0.05). However, skeletal muscle of men was 60% more sensitive to aspirin inhibition than women (p < 0.05). In summary, the current findings 1) confirm low-dose aspirin inhibits the PGE2 /COX pathway in human skeletal muscle, 2) show that resistance exercise does not alter aspirin inhibitory efficacy, and 3) suggest the skeletal muscle of men and women could respond differently to long-term consumption of low-dose aspirin, one of the most common chronically consumed drugs in the world.

Decoding variants in drug-metabolizing enzymes and transporters in solid tumor patients by whole-exome sequencing

Background

Pharmacogenetics is involved in customizing therapy according to the genetic makeup of an individual, and is applicable for chemotherapy, radiotherapy as well as targeted therapy. Drug metabolizing enzymes (DMEs) involving both phase I, and phase II reactions are widely studied. Our study was involved in whole exome sequencing (WES) of cancer patients, followed by analysis for identifying key variations in DMEs, and associated transporters that have a potential impact on treatment outcome.

Methodology

A total of 181 solid tumor patients at stage >/= III were subjected to WES by the SureSelect^XT Human All Exon V6 + UTR library preparation kit, and sequencing in the Illumina NextSeq 550 system. Bioinformatics analysis involved use of GATK pipeline, and the variants were further assessed for population frequency, functional impact with annovar insilico algorithms. Further variant information from significant DMEs, and transporters were extracted and analyzed with PharmGKB to assess level of evidence and infer their impact on the pathways involved in drug response.

Results

The total study cohort of 181 solid tumor patients included 60 males, and 121 females respectively. Among DMEs, deleterious mutation in dihydropyrimidine dehydrogenase (DPYD; rs67376798), solute carrier organic anion transporter family member 1B1 (SLCO1B1*5), and cytochrome P450 2D6 (CYP2D6*10) associated with metabolism of anticancer drugs was detected to be in high frequency of 26%, 21% and 25% respectively.

Conclusion

Our analysis detected variations in both phase I and phase II DMEs, as well as associated transporter genes which has been documented to reduce drug efficacy, as well as cause grade 3 and 4 toxicity. Our study reiterates the significance of pharmacogenomics in stratifying patients for appropriate therapy regimen focused at better treatment outcome and quality of life.

Cholinergic and dopaminergic effects on prediction error and uncertainty responses during sensory associative learning

Navigating the physical world requires learning probabilistic associations between sensory events and their change in time (volatility). Bayesian accounts of this learning process rest on hierarchical prediction errors (PEs) that are weighted by estimates of uncertainty (or its inverse, precision). In a previous fMRI study we found that low-level precision-weighted PEs about visual outcomes (that update beliefs about associations) activated the putative dopaminergic midbrain; by contrast, precision-weighted PEs about cue-outcome associations (that update beliefs about volatility) activated the cholinergic basal forebrain. These findings suggested selective dopaminergic and cholinergic influences on precision-weighted PEs at different hierarchical levels. Here, we tested this hypothesis, repeating our fMRI study under pharmacological manipulations in healthy participants. Specifically, we performed two pharmacological fMRI studies with a between-subject double-blind placebo-controlled design: study 1 used antagonists of dopaminergic (amisulpride) and muscarinic (biperiden) receptors, study 2 used enhancing drugs of dopaminergic (levodopa) and cholinergic (galantamine) modulation. Pooled across all pharmacological conditions of study 1 and study 2, respectively, we found that low-level precision-weighted PEs activated the midbrain and high-level precision-weighted PEs the basal forebrain as in our previous study. However, we found pharmacological effects on brain activity associated with these computational quantities only when splitting the precision-weighted PEs into their PE and precision components: in a brainstem region putatively containing cholinergic (pedunculopontine and laterodorsal tegmental) nuclei, biperiden (compared to placebo) enhanced low-level PE responses and attenuated high-level PE activity, while amisulpride reduced high-level PE responses. Additionally, in the putative dopaminergic midbrain, galantamine compared to placebo enhanced low-level PE responses (in a body-weight dependent manner) and amisulpride enhanced high-level precision activity. Task behaviour was not affected by any of the drugs. These results do not support our hypothesis of a clear-cut dichotomy between different hierarchical inference levels and neurotransmitter systems, but suggest a more complex interaction between these neuromodulatory systems and hierarchical Bayesian quantities. However, our present results may have been affected by confounds inherent to pharmacological fMRI. We discuss these confounds and outline improved experimental tests for the future.

Low-dose aspirin and COX inhibition in human skeletal muscle

Skeletal muscle health has been shown to benefit from regular consumption of cyclooxygenase (COX)-inhibiting drugs. Aspirin, especially at low doses, is one of the most commonly consumed COX inhibitors, yet investigations of low-dose aspirin effects on skeletal muscle are nonexistent. The goal of this study was to examine the efficacy of low-dose aspirin on skeletal muscle COX production of the inflammatory regulator prostaglandin (PG)E₂ at rest and after exercise. Skeletal muscle biopsies (vastus lateralis) were taken from eight individuals [4 men, 4 women; 25 ± 1 yr; 81.4 ± 3.4 kg; maximal oxygen consumption (V̇o_2max): 3.33 ± 0.21 L/min] before and 3.5 h after 40 min of cycling at 70% of V̇o_2max for the measurement of ex vivo PGE₂ production. Muscle strips were incubated in Krebs-Henseleit buffer (control) or supplemented with one of two aspirin concentrations that reflected blood levels after a low (10 µM; typical oral dose: 75-325 mg) or standard (100 µM; typical oral dose: 975-1,000 mg) dose. Low (-22 ± 5%)- and standard (-28 ± 5%)-dose aspirin concentrations both reduced skeletal muscle PGE₂ production, independent of exercise (P < 0.05). There was no difference in PGE₂ suppression between the two doses (P > 0.05). In summary, low-dose aspirin levels are sufficient to inhibit the COX enzyme in skeletal muscle and significantly reduce production of PGE₂, a known regulator of skeletal muscle health. Aerobic exercise does not appear to alter the inhibitory efficacy of aspirin. These findings may have implications for the tens of millions of individuals who chronically consume low-dose aspirin.NEW & NOTEWORTHY This study demonstrated that even low-dose aspirin concentrations can significantly reduce the prostaglandin (PG)E₂/cyclooxygenase (COX) pathway activity in human skeletal muscle and this effect is not altered during the recovery period following aerobic exercise. These findings are noteworthy since aspirin is one of the most commonly consumed drugs in the world and nonaspirin COX-inhibiting drugs have been shown to regulate skeletal muscle health in sedentary and exercise-training individuals.

Polygenic Score for β-Blocker Survival Benefit in European Ancestry Patients With Reduced Ejection Fraction Heart Failure

BACKGROUND

β-Blockers (BBs) are mainstay therapy for heart failure with reduced ejection fraction. However, individual patient responses to BB vary, which may be partially due to genetic variation. The goal of this study was to derive and validate the first polygenic response predictor (PRP) for BB survival benefit in heart failure with reduced ejection fraction patients.

METHODS

Derivation and validation analyses were performed in n=1436 total HF patients of European descent and with ejection fraction <50%. The PRP was derived in a random subset of the Henry Ford Heart Failure Pharmacogenomic Registry (n=248) and then validated in a meta-analysis of the remaining patients from Henry Ford Heart Failure Pharmacogenomic Registry (n=247), the TIME-CHF (Trial of Intensified Versus Standard Medical Therapy in Elderly Patients With Congestive Heart Failure; n=431), and HF-ACTION trial (Heart Failure: a Controlled Trial Investigating Outcomes of Exercise Training; n=510). The PRP was constructed from a genome-wide analysis of BB×genotype interaction predicting time to all-cause mortality, adjusted for Meta-Analysis Global Group in Chronic Heart Failure score, genotype, level of BB exposure, and BB propensity score.

RESULTS

Five-fold cross-validation summaries out to 1000 single-nucleotide polymorphisms identified optimal prediction with a 44 single-nucleotide polymorphism score and cutoff at the 30th percentile. In validation testing (n=1188), greater BB exposure was associated with reduced all-cause mortality in patients with low PRP score (n=251; hazard ratio, 0.19 [95% CI, 0.04-0.51]; P=0.0075) but not high PRP score (n=937; hazard ratio, 0.84 [95% CI, 0.53-1.3]; P=0.448)-a difference that was statistically significant (P interaction, 0.0235). Results were consistent regardless of atrial fibrillation, ejection fraction (≤40% versus 41%-50%), or when examining cardiovascular death.

CONCLUSIONS

Among patients of European ancestry with heart failure with reduced ejection fraction, a PRP distinguished patients who derived substantial survival benefit from BB exposure from a larger group that did not. Additional work is needed to prospectively test clinical utility and to develop PRPs for other population groups and other medications.

Approaching sites of action of drugs in clinical pharmacology: New analytical options and their challenges

Clinical pharmacology is an important discipline for drug development aiming to define pharmacokinetics (PK), pharmacodynamics (PD) and optimum exposure to drugs, i.e. the concentration-response relationship and its modulators. For this purpose, information on drug concentrations at the anatomical, cellular and molecular sites of action is particularly valuable. In pharmacological assays, the limited accessibility of target cells in readily available samples (i.e. blood) often hampers mass spectrometry-based monitoring of the absolute quantity of a compound and the determination of its molecular action at the cellular level. Recently, new sample collection methods have been developed for the specific capture of rare circulating cells, especially for the diagnosis of circulating tumour cells. In parallel, new advances and developments in mass spectrometric instrumentation now allow analyses to be scaled down to the cellular level. Together, these developments may permit the monitoring of minute drug quantities and show their effect at the cellular level. In turn, such PK/PD associations on a cellular level would not only enrich our pharmacological knowledge of a given compound but also expand the basis for PK/PD simulations. In this review, we describe novel concepts supporting clinical pharmacology at the anatomical, cellular and molecular sites of action, and highlight the new challenges in mass spectrometry-based monitoring. Moreover, we present methods to tackle these challenges and define future needs.

Cardiovascular Risk Management and Hepatitis C: Combining Drugs

Direct-acting antivirals (DAAs) are known victims (substrate) and perpetrators (cause) of drug–drug interactions (DDIs). These DAAs are used for the treatment of hepatitis C virus (HCV) infections and are highly effective drugs. Drugs used for cardiovascular risk management are frequently used by HCV-infected patients, whom also are treated with DAAs. Therefore, the aim of this review was to describe DDIs between cardiovascular drugs (CVDs) and DAAs. An extensive literature search was performed containing search terms for the marketed DAAs and CVDs (β-blocking agents, ACE inhibitors, angiotensin II antagonists, renin inhibitors, diuretics, calcium channel blockers, statins/ezetimibe, fibrates, platelet aggregation inhibitors, vitamin K antagonists, heparins, direct Xa inhibitors, nitrates, amiodarone, and digoxin). In particular, the drug labels from the European Medicines Agency and the US Food and Drug Administration were used. A main finding of this review is that CVDs are mostly victims of DDIs with DAAs. Therefore, when possible, monitoring of pharmacodynamics is recommended when coadministering these drugs with DAAs. Nevertheless, it is sometimes better to discontinue a drug on a temporary basis (statins, ezetimide). The DAAs are victims of DDIs in combination with bisoprolol, carvedilol, labetalol, verapamil, and gemfibrozil. Despite there are many DDIs predicted in this review, most of these DDIs can be managed by monitoring the efficacy and toxicity of the victim drug or by switching to another CVD/DAA.

Challenges in pharmacotherapy for older adults: a framework for pharmacogenomics implementation

Older adults are at high risk for inappropriate prescribing, developing polypharmacy, adverse drug events and poor treatment outcomes due to multimorbidity and geriatric syndromes. Pharmacogenomics could allow healthcare professionals to provide optimal patient care while minimizing the risk of adverse drug events and simplifying complex medication regimens. The implementation of pharmacogenomics in geriatrics medicine requires a broad multilayered bottom-up approach. These include curriculum redesign, rethinking experiential education and patient and provider education. There are barriers associated with adopting pharmacogenomics into clinical practice. These barriers may include economic factors, workflow and informatics support. However, addressing these barriers primarily requires creating a culture of innovative practices in patient care, ongoing interprofessional continuing education and an interdisciplinary approach for patient care.

Computational Methods for the Integrative Analysis of Genomics and Pharmacological Data

Since the pioneering NCI-60 panel of the late'80's, several major screenings of genetic profiling and drug testing in cancer cell lines have been conducted to investigate how genetic backgrounds and transcriptional patterns shape cancer's response to therapy and to identify disease-specific genes associated with drug response. Historically, pharmacogenomics screenings have been largely heterogeneous in terms of investigated cell lines, assay technologies, number of compounds, type and quality of genomic data, and methods for their computational analysis. The analysis of this enormous and heterogeneous amount of data required the development of computational methods for the integration of genomic profiles with drug responses across multiple screenings. Here, we will review the computational tools that have been developed to integrate cancer cell lines' genomic profiles and sensitivity to small molecule perturbations obtained from different screenings.

NOS3 Deletion in Cav1 Deficient Mice Decreases Drug Sensitivity to a Nitric Oxide Donor and Two Nitric Oxide Synthase Inhibitors

Purpose

This study aims to investigate the pharmacologic consequence of genetic deletion of nitric oxide synthase 3 (NOS3) in caveolin 1 (Cav1)-/- mice (double knockout [DKO]) in response to a nitric oxide (NO) donor and two NOS inhibitors.

Methods

NO donor sodium nitroprusside (SNP; 10-40 mg/mL), NOS inhibitor L-NG-nitroarginine methyl ester (L-NAME; 10-200 μM), and cavtratin (10-75 μM ) was administered topically to the eye while the contralateral eyes were vehicle controls. Intraocular pressure (IOP) was measured in both eyes by tonometry. Cyclic guanosine monophosphate (cGMP) level in outflow tissue was measured by ELISA assay. Protein expression were analyzed by western blot.

Results

Inducible NOS (iNOS) expression significantly increased in the DKO mice compared with the wild type (WT), Cav1 knockout (Cav1 KO), and NOS3 KO mice. In contrast to WT, Cav1 KO and NOS3 KO mice, SNP concentration of up to 30 mg/mL did not significantly affect IOP in DKO mice. However, higher concentration (40 mg/mL) SNP significantly reduced IOP by 14% (n = 8, P < 0.01). Similarly, only 200 μM L-NAME produced a significant increase in IOP (n = 10, P < 0.05). Cavtratin did not significantly change IOP in DKO and NOS3 KO mice. cGMP activity in DKO mice was significantly lower than Cav1 KO mice (n = 4, P < 0.05).

Conclusions

In conclusion, our results demonstrated that genetic deletion of NOS3 in Cav1 deficient mice resulted in reduced sensitivity to the NO donor SNP and the two NOS inhibitors possibly due to compromised NOS and cGMP activity.

Is population structure in the genetic biobank era irrelevant, a challenge, or an opportunity?

Replicable genetic association signals have consistently been found through genome-wide association studies in recent years. The recent dramatic expansion of study sizes improves power of estimation of effect sizes, genomic prediction, causal inference, and polygenic selection, but it simultaneously increases susceptibility of these methods to bias due to subtle population structure. Standard methods using genetic principal components to correct for structure might not always be appropriate and we use a simulation study to illustrate when correction might be ineffective for avoiding biases. New methods such as trans-ethnic modeling and chromosome painting allow for a richer understanding of the relationship between traits and population structure. We illustrate the arguments using real examples (stroke and educational attainment) and provide a more nuanced understanding of population structure, which is set to be revisited as a critical aspect of future analyses in genetic epidemiology. We also make simple recommendations for how problems can be avoided in the future. Our results have particular importance for the implementation of GWAS meta-analysis, for prediction of traits, and for causal inference.

High Content Solid Dispersions for Dose Window Extension: A Basis for Design Flexibility in Fused Deposition Modelling

PURPOSE

This study uses high drug content solid dispersions for dose window extension beyond current demonstrations using fused deposition modelling (FDM) to; i) accommodate pharmaceutically relevant doses of drugs of varying potencies at acceptable dosage form sizes and ii) enable enhanced dose flexibility via modular dosage form design concepts.

METHODS

FDM was used to generate ~0.5 mm thick discs of varying diameter (2-10 mm) from melt-extruded feedstocks based on 10% to 50% w/w felodipine in ethyl cellulose. Drug content was determined by UV spectroscopy and dispensing precision from printed disc mass.

RESULTS

Mean felodipine content was within ±5% of target values for all print volumes and compositions including contents as high as ~50% w/w. However, poor dispensing precision was evident at all print volumes.

CONCLUSIONS

In pursuit of dose flexibility, this successful demonstration of dose window extension using high content solid dispersions preserves FDM design flexibility by maintaining applicability to drugs of varying potencies. The achieved uniformity of content supports the application of varying content solid dispersions to modular dosage form concepts to enhance dose flexibility. However, poor dispensing precision impedes its utilisation until appropriate compatibility between FDM hardware and materials at varying drug contents can be attained.

The GenomeAsia 100K Project enables genetic discoveries across Asia

The underrepresentation of non-Europeans in human genetic studies so far has limited the diversity of individuals in genomic datasets and led to reduced medical relevance for a large proportion of the world’s population. Population-specific reference genome datasets as well as genome-wide association studies in diverse populations are needed to address this issue. Here we describe the pilot phase of the GenomeAsia 100K Project. This includes a whole-genome sequencing reference dataset from 1,739 individuals of 219 population groups and 64 countries across Asia. We catalogue genetic variation, population structure, disease associations and founder effects. We also explore the use of this dataset in imputation, to facilitate genetic studies in populations across Asia and worldwide.

Using whole-genome sequencing data from 1,739 individuals, the GenomeAsia 100K Project catalogues genetic variation, population structure and disease associations to facilitate genetic studies in Asian populations and increase representation in genetics studies worldwide.

Genetic Signatures of Drug Response Variability in Drosophila melanogaster

Knowledge of the genetic basis underlying variation in response to environmental exposures or treatments is important in many research areas. For example, knowing the set of causal genetic variants for drug responses could revolutionize personalized medicine. We used Drosophila melanogaster to investigate the genetic signature underlying behavioral variability in response to methylphenidate (MPH), a drug used in the treatment of attention-deficit/hyperactivity disorder. We exposed a wild-type D. melanogaster population to MPH and a control treatment, and observed an increase in locomotor activity in MPH-exposed individuals. Whole-genome transcriptomic analyses revealed that the behavioral response to MPH was associated with abundant gene expression alterations. To confirm these patterns in a different genetic background and to further advance knowledge on the genetic signature of drug response variability, we used a system of inbred lines, the Drosophila Genetic Reference Panel (DGRP). Based on the DGRP, we showed that the behavioral response to MPH was strongly genotype-dependent. Using an integrative genomic approach, we incorporated known gene interactions into the genomic analyses of the DGRP, and identified putative candidate genes for variability in drug response. We successfully validated 71% of the investigated candidate genes by gene expression knockdown. Furthermore, we showed that MPH has cross-generational behavioral and transcriptomic effects. Our findings establish a foundation for understanding the genetic mechanisms driving genotype-specific responses to medical treatment, and highlight the opportunities that integrative genomic approaches have in optimizing medical treatment of complex diseases.

In vitro and molecular chemosensitivity in human cholangiocarcinoma tissues

Adjuvant chemotherapy is required for cholangiocarcinoma (CCA) patients after surgical treatment. Gemcitabine and gemcitabine plus cisplatin are considered the appropriate regimen; however, the response spectrum to chemotherapy differs between patients. Thus, the present study aims to evaluate the response pattern of individual CCA patients by using an in vitro method, histoculture drug response assay (HDRA), to predict the chemosensitivity of individual patients in a prospective study. Moreover, we also investigate the expression of gemcitabine and cisplatin sensitivity factors in CCA tissues in the same cases. Based on the dose response curve, 1000 and 1500 μg/ml of gemcitabine were used as the testing concentrations. For cisplatin, concentrations of 20 and 25 μg/ml were selected for testing and for the combination regimen, 1000 μg/ml of gemcitabine and 20 μg/ml of cisplatin were chosen. The median %IR of each drug was measured as the cut-off to categorize the response pattern into response and non-response groups. In addition, we compared the effectiveness of the chemotherapy regimens between gemcitabine alone and gemcitabine plus cisplatin. The %IR of the combination of gemcitabine and cisplatin was significantly higher than gemcitabine alone. The relationship between the expression level of gemcitabine and cisplatin sensitive factors and the individual response pattern as well as clinicopathological data of CCA patients were analyzed. The results indicated that a low expression of the gemcitabine sensitive factor hENT-1 was significantly associated with the non-response group in vitro (p = 0.002). Moreover, the low expression of hENT-1 was also significantly associated with advanced stages CCA in the patients (p = 0.025). A low expression of MT and ERCC1 was significantly correlated with the response group in the in vitro experiments (p = 0.015 and p = 0.037 for MT and ERCC1, respectively). Therefore, HDRA may serve as an aid to selecting chemotherapy, and the expression of hNET-1, MT and ERCC1 may serve as biomarkers for predicting chemotherapy success.

Effects of pharmacokinetics-related genetic polymorphisms on the side effect profile of afatinib in patients with non-small cell lung cancer

OBJECTIVES

Epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) represent the first-line treatment for patients with advanced EGFR mutation-positive non-small-cell lung cancer. Afatinib is a second-generation EGFR-TKI with excellent therapeutic effects. However, severe diarrhea and skin disorders are observed at high frequencies, often leading to treatment interruption because of low quality of life (QOL). The relationship between individual variations and the onset of these side effects remains to be elucidated. This study aimed to reveal the association among these side effects, pharmacokinetics, and related genetic polymorphisms.

MATERIALS AND METHODS

In total, 33 patients were recruited between July 2014 and June 2017. Afatinib plasma concentrations were measured at day 9 when the concentrations reached a steady state (early phase) and when the prescription dose was stable for more than 1 month (stable phase). We analyzed single nucleotide polymorphisms in the genes ATP-binding cassette sub-family B member 1 (ABCB1), ABCG2, and flavin-containing monooxygenase 3.

RESULTS

The incidences of both diarrhea and acneiform eruption were greater than 80%. Afatinib plasma concentration and the severity of diarrhea in the early phase were correlated. Pharmacokinetics-related genetic polymorphisms influenced the severity of diarrhea. Particularly, the afatinib plasma concentration was higher and diarrhea was more severe in patients carrying the A allele of ABCG2 C421A. Onset of side effects, genetic polymorphisms, and diarrhea in the maintenance phase or acneiform eruption in the early or maintenance phases were not correlated. The severity of diarrhea is influenced by drug plasma concentrations in the early phase and genetic polymorphisms related to afatinib pharmacokinetics.

CONCLUSION

Particular genetic polymorphisms can be screened before afatinib administration and the dose adapted to individual patients can be controlled, leading to reduced side effects, improved QOL, and better patient compliance to maintain the therapeutic effects.

In Silico Target Prediction for Small Molecules

Drugs modulate disease states through their actions on targets in the body. Determining these targets aids the focused development of new treatments, and helps to better characterize those already employed. One means of accomplishing this is through the deployment of in silico methodologies, harnessing computational analytical and predictive power to produce educated hypotheses for experimental verification. Here, we provide an overview of the current state of the art, describe some of the well-established methods in detail, and reflect on how they, and emerging technologies promoting the incorporation of complex and heterogeneous data-sets, can be employed to improve our understanding of (poly)pharmacology.

Initial Assessment of Variability of Responses to Toxicants in Donor-Specific Endothelial Colony Forming Cells

There is increased interest in using high throughput in vitro assays to characterize human population variability in response to toxicants and drugs. Utilizing primary human endothelial colony-forming cells (ECFCs) isolated from blood would be highly useful for this purpose because these cells are involved in neonatal and adult vasculogenesis. We characterized the cytotoxicity of four known toxic chemicals (NaAsO2, CdCl2, tributyltin [TBT], and menadione) and their four relatively nontoxic counterparts (Na2HAsO4, ZnCl2, SnCl2, and phytonadione, respectively) in eight ECFC clones representing four neonatal donors (2 male and 2 female donors, 2 clones per donor). ECFCs were exposed to 9 concentrations of each chemical in duplicate; cell viability was evaluated 48 h later using the fluorescent vital dye fluorescent dye 5-Carboxyfluorescein Diacetate (CFDA), yielding concentration-effect curves from each experiment. Technical (day-to-day) variability of the assay, assessed from three independent experiments, was low: p-values for the differences of results were 0.74 and 0.64 for the comparison of day 2 vs. day 1 and day 3 vs. day 1, respectively. The statistical analysis used to compare the entire concentration-effect curves has revealed significant differences in levels of cytotoxicity induced by the toxic and relatively nontoxic chemical counterparts, demonstrating that donor-specific ECFCs can clearly differentiate between these two groups of chemicals. Partitioning of the total variance in the nested design assessed the contributions of between-clone and between-donor variability for different levels of cytotoxicity. Individual ECFC clones demonstrated highly reproducible responses to the chemicals. The most toxic chemical was TBT, followed by NaAsO2, CdCl2, and Menadione. Nontoxic counterparts exhibited low cytotoxicity at the higher end of concentration ranges tested. Low variability was observed between ECFC clones obtained from the same donor or different donors for CdCl2, NaAsO2, and TBT, but for menadione, the between-donor variability was much greater than the between-clone variability. The low between-clone variability indicates that an ECFC clone may represent an individual donor in cell-based assays, although this finding must be confirmed using a larger number of donors. Such confirmation would demonstrate that an in vitro ECFC-based testing platform can be used to characterize the inter-individual variability of neonatal ECFCs exposed to drugs and/or environmental toxicants.

Pharmacogenomics in Critical Care

Since the successful completion of the Human Genome Project in 2003, extensive genomic research has continued to alter pathophysiology at the molecular level. This research includes investigation of the specific receptors and metabolizing enzymes in drug pharmacodynamics and pharmacokinetics, specifically the cytochrome P450 system located primarily in the liver. In this article, pharmacogenomics and the role of the cytochrome P450 system in metabolism of various drugs are discussed. Specifically, drugs that are used in the critical care setting and are of clinical significance to the bedside critical care nurse are examined.

DRD2/ANKK1 gene polymorphisms in forensic autopsies of methamphetamine intoxication fatalities

Dopamine D2 receptor/ankyrin repeat and kinase domain containing 1 (DRD2/ANKK1) gene polymorphisms have been associated with responses to psychotropic drugs and addiction. We analyzed two DRD2/ANKK1 polymorphisms, Taq1A and -141C Ins/Del, in 37 fatal methamphetamine (MA) intoxication cases and 235 control cases in which MA and psychotropic drugs were not detected. The association among polymorphism, cause of death, and cerebrospinal fluid (CSF) dopamine concentration was evaluated. The Taq1A polymorphism distribution in the fatal MA intoxication cases differed from in the controls (P = 0.030) with a significantly high A1/A1 + A1/A2 genotype frequency. No significant associations were observed between -141C Ins/Del polymorphisms and MA intoxication cases or between DRD2/ANKK1 polymorphisms and CSF dopamine concentrations. Our findings suggest that the DRD2/ANKK1 Taq1A polymorphism is associated with susceptibility to fatal MA intoxication.

Genetic variation in human drug-related genes

Background

Variability in drug efficacy and adverse effects are observed in clinical practice. While the extent of genetic variability in classic pharmacokinetic genes is rather well understood, the role of genetic variation in drug targets is typically less studied.

Methods

Based on 60,706 human exomes from the ExAC dataset, we performed an in-depth computational analysis of the prevalence of functional variants in 806 drug-related genes, including 628 known drug targets. We further computed the likelihood of 1236 FDA-approved drugs to be affected by functional variants in their targets in the whole ExAC population as well as different geographic sub-populations.

Results

We find that most genetic variants in drug-related genes are very rare (f < 0.1%) and thus will likely not be observed in clinical trials. Furthermore, we show that patient risk varies for many drugs and with respect to geographic ancestry. A focused analysis of oncological drug targets indicates that the probability of a patient carrying germline variants in oncological drug targets is, at 44%, high enough to suggest that not only somatic alterations but also germline variants carried over into the tumor genome could affect the response to antineoplastic agents.

Conclusions

This study indicates that even though many variants are very rare and thus likely not observed in clinical trials, four in five patients are likely to carry a variant with possibly functional effects in a target for commonly prescribed drugs. Such variants could potentially alter drug efficacy.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-017-0502-5) contains supplementary material, which is available to authorized users.

Pharmacogenomics of GPCR Drug Targets

Natural genetic variation in the human genome is a cause of individual differences in responses to medications and is an underappreciated burden on public health. Although 108 G-protein-coupled receptors (GPCRs) are the targets of 475 (∼34%) Food and Drug Administration (FDA)-approved drugs and account for a global sales volume of over 180 billion US dollars annually, the prevalence of genetic variation among GPCRs targeted by drugs is unknown. By analyzing data from 68,496 individuals, we find that GPCRs targeted by drugs show genetic variation within functional regions such as drug- and effector-binding sites in the human population. We experimentally show that certain variants of μ-opioid and Cholecystokinin-A receptors could lead to altered or adverse drug response. By analyzing UK National Health Service drug prescription and sales data, we suggest that characterizing GPCR variants could increase prescription precision, improving patients’ quality of life, and relieve the economic and societal burden due to variable drug responsiveness.

Video Abstract

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GPCRs targeted by FDA-approved drugs show genetic variation in the human population

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Genetic variation occurs in functional sites and may result in altered drug response

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We present an online resource of GPCR genetic variants for pharmacogenomics research

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Understanding variation in drug targets may help alleviate economic healthcare burden

Identification of cancer genes that are independent of dominant proliferation and lineage programs

Large, multidimensional “landscaping” projects have provided datasets that can be mined to identify potential targets for subgroups of tumors. Here, we analyzed genomic and transcriptomic data from human breast tumors to identify genes whose expression is enriched in tumors harboring specific genetic alterations. However, this analysis revealed that two other factors, proliferation rate and tumor lineage, are more dominant factors in shaping tumor transcriptional programs than genetic alterations. This discovery shifted our attention to identifying genes that are independent of the dominant proliferation and lineage programs. A small subset of these genes represents candidate targets for combination cancer therapies because they are druggable, maintained after treatment with chemotherapy, essential for cell line survival, and elevated in drug-resistant stem-like cancer cells.

Large, multidimensional cancer datasets provide a resource that can be mined to identify candidate therapeutic targets for specific subgroups of tumors. Here, we analyzed human breast cancer data to identify transcriptional programs associated with tumors bearing specific genetic driver alterations. Using an unbiased approach, we identified thousands of genes whose expression was enriched in tumors with specific genetic alterations. However, expression of the vast majority of these genes was not enriched if associations were analyzed within individual breast tumor molecular subtypes, across multiple tumor types, or after gene expression was normalized to account for differences in proliferation or tumor lineage. Together with linear modeling results, these findings suggest that most transcriptional programs associated with specific genetic alterations in oncogenes and tumor suppressors are highly context-dependent and are predominantly linked to differences in proliferation programs between distinct breast cancer subtypes. We demonstrate that such proliferation-dependent gene expression dominates tumor transcriptional programs relative to matched normal tissues. However, we also identified a relatively small group of cancer-associated genes that are both proliferation- and lineage-independent. A subset of these genes are attractive candidate targets for combination therapy because they are essential in breast cancer cell lines, druggable, enriched in stem-like breast cancer cells, and resistant to chemotherapy-induced down-regulation.

Integrating cardiomyocytes from human pluripotent stem cells in safety pharmacology: has the time come?

Cardiotoxicity is a severe side effect of drugs that induce structural or electrophysiological changes in heart muscle cells. As a result, the heart undergoes failure and potentially lethal arrhythmias. It is still a major reason for drug failure in preclinical and clinical phases of drug discovery. Current methods for predicting cardiotoxicity are based on guidelines that combine electrophysiological analysis of cell lines expressing ion channels ectopically in vitro with animal models and clinical trials. Although no new cases of drugs linked to lethal arrhythmias have been reported since the introduction of these guidelines in 2005, their limited predictive power likely means that potentially valuable drugs may not reach clinical practice. Human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) are now emerging as potentially more predictive alternatives, particularly for the early phases of preclinical research. However, these cells are phenotypically immature and culture and assay methods not standardized, which could be a hurdle to the development of predictive computational models and their implementation into the drug discovery pipeline, in contrast to the ambitions of the comprehensive pro-arrhythmia in vitro assay (CiPA) initiative. Here, we review present and future preclinical cardiotoxicity screening and suggest possible hPSC-CM-based strategies that may help to move the field forward. Coordinated efforts by basic scientists, companies and hPSC banks to standardize experimental conditions for generating reliable and reproducible safety indices will be helpful not only for cardiotoxicity prediction but also for precision medicine.

LINKED ARTICLES

This article is part of a themed section on New Insights into Cardiotoxicity Caused by Chemotherapeutic Agents. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v174.21/issuetoc.

Circulating Tumor Cells as Cancer Biomarkers in the Clinic

It is believed that the development of metastatic cancer requires the presence of circulating tumor cells (CTCs) , which are found in a patient's circulation as rare abnormal cells comingled with billions of the normal red and white blood cells. The systems developed for detection of CTCs have brought progress to cancer treatment. The molecular characterization of CTCs can aid in the development of new drugs, and their presence during treatment can help clinicians determine the prognosis of the patient. Studies have been carried out in patients early in the disease course, with only primary tumors, and the role of CTCs in prognosis seems to be as important as it is in patients with metastatic disease. The published studies on CTCs have focused on their prognostic significance, their utility in real-time monitoring of therapies, the identification of therapeutic and resistance targets, and understanding the process of metastasis . The analysis of CTCs during the early stages, as a "liquid biopsy," helps to monitor patients at different points in the disease course, including minimal residual disease, providing valuable information about the very early assessment of treatment effectiveness. Finally, CTCs can be used to screen patients with family histories of cancer or with diseases that can lead to the development of cancer. With standard protocols, this easily obtained and practical tool can be used to prevent the growth and spread of cancer. In this chapter, we review some important aspects of CTCs , surveying the disease aspects where these cells have been investigated.