FASEB J. 2022 May;36 Suppl 1. doi: 10.1096/fasebj.2022.36.S1.R4280.

ABSTRACT

PharmGKB is a user-friendly online pharmacogenomics database that annotates clinical guidelines for optimizing drug therapy based on patient genotypes. The majority of guidelines in PharmGKB are based on the interindividual variability in cytochrome P450 (CYP) enzymes responsible for metabolizing drugs. By individualizing patient therapy according to CYP genotypes, there is potential to improve pharmacotherapy outcomes and minimize the risk of adverse events. Although there is growing interest amongst educators and students to integrate pharmacogenetic content into health science curricula, there is a lack of educational resources that teach students how to utilize resources such as PharmGKB to inform clinical decision making. The purpose of this study was to assess and disseminate a case-based interactive lesson on pharmacogenetic-based drug dosing principles that uses PharmGKB. Seventy-one high school students participated in a two-hour Zoom session as part of a four-day Toxicology, Health, and Environmental Disease Program. The lesson was divided into a didactic lecture on pharmacogenetics followed by a group-based analysis of hypothetical case scenarios. Case questions focused on genetic variation in CYP enzymes in the context of different clinical scenarios. Examples included the use of codeine for analgesia (CYP2D6) and clopidogrel for stroke prevention (CYP2C19). Assessment of student understanding was measured by percent gain in correct answers between pre- and post-lesson polling questions. The first question focused on pharmacology concepts while the last two focused on genetics concepts. Students had high pre-test scores on the pharmacology question having learned these concepts earlier in the program. For the additional two questions, there was a positive gain (42%) demonstrating an increase in knowledge during the lesson. Seventy-eight percent of students would be 'extremely likely' or 'very likely' to recommend this activity. We propose that an interactive, group-based activity can be used to teach basic principles of pharmacogenetics and empower students and educators to effectively use online drug resources.

PMID:35553966 | DOI:10.1096/fasebj.2022.36.S1.R4280

FASEB J. 2022 May;36 Suppl 1. doi: 10.1096/fasebj.2022.36.S1.0R546.

ABSTRACT

BACKGROUND: (-)-∆ 9-Tetrahydrocannabinol (THC) is the most abundant psychoactive compound in marijuana. With legalization of marijuana, its use has increased including by pregnant women. The latter raises concerns of fetal toxicity which is likely driven by fetal THC exposure. Interestingly, in the catheterized maternal-fetal macaque model, fetal THC exposure is lower than its corresponding maternal exposure (fetal/maternal AUC0-inf ratio of 0.37). This difference is supported by sparse human THC umbilical vein/maternal plasma concentrations at term. The most likely explanation for these observations is that THC is effluxed by P-glycoprotein (P-gp) which is highly expressed in the human placenta. THC oral pharmacokinetics studies in P-gp knock-out mice support the hypothesis that P-gp can transport THC. Therefore, the objective of our study was to investigate if THC is effluxed in human placentae by estimating the maternal to fetal clearance (m-f-CL) and fetal to maternal clearance (f-m-CL) using the dual cotyledon, dual perfusion, placenta model.

METHODS: Term placentae were utilized from uncomplicated, unlabored, cesarean deliveries with no known history of tobacco or drug use. Two cotyledons from each placenta were perfused at physiological rates (m: 10 mL/min; f: 4 mL/min) for 2-4 hours in a single-pass mode with oxygenated HBSS buffer containing 0.2% BSA, 2000 U/L sodium heparin and 5 mg/mL gentamicin. To determine m-f CL, the maternal perfusate also contained 5 μM THC, a P-gp transporter probe (1 or 10 μM saquinavir), and a passive diffusion probe (20 μg/mL antipyrine) and effluent from the fetal vein and intervillous space were collected at multiple timepoints. To determine f-m-CL, the fetal perfusate of the second cotyledon contained the aforementioned drugs. All perfusions were conducted with (n = 7) and without (n = 5) a pan efflux transporter inhibitor, 4 μM valspodar. THC concentrations in the effluent were quantified using LC-MS/MS. THC CL indices, i.e. m-f-CL and f-m-CL, normalized to the corresponding antipyrine CL, were compared in the absence and presence of valspodar.

RESULTS: THC m-f-CL index, 0.40 ± 0.15, was not significantly different from the f-m-CL index, 0.54 ± 0.13 (p = 0.31; two-tailed Wilcoxon signed rank test), suggesting that THC passively diffuses across the placental barrier. Surprisingly, in the presence of valspodar, THC m-f-CL index, 0.24 ± 0.14, was significantly lower than the corresponding f-m-CL index, 0.44 ± 0.14 (p = 0.016; two-tailed Wilcoxon signed rank test). The reason for this difference is unknown.

CONCLUSIONS: Because THC passively crosses the human placenta, changes in activity of placental transporters (e.g. drugs that inhibit/induce placental transporters or pharmacogenetics) should not alter fetal THC exposure. Further, mechanisms other than P-gp efflux (e.g. binding to placental tissue) need to be explored to explain the fetal and maternal THC exposure of less than unity detailed in the introduction.

PMID:35553017 | DOI:10.1096/fasebj.2022.36.S1.0R546

FASEB J. 2022 May;36 Suppl 1. doi: 10.1096/fasebj.2022.36.S1.R6046.

ABSTRACT

OBJECTIVE: Social determinants of health, including race, ethnicity, and gender, represent important factors in health care delivery and patient outcomes, and contribute to health disparities. Pharmacology, as an integrated discipline, lies at the nexus between foundational science and clinical practice, providing a platform for educators to discuss the impact of social determinants on patient outcomes. Our goal is to create a framework that provides guidance for topics in pharmacotherapeutics for educators, learners, and providers to use in promoting antiracism in medical curricula.

METHODS: Through iterative discussions, we developed a conceptual framework that includes topics taught across medical schools, such as drug metabolism, pharmacogenomics, adverse drug reactions, prescribing guidelines, factors affecting medication adherence, pain management, and therapeutic outcomes. Under each topic, we describe how social constructs such as race, ethnicity, and gender can impact pharmacology and therapeutic outcomes.

RESULTS: Literature reports show that some topics in pharmacology education have already established cultural competency and should be adopted widely by all pharmacology educators, e.g., using more appropriate terminology for drug reactions such as vancomycin-infusion reaction. Other topics are less established, so a more nuanced discussion with students is required. Society guidelines for managing diseases such as hypertension include prescribing recommendations based on race, with which learners are expected to be familiar as they enter clinical training but are actively being debated. Similarly, inter-ethnic differences in drug metabolism are often reported as a function of genetic polymorphisms without considering non-genetic factors.

CONCLUSIONS: We have developed a conceptual framework for promoting antiracism in pharmacology education by categorizing topics based on those where cultural competencies are clearly established and those where a more nuanced discussion is required with learners, as well as identifying and reducing bias in assessment. These are generalizable across health professions in which pharmacology education is a discipline in the curriculum.

PMID:35552881 | DOI:10.1096/fasebj.2022.36.S1.R6046

J Clin Psychiatry. 2022 May 9;83(4):21m14110. doi: 10.4088/JCP.21m14110.

ABSTRACT

Background: Atypical antipsychotics can induce metabolic side effects, but whether they are dose-dependent remains unclear.

Objective: To assess the effect of risperidone and/or paliperidone dosing on weight gain and blood lipids, glucose, and blood pressure alterations.

Methods: Data for 438 patients taking risperidone and/or its metabolite (paliperidone) for up to 1 year were obtained between 2007 and 2018 from a longitudinal study monitoring metabolic parameters.

Results: For each milligram increase in dose, we observed a weight increase of 0.16% at 1 month of treatment (P = .002) and increases of 0.29%, 0.21%, and 0.25% at 3, 6, and 12 months of treatment, respectively (P < .001 for each). Moreover, dose increases of 1 mg raised the risk of a ≥ 5% weight gain after 1 month (OR = 1.18; P = .012), a strong predictor of important weight gain in the long term. When we split the cohort into age categories, the dose had an effect on weight change after 3 months of treatment (up to 1.63%, P = .008) among adolescents (age ≤ 17 years), at 3 (0.13%, P = .013) and 12 (0.13%, P = .036) months among adults (age > 17 and < 65 years), and at each timepoint (up to 1.58%, P < .001) among older patients (age ≥ 65 years). In the whole cohort, for each additional milligram we observed a 0.05 mmol/L increase in total cholesterol (P = .018) and a 0.04 mmol/L increase in LDL cholesterol (P = .011) after 1 year.

Conclusions: Although of small amplitude, these results show an effect of daily risperidone dose on weight gain and blood cholesterol levels. Particular attention should be given to the decision of increasing the drug dose, and minimum effective dosages should be preferred.

PMID:35551499 | DOI:10.4088/JCP.21m14110

Nat Genet. 2022 May 12. doi: 10.1038/s41588-022-01058-3. Online ahead of print.

ABSTRACT

We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 × 10-9), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background.

PMID:35551307 | DOI:10.1038/s41588-022-01058-3

Comput Methods Programs Biomed. 2022 Apr 26;221:106839. doi: 10.1016/j.cmpb.2022.106839. Online ahead of print.

ABSTRACT

BACKGROUND AND OBJECTIVE: Platinum-induced nephrotoxicity is a severe and unexpected adverse drug reaction that could lead to treatment failure in non-small cell lung cancer patients. Better prediction and management of this nephrotoxicity can increase patient survival. Our study aimed to build up and compare the best machine learning models with clinical and genomic features to predict platinum-induced nephrotoxicity in non-small cell lung cancer patients.

METHODS: Clinical and genomic data of patients undergoing platinum chemotherapy at Wan Fang Hospital were collected after they were recruited. Twelve models were established by artificial neural network, logistic regression, random forest, and support vector machine with integrated, clinical, and genomic modes. Grid search and genetic algorithm were applied to construct the fine-tuned model with the best combination of predictive hyperparameters and features. Accuracy, precision, recall, F1 score, and area under the receiver operating characteristic curve were calculated to compare the performance of the 12 models.

RESULTS: In total, 118 patients were recruited for this study, among which 28 (23.73%) were experiencing nephrotoxicity. Machine learning models with clinical and genomic features achieved better prediction performances than clinical or genomic features alone. Artificial neural network with clinical and genomic features demonstrated the best predictive outcomes among all 12 models. The average accuracy, precision, recall, F1 score and area under the receiver operating characteristic curve of the artificial neural network with integrated mode were 0.923, 0.950, 0.713, 0.808 and 0.900, respectively.

CONCLUSIONS: Machine learning models with clinical and genomic features can be a preliminary tool for oncologists to predict platinum-induced nephrotoxicity and provide preventive strategies in advance.

PMID:35550456 | DOI:10.1016/j.cmpb.2022.106839

Front Pharmacol. 2022 Apr 25;13:886377. doi: 10.3389/fphar.2022.886377. eCollection 2022.

ABSTRACT

Adverse drug reactions (ADR) remain the major problems in healthcare. Most severe ADR are unpredictable, dose-independent and termed as type B idiosyncratic reactions. Recent pharmacogenomic studies have demonstrated the strong associations between severe ADR and genetic markers, including specific HLA alleles (e.g., HLA-B*15:02/HLA-B*57:01/HLA-A*31:01 for carbamazepine-induced severe cutaneous adverse drug reactions [SCAR], HLA-B*58:01 for allopurinol-SCAR, HLA-B*57:01 for abacavir-hypersensitivity, HLA-B*13:01 for dapsone/co-trimoxazole-induced SCAR, and HLA-A*33:01 for terbinafine-induced liver injury), drug metabolism enzymes (such as CYP2C9*3 for phenytoin-induced SCAR and missense variant of TPMT/NUDT15 for thiopurine-induced leukopenia), drug transporters (e.g., SLCO1B1 polymorphism for statin-induced myopathy), and T cell receptors (Sulfanilamide binding into the CDR3/Vα of the TCR 1.3). This mini review article aims to summarize the current knowledge of pharmacogenomics of severe ADR, and the potentially clinical use of these genetic markers for avoidance of ADR.

PMID:35548363 | PMC:PMC9081981 | DOI:10.3389/fphar.2022.886377

Curr Alzheimer Res. 2022 May 11. doi: 10.2174/1567205019666220511140955. Online ahead of print.

ABSTRACT

BACKGROUND: Alzheimer's disease (AD) is the most common form of neurodegenerative disorder. The association of BIN1, CLU and IDE genetic polymorphisms with AD risk have been evaluated overtimes that produced conflicting outcomes.

OBJECTIVE: We performed this meta-analysis to investigate the contribution of BIN1 (rs744373 and rs7561528), CLU (rs11136000 and rs9331888), and IDE (rs1887922) polymorphisms to AD risk.

METHODS: From a systemic literature search up to July 15, 2021, we included 25 studies with rs744373, 16 studies with rs7561528, 37 studies with rs11136000, 16 studies with rs9331888, and 4 studies with rs1887922. To analyze the correlation, we constructed seven genetic models that used odds ratio and 95% confidence intervals. We used RevMan 5.4 for meta-analysis.

RESULTS: Our study suggests that BIN1 rs744373 is associated with a significantly increased risk of AD in five genetic models (OR>1). Again, CLU rs11136000 showed reduced association in all genetic models (OR<1). CLU rs9331888 revealed an increased association in two models (OR>1). The IDE rs1887922 showed significantly increased risk in four models (OR>1). From subgroup analysis, a significantly increased risk of AD was observed in Caucasians and Asians for BIN1 rs744373. Again, BIN1 rs7561528 showed a significantly enhanced risk of AD only in Caucasians. CLU rs11136000 showed significantly reduced risk in Caucasians but rs9331888 showed increased risk in the same ethnicity.

CONCLUSION: Our meta-analysis confirms the association of BIN1 rs744373, CLU rs9331888 and IDE rs1887922 polymorphisms with an increased risk of AD, especially in Caucasians. Again, CLU rs11136000 is associated with reduced AD risk in the overall population and Caucasians.

PMID:35546756 | DOI:10.2174/1567205019666220511140955

Pharmacogenomics. 2022 May 12. doi: 10.2217/pgs-2022-0054. Online ahead of print.

NO ABSTRACT

PMID:35546341 | DOI:10.2217/pgs-2022-0054

Pharmacogenomics. 2022 May 12. doi: 10.2217/pgs-2022-0050. Online ahead of print.

NO ABSTRACT

PMID:35546339 | DOI:10.2217/pgs-2022-0050

Eur Neuropsychopharmacol. 2022 May 8;59:26-35. doi: 10.1016/j.euroneuro.2022.04.001. Online ahead of print.

ABSTRACT

Abnormalities in Ca2+ homeostasis in Bipolar Disorders (BD) have been associated with impairments in glutamatergic receptors and voltage-gated calcium channels. Increased anterior cingulate cortex (ACC) glutamatergic neurometabolites have been consistently disclosed in BD by proton magnetic resonance spectroscopy (1H-MRS). A single nucleotide polymorphism (SNP) in the CACNA1C gene (rs1006737), which encodes the alpha 1-C subunit of the L-type calcium channel, has been associated with BD and is reported to modulate intra-cellular Ca2+. Thus, this study aimed to explore the association of the CACNA1C genotype with ACC glutamatergic metabolites measured by 1H-MRS in both BD and HC subjects. A total of 194 subjects (121 euthymic BD type I patients and 73 healthy controls (HC) were genotyped for CACNA1C rs1006737, underwent a 3-Tesla 1H-MRS imaging examination and ACC glutamatergic metabolite were assessed. We found overall increased glutamatergic metabolites in AA carriers in BD. Specifically, higher Glx/Cr was observed in subjects with the AA genotype compared to both AG and GG in the overall sample (BD + HC). Also, female individuals in the BD group with AA genotype were found to have higher Glx/Cr compared to those with other genotypes. CACNA1C AA carriers in use of anticonvulsant medication had higher estimated Glutamine (Glx-Glu) than the other genotypes. Thus, this study suggest an association between calcium channel genetics and increased glutamatergic metabolites in BD, possibly playing a synergic role in intracellular Ca2+ overload and excitotoxicity.

PMID:35544990 | DOI:10.1016/j.euroneuro.2022.04.001

Circ Genom Precis Med. 2022 May 11:101161CIRCGEN121003503. doi: 10.1161/CIRCGEN.121.003503. Online ahead of print.

ABSTRACT

BACKGROUND: Statin-associated muscle symptoms (SAMS) are the most frequently reported adverse events for statin therapies. Previous studies have reported an association between the p.Val174Ala missense variant in SLCO1B1 and SAMS in simvastatin-treated subjects; however, evidence for genetic predictors of SAMS in atorvastatin- or rosuvastatin-treated subjects is currently lacking.

METHODS: ODYSSEY OUTCOMES (Evaluation of Cardiovascular Outcomes After an Acute Coronary Syndrome During Treatment With Alirocumab; n=18 924) was a double-blind, randomized, placebo-controlled study evaluating the efficacy and safety of alirocumab (a PCSK9 [proprotein convertase subtilisin kexin 9] inhibitor) in acute coronary syndrome patients receiving high-intensity statin therapy. The goal of this pharmacogenomic analysis was to identify genetic variants associated with atorvastatin- and rosuvastatin-mediated SAMS among ODYSSEY OUTCOMES subjects who consented to participate in the genetic study (n=11 880). We performed multi-ancestry exome-wide and genome-wide association studies and gene burden analysis across 2 phenotypes (clinical SAMS [n=10 617] and creatine kinase [n=9630] levels).

RESULTS: A novel genome-wide significant association for an intronic variant (rs6667912) located within TMEM9 (odds ratio [95% CI], 1.39 [1.24-1.55]; P=3.71×10-8) for patients with clinical SAMS (cases=894, controls=9723) was identified. This variant is located ≈30 kb upstream of CACNA1S, a locus associated with severe SAMS. We replicated 2 loci, at LINC0093 and LILRB5, previously associated with creatine kinase levels during statin treatment. No association was observed between p.Val174Ala (rs4149056) in SLCO1B1 and SAMS (odds ratio [95% CI], 1.03 [0.90-1.18]; P=0.69).

CONCLUSIONS: This study comprises the largest discovery exome-wide and genome-wide association studies for atorvastatin- or rosuvastatin-mediated SAMS to date. These novel genetic findings may provide biological/mechanistic insight into this drug-induced toxicity, and help identify at-risk patients before selection of lipid-lowering therapies.

PMID:35543701 | DOI:10.1161/CIRCGEN.121.003503

J Antimicrob Chemother. 2022 May 11:dkac150. doi: 10.1093/jac/dkac150. Online ahead of print.

NO ABSTRACT

PMID:35538913 | DOI:10.1093/jac/dkac150

Exp Dermatol. 2022 May 10. doi: 10.1111/exd.14602. Online ahead of print.

ABSTRACT

Antihistamines, especially H1 antihistamines, are widely used in the treatment of allergic diseases such as urticaria and allergic rhinitis, mainly for reversing elevated histamine and anti-allergic effects. Antihistamines are generally safe, but some patients experience adverse reactions, such as cardiotoxicity, central inhibition, and anticholinergic effects. There are also individual differences in antihistamine efficacy in clinical practice. The concept of individualized medicine has been deeply rooted in people's minds since it was put forward. Pharmacogenomics is the study of the role of inheritance in individual variations in drug response. In recent decades, pharmacogenomics has been developing rapidly, which provides new ideas for individualized medicine. Polymorphisms in the genes encoding metabolic enzymes, transporters, and target receptors have been shown to affect the efficacy of antihistamines. In addition, recent evidence suggests that gene polymorphisms influence urticaria susceptibility and antihistamine therapy. Here, we summarize current reports in this area, aiming to contribute to future research in antihistamines and clinical guidance for antihistamines use in individualized medicine.

PMID:35538735 | DOI:10.1111/exd.14602

Clin Pharmacol Ther. 2022 May 10. doi: 10.1002/cpt.2637. Online ahead of print.

ABSTRACT

Therapy of molybdenum co-factor (Moco) deficiency has received FDA approval in 2021. While urothione, the urinary excreted catabolite of Moco, is used as diagnostic biomarker for Moco-deficiency, its catabolic pathway remains unknown. Here, we identified the urothione-synthesizing methyltransferase using mouse liver tissue by anion exchange/size exclusion chromatography and peptide mass fingerprinting. We show that the catabolic Moco S-methylating enzyme corresponds to thiopurine S-methyltransferase (TPMT), a highly polymorphic drug-metabolizing enzyme associated with drug-related haematotoxicity but unknown physiological role. Urothione synthesis was investigated in vitro using recombinantly expressed human TPMT protein, liver lysates from Tpmt wild-type and knock-out (Tpmt-/-) mice as well as human liver cytosol. Urothione levels were quantified by LC-MS/MS in kidney and urine of mice. TPMT-genotype/phenotype and excretion levels of urothione were investigated in human samples and validated in an independent population-based study. As Moco provides a physiological substrate (thiopterin) of TPMT, thiopterin-methylating activity was associated with TPMT activity determined with its drug substrate (6-thioguanin) in mice and humans. Urothione concentration was extremely low in kidney and urine of Tpmt-/- mice. Urinary urothione concentration in TPMT-deficient patients depends on common TPMT polymorphisms, with extremely low levels in homozygous variant carriers (TPMT*3A/*3A) but normal levels in compound heterozygous carriers (TPMT*3A/*3C) as validated in the population-based study. Our work newly identified an endogenous substrate for TPMT and shows an unprecedented link between Moco-catabolism and drug-metabolism. Moreover, the TPMT example indicates that phenotypic consequences of genetic polymorphisms may differ between drug- and endogenous substrates.

PMID:35538648 | DOI:10.1002/cpt.2637

Br J Clin Pharmacol. 2022 May 10. doi: 10.1111/bcp.15393. Online ahead of print.

ABSTRACT

AIMS: Methadone metabolism and clearance are determined principally by polymorphic cytochrome P4502B6 (CYP2B6). Some CYP2B6 allelic variants affect methadone metabolism in vitro and disposition in vivo. We assessed methadone metabolism by CYP2B6 minor variants in vitro. We also assessed the influence of CYP2B6 variants, and P450 oxidoreductase (POR) and CYP2C19 variants, on methadone clearance in surgical patients in vivo.

METHODS: CYP2B6 and P450 oxidoreductase variants were coexpressed with cytochrome b5 . Metabolism of methadone racemate and enantiomers was measured at therapeutic concentrations and intrinsic clearances determined. Adolescents receiving methadone for surgery were genotyped for CYP2B6, CYP2C19 and POR, and methadone clearance and metabolite formation clearance determined.

RESULTS: In vitro, CYP2B6.4 was more active than wild type CYP2B6.1. CYPs 2B6.5, 2B6.6, 2B6.7, 2B6.9, 2B6.17, 2B6.19 and 2B6.26 were less active. CYPs 2B6.16 and 2B6.18 were inactive. CYP2B6.1 expressed with POR variants POR.28, POR.5, and P228L had lower rates of methadone metabolism than wild-type reductase. In vivo, methadone clinical clearance decreased linearly with the number of CYP2B6 slow metabolizer alleles, but were not different in CYP2C19 slow or rapid metabolizer phenotypes, or in carriers of the POR*28 allele.

CONCLUSIONS: Several CYP2B6 and POR variants were slow metabolizers of methadone in vitro. Polymorphisms in CYP2B6, but not CYP2C19 or P450 reductase, affected methadone clearance in vivo. CYP2B6 polymorphisms 516G>T and 983T>C code for canonical loss of function variants, and should be assessed when considering genetic influences on clinical methadone disposition. These complementary translational in vitro and in vivo results inform on pharmacogenetic variability affecting methadone disposition in patients.

PMID:35538637 | DOI:10.1111/bcp.15393

Annu Rev Genomics Hum Genet. 2022 May 10. doi: 10.1146/annurev-genom-111621-102737. Online ahead of print.

ABSTRACT

Pharmacogenomic testing can be an effective tool to enhance medication safety and efficacy. Pharmacogenomically actionable medications are widely used, and approximately 90-95% of individuals have an actionable genotype for at least one pharmacogene. For pharmacogenomic testing to have the greatest impact on medication safety and clinical care, genetic information should be made available at the time of prescribing (preemptive testing). However, the use of preemptive pharmacogenomic testing is associated with some logistical concerns, such as consistent reimbursement, processes for reporting preemptive results over an individual's lifetime, and result portability. Lessons can be learned from institutions that have implemented preemptive pharmacogenomic testing. In this review, we discuss the rationale and best practices for implementing pharmacogenomics preemptively. Expected final online publication date for the Annual Review of Genomics and Human Genetics, Volume 23 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

PMID:35537468 | DOI:10.1146/annurev-genom-111621-102737

Cancer Res. 2022 May 10:canres.2395.2021. doi: 10.1158/0008-5472.CAN-21-2395. Online ahead of print.

ABSTRACT

Identifying biomarkers predictive of cancer cell response to drug treatment constitutes one of the main challenges in precision oncology. Recent large-scale cancer pharmacogenomic studies have opened new avenues of research to develop predictive biomarkers by profiling thousands of human cancer cell lines at the molecular level and screening them with hundreds of approved drugs and experimental chemical compounds. Many studies have leveraged these data to build predictive models of response using various statistical and machine learning methods. However, a common pitfall to these methods is the lack of interpretability as to how they make predictions, hindering the clinical translation of these models. To alleviate this issue, we used the recent logic modeling approach to develop a new machine learning pipeline that explores the space of bimodally expressed genes in multiple large in vitro pharmacogenomic studies and builds multivariate, nonlinear, yet interpretable logic-based models predictive of drug response. The performance of this approach was showcased in a compendium of the three largest in vitro pharmacogenomic data sets to build robust and interpretable models for 101 drugs that span 17 drug classes with high validation rates in independent datasets. These results along with in vivo and clinical validation, support a better translation of gene expression biomarkers between model systems using bimodal gene expression.

PMID:35536872 | DOI:10.1158/0008-5472.CAN-21-2395

J Hum Genet. 2022 May 9. doi: 10.1038/s10038-022-01040-1. Online ahead of print.

ABSTRACT

Pharmacogenomics (PGx) is a research area aimed at identifying genetic factors that are associated with drug responses, including drug efficacy, adverse drug reactions, and the appropriate drug dosage on a case-to-case basis. To promote the clinical implementation of PGx testing, which is currently of limited use in clinical practice, recent research has focused on providing reliable evidence for its clinical utility. In neurology, psychiatry, and neurosurgery, several human leukocyte antigen (HLA) alleles have been reportedly associated with cutaneous adverse drug reactions (cADRs) induced by antiepileptic drugs, which significantly carry the risk of developing cADRs. Prior to using antiepileptic drugs such as carbamazepine and lamotrigine, which are prone to cause severe cADRs, preemptive HLA genetic testing and therapeutic interventions such as drug selection and dosage adjustment based on the results of the tests can reduce the incidence of cADRs in the population before the initiation of treatment.

PMID:35534674 | DOI:10.1038/s10038-022-01040-1

Cell Death Dis. 2022 May 9;13(5):445. doi: 10.1038/s41419-022-04905-7.

NO ABSTRACT

PMID:35534470 | DOI:10.1038/s41419-022-04905-7