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The therapeutic efficacy of tamoxifen is predominantly mediated by its active metabolites 4-hydroxy-tamoxifen and endoxifen, whose formation is catalyzed by the polymorphic cytochrome P450 2D6 (CYP2D6). Yet, known CYP2D6 polymorphisms only partially determine metabolite concentrations in vivo. We performed the first cross-ancestry genome-wide association study with well-characterized patients of European, Middle-Eastern, and Asian descent (N = 497) to identify genetic factors impacting active and parent metabolite formation. Genome-wide significant variants were functionally evaluated in an independent liver cohort (N = 149) and in silico. Metabolite prediction models were validated in two independent European breast cancer cohorts (N = 287, N = 189). Within a single 1-megabase (Mb) region of chromosome 22q13 encompassing the CYP2D6 gene, 589 variants were significantly associated with tamoxifen metabolite concentrations, particularly endoxifen and metabolic ratio (MR) endoxifen/N-desmethyltamoxifen (minimal P = 5.4E-35 and 2.5E-65, respectively). Previously suggested other loci were not confirmed. Functional analyses revealed 66% of associated, mostly intergenic variants to be significantly correlated with hepatic CYP2D6 activity or expression (ρ = 0.35 to -0.52), and six hotspot regions in the extended 22q13 locus impacting gene regulatory function. Machine learning models based on hotspot variants (N = 12) plus CYP2D6 activity score (AS) increased the explained variability (~ 9%) compared with AS alone, explaining up to 49% (median R2 ) and 72% of the variability in endoxifen and MR endoxifen/N-desmethyltamoxifen, respectively. Our findings suggest that the extended CYP2D6 locus at 22q13 is the principal genetic determinant of endoxifen plasma concentration. Long-distance haplotypes connecting CYP2D6 with adjacent regulatory sites and nongenetic factors may account for the unexplained portion of variability.

Recent advances in next-generation sequencing (NGS) have resulted in the identification of tens of thousands of rare pharmacogenetic variations with unknown functional effects. However, although such pharmacogenetic variations have been estimated to account for a considerable amount of the heritable variability in drug response and toxicity, accurate interpretation at the level of the individual patient remains challenging. We discuss emerging strategies and concepts to close this translational gap. We illustrate how massively parallel experimental assays, artificial intelligence (AI), and machine learning can synergize with population-scale biobank projects to facilitate the interpretation of NGS data to individualize clinical decision-making and personalized medicine.

The Pharmacogene Variation Consortium (PharmVar) catalogs star (*) allele nomenclature for the polymorphic human CYP3A5 gene. Genetic variation within the CYP3A5 gene locus impacts the metabolism of several clinically important drugs, including the immunosuppressants tacrolimus, sirolimus, cyclosporine, and the benzodiazepine midazolam. Variable CYP3A5 activity is of clinical importance regarding tacrolimus metabolism. This GeneFocus provides a CYP3A5 gene summary with a focus on aspects regarding standardized nomenclature. In addition, this review also summarizes recent changes and updates, including the retirement of several allelic variants and provides an overview of how PharmVar CYP3A5 star allele nomenclature is utilized by the Pharmacogenomics Knowledgebase (PharmGKB) and the Clinical Pharmacogenetics Implementation Consortium (CPIC).

Since the discovery of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in late 2019, intense research efforts on an unprecedented scale have focused on the study of viral entry mechanisms and adaptive immunity. While the identification of angiotensin-converting enzyme 2 (ACE2) and other co-receptors has elucidated the molecular and structural basis for viral entry, the pathobiological mechanisms of SARS-CoV-2 in human tissues are less understood. Recent advances in bioengineering have opened opportunities for the use of organotypic human tissue models to investigate host-virus interactions and test antiviral drug candidates in a physiological context. Although it is too early to accurately quantify the added value of these systems compared with conventional cell systems, it can be assumed that these advanced three-dimensional (3D) models contribute toward improved result translation. This mini-review summarizes recent work to study SARS-CoV-2 infection in human 3D tissue models with an emphasis on the pharmacological tools that have been developed to understand and prevent viral entry and replication.

Pregnane X receptor (PXR), constitutive androstane receptor (CAR), and PXR/CAR knockout (KO) HepaRG cells, as well as a PXR reporter gene assay, were used to investigate the mechanism of CYP3A4 and CYP2B6 induction by prototypical substrates and a group of compounds from the Merck KGaA oncology drug discovery pipeline. The basal and inducible gene expression of CYP3A4 and CYP2B6 of nuclear hormone receptor (NHR) KO HepaRG relative to control HepaRG was characterized. The basal expression of CYP3A4 was markedly higher in the PXR (10-fold) and CAR (11-fold) KO cell lines compared with control HepaRG, whereas inducibility was substantially lower. Inversely, basal expression of CYP3A4 in PXR/CAR double KO (dKO) was low (10-fold reduction). Basal CYP2B6 expression was high in PXR KO (9-fold) cells which showed low inducibility, whereas the basal expression remained unchanged in CAR and dKO cell lines compared with control cells. Most of the test compounds induced CYP3A4 and CYP2B6 via PXR and, to a lesser extent, via CAR. Furthermore, other non-NHR-driven induction mechanisms were implicated, either alone or in addition to NHRs. Notably, 5 of the 16 compounds (31%) that were PXR inducers in HepaRG did not activate PXR in the reporter gene assay, illustrating the limitations of this system. This study indicates that HepaRG is a highly sensitive system fit for early screening of cytochrome P450 (P450) induction in drug discovery. Furthermore, it shows the applicability of HepaRG NHR KO cells as tools to deconvolute mechanisms of P450 induction using novel compounds representative for oncology drug discovery. SIGNIFICANCE STATEMENT: This work describes the identification of induction mechanisms of CYP3A4 and CYP2B6 for an assembly of oncology drug candidates using HepaRG nuclear hormone receptor knockout and displays its advantages compared to a pregnane X receptor reporter gene assay. With this study, risk assessment of drug candidates in early drug development can be improved.

Adipocytes are specialized cells with pleiotropic roles in physiology and pathology. Several types of fat cells with distinct metabolic properties coexist in various anatomically defined fat depots in mammals. White, beige, and brown adipocytes differ in their handling of lipids and thermogenic capacity, promoting differences in size and morphology. Moreover, adipocytes release lipids and proteins with paracrine and endocrine functions. The intrinsic properties of adipocytes pose specific challenges in culture. Mature adipocytes float in suspension culture due to high triacylglycerol content and are fragile. Moreover, a fully differentiated state, notably acquirement of the unilocular lipid droplet of white adipocyte, has so far not been reached in two-dimensional culture. Cultures of mouse and human-differentiated preadipocyte cell lines and primary cells have been established to mimic white, beige, and brown adipocytes. Here, we survey various models of differentiated preadipocyte cells and primary mature adipocyte survival describing main characteristics, culture conditions, advantages, and limitations. An important development is the advent of three-dimensional culture, notably of adipose spheroids that recapitulate in vivo adipocyte function and morphology in fat depots. Challenges for the future include isolation and culture of adipose-derived stem cells from different anatomic location in animal models and humans differing in sex, age, fat mass, and pathophysiological conditions. Further understanding of fat cell physiology and dysfunction will be achieved through genetic manipulation, notably CRISPR-mediated gene editing. Capturing adipocyte heterogeneity at the single-cell level within a single fat depot will be key to understanding diversities in cardiometabolic parameters among lean and obese individuals.

The Pharmacogene Variation Consortium (PharmVar) catalogues star (*) allele nomenclature for the polymorphic human CYP2B6 gene. Genetic variation within the CYP2B6 gene locus impacts the metabolism or bioactivation of clinically important drugs. Of particular importance are efficacy and safety concerns regarding: efavirenz, which is used for the treatment of HIV type-1 infection; methadone, a mainstay in the treatment of opioid use disorder and as an analgesic; ketamine, used as an antidepressant and analgesic; and bupropion, which is prescribed to treat depression and for smoking cessation. This GeneFocus provides a comprehensive overview and summary of CYP2B6 and describes how haplotype information catalogued by PharmVar is utilized by the Pharmacogenomics Knowledgebase (PharmGKB) and the Clinical Pharmacogenetics Implementation Consortium (CPIC).

Background: Previous studies have shown that haloperidol biotransformation is mainly metabolized by CYP2D6. The CYP2D6 gene is highly polymorphic, contributing to inter-individual differences in enzymatic activity, and may impact haloperidol biotransformation rates, resulting in variable drug efficacy and safety profiles. Objective: The study aimed to investigate the correlation of the CYPD6 activity with haloperidol's efficacy and safety rates in patients with alcohol-induced psychotic disorders. objective: To investigate the correlation of the CYPD6 activity with the efficacy and safety rates of haloperidol in patients with alcohol-induced psychotic disorders. Method: One hundred male patients received 5-10 mg/day haloperidol by injections for 5 days. The efficacy and safety assessments were performed using PANSS, UKU, and SAS-validated psychometric scales. Results: No relationship between haloperidol efficacy or safety and the experimental endogenous pharmacometabolomic marker for CYP2D6 activity, urinary 6-НО-ТНВС/pinoline ratio was identified. In contrast, we found a statistically significant association between haloperidol adverse events and the most common CYP2D6 loss-of-function allele CYP2D6*4 (p Conclusion: Evaluation of the single polymorphism rs3892097 that defines CYP2D6*4 can predict the safety profile of haloperidol in patients with AIPD, whereas metabolic evaluation using an endogenous marker was not a suitable predictor. Furthermore, our results suggest haloperidol dose reductions could be considered in AIPD patients with at least one inactive CYP2D6 allele.

Genetic factors have long been recognized as important determinants of interindividual variability in drug efficacy and toxicity. However, despite the increasing number of established gene-drug associations, candidate polymorphisms can only explain a fraction of the genetically encoded functional variability in drug disposition. Advancements in genetic profiling methods now allow to analyse the landscape of human pharmacogenetic variations comprehensively, which opens new opportunities to identify novel factors that could explain the "missing heritability." Here, we provide an updated overview of the landscape of pharmacogenomic variability based on recent analyses of population-scale sequencing projects. We then summarize the current state-of-the-art how the functional consequences of variants with unknown effects can be quantitatively estimated while discussing challenges and peculiarities that are specific to pharmacogenes. In the last sections, we discuss the importance of considering ethnogeographic diversity to provide equitable benefits of pharmacogenomics and summarize current roadblocks for the implementation of sequencing-based guidance of clinical decision-making. Based on the current state of the field, we conclude that testing is likely to gradually shift from the interrogation of selected candidate polymorphisms to comprehensive sequencing, which allows to consider the full spectrum of pharmacogenomic variations for a true personalization of genomic prescribing.

Over the last decade, next-generation sequencing (NGS) methods have become increasingly used in various areas of human genomics. In routine clinical care, their use is already implemented in oncology to profile the mutational landscape of a tumor, as well as in rare disease diagnostics. However, its utilization in pharmacogenomics is largely lacking behind. Recent population-scale genome data has revealed that human pharmacogenes carry a plethora of rare genetic variations that are not interrogated by conventional array-based profiling methods and it is estimated that these variants could explain around 30% of the genetically encoded functional pharmacogenetic variability.To interpret the impact of such variants on drug response a multitude of computational tools have been developed, but, while there have been major advancements, it remains to be shown whether their accuracy is sufficient to improve personalized pharmacogenetic recommendations in robust trials. In addition, conventional short-read sequencing methods face difficulties in the interrogation of complex pharmacogenes and high NGS test costs require stringent evaluations of cost-effectiveness to decide about reimbursement by national healthcare programs. Here, we illustrate current challenges and discuss future directions toward the clinical implementation of NGS to inform genotype-guided decision-making.

The intestinal epithelium acts as a selective barrier for the absorption of water, nutrients and orally administered drugs. To evaluate the gastrointestinal permeability of a candidate molecule, scientists and drug developers have a multitude of cell culture models at their disposal. Static transwell cultures constitute the most extensively characterized intestinal in vitro system and can accurately categorize molecules into low, intermediate and high permeability compounds. However, they lack key aspects of intestinal physiology, including the cellular complexity of the intestinal epithelium, flow, mechanical strain, or interactions with intestinal mucus and microbes. To emulate these features, a variety of different culture paradigms, including microfluidic chips, organoids and intestinal slice cultures have been developed. Here, we provide an updated overview of intestinal in vitro cell culture systems and critically review their suitability for drug absorption studies. The available data show that these advanced culture models offer impressive possibilities for emulating intestinal complexity. However, there is a paucity of systematic absorption studies and benchmarking data and it remains unclear whether the increase in model complexity and costs translates into improved drug permeability predictions. In the absence of such data, conventional static transwell cultures remain the current gold-standard paradigm for drug absorption studies.

Background Inter-individual differences in dihydropyrimidine dehydrogenase (DPYD encoding DPD) and thiopurine S-methyltransferase (TPMT) activity are important predictors for fluoropyrimidine and thiopurine toxicity. While several variants in these genes are known to decrease enzyme activities, many additional genetic variations with unclear functional consequences have been identified, complicating informed clinical decision-making in the respective carriers. Methods We used a novel pharmacogenetically trained ensemble classifier to analyse DPYD and TPMT genetic variability based on sequencing data from 138,842 individuals across eight populations. Results The algorithm accurately predicted in vivo consequences of DPYD and TPMT variants (accuracy 91.4% compared to 95.3% in vitro). Further analysis showed high genetic complexity of DPD deficiency, advocating for sequencing-based DPYD profiling, whereas genotyping of four variants in TPMT was sufficient to explain >95% of phenotypic TPMT variability. Lastly, we provided population-scale profiles of ethnogeographic variability in DPD and TPMT phenotypes, and revealed striking interethnic differences in frequency and genetic constitution of DPD and TPMT deficiency. Conclusion These results provide the most comprehensive data set of DPYD and TPMT variability published to date with important implications for population-adjusted genetic profiling strategies of fluoropyrimidine and thiopurine risk factors and precision public health.

The 12(th) International Society for the Study of Xenobiotics (ISSX) meeting, held in Portland, OR, USA from July 28–31, 2019, was attended by diverse members of the pharmaceutical sciences community. The ISSX New Investigators Group provides learning and professional growth opportunities for student and early career members of ISSX. To share meeting content with those who were unable to attend, the ISSX New Investigators herein elected to highlight the “Advances in the Study of Drug Metabolism” symposium, as it engaged attendees with diverse backgrounds. This session covered a wide range of current topics in drug metabolism research including predicting sites and routes of metabolism, metabolite identification, ligand docking, and medicinal and natural products chemistry, and highlighted approaches complemented by computational modeling. In silico tools have been increasingly applied in both academic and industrial settings, alongside traditional and evolving in vitro techniques, to strengthen and streamline pharmaceutical research. Approaches such as quantum mechanics simulations facilitate understanding of reaction energetics towards prediction of routes and sites of drug metabolism. Furthermore, in tandem with crystallographic and orthogonal wet lab techniques for structural validation of drug metabolizing enzymes, in silico models can aid understanding of substrate recognition by particular enzymes, identify metabolic soft spots and predict toxic metabolites for improved molecular design. Of note, integration of chemical synthesis and biosynthesis using natural products remains an important approach for identifying new chemical scaffolds in drug discovery. These subjects, compiled by the symposium organizers, presenters, and the ISSX New Investigators Group, are discussed in this review.

FINDbase (http://www.findbase.org) is a comprehensive data resource recording the prevalence of clinically relevant genomic variants in various populations worldwide, such as pathogenic variants underlying genetic disorders as well as pharmacogenomic biomarkers that can guide drug treatment. Here, we report significant new developments and technological advancements in the database architecture, leading to a completely revamped database structure, querying interface, accompanied with substantial extensions of data content and curation. In particular, the FINDbase upgrade further improves the user experience by introducing responsive features that support a wide variety of mobile and stationary devices, while enhancing computational runtime due to the use of a modern Javascript framework such as ReactJS. Data collection is significantly enriched, with the data records being divided in a Public and Private version, the latter being accessed on the basis of data contribution, according to the microattribution approach, while the front end was redesigned to support the new functionalities and querying tools. The abovementioned updates further enhance the impact of FINDbase, improve the overall user experience, facilitate further data sharing by microattribution, and strengthen the role of FINDbase as a key resource for personalized medicine applications and personalized public health.

ATP-binding cassette (ABC) transporters constitute a superfamily of 48 structurally similar membrane transporters that mediate the ATP-dependent cellular export of a plethora of endogenous and xenobiotic substances. Importantly, genetic variants in ABC genes that affect gene function have clinically important effects on drug disposition and can be predictors of the risk of adverse drug reactions and efficacy of chemotherapeutics, calcium channel blockers, and protease inhibitors. Furthermore, loss-of-function of ABC transporters is associated with a variety of congenital disorders. Despite their clinical importance, information about the frequencies and global distribution of functionally relevant ABC variants is limited and little is known about the overall genetic complexity of this important gene family. Here, we systematically mapped the genetic landscape of the entire human ABC superfamily using Next-Generation Sequencing data from 138,632 individuals across seven major populations. Overall, we identified 62,793 exonic variants, 98.5% of which were rare. By integrating five computational prediction algorithms with structural mapping approaches using experimentally determined crystal structures, we found that the functional ABC variability is extensive and highly population-specific. Every individual harbored between 9.3 and 13.9 deleterious ABC variants, 76% of which were found only in a single population. Carrier rates of pathogenic variants in ABC transporter genes associated with autosomal recessive congenital diseases, such as cystic fibrosis or pseudoxanthoma elasticum, closely mirrored the corresponding population-specific disease prevalence, thus providing a novel resource for rare disease epidemiology. Combined, we provide the most comprehensive, systematic, and consolidated overview of ethnogeographic ABC transporter variability with important implications for personalized medicine, clinical genetics, and precision public health.

The common loss-of-function mutation R577X in the structural muscle protein ACTN3 emerged as a potential target of positive selection from early studies and has been the focus of insightful physiological work suggesting a significant impact on muscle metabolism. Adaptation to cold climates has been proposed as a key adaptive mechanism explaining its global allele frequency patterns. Here, we re-examine this hypothesis analyzing modern (n = 3,626) and ancient (n = 1,651) genomic data by using allele-frequency as well as haplotype homozygosity-based methods. The presented results are more consistent with genetic drift rather than selection in cold climates as the main driver of the ACTN3 R577X frequency distribution in human populations across the world. This Matters Arising paper is in response to Wyckelsma et al. (2021)

Statins are the first-line treatment for familial hypercholesterolemia (FH), but response is highly variable due to genetic and nongenetic factors. Here, we explored the association between response and genetic variability in 114 Brazilian adult FH patients. Specifically, a panel of 84 genes was analyzed by exon-targeted gene sequencing (ETGS), and the functional impact of variants in pharmacokinetic (PK) genes was assessed using an array of functionality prediction methods. Low-density lipoprotein cholesterol (LDL-c) response to statins (reduction ≥ 50%) and statin-related adverse event (SRAE) risk were assessed in carriers of deleterious variants in PK-related genes using multivariate linear regression analyses. Fifty-eight (50.8%) FH patients responded to statins, and 24 (21.0%) had SRAE. Results of the multivariate regression analysis revealed that ABCC1 rs45511401 significantly increased LDL-c reduction after statin treatment (p < 0.05). In silico analysis of the amino-acid change using molecular docking showed that ABCC1 rs45511401 possibly impairs statin efflux. Deleterious variants in PK genes were not associated with an increased risk of SRAE. In conclusion, the deleterious variant ABCC1 rs45511401 enhanced LDL-c response in Brazilian FH patients. As such, this variant might be a promising candidate for the individualization of statin therapy.

Background The efficacy and safety of tofacitinib, a Janus kinase inhibitor, in patients who are hospitalized with coronavirus disease 2019 (Covid-19) pneumonia are unclear. Methods We randomly assigned, in a 1:1 ratio, hospitalized adults with Covid-19 pneumonia to receive either tofacitinib at a dose of 10 mg or placebo twice daily for up to 14 days or until hospital discharge. The primary outcome was the occurrence of death or respiratory failure through day 28 as assessed with the use of an eight-level ordinal scale (with scores ranging from 1 to 8 and higher scores indicating a worse condition). All-cause mortality and safety were also assessed. Results A total of 289 patients underwent randomization at 15 sites in Brazil. Overall, 89.3% of the patients received glucocorticoids during hospitalization. The cumulative incidence of death or respiratory failure through day 28 was 18.1% in the tofacitinib group and 29.0% in the placebo group (risk ratio, 0.63; 95% confidence interval [CI], 0.41 to 0.97; P=0.04). Death from any cause through day 28 occurred in 2.8% of the patients in the tofacitinib group and in 5.5% of those in the placebo group (hazard ratio, 0.49; 95% CI, 0.15 to 1.63). The proportional odds of having a worse score on the eight-level ordinal scale with tofacitinib, as compared with placebo, was 0.60 (95% CI, 0.36 to 1.00) at day 14 and 0.54 (95% CI, 0.27 to 1.06) at day 28. Serious adverse events occurred in 20 patients (14.1%) in the tofacitinib group and in 17 (12.0%) in the placebo group. Conclusions Among patients hospitalized with Covid-19 pneumonia, tofacitinib led to a lower risk of death or respiratory failure through day 28 than placebo. (Funded by Pfizer; STOP-COVID ClinicalTrials.gov number, NCT04469114.)

Statins are the first-line treatment for familial hypercholesterolemia (FH), but response is highly variable due to genetic and nongenetic factors. Here, we explored the association between response and genetic variability in 114 Brazilian adult FH patients. Specifically, a panel of 84 genes was analyzed by exon-targeted gene sequencing (ETGS), and the functional impact of variants in pharmacokinetic (PK) genes was assessed using an array of functionality prediction methods. Low-density lipoprotein cholesterol (LDL-c) response to statins (reduction ≥ 50%) and statin-related adverse event (SRAE) risk were assessed in carriers of deleterious variants in PK-related genes using multivariate linear regression analyses. Fifty-eight (50.8%) FH patients responded to statins, and 24 (21.0%) had SRAE. Results of the multivariate regression analysis revealed that

Background One of the main hurdles of oncological therapy is the development of drug resistance. The ABC transporter gene family contributes majorly to cancer chemoresistance. However, effects of somatic expression of most ABC transporters on cancer outcomes remain largely unclear. Methods We systematically analyzed expression signatures of all 48 human ABC transporters in samples from 8562 patients across 14 different cancer types. The association between CFTR (ABCC7) expression and outcomes was analyzed experimentally using knock-downs and pharmacological CFTR stimulation. Results Across 720 analyzed clinical associations with patient outcomes, 363 were nominally significant of which 29 remained significant after stringent Bonferroni correction. Among those were various previously known associations, as well as a multitude of novel factors that correlated with poor prognosis or predicted improved outcomes. The association between low CFTR levels and reduced survival in lung adenocarcinoma was confirmed in two independent cohorts of 246 patients with a history of smoking (logrank P = 0.0021, hazard ratio [HR], 0.49) and 143 never-smokers (logrank P = 0.0023, HR 0.31). Further in vitro experiments using naturally CFTR expressing lung adenocarcinoma cells showed that treatment with CFTR potentiators significantly reduced proliferation at therapeutically relevant concentrations. Conclusions These results suggest that CFTR acts as a pharmacologically activatable tumor suppressor and constitutes a promising target for adjuvant therapy in lung adenocarcinoma.

High-aspect-ratio and hierarchically nanostructured surfaces are common in nature. Synthetic variants are of interest for their specific chemical, mechanic, electric, photonic, or biologic properties but are cumbersome in fabrication or suffer from structural collapse. Here, we replicated and directly biofunctionalized robust, large-area, and high-aspect-ratio nanostructures by nanoimprint lithography of an off-stoichiometric thiol-ene-epoxy polymer. We structured-in a single-step process-dense arrays of pillars with a diameter as low as 100 nm and an aspect ratio of 7.2; holes with a diameter of 70 nm and an aspect ratio of20; and complex hierarchically layered structures, all with minimal collapse and defectivity. We show that the nanopillar arrays alter mechanosensing of human hepatic cells and provide precise spatial control of cell attachment. We speculate that our results can enable the widespread use of high-aspect-ratio nanotopograhy applications in mechanics, optics, and biomedicine.

Hearing loss is one of the top contributors to years lived with disability and is a risk factor for dementia. Molecular evidence on the cellular origins of hearing loss in humans is growing. Here, we performed a genome-wide association meta-analysis of clinically diagnosed and self-reported hearing impairment on 723,266 individuals and identified 48 significant loci, 10 of which are novel. A large proportion of associations comprised missense variants, half of which lie within known familial hearing loss loci. We used single-cell RNA-sequencing data from mouse cochlea and brain and mapped common-variant genomic results to spindle, root, and basal cells from the stria vascularis, a structure in the cochlea necessary for normal hearing. Our findings indicate the importance of the stria vascularis in the mechanism of hearing impairment, providing future paths for developing targets for therapeutic intervention in hearing loss. publishedVersion

Preemptive targeted pharmacogenetic testing of candidate variations in DPYD is currently being used to limit toxicity associated with fluoropyrimidines. The use of innovative next generation sequencing (NGS) approaches could unveil additional rare (minor allele frequency 1%) genetic risk variants. However, their predictive value and management in clinical practice are still controversial, at least partly due to the challenges associated with functional analyses of rare variants. The aim of this study was to define the predictive power of rare DPYD variants burden on the risk of severe fluoropyrimidine-related toxicity. The DPYD coding sequence and untranslated regions were analyzed by NGS in 120 patients developing grade 3-5 (NCI-CTC vs3.0) fluoropyrimidine-related toxicity and 104 matched controls (no-toxicity). The functional impact of rare variants was assessed using two different in silico predictive tools (i.e., Predict2SNP and ADME Prediction Framework) and structural modeling. Plasma concentrations of uracil (U) and dihydrouracil (UH2) were quantified in carriers of the novel variants. Here, we demonstrate that the burden of rare variants was significantly higher in patients with toxicity compared to controls (p = 0.007, Mann-Whitney test). Carriers of at least one rare missense DPYD variant had a 16-fold increased risk in the first cycle and an 11-fold increased risk during the entire course of chemotherapy of developing a severe adverse event compared to controls (p = 0.013 and p = 0.0250, respectively by multinomial regression model). Quantification of plasmatic U/UH2 metabolites and in silico visualization of the encoded protein were consistent with the predicted functional effect for the novel variations. Analysis and consideration of rare variants by DPYD-sequencing could improve prevention of severe toxicity of fluoropyrimidines and improve patients' quality of life.

Statins are inhibitors of 3-hydroxy-3-methylglutaryl-CoA reductase, a key enzyme in cholesterol biosynthesis, that are highly effective in reducing plasma low-density lipoprotein (LDL) cholesterol and decreasing the risk of cardiovascular events. In recent years, a multitude of variants in genes involved in pharmacokinetics (PK) and pharmacodynamics (PD) have been suggested to influence the cholesterol-lowering response. However, the vast majority of studies have analyzed the pharmacogenetic associations in populations in Europe and the USA, whereas data in other populations, including Brazil, are mostly lacking. This narrative review provides an update of clinical studies on statin pharmacogenomics in Brazilian cohorts exploring lipid-lowering response, adverse events and pleiotropic effects. We find that variants in drug transporter genes (SLCO1B1 and ABCB1) positively impacted atorvastatin and simvastatin response, whereas variants in genes of drug metabolizing enzymes (CYP3A5) decreased response. Furthermore, multiple associations of variants in PD genes (HMGCR, LDLR and APOB) with statin response were identified. Few studies have explored statin-related adverse events, and only ABCB1 but not SLCO1B1 variants were robustly associated with increased risk in Brazil. Statin-related pleiotropic effects were shown to be influenced by variants in PD (LDLR, NR1H2) and antioxidant enzyme (NOS3, SOD2, MTHFR, SELENOP) genes. The findings of these studies indicate that statin pharmacogenomic associations are distinctly different in Brazil compared to other populations. This review also discusses the clinical implications of pharmacogenetic studies and the rising importance of investigating rare variants to explore their association with statin response.

Background Fluorescent reporter labeling and promoter-driven Cre-recombinant technologies have facilitated cellular investigations of physiological and pathological processes, including the widespread use of the Cx3cr1CreER-Eyfp/wt mouse strain for studies of microglia. Methods Immunohistochemistry, Flow Cytometry, RNA sequencing and whole-genome sequencing were used to identify the subpopulation of microglia in Cx3cr1CreER-Eyfp/wt mouse brains. Genetically mediated microglia depletion using Cx3cr1CreER-Eyfp/wtRosa26DTA/wt mice and CSF1 receptor inhibitor PLX3397 were used to deplete microglia. Primary microglia proliferation and migration assay were used for in vitro studies. Results We unexpectedly identified a subpopulation of microglia devoid of genetic modification, exhibiting higher Cx3cr1 and CX3CR1 expression than Cx3cr1CreER-Eyfp/wtCre+Eyfp+ microglia in Cx3cr1CreER-Eyfp/wt mouse brains, thus termed Cx3cr1highCre−Eyfp− microglia. This subpopulation constituted less than 1% of all microglia under homeostatic conditions, but after Cre-driven DTA-mediated microglial depletion, Cx3cr1highCre−Eyfp− microglia escaped depletion and proliferated extensively, eventually occupying one-third of the total microglial pool. We further demonstrated that the Cx3cr1highCre−Eyfp− microglia had lost their genetic heterozygosity and become homozygous for wild-type Cx3cr1. Therefore, Cx3cr1highCre−Eyfp− microglia are Cx3cr1wt/wtCre−Eyfp−. Finally, we demonstrated that CX3CL1–CX3CR1 signaling regulates microglial repopulation both in vivo and in vitro. Conclusions Our results raise a cautionary note regarding the use of Cx3cr1CreER-Eyfp/wt mouse strains, particularly when interpreting the results of fate mapping, and microglial depletion and repopulation studies.

Organotypic and microphysiological culture of primary human tissues and cancers has emerged as a powerful set of technologies that allow to faithfully mimic cellular metabolism and functions ex vivo. The predominant 3D culture methods include spheroids and microfluidic chips. These cultures use low cell numbers and culture volumes, which, however, poses important limitations for the available amounts of sample for downstream analyses. Here, we describe a detailed method for the measurement of glucose consumption dynamics in organotypic culture using a bienzymatic colorimetric assay that accurately quantifies glucose levels using nanoliter input volumes. As an example we utilize spheroids consisting of primary human hepatocytes. The assay has been carefully optimized and benchmarked and is compatible with both longitudinal and high-throughput screening in both static and perfused conditions. The method is straightforward and only requires a microplate reader capable of running absorbance kinetic measurements.

Deep learning-based cell segmentation is increasingly utilized in cell biology and molecular pathology, due to massive accumulation of diverse large-scale datasets and excellent progress in cell representation. However, the development of specialized algorithms has long been hampered by a paucity of annotated training data, whereas the performance of generalist algorithm was limited without experiment-specific calibration. Here, we present a deep learning-based tool called Scellseg consisted of novel pre-trained network architecture and contrastive fine-tuning strategy. In comparison to four commonly used algorithms, Scellseg outperformed others in average precision and Aggregated Jaccard Index on three disparate datasets. Interestingly, we found that eight images are sufficient for model tuning to achieve satisfied performance based on a shot data scale experiment. We also developed a graphical user interface integrated with functions of annotation, fine-tuning and inference, that allows biologists to easily specialize their self-adaptive segmentation model for analyzing images at the single-cell level.