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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.

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.

Individuals differ substantially in their response to pharmacological treatment. Personalized medicine aspires to embrace these inter-individual differences and customize therapy by taking a wealth of patient-specific data into account. Pharmacogenomic constitutes a cornerstone of personalized medicine that provides therapeutic guidance based on the genomic profile of a given patient. Pharmacogenomics already has applications in the clinics, particularly in oncology, whereas future development in this area is needed in order to establish pharmacogenomic biomarkers as useful clinical tools. In this review we present an updated overview of current and emerging pharmacogenomic biomarkers in different therapeutic areas and critically discuss their potential to transform clinical care. Furthermore, we discuss opportunities of technological, methodological and institutional advances to improve biomarker discovery. We also summarize recent progress in our understanding of epigenetic effects on drug disposition and response, including a discussion of the only few pharmacogenomic biomarkers implemented into routine care. We anticipate, in part due to exciting rapid developments in Next Generation Sequencing technologies, machine learning methods and national biobanks, that the field will make great advances in the upcoming years towards unlocking the full potential of genomic data.

Autosomal recessive (AR) disorders pose a significant burden for public health. However, despite their clinical importance, epidemiology and molecular genetics of many AR diseases remain poorly characterized. Here, we analyzed the genetic variability of 508 genes associated with AR disorders based on sequencing data from 141,456 individuals across seven ethnogeographic groups by integrating variants with documented pathogenicity from ClinVar, with stringent functionality predictions for variants with unknown pathogenicity. We first validated our model using 85 diseases for which population-specific prevalence data were available and found that our estimates strongly correlated with the respective clinically observed disease frequencies (r = 0.68; p 25 additional population-specific founder mutations. The presented analyses reveal the molecular genetics of AR diseases with unprecedented resolution and provide insights into epidemiology, complexity, and population-specific founder effects. These data can serve as a powerful resource for clinical geneticists to inform population-adjusted genetic screening programs, particularly in otherwise understudied ethnogeographic groups.

The fast skeletal muscle protein α-actinin-3 is absent in 1.5 billion people worldwide due to homozygosity for a nonsense polymorphism in the ACTN3 gene (R577X) 1. The prevalence of the 577X allele increased as modern humans moved to colder climates, suggesting a link between α-actinin-3 deficiency and improved cold tolerance 1,2. Here, we show that humans lacking α-actinin-3 (XX) are superior in maintaining core body temperature during cold-water immersion due to changes in skeletal muscle thermogenesis. Muscles of XX individuals displayed a shift towards more slow-twitch isoforms of myosin heavy chain (MyHC) and sarcoplasmic reticulum (SR) proteins, accompanied by altered neuronal muscle activation resulting in increased tone rather than overt shivering 3,4. Experiments on Actn3 knockout mice showed no alterations in brown adipose tissue (BAT) properties that could explain the improved cold tolerance in XX individuals. Thus, this study provides a clear mechanism for the positive selection of the ACTN3 X-allele in cold climates and supports a key thermogenic role of skeletal muscle during cold exposure in humans.

Baricitinib, is an oral Janus kinase (JAK)1/JAK2 inhibitor approved for the treatment of rheumatoid arthritis (RA) that was independently predicted, using artificial intelligence (AI)‐algorithms, to be useful for COVID‐19 infection via a proposed anti‐cytokine effects and as an inhibitor of host cell viral propagation. We evaluated the in vitro pharmacology of baricitinib across relevant leukocyte subpopulations coupled to its in vivo pharmacokinetics and showed it inhibited signaling of cytokines implicated in COVID‐19 infection. We validated the AI‐predicted biochemical inhibitory effects of baricitinib on human numb‐associated kinase (hNAK) members measuring nanomolar affinities for AAK1, BIKE, and GAK. Inhibition of NAKs led to reduced viral infectivity with baricitinib using human primary liver spheroids. These effects occurred at exposure levels seen clinically. In a case series of patients with bilateral COVID‐19 pneumonia, baricitinib treatment was associated with clinical and radiologic recovery, a rapid decline in SARS‐CoV‐2 viral load, inflammatory markers, and IL‐6 levels. Collectively, these data support further evaluation of the anti‐cytokine and anti‐viral activity of baricitinib and supports its assessment in randomized trials in hospitalized COVID‐19 patients.

A 2016 study proposed induction of the cytochrome P450 (CYP) enzyme CYP3A5 as a key mechanism for chemotherapy resistance and suggested CYP3A5 as a promising therapeutic target. However, in the context of the available literature we are skeptical that CYP3A5 contributes significantly to cancer drug resistance.

Skeletal muscle preservation is a dynamic process that involves constant repair and regeneration. However, the regenerative capacity of muscle cells declines in hyperglycemia. This study aimed to explore the molecular mechanisms underlying this glucotoxicity during myoblast differentiation. C2C12 cells were exposed to different concentrations of glucose, to recapitulate the development of skeletal muscles in vivo in normo- and hyperglycemic conditions. In high glucose conditions, we found significant increases in levels of total cellular reactive oxygen species (ROS) and a reorganization of SUMO enzyme transcripts and SUMOylated proteins. Furthermore, in anticipation of the ROS-induced damage to newly formed myotubes, we observed acceleration of myogenesis. Interestingly, we found a tight relationship between SUMOylation of the Histone methyltransferase SET7/9 and the maintenance of sarcomeric structures of newly formed myotubes. Finally, treatment with the antioxidant anacardic acid preserved the function and activity of myotubes generated in high-glucose conditions by interfering with both ROS and SUMO pathways. Combined, these results suggest that increased oxidative stress and modulation of SUMO reactions are key mediators of glucotoxicity and inhibition of these perturbations using antioxidants might improve muscle regeneration in hyperglycemia.

Recent phenotypically and functionally relevant human hepatic in vitro systems combine the ability to preserve interindividual molecular differences between patients’ livers in culture with the accessibility and high-throughput compatibility of in vitro assays. These features facilitate studies of specific genetic polymorphisms by using cells from donors with defined variants of interest or by selective gene knock-down experiments. Furthermore, these models constitute promising tools to evaluate drug–drug interactions as well as the effects of liver diseases on drug pharmacokinetics in co-cultures of hepatocytes and non-parenchymal cells. In the near future, we anticipate that these tools will be of high relevance for predicting the in vivo kinetics, toxicity and drug–drug interactions of drug candidates already during preclinical development.

High failure rates of drug candidates in the clinics, restricted-use warnings as well as withdrawals of drugs in postmarketing stages are of substantial concern for the pharmaceutical industry and drug-induced liver injury (DILI) constitutes one of the most frequent reasons for such safety failures. Importantly, as DILI cannot be accurately predicted using animal models, animal safety tests are commonly complemented with assessments in human in vitro systems. 3D spheroid cultures of primary human hepatocytes in chemically defined conditions, hereafter termed CD-spheroids, have recently emerged as a microphysiological model system in which hepatocytes retain their molecular phenotypes and hepatic functions for multiple weeks in culture. However, their predictive power for the detection of hepatotoxic liabilities has not been systematically assessed. Therefore, we here evaluated the hepatotoxicity of 123 drugs with or without direct implication in clinical DILI events. Importantly, using ATP quantifications as the single endpoint, the model accurately distinguished between hepatotoxic and nontoxic structural analogues and exceeded both sensitivity and specificity of all previously published in vitro assays at substantially lower exposure levels, successfully detecting 69% of all hepatotoxic compounds without producing any false positive results (100% specificity). Furthermore, the platform supports the culture of spheroids of primary hepatocytes from preclinical animal models, thereby allowing the identification of animal-specific toxicity events. We anticipate that CD-spheroids represent a powerful and versatile tool in drug discovery and preclinical drug development that can reliably flag hepatotoxic drug candidates and provide guidance for the selection of the most suitable animal models.

Three-Dimensional (3D) liver microtissues, specifically prepared from primary human hepatocytes (PHH) in coculture with nonparenchymal cells (NPCs), have been shown to be a valuable tool for in vitro toxicology. However, a lack of thorough characterization on a functional, transcriptomic, and proteomic level of such models during long-term cultivation is evident. By integrating multiple omics technologies, we provide in this study an in-depth long-term characterization of 3D microtissues composed of PHH from three different donors cocultured with primary NPCs. The 3D human liver microtissues (hLiMTs) exhibited stable adenosine triphosphate (ATP) content and albumin secretion over 5 weeks. Histological analysis indicated a healthy liver tissue with polarized expression of bile salt export pump (BSEP) and multidrug resistance protein 2 (MRP2) in a structure reminiscent of bile canaliculi. The 3D microtissues exhibited stable basal and inducible cytochrome P450 activities up to 5 weeks in culture. Analysis of 40,716 transcripts using RNA arrays revealed distinct similarities to native human liver gene expression. Long-term culture showed a stable phenotype up to 5 weeks, with differences in liver gene expression primarily attributed to individual donors. Proteomic profiling of 2200 unique proteins by label-free LC-MS/MS revealed a relatively stable protein expression where only 7.3% were up- or downregulated more than twofold from day 7 to 35 in culture. Taken together, these results suggest that hLiMTs represent a responsive and physiologically relevant in vitro liver model that maintains stable function over 5 weeks and is therefore well suited for repeated-dose toxicity testing.

Enhancing the early detection of new therapies that are likely to carry a safety liability in the context of the intended patient population would provide a major advance in drug discovery. Microphysiological systems (MPS) technology offers an opportunity to support enhanced preclinical to clinical translation through the generation of higher-quality preclinical physiological data. In this review, we highlight this technological opportunity by focusing on key target organs associated with drug safety and metabolism. By focusing on MPS models that have been developed for these organs, alongside other relevant in vitro models, we review the current state of the art and the challenges that still need to be overcome to ensure application of this technology in enhancing drug discovery.

Genetic polymorphisms in cytochrome P450 (CYP) genes can result in altered metabolic activity toward a plethora of clinically important medications. Thus, single nucleotide variants and copy number variations in CYP genes are major determinants of drug pharmacokinetics and toxicity and constitute pharmacogenetic biomarkers for drug dosing, efficacy, and safety. Strikingly, the distribution of CYP alleles differs considerably between populations with important implications for personalized drug therapy and healthcare programs. To provide a global distribution map of CYP alleles with clinical importance, we integrated whole‐genome and exome sequencing data from 56,945 unrelated individuals of five major human populations. By combining this dataset with population‐specific linkage information, we derive the frequencies of 176 CYP haplotypes, providing an extensive resource for major genetic determinants of drug metabolism. Furthermore, we aggregated this dataset into spectra of predicted functional variability in the respective populations and discuss the implications for population‐adjusted pharmacological treatment strategies.

The genomic inter-individual heterogeneity remains a significant challenge for both clinical decision-making and the design of clinical trials. Although next-generation sequencing (NGS) is increasingly implemented in drug development and clinical trials, translation of the obtained genomic information into actionable clinical advice lags behind. Major reasons are the paucity of sufficiently powered trials that can quantify the added value of pharmacogenetic testing, and the considerable pharmacogenetic complexity with millions of rare variants with unclear functional consequences. The resulting uncertainty is reflected in inconsistencies of pharmacogenomic drug labels in Europe and the United States. In this review, we discuss how the knowledge gap for bridging pharmacogenomics into the clinics can be reduced. First, emerging methods that allow the high-throughput experimental characterization of pharmacogenomic variants combined with novel computational tools hold promise to improve the accuracy of drug response predictions. Second, tapping of large biobanks of therapeutic drug monitoring data allows to conduct high-powered retrospective studies that can validate the clinical importance of genetic variants, which are currently incompletely characterized. Combined, we are confident that these methods will improve the accuracy of drug response predictions and will narrow the gap between variant identification and its utilization for clinical decision-support.

Recently, it was published that CYP3A5 contributes to chemotherapeutic drug resistance in a wide range of solid tumors, including hepatocellular carcinoma. However, CYP3A5 is highly polymorphic and 90% of Caucasians are homozygous for the loss-of-function allele CYP3A5*3. Here, we evaluate the relationship between CYP3A5 genotype and expression level of both CYP3A5 transcripts and protein in biopsies from 19 pairs of liver tumors and corresponding peritumoral tissue. We find that CYP3A5 transcript levels are reduced compared with peritumoral controls. Moreover, we do not detect CYP3A5 protein in homozygous CYP3A5*3 carriers and no relative increase of CYP3A5 in tumoral tissue of CYP3A5*1 carriers. We conclude that anticancer drug resistance is unlikely to be caused by increased CYP3A5 expression.

SUMOylation is a dynamic, reversible, enzymatic drug-targetable post-translational modification (PTM) reaction where the Small Ubiquitin-like Modifier (SUMO) moieties are attached to proteins. This reaction regulates various biological functions like cell growth, differentiation, and it is crucial for maintaining organ homeostasis. However, the actions of SUMO in skeletal muscle pathophysiology are still not investigated. In this study, we quantified the abundance of the SUMO enzymes and determined the distribution of SUMOylated proteins along the fibers of nine different muscles. We find that skeletal muscles contain a distinctive group of SUMO enzymes and SUMOylated proteins in relation to their different metabolism, functions, and fiber type composition. In addition, before the activation of protein degradation pathways, this unique set is quickly altered in response to muscle sedentariness. Finally, we demonstrated that PAX6 acts as an upstream regulator of the SUMO conjugation reaction, which can become a potential therapeutic marker to prevent muscle diseases generated by inactivity.

Objective- The Wnt/β-catenin pathway orchestrates development of the blood-brain barrier, but the downstream mechanisms involved at different developmental windows and in different central nervous system (CNS) tissues have remained elusive. Approach and Results- Here, we create a new mouse model allowing spatiotemporal investigations of Wnt/β-catenin signaling by induced overexpression of Axin1, an inhibitor of β-catenin signaling, specifically in endothelial cells ( Axin1 iEC- OE). AOE (Axin1 overexpression) in Axin1 iEC- OE mice at stages following the initial vascular invasion of the CNS did not impair angiogenesis but led to premature vascular regression followed by progressive dilation and inhibition of vascular maturation resulting in forebrain-specific hemorrhage 4 days post-AOE. Analysis of the temporal Wnt/β-catenin driven CNS vascular development in zebrafish also suggested that Axin1 iEC- OE led to CNS vascular regression and impaired maturation but not inhibition of ongoing angiogenesis within the CNS. Transcriptomic profiling of isolated, β-catenin signaling-deficient endothelial cells during early blood-brain barrier-development (E11.5) revealed ECM (extracellular matrix) proteins as one of the most severely deregulated clusters. Among the 20 genes constituting the forebrain endothelial cell-specific response signature, 8 ( Adamtsl2, Apod, Ctsw, Htra3, Pglyrp1, Spock2, Ttyh2, and Wfdc1) encoded bona fide ECM proteins. This specific β-catenin-responsive ECM signature was also repressed in Axin1 iEC- OE and endothelial cell-specific β-catenin-knockout mice ( Ctnnb1-KOiEC) during initial blood-brain barrier maturation (E14.5), consistent with an important role of Wnt/β-catenin signaling in orchestrating the development of the forebrain vascular ECM. Conclusions- These results suggest a novel mechanism of establishing a CNS endothelium-specific ECM signature downstream of Wnt-β-catenin that impact spatiotemporally on blood-brain barrier differentiation during forebrain vessel development. Visual Overview- An online visual overview is available for this article., SCOPUS: ar.j, info:eu-repo/semantics/published

Adverse reactions or lack of response to medications are important concerns for drug development programs. However, faithful predictions of drug metabolism and toxicity are difficult because animal models show only limited translatability to humans. Furthermore, current in vitro systems, such as hepatic cell lines or primary human hepatocyte (PHH) 2-dimensional (2D) monolayer cultures, can be used only for acute toxicity tests because of their immature phenotypes and inherent instability. Therefore, the migration to novel phenotypically stable models is of prime importance for the pharmaceutical industry. Novel 3-dimensional (3D) culture systems have been shown to accurately mimic in vivo hepatic phenotypes on transcriptomic and proteomic level, but information about their metabolic stability is lacking. Using a combination of targeted and untargeted high-resolution mass spectrometry, we found that PHHs in 3D spheroid cultures remained metabolically stable for multiple weeks, whereas metabolic patterns of PHHs from the same donors cultured as conventional 2D monolayers rapidly deteriorated. Furthermore, pharmacokinetic differences between donors were maintained in 3D spheroid cultures, enabling studies of interindividual variability in drug metabolism and toxicity. We conclude that the 3D spheroid system is metabolically stable and constitutes a suitable model for in vitro studies of long-term drug metabolism and pharmacokinetics.—Vorrink, S. U., Ullah, S., Schmid, S., Nandania, J., Velagapudi, V., Beck, O., Ingelman-Sundberg, M., Lauschke, V. M. Endogenous and xenobiotic metabolic stability of primary human hepatocytes in long-term 3D spheroid cultures revealed by a combination of targeted and untargeted metabolomics.

The liver fulfills critical metabolic functions, such as controlling blood sugar and ammonia levels, and is of central importance for lipid metabolism and detoxification of environmental and chemical agents, including drugs. Liver injuries of different etiology can elicit a spectrum of responses. Some hepatocytes initiate molecular programs resulting in cell death, whereas others undergo cellular divisions to regenerate the damaged organ. Interestingly, recent research indicates that microRNAs serve as very rapid as well as long-term regulators in these processes. In this review, we discuss their importance in liver disease etiology and progression as well as for therapy with particular focus on metabolic and inflammatory conditions. Furthermore, we highlight the central role of microRNAs in controlling hepatocyte differentiation and plasticity, which are required for successful regeneration, but under certain conditions, such as chronic liver insults, can result in the formation of hepatocellular carcinoma.

In this study we characterized the genetic variability of 146 clinically relevant genes influencing drug pharmacokinetics in African and European subpopulations, which are key determinants for interindividual variations in drug efficacy and adverse drug reactions.By integrating data from the 1000 Genomes Project (n = 1,092 individuals) and the Exome Sequencing Project (ESP; n = 6,503 individuals), single-nucleotide variants (SNVs) were identified and analyzed regarding frequency, functional consequences, and ethnic diversity.In total, we found 12,152 SNVs in exons, 312 of which were novel. The majority of variants were rare (minor allele frequency (MAF)1%; 92.9%) and nonsynonymous (56.2%). We calculated that individuals of European and African descent harbor, on average, 100.8 and 121.4 variants across the 146 pharmacogenes studied, respectively. Additionally, by analyzing variation patterns across these populations, we pinpointed potential priority genes for population-adjusted genetic profiling strategies. Furthermore, we estimated, based on our variant frequency analyses, that approximately 30-40% of functional variability in pharmacogenes can be attributed to rare variants.Our results indicate that these clinically important genes are genetically highly variable and differ considerably between populations. Furthermore, the large extent of rare variants emphasizes the need for sequencing-based approaches and effective functionality predictions to allow for true personalized medicine.Genet Med 19 1, 20-29.

Hepatocytes are dynamic cells that, upon injury, can alternate between nondividing differentiated and dedifferentiated proliferating states in vivo. However, in two-dimensional cultures, primary human hepatocytes (PHHs) rapidly dedifferentiate, resulting in loss of hepatic functions that significantly limits their usefulness as an in vitro model of liver biology, liver diseases, as well as drug metabolism and toxicity. Thus, understanding the underlying mechanisms and stalling of the dedifferentiation process would be highly beneficial to establish more-accurate and relevant long-term in vitro hepatocyte models. Here, we present comprehensive analyses of whole proteome and transcriptome dynamics during the initiation of dedifferentiation during the first 24 hours of culture. We report that early major rearrangements of the noncoding transcriptome, hallmarked by increased expression of small nucleolar RNAs, long noncoding RNAs, microRNAs (miRNAs), and ribosomal genes, precede most changes in coding genes during dedifferentiation of PHHs, and we speculated that these modulations could drive the hepatic dedifferentiation process. To functionally test this hypothesis, we globally inhibited the miRNA machinery using two established chemically distinct compounds, acriflavine and poly-l-lysine. These inhibition experiments resulted in a significantly impaired miRNA response and, most important, in a pronounced reduction in the down-regulation of hepatic genes with importance for liver function. Thus, we provide strong evidence for the importance of noncoding RNAs, in particular, miRNAs, in hepatic dedifferentiation, which can aid the development of more-efficient differentiation protocols for stem-cell-derived hepatocytes and broaden our understanding of the dynamic properties of hepatocytes with respect to liver regeneration. Conclusion: miRNAs are important drivers of hepatic dedifferentiation, and our results provide valuable information regarding the mechanisms behind liver regeneration and possibilities to inhibit dedifferentiation in vitro. (Hepatology 2016;64:1743-1756)

Assessing the potential of a new drug to cause drug-induced liver injury (DILI) is a challenge for the pharmaceutical industry. We therefore determined whether cell models currently used in safety assessment (HepG2, HepaRG, Upcyte and primary human hepatocytes in conjunction with basic but commonly used endpoints) are actually able to distinguish between novel chemical entities (NCEs) with respect to their potential to cause DILI. A panel of thirteen compounds (nine DILI implicated and four non-DILI implicated in man) were selected for our study, which was conducted, for the first time, across multiple laboratories. None of the cell models could distinguish faithfully between DILI and non-DILI compounds. Only when nominal in vitro concentrations were adjusted for in vivo exposure levels were primary human hepatocytes (PHH) found to be the most accurate cell model, closely followed by HepG2. From a practical perspective, this study revealed significant inter-laboratory variation in the response of PHH, HepG2 and Upcyte cells, but not HepaRG cells. This variation was also observed to be compound dependent. Interestingly, differences between donors (hepatocytes), clones (HepG2) and the effect of cryopreservation (HepaRG and hepatocytes) were less important than differences between the cell models per se. In summary, these results demonstrate that basic cell health endpoints will not predict hepatotoxic risk in simple hepatic cells in the absence of pharmacokinetic data and that a multicenter assessment of more sophisticated signals of molecular initiating events is required to determine whether these cells can be incorporated in early safety assessment. Electronic supplementary material The online version of this article (doi:10.1007/s00204-016-1745-4) contains supplementary material, which is available to authorized users.

Recent research highlighted the large extent of rare variants in pharmacogenes and, on this basis, it was estimated that rare variants account for 30–40% of the functional variability in pharmacogenes. It has been proposed that comprehensive next-generation sequencing (NGS)-based sequencing of pharmacogenes could soon be a cost-effective methodology for clinical routine genotyping. Yet, multiple challenges on technical, interpretative and ethical levels need to be overcome to enable the reasonable dissemination of comprehensive pharmacogenetic genotyping, that includes rare genetic variation, into clinical practice. We argue that current pre-emptive pharmacogenetic testing cannot be based on comprehensive approaches but needs to be restricted to validated variants. Rather, comprehensive strategies should only be used for retrospective analyses of patients exhibiting unanticipated drug responses. Thereby, subsequent to computational analyses and functional validations, emerging variants with confirmed functional relevance can be incorporated into candidate genotyping strategies, thus refining and enhancing future pre-emptive genetic testing.

Purpose: Biomedical databases combining electronic medical records and phenotypic and genomic data constitute a powerful resource for the personalization of treatment. To leverage the wealth of information provided, algorithms are required that systematically translate the contained information into treatment recommendations based on existing genotype-phenotype associations. Methods: We developed and tested algorithms for translation of preexisting genotype data of over 44,000 participants of the Estonian biobank into pharmacogenetic recommendations. We compared the results obtained by genome sequencing, exome sequencing, and genotyping using microarrays, and evaluated the impact of pharmacogenetic reporting based on drug prescription statistics in the Nordic countries and Estonia. Results: Our most striking result was that the performance of genotyping arrays is similar to that of genome sequencing, whereas exome sequencing is not suitable for pharmacogenetic predictions. Interestingly, 99.8% of all assessed individuals had a genotype associated with increased risks to at least one medication, and thereby the implementation of pharmacogenetic recommendations based on genotyping affects at least 50 daily drug doses per 1000 inhabitants. Conclusion: We find that microarrays are a cost-effective solution for creating preemptive pharmacogenetic reports, and with slight modifications, existing databases can be applied for automated pharmacogenetic decision support for clinicians.

Up to half of all patients do not respond to pharmacological treatment as intended. A substantial fraction of these inter-individual differences is due to heritable factors and a growing number of associations between genetic variations and drug response phenotypes have been identified. Importantly, the rapid progress in Next Generation Sequencing technologies in recent years unveiled the true complexity of the genetic landscape in pharmacogenes with tens of thousands of rare genetic variants. As each individual was found to harbor numerous such rare variants they are anticipated to be important contributors to the genetically encoded inter-individual variability in drug effects. The fundamental challenge however is their functional interpretation due to the sheer scale of the problem that renders systematic experimental characterization of these variants currently unfeasible. Here, we review concepts and important progress in the development of computational prediction methods that allow to evaluate the effect of amino acid sequence alterations in drug metabolizing enzymes and transporters. In addition, we discuss recent advances in the interpretation of functional effects of non-coding variants, such as variations in splice sites, regulatory regions and miRNA binding sites. We anticipate that these methodologies will provide a useful toolkit to facilitate the integration of the vast extent of rare genetic variability into drug response predictions in a precision medicine framework.

Organic anion transporting polypeptides (OATP) encoded by the SLCO gene family constitute clinically important transporters involved in the disposition of endogenous compounds and many commonly prescribed drugs, including statins, methotrexate and antihypertensive medications. Common genetic polymorphisms in SLCO genes are known to affect OATP function and modulate efficacy and safety of OATP substrates. However, current frequency data of these variants and haplotypes is generally based on few rather heterogenous populations of relatively small sample size. Furthermore, the genetic variability beyond these selected pharmacogenetic biomarkers has not been systematically analyzed. Here, we provide a global consolidated map of SLCO variability by leveraging fully compatible Next Generation Sequencing data from 138,632 unrelated individuals across seven major human populations. Overall, we find 9811 exonic single nucleotide variants and 155 copy number variations of which 99.3% were rare with frequencies

The liver fulfills central roles in metabolic control and detoxification and, as such, is continuously exposed to a plethora of insults. Importantly, the liver has a unique ability to regenerate and can completely recoup from most acute, non-iterative insults. However, multiple conditions, including viral hepatitis, non-alcoholic fatty liver disease (NAFLD), long-term alcohol abuse and chronic use of certain medications, can cause persistent injury in which the regenerative capacity eventually becomes dysfunctional, resulting in hepatic scaring and cirrhosis. Calcium is a versatile secondary messenger that regulates multiple hepatic functions, including lipid and carbohydrate metabolism, as well as bile secretion and choleresis. Accordingly, dysregulation of calcium signaling is a hallmark of both acute and chronic liver diseases. In addition, recent research implicates calcium transients as essential components of liver regeneration. In this review, we provide a comprehensive overview of the role of calcium signaling in liver health and disease and discuss the importance of calcium in the orchestration of the ensuing regenerative response. Furthermore, we highlight similarities and differences in spatiotemporal calcium regulation between liver insults of different etiologies. Finally, we discuss intracellular calcium control as an emerging therapeutic target for liver injury and summarize recent clinical findings of calcium modulation for the treatment of ischemic-reperfusion injury, cholestasis and NAFLD.

BackgroundAdverse drug reactions are a major concern in drug development and clinical therapy. Genetic polymorphisms in genes involved in drug metabolism and transport are major determinants of treatment efficacy and adverse reactions, and constitute important biomarkers for drug dosing, efficacy and safety. Importantly, human populations and subgroups differ substantially in their pharmacogenetic variability profiles, with important consequences for personalised medicine strategies and precision public health approaches. Despite their long migration history, Ashkenazi Jews constitute a rather isolated population with a unique genetic signature that is distinctly different from other populations.ObjectiveTo provide a comprehensive overview of the pharmacogenetic profile in Ashkenazim.MethodsWe analysed next-generation sequencing data from 5076 Ashkenazim individuals and used sequence data from 117 425 non-Jewish individuals as reference.ResultsWe derived frequencies of 164 alleles in 17 clinically relevant pharmacogenes and derived profiles of putative functional consequences, providing the most comprehensive data set of Jewish pharmacogenetic diversity published to date. Furthermore, we detected 127 variants with an aggregated frequency of 20.7% that were specifically found in Ashkenazim, of which 55 variants were putatively deleterious (aggregated frequency of 9.4%).ConclusionThe revealed pattern of pharmacogenetic variability in Ashkenazi Jews is distinctly different from other populations and is expected to translate into unique functional consequences, especially for the metabolism of CYP2A6, CYP2C9, NAT2 and VKORC1 substrates. We anticipate that the presented data will serve as a powerful resource for the guidance of pharmacogenetic treatment decisions and the optimisation of population-specific genotyping strategies in the Ashkenazi diaspora.

Personalized drug therapy aims to optimize the efficacy of pharmacological treatments by considering genetic, pathophysiological, dietary, and environmental factors as well as comedications and compliance. A multitude of associations between the specific genetic constitution of the patient and drug pharmacokinetics and pharmacodynamics has been identified in the last decades that encompass mainly common single nucleotide variants (SNVs) and gene copy number variations (CNVs) of importance for the function of genes encoding drug-metabolizing enzymes and transporters involved in drug absorption, distribution, metabolism, and excretion (ADME). In addition, genetic variation in factors encoding the major histocompatibility complex have been helpful to predict immune-mediated drug toxicity. This knowledge has been translated into clinical applications through the implementation of pharmacogenomic biomarkers. Over 230 of such markers that can, to a certain extent, predict drug efficacy or the likelihood of adverse drug reactions (ADRs) are recognized by the US Food and Drug Administration (FDA) and the European Medicines Agency (EMA) and are included in the drug labels of the respective medication. They are of particular value in cancer therapy to provide information of use to avoid ADRs and lack of response.

Background Variability in genes implicated in drug pharmacokinetics or drug response can modulate treatment efficacy or predispose to adverse drug reactions. Besides common genetic polymorphisms, recent sequencing projects revealed a plethora of rare genetic variants in genes encoding proteins involved in drug metabolism, transport, and response. Results To understand the global importance of rare pharmacogenetic gene variants, we mapped the variability in 208 pharmacogenes by analyzing exome sequencing data from 60,706 unrelated individuals and estimated the importance of rare and common genetic variants using a computational prediction framework optimized for pharmacogenetic assessments. Our analyses reveal that rare pharmacogenetic variants were strongly enriched in mutations predicted to cause functional alterations. For more than half of the pharmacogenes, rare variants account for the entire genetic variability. Each individual harbored on average a total of 40.6 putatively functional variants, rare variants accounting for 10.8% of these. Overall, the contribution of rare variants was found to be highly gene- and drug-specific. Using warfarin, simvastatin, voriconazole, olanzapine, and irinotecan as examples, we conclude that rare genetic variants likely account for a substantial part of the unexplained inter-individual differences in drug metabolism phenotypes. Conclusions Combined, our data reveal high gene and drug specificity in the contributions of rare variants. We provide a proof-of-concept on how this information can be utilized to pinpoint genes for which sequencing-based genotyping can add important information to predict drug response, which provides useful information for the design of clinical trials in drug development and the personalization of pharmacological treatment. Electronic supplementary material The online version of this article (10.1186/s40246-018-0157-3) contains supplementary material, which is available to authorized users.

Pharmacological treatment and exposure to xenobiotics can cause substantial changes in epigenetic signatures. The majority of these epigenetic changes, caused by the compounds in question, occur downstream of transcriptional activation mechanisms, whereby the epigenetic alterations can create a transcriptional memory and stably modulate cell function. The increasing understanding of epigenetic mechanisms and their importance in disease has prompted the development of therapeutic interventions that target epigenetic modulatory mechanisms, particularly in oncology where inhibitors of epigenetic-modifying proteins (epidrugs) have been successfully used in treatment, mostly in combination with standard-of-care chemotherapy, either provoking direct cytotoxicity or inhibiting resistance to anticancer drugs. In addition, emerging methods for detecting epigenetically modified DNA in bodily fluids may provide information about tumor phenotype or drug treatment success. However, it is important to note that many technical pitfalls, such as the nondeconvolution of methylcytosine and hydroxymethylcytosine, compromise epigenetic analyses and the interpretation of results. In this review, we provide an update on the field, with an emphasis on the novel therapeutic opportunities made possible by epidrugs.

Prediction of phenotypic consequences of mutations constitutes an important aspect of precision medicine. Current computational tools mostly rely on evolutionary conservation and have been calibrated on variants associated with disease, which poses conceptual problems for assessment of variants in poorly conserved pharmacogenes. Here, we evaluated the performance of 18 current functionality prediction methods leveraging experimental high-quality activity data from 337 variants in genes involved in drug metabolism and transport and found that these models only achieved probabilities of 0.1–50.6% to make informed conclusions. We therefore developed a functionality prediction framework optimized for pharmacogenetic assessments that significantly outperformed current algorithms. Our model achieved 93% for both sensitivity and specificity for both loss-of-function and functionally neutral variants, and we confirmed its superior performance using cross validation analyses. This novel model holds promise to improve the translation of personal genetic information into biological conclusions and pharmacogenetic recommendations, thereby facilitating the implementation of Next-Generation Sequencing data into clinical diagnostics.

In this issue of Clinical Science, Schueller et al. [Clin. Sci. (2017) 131, 1971-1987] evaluated the role of miR-223 across multiple etiologies of acute and chronic liver insults in murine models and clinical samples. The authors find that while miR-223 is not mechanistically involved in liver injury, its intracellular levels in hepatocytes are increased upon hepatic damage in a broad panel of mechanistically distinct injury models. Furthermore, the authors provide evidence that circulating miR-223 levels provide a promising minimally invasive biomarker for acute liver failure (ALF) that defines a distinct subset of ALF cases and correlates with clinical outcomes. Combined, the highlighted study suggests that miR-223 constitutes a promising biomarker whose clinical validity and utility warrant further investigations.

Reliable and versatile hepatic in vitro systems for the prediction of drug pharmacokinetics and toxicity are essential constituents of preclinical safety assessment pipelines for new medicines. Here, we compared three emerging cell systems-hepatocytes derived from induced pluripotent stem cells, HepaRG cells, and three-dimensional primary human hepatocyte (PHH) spheroids-at transcriptional and functional levels in a multicenter study to evaluate their potential as predictive models for drug-induced hepatotoxicity. Transcriptomic analyses revealed widespread gene expression differences between the three cell models, with 8148 of 17,462 analyzed genes (47%) being differentially expressed. Expression levels of genes involved in the metabolism of endogenous as well as xenobiotic compounds were significantly elevated in PHH spheroids, whereas genes involved in cell division and endocytosis were significantly upregulated in HepaRG cells and hepatocytes derived from induced pluripotent stem cells, respectively. Consequently, PHH spheroids were more sensitive to a panel of drugs with distinctly different toxicity mechanisms, an effect that was amplified by long-term exposure using repeated treatments. Importantly, toxicogenomic analyses revealed that transcriptomic changes in PHH spheroids were in compliance with cholestatic, carcinogenic, or steatogenic in vivo toxicity mechanisms at clinically relevant drug concentrations. Combined, the data reveal important phenotypic differences between the three cell systems and suggest that PHH spheroids can be used for functional investigations of drug-induced liver injury in vivo in humans.

Responses to drugs and pharmacological treatments differ considerably between individuals. Importantly, only 50%–75% of patients have been shown to react adequately to pharmacological interventions, whereas the others experience either a lack of efficacy or suffer from adverse events. The liver is of central importance in the metabolism of most drugs. Because of this exposed status, hepatotoxicity is amongst the most common adverse drug reactions and hepatic liabilities are the most prevalent reason for the termination of development programs of novel drug candidates. In recent years, more and more factors were unveiled that shape hepatic drug responses and thus underlie the observed inter-individual variability. In this review, we provide a comprehensive overview of different principle mechanisms of drug hepatotoxicity and illustrate how patient-specific factors, such as genetic, physiological and environmental factors, can shape drug responses. Furthermore, we highlight other parameters, such as concomitantly prescribed medications or liver diseases and how they modulate drug toxicity, pharmacokinetics and dynamics. Finally, we discuss recent progress in the field of in vitro toxicity models and evaluate their utility in reflecting patient-specific factors to study inter-individual differences in drug response and toxicity, as this understanding is necessary to pave the way for a patient-adjusted medicine.

The liver is an organ with critical importance for drug treatment as the disposition and response to a given drug is often determined by its hepatic metabolism. Patient-specific factors can entail increased susceptibility to drug-induced liver injury, which constitutes a major risk for drug development programs causing attrition of promising drug candidates or costly withdrawals in postmarketing stages. Hitherto, mainly animal studies and 2D hepatocyte systems have been used for the examination of human drug metabolism and toxicity. Yet, these models are far from satisfactory due to extensive species differences and because hepatocytes in 2D cultures rapidly dedifferentiate resulting in the loss of their hepatic phenotype and functionality. With the increasing comprehension that 3D cell culture systems more accurately reflect in vivo physiology, in the recent decade more and more research has focused on the development and optimization of various 3D culture strategies in an attempt to preserve liver properties in vitro. In this contribution, we critically review these developments, which have resulted in an arsenal of different static and perfused 3D models. These systems include sandwich-cultured hepatocytes, spheroid culture platforms, and various microfluidic liver or multiorgan biochips. Importantly, in many of these models hepatocytes maintain their phenotype for prolonged times, which allows probing the potential of newly developed chemical entities to cause chronic hepatotoxicity. Moreover, some platforms permit the investigation of drug action in specific genetic backgrounds or diseased hepatocytes, thereby significantly expanding the repertoire of tools to detect drug-induced liver injuries. It is concluded that the development of 3D liver models has hitherto been fruitful and that systems are now at hand whose sensitivity and specificity in detecting hepatotoxicity are superior to those of classical 2D culture systems. For the future, we highlight the need to develop more integrated coculture model systems to emulate immunotoxicities that arise due to complex interactions between hepatocytes and immune cells.

This manuscript provides nomenclature recommendations developed by an international workgroup to increase transparency and standardization of pharmacogenetic (PGx) result reporting. Presently, sequence variants identified by PGx tests are described using different nomenclature systems. In addition, PGx analysis may detect different sets of variants for each gene, which can affect interpretation of results. This practice has caused confusion and may thereby impede the adoption of clinical PGx testing. Standardization is critical to move PGx forward.

To improve the epigenomic analysis of tissues rich in 5-hydroxymethylcytosine (hmC), we developed a novel protocol called TAB-Methyl-SEQ, which allows for single base resolution profiling of both hmC and 5-methylcytosine by targeted next-generation sequencing. TAB-Methyl-SEQ data were extensively validated by a set of five methodologically different protocols. Importantly, these extensive cross-comparisons revealed that protocols based on Tet1-assisted bisulfite conversion provided more precise hmC values than TrueMethyl-based methods. A total of 109 454 CpG sites were analyzed by TAB-Methyl-SEQ for mC and hmC in 188 genes from 20 different adult human livers. We describe three types of variability of hepatic hmC profiles: (i) sample-specific variability at 40.8% of CpG sites analyzed, where the local hmC values correlate to the global hmC content of livers (measured by LC-MS), (ii) gene-specific variability, where hmC levels in the coding regions positively correlate to expression of the respective gene and (iii) site-specific variability, where prominent hmC peaks span only 1 to 3 neighboring CpG sites. Our data suggest that both the gene- and site-specific components of hmC variability might contribute to the epigenetic control of hepatic genes. The protocol described here should be useful for targeted DNA analysis in a variety of applications.

Interindividual variability in drug metabolism and drug toxicity persists as a major problem for drug development and treatment. Increased or decreased capacity for drug elimination or drug action reduces drug efficacy and places substantial economic burdens on society (e.g., due to treatment of adverse drug reactions) [1]. To a great extent this variation is based on genetic differences, and indeed many drugs now carry pharmacogenomic labels regarding mandatory or informative genetic tests that have to/can be performed before prescription (http://www.fda.gov/drugs/scienceresearch/researchareas/pharmacogenetics/ucm083378.htm).

Trends Many studies assess epigenetic signatures in bodily fluids and make conclusions about epigenetic patterns in inaccessible tissues of interest such as brain, thus neglecting the tissue specificity of epigenetic marks. There is a growing lag between the forefront of epigenetics and the methods routinely applied in epigenetic studies. For instance, while techniques to detect the functionally relevant methylcytosine derivate 5-hydroxymethylcytosine were described years ago, only a few studies use such detection methods.

Abnormal plasma apolipoprotein levels are consistently implicated in CVD risk. Although 30% to 60% of their interindividual variability is genetic, common genetic variants explain only 10% to 20% of these differences. Rare genetic variants may be major sources of the missing heritability, yet quantitative evaluations of their contribution to phenotypic variability are lacking. Here, we analyzed whole-genome and whole-exome sequencing data from 138,632 individuals across seven major human populations to present a systematic overview of genetic apolipoprotein variability. We provide population-specific frequencies of 38 clinically important apolipoprotein alleles and identify further 6,875 genetic variants, 33% of which are novel and 98.7% of which are rare with minor allele frequencies

Much of the inter-individual variability in drug efficacy and risk of adverse reactions is due to polymorphisms in genes encoding proteins involved in drug pharmacokinetics and pharmacodynamics or immunological responses. Pharmacogenetic research has identified a multitude of gene-drug response associations, which have resulted in genetically guided treatment and dosing decisions to yield a higher success rate of pharmacological treatment. The rapid technological developments for genetic analyses reveal that the number of genetic variants with importance for drug action is much higher than previously thought and that a true personalized prediction of drug response requires attention to millions of rare mutations. Here, we review the evolutionary background of genetic polymorphisms in drug-metabolizing enzymes, provide some important examples of current use of pharmacogenomic biomarkers, and give an update of germline and somatic genome biomarkers that are in use in drug development and clinical practice. We also discuss the current technology development with emphasis on complex genetic loci, review current initiatives for validation of pharmacogenomic biomarkers, and present scenarios for the future taking rare genetic variants into account for a true personalized genetically guided drug prescription. We conclude that pharmacogenomic information for patient stratification is of value to tailor optimized treatment regimens particularly in oncology. However, the routine use of pharmacogenomic biomarkers in clinical practice in other therapeutic areas is currently sparse and the prospects of its future implementation are being scrutinized by different international consortia.

Non-alcoholic fatty liver disease (NAFLD) has emerged as a public health concern as reflected in its widespread distribution in the general population. Yet, treatment options are scarce which is at least in part due to lack of reliable human in vitro disease models. Here, we report a human hepatic 3D spheroid system cultured under defined chemical conditions that has the potential to mimic steatotic conditions in a reversible manner, useful for identification of novel drug treatment conditions. Primary human hepatocytes (PHH) from different donors were cultured as spheroid microtissues in physiological in vivo -like culture conditions. Hepatic steatosis was induced over the course of three weeks in culture by supplementing the culture medium with pathophysiological concentrations of free fatty acids, carbohydrates and insulin. Effects of steatosis in the 3D system were evaluated on transcriptional, metabolomic and lipidomic levels. Free fatty acids on one hand as well as a combination of insulin and monosaccharides, promoted lipid accumulation in hepatocytes and increased expression of lipogenic genes, such as fatty acid synthase. This milieu also promoted development of insulin resistance within 2 weeks as manifested by an increase in gluconeogenic and insulin resistance markers, which are observed in type 2 diabetes mellitus and metabolic syndrome. Induced steatosis was reversible after withdrawal of lipogenic substrates and a further reduction in cellular fat content was observed following treatment with different antisteatotic compounds, such as metformin, glucagon, olaparib and antioxidants. Taken together, these results demonstrate that the 3D hepatic spheroids can serve as a valuable, HTS compatible model for the study of liver steatosis and facilitate translational discovery of novel drug targets.

Summary How signaling dynamics encode information is a central question in biology. During vertebrate development, dynamic Notch signaling oscillations control segmentation of the presomitic mesoderm (PSM). In mouse embryos, this molecular clock comprises signaling oscillations of several pathways, i.e., Notch, Wnt, and FGF signaling. Here, we directly address the role of the relative timing between Wnt and Notch signaling oscillations during PSM patterning. To this end, we developed a new experimental strategy using microfluidics-based entrainment that enables specific control of the rhythm of segmentation clock oscillations. Using this approach, we find that Wnt and Notch signaling are coupled at the level of their oscillation dynamics. Furthermore, we provide functional evidence that the oscillation phase shift between Wnt and Notch signaling is critical for PSM segmentation. Our work hence reveals that dynamic signaling, i.e., the relative timing between oscillatory signals, encodes essential information during multicellular development., Graphical Abstract, Highlights • Wnt and Notch signaling wave dynamics differ within segmenting mouse mesoderm • Entraining oscillations by microfluidics allows external control of the dynamics • Oscillatory Wnt and Notch signaling networks are coupled at the level of dynamics • Relative timing of Wnt and Notch signaling oscillations is critical for segmentation, The relative timing between oscillatory Wnt and Notch signaling is critical for the segmentation of mouse embryo mesoderm.

Drug-induced liver injury (DILI) is a major concern for the pharmaceutical industry and constitutes one of the most important reasons for the termination of promising drug development projects. Reliable prediction of DILI liability in preclinical stages is difficult, as current experimental model systems do not accurately reflect the molecular phenotype and functionality of the human liver. As a result, multiple drugs that passed preclinical safety evaluations failed due to liver toxicity in clinical trials or postmarketing stages in recent years. To improve the selection of molecules that are taken forward into the clinics, the development of more predictive in vitro systems that enable high-throughput screening of hepatotoxic liabilities and allow for investigative studies into DILI mechanisms has gained growing interest. Specifically, it became increasingly clear that the choice of cell types and culture method both constitute important parameters that affect the predictive power of test systems. In this review, we present current 3D culture paradigms for hepatotoxicity tests and critically evaluate their utility and performance for DILI prediction. In addition, we highlight possibilities of these emerging platforms for mechanistic evaluations of selected drug candidates and present current research directions towards the further improvement of preclinical liver safety tests. We conclude that organotypic and microphysiological liver systems have provided an important step towards more reliable DILI prediction. Furthermore, we expect that the increasing availability of comprehensive benchmarking studies will facilitate model dissemination that might eventually result in their regulatory acceptance.

The liver plays a central role in glucose homeostasis and hepatic insulin resistance constitutes a key feature of type 2 diabetes. However, platforms that accurately mimic human hepatic glucose disposition and allow for rapid and scalable quantification of glucose consumption dynamics are lacking. Here, we developed and optimized a colorimetric glucose assay based on the glucose oxidase-peroxidase system and demonstrate that the system can monitor glucose consumption in 3D primary human liver cell cultures over multiple days. The system was highly sensitive (limit of detection of 3.5 µM) and exceptionally accurate (R2 = 0.999) while requiring only nanoliter input volumes (250 nL), enabling longitudinal profiling of individual liver microtissues. By utilizing a novel polymer, off-stoichiometric thiol-ene (OSTE), and click-chemistry based on thiol-Michael additions, we furthermore show that the assay can be covalently bound to custom-build chips, facilitating the integration of the sensor into microfluidic devices. Using this system, we find that glucose uptake of our 3D human liver cultures closely resembles human hepatic glucose uptake in vivo as measured by euglycemic-hyperinsulinemic clamp. By comparing isogenic insulin-resistant and insulin-sensitive liver cultures we furthermore show that insulin and extracellular glucose levels account for 55% and 45% of hepatic glucose consumption, respectively. In conclusion, the presented data show that the integration of accurate and scalable nanoliter glucose sensors with physiologically relevant organotypic human liver models enables longitudinal profiling of hepatic glucose consumption dynamics that will facilitate studies into the biology and pathobiology of glycemic control, as well as antidiabetic drug screening.