Polygenic architecture informs potential vulnerability to drug-induced liver injury

Koido, Masaru; Kawakami, Eri; Fukumura, Junko; Noguchi, Yuzo; Ohori, Momoko; Nio, Yasunori; Nicoletti, Paola; Aithal, Guruprasad P.; Daly, Ann K.; Watkins, Paul B.; Anayama, Hisashi; Dragan, Yvonne P.; Shinozawa, Tadahiro; Takebe, Takanori

doi:10.1038/s41591-020-1023-0

Cited by 56 publications

(49 citation statements)

References 41 publications

(42 reference statements)

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“…That is in accordance with a condition of chronic stress and continuous attempt to restore homeostasis (García-Ruiz & Fernández-Checa, 2018). Our results partly overlap with findings in recent GWAS DILI studies, where cholestatic injury phenotype has been associated with UPR and mitochondrial stress, but most importantly with an increased sensitivity to ROS upon additional drug treatment (Koido et al, 2020). Interestingly, ER stress response did not show a connection with donor traits: ER stress related modules, collectively, were a stable and preserved set of biomarkers for the unfolded protein response.…”

Section: Discussionsupporting

confidence: 92%

“…In contrast, CSA did not show a good correlation with the MoA of APAP datasets, suggesting that oxidative stress is a secondary/late effect to high dose CSA exposure. Although several publications indicate that oxidative stress is involved during CSA induced cholestasis in liver (Kawamoto et al, 2017; Koido et al, 2020; Wolters et al, 2016), our analysis of CSA exposed hepatocytes using the TXG-MAPr tool showed that the ER stress should not be neglected in the mechanism of CSA induced liver injury as was also suggested by other literature (Koido et al, 2020; Van den Hof et al, 2015b). To validate the applicability of the PHH TXG-MAPr for other transcriptomic platforms, we showed that Agilent microarray data of APAP exposure in PHH showed strong correlation with Affymetrix based data in TG-GATEs.…”

Section: Discussionsupporting

confidence: 59%

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The human hepatocyte TXG-MAPr: WGCNA transcriptomic modules to support mechanism-based risk assessment

Callegaro

Kunnen

Trairatphisan

et al. 2021

Preprint

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Mechanism-based risk assessment is urged to advance and fully permeate into current safety assessment practices, possibly at early phases of drug safety testing. Toxicogenomics is a promising source of comprehensive and mechanisms-revealing data, but analysis tools to interpret mechanisms of toxicity and specific for the testing systems (e.g. hepatocytes) are lacking. In this study we present the TXG-MAPr webtool (available at https://txg-mapr.eu/WGCNA_PHH/TGGATEs_PHH/), an R-Shiny-based implementation of weighted gene co-expression networks (WGCNA) obtained from the Primary Human Hepatocytes (PHH) TG-GATEs dataset. Gene co-expression networks (modules) were annotated with functional information (pathway enrichment, transcription factor) to reveal their mechanistic interpretation. Several well-known stress response pathways were captured in the modules, are perturbed by specific stressors and show preserved in rat systems (rat primary hepatocytes and rat in vivo liver), highlighting stress responses that translate across species/testing systems. The TXG-MAPr tool was successfully applied to investigate the mechanism of toxicity of TG-GATEs compounds and using external datasets obtained from different hepatocyte cells and microarray platforms. Additionally, we suggest that module responses can be calculated from targeted RNA-seq data therefore imputing biological responses from a limited gene. By analyzing 50 different PHH donors' responses to a common stressor, tunicamycin, we were able to suggest modules associated with donor's traits, e.g. pre-existing disease state, therefore connected to donors' variability. In conclusion, we demonstrated that gene co-expression analysis coupled to an interactive visualization environment, the TXG-MAPr, is a promising approach to achieve mechanistic relevant, cross-species and cross-platform evaluation of toxicogenomic data.

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Section: Discussionsupporting

confidence: 92%

Section: Discussionsupporting

confidence: 59%

The human hepatocyte TXG-MAPr: WGCNA transcriptomic modules to support mechanism-based risk assessment

Callegaro

Kunnen

Trairatphisan

et al. 2021

Preprint

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“…Identifying clinically relevant genetic signals (biomarkers) for drug efficacy/ toxicity in organoid models are critical to rationalize and enhance the drug discovery and development process. In support, organoid-based modeling of drug-induced liver injury revealed critical correlation between organoid and patient's phenotype, thus informing novel polygenic signatures behind the disease susceptibility [30]. It is not only critical to demonstrate the correlative functional characteristics in the patient-derived organoids, but also establish measurable clinically relevant phenotypes in long-term culture condition before being translated as diagnostic and/ or prognostic tools.…”

Section: Clinical Relevance (Diagnostic Potential)mentioning

confidence: 97%

“…The use of disease-specific digestive organoids along with healthy organoids will facilitate our understanding of molecular mechanisms behind the disease, the identification of potential biomarkers, and the development of patientspecific platforms for drug testing or toxicology studies [30]. In the following subsections, we will discuss four major areas of diseases related to disorders in the digestive tracts: genetic diseases, infectious diseases, inflammatory diseases, and malignant diseases.…”

Section: Digestive Organoid-based Disease Modeling For Drug Discoverymentioning

confidence: 99%

The promise of human organoids in the digestive system

et al. 2020

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The advent of organoid technology has enabled scientists and clinicians to utilize cells from primary tissues or pluripotent stem cells (PSCs) to grow self-organizing tissue systems, thus attaining cellular diversity, spatial organization, and functionality as found within digestive tracts. The development of human gastrointestinal (GI) and hepato-biliary-pancreatic organoids as an in-a-dish model present novel opportunities to study humanistic mechanisms of organogenesis, regeneration and pathogenesis. Herein, we review the recent portfolios of primary tissue-derived and PSC-derived organoids in the digestive systems. We also discuss the promise and challenges in disease modeling and drug development applications for digestive disorders. Facts • Digestive organoids can be generated from two types of stem cells: adult stem cells (AdSCs) or pluripotent stem cells (PSCs) which include embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs). • While AdSC-derived digestive organoids contain mainly epithelial component, PSC-derived digestive organoids harbor epithelial and non-epithelial components. • Patient-specific and gene-edited organoids have been utilized for in vitro digestive disease modeling and mechanistic studies. • Organoids have been utilized for disease phenotyping, drug screening, drug development, and disease modeling.

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“…Along these lines, an interesting recent study developed a polygenic risk score for the susceptibility to DILI based on previous large-scale genome-wide association studies (Koido et al 2020). Using primary hepatocytes and stem cell-derived organoids from multiple donors treated with over ten different drugs, this approach could flag individuals at risk of DILI, which can inform preclinical studies as well as patient selection in clinical trials.…”

Section: Conclusion and Future Perspectivesmentioning

confidence: 99%

Toxicogenomics of drug induced liver injury – from mechanistic understanding to early prediction.

Lauschke

2021

Drug Metabolism Reviews

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Despite rigorous preclinical testing, clinical attrition rates in drug development remain high with drug-induced liver injury (DILI) remaining one of the most frequent causes of project failures. To understand DILI mechanisms, major efforts are put into the development of physiologically relevant cell models and culture paradigms with the aim to enhance preclinical to clinical result translation. While the majority of toxicogenomic studies have been based on cell lines, there are emerging trends toward the predominant use of stem cell-derived organoids and primary human hepatocytes in complex 3D cell models. Such studies have been successful in disentangling diverse toxicity mechanisms, including genotoxicity, mitochondrial injury, steatogenesis and cholestasis and can aid in distinguishing hepatotoxic from nontoxic structural analogs. Furthermore, by leveraging interindividual differences of cells from different donors, these approaches can emulate the complexity of polygenic risk scores, which facilitates personalized drug-specific DILI risk analyses. In summary, toxicogenomic studies into drug-induced hepatotoxicity have majorly contributed to our mechanistic understanding of DILI and the incorporation of organotypic human 3D liver models into the preclinical testing arsenal promises to enhance biological insights during drug discovery, increase confidence in preclinical safety and minimize the translational gap.

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Polygenic architecture informs potential vulnerability to drug-induced liver injury

Cited by 56 publications

References 41 publications

The human hepatocyte TXG-MAPr: WGCNA transcriptomic modules to support mechanism-based risk assessment

The human hepatocyte TXG-MAPr: WGCNA transcriptomic modules to support mechanism-based risk assessment

The promise of human organoids in the digestive system

Toxicogenomics of drug induced liver injury – from mechanistic understanding to early prediction.

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