Review article: time to revisit Child‐Pugh score as the basis for predicting drug clearance in hepatic impairment

From Wiley via Jisc Publications RouterHistory: received 2021-03-04, rev-recd 2021-04-14, accepted 2021-06-04, pub-electronic 2021-07-04Article version: VoRPublication status: PublishedFunder: Egyptian Missions SectorSummary: Background: Prescription information for many drugs entering the market lacks dosage guidance for hepatic impairment. Dedicated studies for assessing the fate of drugs in hepatic impairment commonly stratify patients using Child‐Pugh score. Child‐Pugh is a prognostic clinical score with limitations in reflecting the liver's metabolic capacity. Aims: To demonstrate the need for better drug dosing approaches in hepatic impairment, summarise the current status, identify knowledge gaps related to drug kinetic parameters in hepatic impairment, propose solutions for predicting the liver disease impact on drug exposure and discuss barriers to dosing guidance in those patients. Methods: Relevant reports on dosage adjustment in hepatic impairment were analysed concerning the prediction of the impairment impact on drug kinetics using physiologically‐based pharmacokinetic (PBPK) modelling. Results: PBPK models are suggested as a potential framework to understand drug clearance changes in hepatic impairment. Quantifying changes in abundance and activity of drug‐metabolising enzymes and transporters, understanding the impact of shunting, and accounting for interindividual variations in drug absorption could help in extending the success of these models in hepatically‐impaired populations. These variables might not correlate with Child‐Pugh score as a whole. Therefore, new metabolic activity markers, imaging techniques and other scoring systems are proposed to either support or substitute Child‐Pugh score. Conclusions: Many physiological changes in hepatic impairment determining the fate of drugs do not necessarily correlate with Child‐Pugh score. Quantifying these changes in individual patients is essential in future hepatic impairment studies. Further studies assessing Child‐Pugh alternatives are recommended to allow better prediction of drug exposure

Using a machine learning model to risk stratify for the presence of significant liver disease in a primary care population

Background: Current strategies for detecting significant chronic liver disease (CLD) in the community are based on the extrapolation of diagnostic tests used in secondary care settings. Whilst this approach provides clinical utility, it has limitations related to diagnostic accuracy being predicated on disease prevalence and spectrum bias, which will differ in the community. Machine learning (ML) techniques provide a novel way of identifying significant variables without preconceived bias. As a proof-of-concept study, we wanted to examine the performance of nine different ML models based on both risk factors and abnormal liver enzyme tests in a large community cohort.Methods: Routine demographic and laboratory data was collected on 1,453 patients with risk factors for CLD, including high alcohol consumption, diabetes and obesity, in a community setting in Nottingham (UK) as part of the Scarred Liver project. A total of 87 variables were extracted. Transient elastography (TE) was used to define clinically significant liver fibrosis. The data was split into a training and hold out set. The median age of the cohort was 59, mean body mass index (BMI) 29.7 kg/m2, median TE 5.5 kPa, 49.2% had type 2 diabetes and 20.3% had a TE >8 kPa.Results: The nine different ML models, which included Random Forrest classifier, Support Vector classification and Gradient Boosting classifier, had a range of area under the curve (AUC) statistics of 0.5 to 0.75. Ensemble Stacker model showed the best performance, and this was replicated in the testing dataset (AUC 0.72). Recursive feature elimination found eight variables had a significant impact on model output. The model had superior sensitivity (74%) compared to specificity (60%).Conclusions: ML shows encouraging performance and highlights variables that may have bespoke value for diagnosing community liver disease. Optimising how ML algorithms are integrated into clinical pathways of care and exploring new biomarkers will further enhance diagnostic utility

SOX9 predicts progression towards cirrhosis in patients while its loss protects against liver fibrosis

Fibrosis and organ failure is a common endpoint for many chronic liver diseases. Much is known about the upstream inflammatory mechanisms provoking fibrosis and downstream potential for tissue remodeling. However, less is known about the transcriptional regulation in vivo governing fibrotic matrix deposition by liver myofibroblasts. This gap in understanding has hampered molecular predictions of disease severity and clinical progression and restricted targets for antifibrotic drug development. In this study we show the prevalence of SOX9 in biopsies from patients with chronic liver disease correlated with fibrosis severity and accurately predicted disease progression towards cirrhosis. Inactivation of Sox9 in mice protected against both parenchymal and biliary fibrosis, improved liver function and ameliorated chronic inflammation. SOX9 was downstream of mechanosignaling factor, YAP1. These data demonstrate a role for SOX9 in liver fibrosis and open the way for the transcription factor and its dependent pathways as new diagnostic, prognostic and therapeutic targets in patients with liver fibrosis

Circadian Disruption Primes Myofibroblasts for Accelerated Activation as a Mechanism Underpinning Fibrotic Progression in Non-Alcoholic Fatty Liver Disease

Circadian rhythm governs many aspects of liver physiology and its disruption exacerbates chronic disease. CLOCKΔ19 mice disrupted circadian rhythm and spontaneously developed obesity and metabolic syndrome, a phenotype that parallels the progression of non-alcoholic fatty liver disease (NAFLD). NAFLD represents an increasing health burden with an estimated incidence of around 25% and is associated with an increased risk of progression towards inflammation, fibrosis and carcinomas. Excessive extracellular matrix deposition (fibrosis) is the key driver of chronic disease progression. However, little attention was paid to the impact of disrupted circadian rhythm in hepatic stellate cells (HSCs) which are the primary mediator of fibrotic ECM deposition. Here, we showed in vitro and in vivo that liver fibrosis is significantly increased when circadian rhythm is disrupted by CLOCK mutation. Quiescent HSCs from CLOCKΔ19 mice showed higher expression of RhoGDI pathway components and accelerated activation. Genes altered in this primed CLOCKΔ19 qHSC state may provide biomarkers for early liver disease detection, and include AOC3, which correlated with disease severity in patient serum samples. Integration of CLOCKΔ19 microarray data with ATAC-seq data from WT qHSCs suggested a potential CLOCK regulome promoting a quiescent state and downregulating genes involved in cell projection assembly. CLOCKΔ19 mice showed higher baseline COL1 deposition and significantly worse fibrotic injury after CCl4 treatment. Our data demonstrate that disruption to circadian rhythm primes HSCs towards an accelerated fibrotic response which worsens liver disease

PAK1-dependent mechanotransduction enables myofibroblast nuclear adaptation and chromatin organization during fibrosis.

Myofibroblasts are responsible for scarring during fibrosis. The scar propagates mechanical signals inducing a radical transformation in myofibroblast cell state and increasing profibrotic phenotype. Here, we show mechanical stress from progressive scarring induces nuclear softening and de-repression of heterochromatin. The parallel loss of H3K9Me3 enables a permissive state for distinct chromatin accessibility and profibrotic gene regulation. Integrating chromatin accessibility profiles with RNA expression provides insight into the transcription network underlying the switch in profibrotic myofibroblast states, emphasizing mechanoadaptive regulation of PAK1 as key drivers. Through genetic manipulation in liver and lung fibrosis, loss of PAK1-dependent signaling impairs the mechanoadaptive response in vitro and dramatically improves fibrosis in vivo. Moreover, we provide human validation for mechanisms underpinning PAK1-mediated mechanotransduction in liver and lung fibrosis. Collectively, these observations provide insight into the nuclear mechanics driving the profibrotic chromatin landscape in fibrosis, highlighting actomyosin-dependent mechanisms as potential therapeutic targets in fibrosis

Epimorphin alters the inhibitory effects of SOX9 on Mmp13 in activated hepatic stellate cells.

Liver fibrosis is a major cause of morbidity and mortality. It is characterised by excessive extracellular matrix (ECM) deposition from activated hepatic stellate cells (HSCs). Although potentially reversible, treatment remains limited. Understanding how ECM influences the pathogenesis of the disease may provide insight into novel therapeutic targets for the disease. The extracellular protein Epimorphin (EPIM) has been implicated in tissue repair mechanisms in several tissues, partially, through its ability to manipulate proteases. In this study, we have identified that EPIM modulates the ECM environment produced by activated hepatic stellate cells (HSCs), in part, through down-regulation of pro-fibrotic Sex-determining region Y-box 9 (SOX9).Influence of EPIM on ECM was investigated in cultured primary rat HSCs. Activated HSCs were treated with recombinant EPIM or SOX9 siRNA. Core fibrotic factors were evaluated by immunoblotting, qPCR and chromatin immunoprecipitation (ChIP).During HSC activation EPIM became significantly decreased in contrast to pro-fibrotic markers SOX9, Collagen type 1 (COL1), and α-Smooth muscle actin (α-SMA). Treatment of activated HSCs with recombinant EPIM caused a reduction in α-SMA, SOX9, COL1 and Osteopontin (OPN), while increasing expression of the collagenase matrix metalloproteinase 13 (MMP13). Sox9 abrogation in activated HSCs increased EPIM and MMP13 expression.These data provide evidence for EPIM and SOX9 functioning by mutual negative feedback to regulate attributes of the quiescent or activated state of HSCs. Further understanding of EPIM's role may lead to opportunities to modulate SOX9 as a therapeutic avenue for liver fibrosis

Non-alcoholic fatty liver disease in irritable bowel syndrome:More than a coincidence?

Irritable bowel syndrome (IBS) and non-alcoholic fatty liver disease (NAFLD) are amongst the most common gastrointestinal and liver conditions encountered in primary and secondary care. Recently, there has been interest in the apparent co-incidence of NAFLD in patients with IBS mainly driven by improved understanding of their shared risk factors and pathophysiology. In this paper we summarize the shared risk factors which include; overlapping nutritional and dietary factors as well as shared putative mechanisms of pathophysiology. These include changes in the gut microbiome, gut permeability, immunity, small bowel bacterial overgrowth and bile acid metabolism. This paper describes how these shared risk factors and etiological factors may have practical clinical implications for these highly prevalent conditions. It also highlights some of the limitations of current epidemiological data relating to estimates of the overlapping prevalence of the two conditions which have resulted in inconsistent results and, therefore the need for further research. Early recognition and management of the overlap could potentially have impacts on treatment outcomes, compliance and morbidity of both conditions. Patients with known IBS who have abnormal liver function tests or significant risk factors for NAFLD should be investigated appropriately for this possibility. Similarly, IBS should be considered in patients with NAFLD and symptoms of abdominal pain associated with defecation, an altered bowel habit and bloating

Time to revisit Child-Pugh score as the basis for predicting drug clearance in hepatic impairment

BackgroundPrescription information for many drugs entering the market lacks dosage guidance for hepatic impairment. Dedicated studies for assessing the fate of drugs in hepatic impairment commonly stratify patients using Child-Pugh score. Child-Pugh is a prognostic clinical score with limitations in reflecting the liver's metabolic capacity. AimsTo demonstrate the need for better drug dosing approaches in hepatic impairment, summarise the current status, identify knowledge gaps related to drug kinetic parameters in hepatic impairment, propose solutions for predicting the liver disease impact on drug exposure and discuss barriers to dosing guidance in those patients. MethodsRelevant reports on dosage adjustment in hepatic impairment were analysed concerning the prediction of the impairment impact on drug kinetics using physiologically-based pharmacokinetic (PBPK) modelling. ResultsPBPK models are suggested as a potential framework to understand drug clearance changes in hepatic impairment. Quantifying changes in abundance and activity of drug-metabolising enzymes and transporters, understanding the impact of shunting, and accounting for interindividual variations in drug absorption could help in extending the success of these models in hepatically-impaired populations. These variables might not correlate with Child-Pugh score as a whole. Therefore, new metabolic activity markers, imaging techniques and other scoring systems are proposed to either support or substitute Child-Pugh score. ConclusionsMany physiological changes in hepatic impairment determining the fate of drugs do not necessarily correlate with Child-Pugh score. Quantifying these changes in individual patients is essential in future hepatic impairment studies. Further studies assessing Child-Pugh alternatives are recommended to allow better prediction of drug exposure.QC 20210803</p