Assessment of portal hypertension severity using machine learning models in patients with compensated cirrhosis

Background & Aims: In individuals with compensated advanced chronic liver disease (cACLD), the severity of portal hypertension (PH) determines the risk of decompensation. Invasive measurement of the hepatic venous pressure gradient (HVPG) is the diagnostic gold standard for PH. We evaluated the utility of machine learning models (MLMs) based on standard laboratory parameters to predict the severity of PH in individuals with cACLD. Methods: A detailed laboratory workup of individuals with cACLD recruited from the Vienna cohort (NCT03267615) was utilised to predict clinically significant portal hypertension (CSPH, i.e., HVPG ≥10 mmHg) and severe PH (i.e., HVPG ≥16 mmHg). The MLMs were then evaluated in individual external datasets and optimised in the merged cohort. Results: Among 1,232 participants with cACLD, the prevalence of CSPH/severe PH was similar in the Vienna (n = 163, 67.4%/35.0%) and validation (n = 1,069, 70.3%/34.7%) cohorts. The MLMs were based on 3 (3P: platelet count, bilirubin, international normalised ratio) or 5 (5P: +cholinesterase, +gamma-glutamyl transferase, +activated partial thromboplastin time replacing international normalised ratio) laboratory parameters. The MLMs performed robustly in the Vienna cohort. 5P-MLM had the best AUCs for CSPH (0.813) and severe PH (0.887) and compared favourably to liver stiffness measurement (AUC: 0.808). Their performance in external validation datasets was heterogeneous (AUCs: 0.589-0.887). Training on the merged cohort optimised model performance for CSPH (AUCs for 3P and 5P: 0.775 and 0.789, respectively) and severe PH (0.737 and 0.828, respectively). Conclusions: Internally trained MLMs reliably predicted PH severity in the Vienna cACLD cohort but exhibited heterogeneous results on external validation. The proposed 3P/5P online tool can reliably identify individuals with CSPH or severe PH, who are thus at risk of hepatic decompensation. Impact and implications: We used machine learning models based on widely available laboratory parameters to develop a non-invasive model to predict the severity of portal hypertension in individuals with compensated cirrhosis, who currently require invasive measurement of hepatic venous pressure gradient. We validated our findings in a large multicentre cohort of individuals with advanced chronic liver disease (cACLD) of any cause. Finally, we provide a readily available online calculator, based on 3 (platelet count, bilirubin, international normalised ratio) or 5 (platelet count, bilirubin, activated partial thromboplastin time, gamma-glutamyltransferase, choline-esterase) widely available laboratory parameters, that clinicians can use to predict the likelihood of their patients with cACLD having clinically significant or severe portal hypertension

InForm software: A semi-Automated research tool to identify presumptive human hepatic progenitor cells, and other histological features of pathological significance

Hepatic progenitor cells (HPCs) play an important regenerative role in acute and chronic liver pathologies. Liver disease research often necessitates the grading of disease severity, and pathologists' reports are the current gold-standard for assessment. However, it is often impractical to recruit pathologists in large cohort studies. In this study we utilise PerkinElmer's "InForm" software package to semi-Automate the scoring of patient liver biopsies, and compare outputs to a pathologist's assessment. We examined a cohort of eleven acute hepatitis samples and three non-Alcoholic fatty liver disease (NAFLD) samples, stained with HPC markers (GCTM-5 and Pan Cytokeratin), an inflammatory marker (CD45), Sirius Red to detect collagen and haematoxylin/eosin for general histology. InForm was configured to identify presumptive HPCs, CD45 +ve inflammatory cells, areas of necrosis, fat and collagen deposition (p < 0.0001). Hepatitis samples were then evaluated both by a pathologist using the Ishak-Knodell scoring system, and by InForm through customised algorithms. Necroinflammation as evaluated by a pathologist, correlated with InForm outputs (r 2 = 0.8192, p < 0.05). This study demonstrates that the InForm software package provides a useful tool for liver disease research, allowing rapid, and objective quantification of the presumptive HPCs and identifies histological features that assist with assessing liver disease severity, and potentially can facilitate diagnosis

Total area of spontaneous portosystemic shunts independently predicts hepatic encephalopathy and mortality in liver cirrhosis

BACKGROUND: Spontaneous portosystemic shunts (SPSS) frequently develop in liver cirrhosis. Recent data suggested that presence of a single large SPSS is associated with complications, especially overt hepatic encephalopathy (oHE). However, presence of >1 SPSS is common. This study evaluates the impact of total cross-sectional SPSS area (TSA) on outcome of patients with liver cirrhosis. METHODS: In this retrospective international multicentric study, computed tomography (CT) scans of 908 cirrhotic patients with SPSS were evaluated for TSA. Clinical and laboratory data were recorded. Each detected SPSS radius was measured and TSA calculated. 1-year survival was primary and acute decompensation (oHE, variceal bleeding, ascites) secondary endpoint. RESULTS: 301 patients (169 male) were included in the training cohort. 30% of all patients presented >1 SPSS. TSA cut-off of 83 mm2 was determined to classify patients with small or large TSA (S-/L-TSA). L-TSA patients presented higher MELD (11 vs. 14) and more commonly history of oHE (12% vs. 21%, p83mm2 increases the risk for oHE and mortality in liver cirrhosis. Our results may have impact on clinical use of TSA/SPSS for risk stratification and clinical decision-making considering management of SPSS

Replacement of Retinyl Esters by Polyunsaturated Triacylglycerol Species in Lipid Droplets of Hepatic Stellate Cells during Activation

Activation of hepatic stellate cells has been recognized as one of the first steps in liver injury and repair. During activation, hepatic stellate cells transform into myofibroblasts with concomitant loss of their lipid droplets (LDs) and production of excessive extracellular matrix. Here we aimed to obtain more insight in the dynamics and mechanism of LD loss. We have investigated the LD degradation processes in rat hepatic stellate cells in vitro with a combined approach of confocal Raman microspectroscopy and mass spectrometric analysis of lipids (lipidomics). Upon activation of the hepatic stellate cells, LDs reduce in size, but increase in number during the first 7 days, but the total volume of neutral lipids did not decrease. The LDs also migrate to cellular extensions in the first 7 days, before they disappear. In individual hepatic stellate cells. all LDs have a similar Raman spectrum, suggesting a similar lipid profile. However, Raman studies also showed that the retinyl esters are degraded more rapidly than the triacylglycerols upon activation. Lipidomic analyses confirmed that after 7 days in culture hepatic stellate cells have lost most of their retinyl esters, but not their triacylglycerols and cholesterol esters. Furthermore, we specifically observed a large increase in triacylglycerol-species containing polyunsaturated fatty acids, partly caused by an enhanced incorporation of exogenous arachidonic acid. These results reveal that lipid droplet degradation in activated hepatic stellate cells is a highly dynamic and regulated process. The rapid replacement of retinyl esters by polyunsaturated fatty acids in LDs suggests a role for both lipids or their derivatives like eicosanoids during hepatic stellate cell activation

Unfolded protein response is an early, non-critical event during hepatic stellate cell activation.

Hepatic stellate cells activate upon liver injury and help at restoring damaged tissue by producing extracellular matrix proteins. A drastic increase in matrix proteins results in liver fibrosis and we hypothesize that this sudden increase leads to accumulation of proteins in the endoplasmic reticulum and its compensatory mechanism, the unfolded protein response. We indeed observe a very early, but transient induction of unfolded protein response genes during activation of primary mouse hepatic stellate cells in vitro and in vivo, prior to induction of classical stellate cell activation genes. This unfolded protein response does not seem sufficient to drive stellate cell activation on its own, as chemical induction of endoplasmic reticulum stress with tunicamycin in 3D cultured, quiescent stellate cells is not able to induce stellate cell activation. Inhibition of Jnk is important for the transduction of the unfolded protein response. Stellate cells isolated from Jnk knockout mice do not activate as much as their wild-type counterparts and do not have an induced expression of unfolded protein response genes. A timely termination of the unfolded protein response is essential to prevent endoplasmic reticulum stress-related apoptosis. A pathway known to be involved in this termination is the non-sense-mediated decay pathway. Non-sense-mediated decay inhibitors influence the unfolded protein response at early time points during stellate cell activation. Our data suggest that UPR in HSCs is differentially regulated between acute and chronic stages of the activation process. In conclusion, our data demonstrates that the unfolded protein response is a JNK1-dependent early event during hepatic stellate cell activation, which is counteracted by non-sense-mediated decay and is not sufficient to drive the stellate cell activation process. Therapeutic strategies based on UPR or NMD modulation might interfere with fibrosis, but will remain challenging because of the feedback mechanisms between the stress pathways

Acknowledgement to reviewers of JSAN in 2016

The editors of JSAN would like to express their sincere gratitude to the following reviewers for assessing manuscripts in 2016.[...