A quantitative weight-of-evidence method for confidence assessment of adverse outcome pathway networks: A case study on chemical-induced liver steatosis.

The field of chemical toxicity testing is undergoing a transition to overcome the limitations of in vivo experiments. This evolution involves implementing innovative non-animal approaches to improve predictability and provide a more precise understanding of toxicity mechanisms. Adverse outcome pathway (AOP) networks are pivotal in organizing existing mechanistic knowledge related to toxicological processes. However, these AOP networks are dynamic and require regular updates to incorporate the latest data. Regulatory challenges also persist due to concerns about the reliability of the information they offer. This study introduces a generic Weight-of-Evidence (WoE) scoring method, aligned with the tailored Bradford-Hill criteria, to quantitatively assess the confidence levels in key event relationships (KERs) within AOP networks. We use the previously published AOP network on chemical-induced liver steatosis, a prevalent form of human liver injury, as a case study. Initially, the existing AOP network is optimized with the latest scientific information extracted from PubMed using the free SysRev platform for artificial intelligence (AI)-based abstract inclusion and standardized data collection. The resulting optimized AOP network, constructed using Cytoscape, visually represents confidence levels through node size (key event, KE) and edge thickness (KERs). Additionally, a Shiny application is developed to facilitate user interaction with the dataset, promoting future updates. Our analysis of 173 research papers yielded 100 unique KEs and 221 KERs among which 72 KEs and 170 KERs, respectively, have not been previously documented in the prior AOP network or AOP-wiki. Notably, modifications in de novo lipogenesis, fatty acid uptake and mitochondrial beta-oxidation, leading to lipid accumulation and liver steatosis, garnered the highest KER confidence scores. In conclusion, our study delivers a generic methodology for developing and assessing AOP networks. The quantitative WoE scoring method facilitates in determining the level of support for KERs within the optimized AOP network, offering valuable insights into its utility in both scientific research and regulatory contexts. KERs supported by robust evidence represent promising candidates for inclusion in an in vitro test battery for reliably predicting chemical-induced liver steatosis within regulatory frameworks.

Liver stiffness as a cornerstone in heart disease risk assessment.

Metabolic dysfunction-associated steatotic liver disease (MASLD) typically presents with hepatic fibrosis in advanced disease, resulting in increased liver stiffness. A subset of patients further develops liver cirrhosis and hepatocellular carcinoma. Cardiovascular disease is a common comorbidity in patients with MASLD and its prevalence is increasing in parallel. Recent evidence suggests that especially liver stiffness, whether or not existing against a background of MASLD, is associated with heart diseases. We conducted a narrative review on the role of liver stiffness in the prediction of highly prevalent heart diseases including heart failure, cardiac arrhythmias (in particular atrial fibrillation), coronary heart disease, and aortic valve sclerosis. Research papers were retrieved from major scientific databases (PubMed, Web of Science) until September 2023 using 'liver stiffness' and 'liver fibrosis' as keywords along with the latter cardiac conditions. Increased liver stiffness, determined by vibration-controlled transient elastography or hepatic fibrosis as predicted by biomarker panels, are associated with a variety of cardiovascular diseases, including heart failure, atrial fibrillation, and coronary heart disease. Elevated liver stiffness in patients with metabolic liver disease should lead to considerations of cardiac workup including N-terminal pro-B-type natriuretic peptide/B-type natriuretic peptide determination, electrocardiography, and coronary computed tomography angiography. In addition, patients with MASLD would benefit from heart disease case-finding strategies in which liver stiffness measurements can play a key role. In conclusion, increased liver stiffness should be a trigger to consider a cardiac workup in metabolically compromised patients.