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An in silico target discovery pipeline was developed by including a directional and weighted molecular disease network for metabolic dysfunction-associated steatohepatitis (MASH)-induced liver fibrosis. This approach integrates text mining, network biology, and artificial intelligence/machine learning with clinical transcriptome data for optimal translational power. At the mechanistic level, the critical components influencing disease progression were identified from the disease network using in silico knockouts. The top-ranked genes were then subjected to a target efficacy analysis, following which the top-5 candidate targets were validated in vitro. Three targets, including EP300, were confirmed for their roles in liver fibrosis. EP300 gene-silencing was found to significantly reduce collagen by 37%; compound intervention studies performed in human primary hepatic stellate cells and the hepatic stellate cell line LX-2 showed significant inhibition of collagen to the extent of 81% compared to the TGFβ-stimulated control (1 μM inobrodib in LX-2 cells). The validated in silico pipeline presents a unique approach for the identification of human-disease-mechanism-relevant drug targets. The directionality of the network ensures adherence to physiologically relevant signaling cascades, while the inclusion of clinical data boosts its translational power and ensures identification of the most relevant disease pathways. In silico knockouts thus provide crucial molecular insights for successful target identification. [ABSTRACT FROM AUTHOR]

The prevalence of sarcopenia is increasing while it is often challenging, expensive and timeconsuming to test the effectiveness of interventions against sarcopenia. Translational mouse models that adequately mimic underlying physiological pathways could accelerate research but are scarce. Here, we investigated the translational value of three potential mouse models for sarcopenia, namely partial immobilized (to mimic sedentary lifestyle), caloric restricted (CR; to mimic malnutrition) and a combination (immobilized & CR) model. C57BL/6J mice were calorically restricted (-40%) and/or one hindleg was immobilized for two weeks to induce loss of muscle mass and function. Muscle parameters were compared to those of young control (4 months) and old reference mice (21 months). Transcriptome analysis of quadriceps muscle was performed to identify underlying pathways and were compared with those being expressed in aged human vastus lateralis muscle-biopsies using a meta-analysis of five different human studies. Caloric restriction induced overall loss of lean body mass (-15%, p<0.001), whereas immobilization decreased muscle strength (-28%, p<0.001) and muscle mass of hindleg muscles specifically (on average -25%, p<0.001). The proportion of slow myofibers increased with aging in mice (+5%, p<0.05), and this was not recapitulated by the CR and/or immobilization models. The diameter of fast myofibers decreased with aging (-7%, p<0.05), and this was mimicked by all models. Transcriptome analysis revealed that the combination of CR and immobilization recapitulated more pathways characteristic for human muscle-aging (73%) than naturally aged (21 months old) mice (45%). In conclusion, the combination model exhibits loss of both muscle mass (due to CR) and function (due to immobilization) and has a remarkable similarity with pathways underlying human sarcopenia. These findings underline that external factors such as sedentary behavior and malnutrition are key elements of a translational mouse model and favor the combination model as a rapid model for testing the treatments against sarcopenia. [ABSTRACT FROM AUTHOR]

Fibroblast growth factor 21 (FGF21) is a promising target for treatment of obesity-associated diseases including metabolic dysfunction-associated steatohepatitis (MASH) and atherosclerosis. We evaluated the effects of the bispecific anti-FGF21-β klotho (KLB) agonist antibody bFKB1 in a preclinical model of MASH and atherosclerosis. Low-density lipoprotein receptor knockout (Ldlr-/-).Leiden mice received a high-fat diet for 20 weeks, followed by treatment with an isotype control antibody or bFKB1 for 12 weeks. Effects on plasma risk markers and (histo)pathology of liver, adipose tissue, and heart were evaluated alongside hepatic transcriptomics analysis. bFKB1 lowered body weight (-21%) and adipose tissue mass (-22%) without reducing food intake. The treatment also improved plasma insulin (-80%), cholesterol (-48%), triglycerides (-76%), alanine transaminase (ALT: -79%), and liver weight (-43%). Hepatic steatosis and inflammation were strongly reduced (macrovesicular steatosis -34%; microvesicular steatosis -100%; inflammation -74%) and while the total amount of fibrosis was not affected, bFKB1 did decrease new collagen formation (-49%). Correspondingly, hepatic transcriptomics and pathway analysis revealed the mechanistic background underlying these histological improvements, demonstrating broad inactivation of inflammatory and profibrotic transcriptional programs by bFKB1. In epididymal white adipose tissue, bFKB1 reduced adipocyte size (-16%) and inflammation (-52%) and induced browning, signified by increased uncoupling protein-1 (UCP1) protein expression (8.5-fold increase). In the vasculature, bFKB1 had anti-atherogenic effects, lowering total atherosclerotic lesion area (-38%). bFKB1 has strong beneficial metabolic effects associated with a reduction in hepatic steatosis, inflammation, and atherosclerosis. Analysis of new collagen formation and profibrotic transcriptional programs indicate that bFKB1 treatment may have antifibrotic potential in a longer treatment duration as well., (© 2024 The Author(s). The FASEB Journal published by Wiley Periodicals LLC on behalf of Federation of American Societies for Experimental Biology.)