Background Muscle atrophy is caused by an imbalance between muscle growth and wasting. Delta-like 1 homolog (DLK1), a protein that modulates adipogenesis and muscle development, is a crucial regulator of myogenic programming. Thus, we investigated the effect of exogenous DLK1 on muscular atrophy.
Methods We used muscular atrophy mouse model induced by dexamethasone (Dex). The mice were randomly divided into three groups: (1) control group, (2) Dex-induced muscle atrophy group, and (3) Dex-induced muscle atrophy group treated with DLK1. The effects of DLK1 were also investigated in an in vitro model using C2C12 myotubes.
Results Dex-induced muscular atrophy in mice was associated with increased expression of muscle atrophy markers and decreased expression of muscle differentiation markers, while DLK1 treatment attenuated these degenerative changes together with reduced expression of the muscle growth inhibitor, myostatin. In addition, electron microscopy revealed that DLK1 treatment improved mitochondrial dynamics in the Dex-induced atrophy model. In the in vitro model of muscle atrophy, normalized expression of muscle differentiation markers by DLK1 treatment was mitigated by myostatin knockdown, implying that DLK1 attenuates muscle atrophy through the myostatin pathway.
Conclusion DLK1 treatment inhibited muscular atrophy by suppressing myostatin-driven signaling and improving mitochondrial biogenesis. Thus, DLK1 might be a promising candidate to treat sarcopenia, characterized by muscle atrophy and degeneration.
Background Nonalcoholic fatty liver disease (NAFLD) is the most prevalent cause of chronic liver disease worldwide. Type 2 diabetes mellitus (T2DM) is a risk factor that accelerates NAFLD progression, leading to fibrosis and cirrhosis. Thus, here we aimed to develop a simple model to predict the presence of NAFLD based on clinical parameters of patients with T2DM.
Methods A total of 698 patients with T2DM who visited five medical centers were included. NAFLD was evaluated using transient elastography. Univariate logistic regression analyses were performed to identify potential contributors to NAFLD, followed by multivariable logistic regression analyses to create the final prediction model for NAFLD.
Results Two NAFLD prediction models were developed, with and without serum biomarker use. The non-laboratory model comprised six variables: age, sex, waist circumference, body mass index (BMI), dyslipidemia, and smoking status. For a cutoff value of ≥60, the prediction accuracy was 0.780 (95% confidence interval [CI], 0.743 to 0.817). The second comprehensive model showed an improved discrimination ability of up to 0.815 (95% CI, 0.782 to 0.847) and comprised seven variables: age, sex, waist circumference, BMI, glycated hemoglobin, triglyceride, and alanine aminotransferase to aspartate aminotransferase ratio. Our non-laboratory model showed non-inferiority in the prediction of NAFLD versus previously established models, including serum parameters.
Conclusion The new models are simple and user-friendly screening methods that can identify individuals with T2DM who are at high-risk for NAFLD. Additional studies are warranted to validate these new models as useful predictive tools for NAFLD in clinical
practice.
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Non-Alcoholic Fatty Liver Disease or Type 2 Diabetes Mellitus—The Chicken or the Egg Dilemma Marcin Kosmalski, Agnieszka Śliwińska, Józef Drzewoski Biomedicines.2023; 11(4): 1097. CrossRef