RESUMEN
BACKGROUND & AIMS: Non-alcoholic steatohepatitis (NASH) is associated with increased risk of liver-related and cardiovascular morbidity and mortality. Given the complex pathophysiology of NASH, combining therapies with complementary mechanisms may be beneficial. This trial evaluated the safety and efficacy of semaglutide, a glucagon-like peptide-1 receptor agonist, alone and in combination with the farnesoid X receptor agonist cilofexor and/or the acetyl-coenzyme A carboxylase inhibitor firsocostat in patients with NASH. METHODS: This was a phase II, open-label, proof-of-concept trial in which patients with NASH (F2-F3 on biopsy, or MRI-proton density fat fraction [MRI-PDFF] ≥10% and liver stiffness by transient elastography ≥7 kPa) were randomised to 24 weeks' treatment with semaglutide 2.4 mg once weekly as monotherapy or combined with once-daily cilofexor (30 or 100 mg) and/or once-daily firsocostat 20 mg. The primary endpoint was safety. All efficacy endpoints were exploratory. RESULTS: A total of 108 patients were randomised to semaglutide (n = 21), semaglutide plus cilofexor 30 mg (n = 22), semaglutide plus cilofexor 100 mg (n = 22), semaglutide plus firsocostat (n = 22) or semaglutide, cilofexor 30 mg and firsocostat (n = 21). Treatments were well tolerated - the incidence of adverse events was similar across groups (73-90%) and most events were gastrointestinal in nature. Despite similar weight loss (7-10%), compared with semaglutide monotherapy, combinations resulted in greater improvements in liver steatosis measured by MRI-PDFF (least-squares mean of absolute changes: -9.8 to -11.0% vs. -8.0%), liver biochemistry, and non-invasive tests of fibrosis. CONCLUSIONS: In patients with mild-to-moderate fibrosis due to NASH, semaglutide with firsocostat and/or cilofexor was generally well tolerated. In exploratory efficacy analyses, treatment resulted in additional improvements in liver steatosis and biochemistry vs. semaglutide alone. Given this was a small-scale open-label trial, double-blind placebo-controlled trials with adequate patient numbers are warranted to assess the efficacy and safety of these combinations in NASH. CLINICAL TRIAL REGISTRATION NUMBER: NCT03987074. LAY SUMMARY: Non-alcoholic fatty liver disease and its more severe form, non-alcoholic steatohepatitis (NASH), are serious liver conditions that worsen over time if untreated. The reasons people develop NASH are complex and combining therapies that target different aspects of the disease may be more helpful than using single treatments. This trial showed that the use of 3 different types of drugs, namely semaglutide, cilofexor and firsocostat, in combination was safe and may offer additional benefits over treatment with semaglutide alone.
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Enfermedad del Hígado Graso no Alcohólico , Azetidinas , Método Doble Ciego , Fibrosis , Péptidos Similares al Glucagón , Humanos , Isobutiratos , Ácidos Isonicotínicos , Enfermedad del Hígado Graso no Alcohólico/complicaciones , Oxazoles , Pirimidinas , Resultado del TratamientoRESUMEN
Objective: Semaglutide is a glucagon-like peptide 1 (GLP-1) analog for the once-weekly treatment of type 2 diabetes (T2D). In the global SUSTAIN clinical trial program, semaglutide demonstrated superior glycated hemoglobin (HbA1c) and body weight reductions versus comparators. This post hoc analysis compared the proportion of patients achieving combined reductions in glycemia and body weight versus comparators. Methods: A total of 5,119 subjects with T2D in the phase 3 SUSTAIN 1 through 5 and 7 trials, from 33 countries, were included in this post hoc analysis. Subjects received subcutaneous semaglutide 0.5 or 1.0 mg, placebo or active comparator (sitagliptin 100 mg, exenatide extended release 2.0 mg, insulin glargine, dulaglutide 0.75 or 1.5 mg). The main endpoint was a composite of ≥1.0% HbA1c reduction and ≥5.0% weight loss at end of treatment. Results: Significantly greater proportions of subjects achieved the composite endpoint with semaglutide 0.5 (25 to 38%) and 1.0 mg (38 to 59%) versus comparators (2 to 23%). More subjects treated with semaglutide versus comparators achieved ≥1.0% HbA1c reductions (58 to 77% and 75 to 83% for semaglutide 0.5 and 1.0 mg versus 12 to 68%) and ≥5.0% weight loss (37 to 46%, 45 to 66% versus 4 to 30%). Proportions of subjects achieving targets were significantly higher with semaglutide 1.0 versus 0.5 mg in four of five trials. Semaglutide was well tolerated, with a safety profile similar to other GLP-1 receptor agonists. Conclusion: Significantly more subjects achieved both ≥1.0% HbA1c reduction and ≥5.0% weight loss with once-weekly subcutaneous semaglutide treatment versus comparators in the SUSTAIN trials. A dose-dependent effect was observed with semaglutide. Abbreviations: AE = adverse event; CV = cardiovascular; ER = extended release; GLP-1 = glucagon-like peptide 1; GLP-1 RA = glucagon-like peptide 1 receptor agonist; HbA1c = glycated hemoglobin; OAD = oral antidiabetic drug; sc = subcutaneous; T2D = type 2 diabetes.
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Diabetes Mellitus Tipo 2 , Peso Corporal , Péptidos Similares al Glucagón , Hemoglobina Glucada , Humanos , HipoglucemiantesRESUMEN
Many of the functional traits considered in animal breeding can be analyzed as threshold traits or survival traits with examples including disease traits, conformation scores, calving difficulty and longevity. In this paper we derive and implement a bivariate quantitative genetic model for a threshold character and a survival trait that are genetically and environmentally correlated. For the survival trait, we considered the Weibull log-normal animal frailty model. A Bayesian approach using Gibbs sampling was adopted in which model parameters were augmented with unobserved liabilities associated with the threshold trait. The fully conditional posterior distributions associated with parameters of the threshold trait reduced to well known distributions. For the survival trait the two baseline Weibull parameters were updated jointly by a Metropolis-Hastings step. The remaining model parameters with non-normalized fully conditional distributions were updated univariately using adaptive rejection sampling. The Gibbs sampler was tested in a simulation study and illustrated in a joint analysis of calving difficulty and longevity of dairy cattle. The simulation study showed that the estimated marginal posterior distributions covered well and placed high density to the true values used in the simulation of data. The data analysis of calving difficulty and longevity showed that genetic variation exists for both traits. The additive genetic correlation was moderately favorable with marginal posterior mean equal to 0.37 and 95% central posterior credibility interval ranging between 0.11 and 0.61. Therefore, this study suggests that selection for improving one of the two traits will be beneficial for the other trait as well.
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Modelos Genéticos , Análisis de Supervivencia , Teorema de Bayes , Análisis MultivarianteRESUMEN
Data on doe longevity in a rabbit population were analysed using a semiparametric log-Normal animal frailty model. Longevity was defined as the time from the first positive pregnancy test to death or culling due to pathological problems. Does culled for other reasons had right censored records of longevity. The model included time dependent covariates associated with year by season, the interaction between physiological state and the number of young born alive, and between order of positive pregnancy test and physiological state. The model also included an additive genetic effect and a residual in log frailty. Properties of marginal posterior distributions of specific parameters were inferred from a full Bayesian analysis using Gibbs sampling. All of the fully conditional posterior distributions defining a Gibbs sampler were easy to sample from, either directly or using adaptive rejection sampling. The marginal posterior mean estimates of the additive genetic variance and of the residual variance in log frailty were 0.247 and 0.690.
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Longevidad/fisiología , Modelos Estadísticos , Análisis Multivariante , Análisis de Supervivencia , Animales , Teorema de Bayes , Femenino , Variación Genética , Funciones de Verosimilitud , Modelos Lineales , Embarazo , Resultado del Embarazo , Índice de Embarazo , Conejos , Análisis de Regresión , Estaciones del Año , Factores de TiempoRESUMEN
With the increasing use of survival models in animal breeding to address the genetic aspects of mainly longevity of livestock but also disease traits, the need for methods to infer genetic correlations and to do multivariate evaluations of survival traits and other types of traits has become increasingly important. In this study we derived and implemented a bivariate quantitative genetic model for a linear Gaussian and a survival trait that are genetically and environmentally correlated. For the survival trait, we considered the Weibull log-normal animal frailty model. A Bayesian approach using Gibbs sampling was adopted. Model parameters were inferred from their marginal posterior distributions. The required fully conditional posterior distributions were derived and issues on implementation are discussed. The two Weibull baseline parameters were updated jointly using a Metropolis-Hasting step. The remaining model parameters with non-normalized fully conditional distributions were updated univariately using adaptive rejection sampling. Simulation results showed that the estimated marginal posterior distributions covered well and placed high density to the true parameter values used in the simulation of data. In conclusion, the proposed method allows inferring additive genetic and environmental correlations, and doing multivariate genetic evaluation of a linear Gaussian trait and a survival trait.