This systematic review and meta-analysis examines data from published prospective studies of adults to gauge the dose-response association between physical activity and incident depression.

Background & Aims A common genetic variant near MBOAT7 (rs641738C>T) has been previously associated with hepatic fat and advanced histology in NAFLD; however, these findings have not been consistently replicated in the literature. We aimed to establish whether rs641738C>T is a risk factor across the spectrum of NAFLD and to characterise its role in the regulation of related metabolic phenotypes through a meta-analysis. Methods We performed a meta-analysis of studies with data on the association between rs641738C>T genotype and liver fat, NAFLD histology, and serum alanine aminotransferase (ALT), lipids or insulin. These included directly genotyped studies and population-level data from genome-wide association studies (GWAS). We performed a random effects meta-analysis using recessive, additive and dominant genetic models. Results Data from 1,066,175 participants (9,688 with liver biopsies) across 42 studies were included in the meta-analysis. rs641738C>T was associated with higher liver fat on CT/MRI (+0.03 standard deviations [95% CI 0.02–0.05], p z = 4.8×10 –5 ) and diagnosis of NAFLD (odds ratio [OR] 1.17 [95% CI 1.05–1.3], p z = 0.003) in Caucasian adults. The variant was also positively associated with presence of advanced fibrosis (OR 1.22 [95% CI 1.03–1.45], p z = 0.021) in Caucasian adults using a recessive model of inheritance (CC + CT vs. TT). Meta-analysis of data from previous GWAS found the variant to be associated with higher ALT ( p z = 0.002) and lower serum triglycerides ( p z = 1.5×10 –4 ). rs641738C>T was not associated with fasting insulin and no effect was observed in children with NAFLD. Conclusions Our study validates rs641738C>T near MBOAT7 as a risk factor for the presence and severity of NAFLD in individuals of European descent. Lay summary Fatty liver disease is a common condition where fat builds up in the liver, which can cause liver inflammation and scarring (including ‘cirrhosis’). It is closely linked to obesity and diabetes, but some genes are also thought to be important. We did this study to see whether one specific change (‘variant’) in one gene ( ‘MBOAT7’ ) was linked to fatty liver disease. We took data from over 40 published studies and found that this variant near MBOAT7 is linked to more severe fatty liver disease. This means that drugs designed to work on MBOAT7 could be useful for treating fatty liver disease.

Animal models of human disease are a key component of translational hepatology research, and yet, there is no consensus on which model is optimal for non-alcoholic fatty liver disease (NAFLD). Here, we generated a database of 3,920 rodent models of NAFLD. Study designs were highly heterogeneous and, therefore, few models had been cited more than once.Analysis of genetic models supported the current evidence for the role of adipose dysfunction and suggested a role for innate immunity in the progression of NAFLD. We identified that high fat, high fructose diets most closely recapitulate the human phenotype of NAFLD. There was substantial variability in the nomenclature of animal models: a consensus on terminology of specialist diets is needed. More broadly, this analysis demonstrates the variability in preclinical study design, which has wider implications for the reproducibility of in vivo experiments both in the fields of hepatology and beyond. In conclusion, this systematic analysis provides a framework for phenotypic assessment of NAFLD models and highlights the need for increased standardization and replication.

Background: Medical schools differ, particularly in their teaching, but it is unclear whether such differences matter, although influential claims are often made. The Medical School Differences (MedDifs) study brings together a wide range of measures of UK medical schools, including postgraduate performance, fitness to practise issues, specialty choice, preparedness, satisfaction, teaching styles, entry criteria and institutional factors. Method: Aggregated data were collected for 50 measures across 29 UK medical schools. Data include institutional history (e.g. rate of production of hospital and GP specialists in the past), curricular influences (e.g.