Autophagy coordinates chondrocyte development and early joint formation in zebrafish

Autophagy is a catabolic process responsible for the removal of waste and damaged cellular components by lysosomal degradation. It plays a key role in fundamental cell processes, including ER stress mitigation, control of cell metabolism, and cell differentiation and proliferation, all of which are essential for cartilage cell (chondrocyte) development and survival, and for the formation of cartilage. Correspondingly, autophagy dysregulation has been implicated in several skeletal disorders such as osteoarthritis and osteoporosis. To test the requirement for autophagy during skeletal development in zebrafish, we generated an atg13 CRISPR knockout zebrafish line. This line showed a complete loss of atg13 expression, and restricted autophagic activity in vivo. In the absence of autophagy, chondrocyte maturation was accelerated, with chondrocytes exhibiting signs of premature hypertrophy. Focussing on the jaw element, autophagy disruption affected joint articulation causing restricted mouth opening. This gross behavioural phenotype corresponded with a failure to thrive, and death in homozygote atg13 nulls within 17 days. Taken together, our results are consistent with autophagy contributing to the timely regulation of chondrocyte maturation and for extracellular matrix formation

Statistical issues related to dietary intake as the response variable in intervention trials.

The focus of this paper is dietary intervention trials. We explore the statistical issues involved when the response variable, intake of a food or nutrient, is based on self-report data that are subject to inherent measurement error. There has been little work on handling error in this context. A particular feature of self-reported dietary intake data is that the error may be differential by intervention group. Measurement error methods require information on the nature of the errors in the self-report data. We assume that there is a calibration sub-study in which unbiased biomarker data are available. We outline methods for handling measurement error in this setting and use theory and simulations to investigate how self-report and biomarker data may be combined to estimate the intervention effect. Methods are illustrated using data from the Trial of Nonpharmacologic Intervention in the Elderly, in which the intervention was a sodium-lowering diet and the response was sodium intake. Simulations are used to investigate the methods under differential error, differing reliability of self-reports relative to biomarkers and different proportions of individuals in the calibration sub-study. When the reliability of self-report measurements is comparable with that of the biomarker, it is advantageous to use the self-report data in addition to the biomarker to estimate the intervention effect. If, however, the reliability of the self-report data is low compared with that in the biomarker, then, there is little to be gained by using the self-report data. Our findings have important implications for the design of dietary intervention trials. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd

Application of the LymphGen classification tool to 928 clinically and genetically-characterised cases of diffuse large B cell lymphoma (DLBCL).

We recently published results of targeted sequencing applied to 928 unselected cases of DLBCL registered in the Haematological Malignancy Research Network (HMRN) registry (1). Clustering allowed us to resolve five genomic subtypes. These subtypes shared considerable overlap with those proposed in two independent genomic studies(2, 3), suggesting the potential to use genetics to stratify patients by both risk and biology. In the original studies, clustering techniques were applied to sample cohorts to reveal molecular substructure, but left open the challenge of how to classify an individual patient. This was addressed by the LymphGen classification tool (4). LymphGen assigns an individual case to one of six molecular subtypes. The tool accommodates data from exome or targeted sequencing, either with or without copy number variant (CNV) data. Separate gene expression data allows classification of a seventh, MYC-driven subtype defined by a double hit (DHL) or molecular high-grade (MHG) gene expression signature(5-7).HR was funded by a studentship from the Medical Research Council. DH was supported by a Clinician Scientist Fellowship from the Medical Research Council (MR/M008584/1). The Hodson laboratory receives core funding from Wellcome and MRC to the Wellcome-MRC Cambridge Stem Cell Institute and core funding from the CRUK Cambridge Cancer Centre. HMRN is supported by BCUK 15037 and CRUK 18362

mTOR independent alteration in ULK1 Ser758 phosphorylation following chronic LRRK2 kinase inhibition

Unc-51 Like Kinase 1 (ULK1) is a critical regulator of the biogenesis of autophagosomes, the central component of the catabolic macroautophagy pathway. Regulation of ULK1 activity is dependent upon several phosphorylation events acting to repress or activate the enzymatic function of this protein. Phosphorylation of Ser758 ULK1 has been linked to repression of autophagosome biogenesis and was thought to be exclusively dependent upon mTOR complex 1 kinase activity. In this study, a novel regulation of Ser758 ULK1 phosphorylation is reported following prolonged inhibition of the Parkinson's disease linked protein Leucine Rich Repeat Kinase 2 (LRRK2). Here, modulation of Ser758 ULK1 phosphorylation following LRRK2 inhibition is decoupled from the repression of autophagosome biogenesis and independent of mTOR complex 1 activity

A new multivariate measurement error model with zero-inflated dietary data, and its application to dietary assessment

In the United States the preferred method of obtaining dietary intake data is the 24-hour dietary recall, yet the measure of most interest is usual or long-term average daily intake, which is impossible to measure. Thus, usual dietary intake is assessed with considerable measurement error. Also, diet represents numerous foods, nutrients and other components, each of which have distinctive attributes. Sometimes, it is useful to examine intake of these components separately, but increasingly nutritionists are interested in exploring them collectively to capture overall dietary patterns. Consumption of these components varies widely: some are consumed daily by almost everyone on every day, while others are episodically consumed so that 24-hour recall data are zero-inflated. In addition, they are often correlated with each other. Finally, it is often preferable to analyze the amount of a dietary component relative to the amount of energy (calories) in a diet because dietary recommendations often vary with energy level. The quest to understand overall dietary patterns of usual intake has to this point reached a standstill. There are no statistical methods or models available to model such complex multivariate data with its measurement error and zero inflation. This paper proposes the first such model, and it proposes the first workable solution to fit such a model. After describing the model, we use survey-weighted MCMC computations to fit the model, with uncertainty estimation coming from balanced repeated replication.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS446 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Pathogenic Parkinson's disease mutations across the functional domains of LRRK2 alter the autophagic/lysosomal response to starvation

LRRK2 is one of the most important genetic contributors to Parkinson's disease (PD). Point mutations in this gene cause an autosomal dominant form of PD, but to date no cellular phenotype has been consistently linked with mutations in each of the functional domains (ROC, COR and Kinase) of the protein product of this gene. In this study, primary fibroblasts from individuals carrying pathogenic mutations in the three central domains of LRRK2 were assessed for alterations in the autophagy/lysosomal pathway using a combination of biochemical and cellular approaches. Mutations in all three domains resulted in alterations in markers for autophagy/lysosomal function compared to wild type cells. These data highlight the autophagy and lysosomal pathways as read outs for pathogenic LRRK2 function and as a marker for disease, and provide insight into the mechanisms linking LRRK2 function and mutations

Discovery and progress in our understanding of the regulated secretory pathway in neuroendocrine cells

In this review we start with a historical perspective beginning with the early morphological work done almost 50 years ago. The importance of these pioneering studies is underscored by our brief summary of the key questions addressed by subsequent research into the mechanism of secretion. We then highlight important advances in our understanding of the formation and maturation of neuroendocrine secretory granules, first using in vitro reconstitution systems, then most recently biochemical approaches, and finally genetic manipulations in vitro and in vivo