Clinical management of patients with genetic obesity during COVID-19 pandemic: position paper of the ESE Growth & Genetic Obesity COVID-19 Study Group and Rare Endo-ERN main thematic group on Growth and Obesity

This article aims to provide guidance on prevention and treatment of COVID-19 in patients with genetic obesity. Key principals of the management of patients with genetic obesity during COVID-19 pandemic for patients that have contracted COVID-19 are to be aware of: possible adrenal insufficiency (e.g., POMC deficiency, PWS); a more severe course in patients with concomitant immunodeficiency (e.g., LEP and LEPR deficiency), although defective leptin signalling could also be protective against the pro-inflammatory phenotype of COVID-19; disease severity being masked by insufficient awareness of symptoms in syndromic obesity patients with intellectual deficit (in particular PWS); to adjust medication dose to increased body size, preferably use dosing in m2; the high risk of malnutrition in patients with Sars-Cov2 infection, even in case of obesity. Key principals of the obesity management during the pandemic are to strive for optimal obesity management and a healthy lifestyle within the possibilities of the regulations to prevent weight (re)gain and to address anxiety within consultations, since prevalence of anxiety for COVID-19 is underestimated.Transplantation and immunomodulatio

A data-driven methodology reveals novel myofiber clusters in older human muscles

Skeletal muscles control posture, mobility and strength, and influence whole-body metabolism. Muscles are built of different types of myofibers, each having specific metabolic, molecular, and contractile properties. Fiber classification is, therefore, regarded the key for understanding muscle biology, (patho-) physiology. The expression of three myosin heavy chain (MyHC) isoforms, MyHC-1, MyHC-2A, and MyHC-2X, marks myofibers in humans. Typically, myofiber classification is performed by an eye-based histological analysis. This classical approach is insufficient to capture complex fiber classes, expressing more than one MyHC-isoform. We, therefore, developed a methodological procedure for high-throughput characterization of myofibers on the basis of multiple isoforms. The mean fluorescence intensity of the three most abundant MyHC isoforms was measured per myofiber in muscle biopsies of 56 healthy elderly adults, and myofiber classes were identified using computational biology tools. Unsupervised clustering revealed the existence of six distinct myofiber clusters. A comparison with the visual assessment of myofibers using the same images showed that some of these myofiber clusters could not be detected or were frequently misclassified. The presence of these six clusters was reinforced by RNA expressions levels of sarcomeric genes. In addition, one of the clusters, expressing all three MyHC isoforms, correlated with histological measures of muscle health. To conclude, this methodological procedure enables deep characterization of the complex muscle heterogeneity. This study opens opportunities to further investigate myofiber composition in comparative studies.Development and application of statistical models for medical scientific researc

Same data, different conclusions: Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis

In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists’ gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for organizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed

The trans-ancestral genomic architecture of glycemic traits

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10(-8)), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.Diabetes mellitus: pathophysiological changes and therap

Identifying and prioritizing lower value services from Dutch specialist guidelines and a comparison with the UK do-not-do list

Contains fulltext : 172733.pdf (publisher's version ) (Open Access)BACKGROUND: The term 'lower value services' concerns healthcare that is of little or no value to the patient and consequently should not be provided routinely, or not be provided at all. De-adoption of lower value care may occur through explicit recommendations in clinical guidelines. The present study aimed to generate a comprehensive list of lower value services for the Netherlands that assesses the type of care and associated medical conditions. The list was compared with the NICE do-not-do list (United Kingdom). Finally, the feasibility of prioritizing the list was studied to identify conditions where de-adoption is warranted. METHODS: Dutch clinical guidelines (published from 2010 to 2015) were searched for lower value services. The lower value services identified were categorized by type of care (diagnostics, treatment with and without medication), type of lower value service (not routinely provided or not provided at all), and ICD10 codes (international classification of diseases). The list was prioritized per ICD10 code, based on the number of lower value services per ICD10 code, prevalence, and burden of disease. RESULTS: A total of 1366 lower value services were found in the 193 Dutch guidelines included in our study. Of the lower value services, 30% covered diagnostics, 29% related to surgical and medical treatment without drugs primarily, and 39% related to drug treatment. The majority (77%) of all lower value services was on care that should not be offered at all, whereas the other 23% recommended on care that should not be offered routinely. ICD10 chapters that included most lower value services were neoplasms and diseases of the nervous system. Dutch guidelines appear to contain more lower value services than UK guidelines. The prioritization processes revealed several conditions, including back pain, chronic obstructive pulmonary disease, and ischemic heart diseases, where lower value services most likely occur and de-adoption is warranted. CONCLUSIONS: In this study, a comprehensive list of lower value services for Dutch hospital care was developed. A feasible method for prioritizing lower value services was established. Identifying and prioritizing lower value services is the first of several necessary steps in reducing them