Global Emergency Medicine: A Review of the Literature From 2012

Objectives The Global Emergency Medicine Literature Review ( GEMLR ) conducts an annual search of peer‐reviewed and grey literature relevant to global emergency medicine ( EM ) to identify, review, and disseminate the most important new research in this field to a worldwide audience of academics and clinical practitioners. Methods This year, our search identified 4,818 articles written in six languages. These articles were distributed among 20 reviewers for initial screening based on their relevance to the field of global EM . Two additional reviewers searched and screened the grey literature. A total of 224 articles were deemed appropriate by at least one reviewer and were approved by their editor for formal scoring of overall quality and importance. Results Of the 224 articles that met our predetermined inclusion criteria, 56% were categorized as Emergency Care in Resource‐limited Settings, 18% as EM development, and 26% as Disaster and Humanitarian Response. A total of 28 articles received scores of 16 or higher and were selected for formal summary and critique. Inter‐rater reliability for two reviewers using our scoring system was good, with an intraclass correlation coefficient of 0.625 (95% confidence interval = 0.512 to 0.711). Conclusions In 2012 there were more disaster and humanitarian response articles than in previous years. As in prior years, the majority of articles addressed the acute management of infectious diseases or the care of vulnerable populations such as children and pregnant women. Resumen Medicina de Urgencias y Emergencias Global: Una Revisión de la Literatura de 2012 Objetivos La revisión de la literatura publicada en Medicina de Urgencias y Emergencias ( MUE ) global comporta una búsqueda anual de los trabajos relevantes para la MUE global, tanto publicados tras revisión por pares como corresponedientes a literatura gris. La finalidad es identificar, revisar y diseminar las investigaciones novedosas más importantes en este campoa médicos clínicos y universitarios de todo el mundo. Metodología Este año, nuestra búsqueda identificó 4.818 artículos escritos en seis lenguas. Estos artículos se distribuyeron entre 20 revisores para el despistaje inicial basándose en su relevancia para el campo de la MUE global. Dos revisores adicionales buscaron y filtraron la literatura gris. Un total de 224 artículos se consideraron apropiados por al menos un revisor, y se aprobaron por su editor para la puntuación formal de la calidad e importancia totales. Resultados De los 224 artículos que cumplieron nuestros criterios de inclusión predeterminados, un 56% se clasificaron como atención de urgencias y emergencias en ámbitos de recursos limitados, un 18% como desarrollo de la MUE y un 26% como catástrofes y respuesta humanitaria. Un total de 28 artículos recibieron una puntuación de 16 o más y se seleccionaron para el resumen y la crítica formal. La fiabilidad interobservador para los 2 revisores usando nuestro sistema de puntuación fue buena, con un coeficiente de correlación intraclase de 0,625 ( IC 95% = 0,512 a 0,711). Conclusiones En 2012 hubo más artículos sobre catástrofes y respuesta humanitaria que en años anteriores. Como en los años previos, la mayoría de los artículos valoraron el manejo agudo de enfermedades infecciosas o la atención de poblaciones vulnerables como los niños y las mujeres embarazadas.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/99685/1/acem12173.pd

Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p

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.Peer reviewe

Comparison of mRNA splicing assay protocols across multiple laboratories: recommendations for best practice in standardized clinical testing

BACKGROUND: Accurate evaluation of unclassified sequence variants in cancer predisposition genes is essential for clinical management and depends on a multifactorial analysis of clinical, genetic, pathologic, and bioinformatic variables and assays of transcript length and abundance. The integrity of assay data in turn relies on appropriate assay design, interpretation, and reporting

Many sequence variants affecting diversity of adult human height.

Contains fulltext : 69151.pdf (publisher's version ) (Closed access)Adult human height is one of the classical complex human traits. We searched for sequence variants that affect height by scanning the genomes of 25,174 Icelanders, 2,876 Dutch, 1,770 European Americans and 1,148 African Americans. We then combined these results with previously published results from the Diabetes Genetics Initiative on 3,024 Scandinavians and tested a selected subset of SNPs in 5,517 Danes. We identified 27 regions of the genome with one or more sequence variants showing significant association with height. The estimated effects per allele of these variants ranged between 0.3 and 0.6 cm and, taken together, they explain around 3.7% of the population variation in height. The genes neighboring the identified loci cluster in biological processes related to skeletal development and mitosis. Association to three previously reported loci are replicated in our analyses, and the strongest association was with SNPs in the ZBTB38 gene