48 research outputs found

    The HTA Core Model: A novel method for producing and reporting health technology assessments

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    Objectives: The aim of this study was to develop and test a generic framework to enable international collaboration for producing and sharing results of health technology assessments (HTAs). Methods: Ten international teams constructed the HTA Core Model, dividing information contained in a comprehensive HTA into standardized pieces, the assessment elements. Each element contains a generic issue that is translated into practical research questions while performing an assessment. Elements were described in detail in element cards. Two pilot assessments, designated as Core HTAs were also produced. The Model and Core HTAs were both validated. Guidance on the use of the HTA Core Model was compiled into a Handbook. Results: The HTA Core Model considers health technologies through nine domains. Two applications of the Model were developed, one for medical and surgical interventions and another for diagnostic technologies. Two Core HTAs were produced in parallel with developing the model, providing the first real-life testing of the Model and input for further development. The results of formal validation and public feedback were primarily positive. Development needs were also identified and considered. An online Handbook is available. Conclusions: The HTA Core Model is a novel approach to HTA. It enables effective international production and sharing of HTA results in a structured format. The face validity of the Model was confirmed during the project, but further testing and refining are needed to ensure optimal usefulness and user-friendliness. Core HTAs are intended to serve as a basis for local HTA reports. Core HTAs do not contain recommendations on technology us

    GABA uptake transporters support dopamine release in dorsal striatum with maladaptive downregulation in a parkinsonism model

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    Striatal dopamine (DA) is critical for action and learning. Recent data show that DA release is under tonic inhibition by striatal GABA. Ambient striatal GABA tone on striatal projection neurons can be determined by plasma membrane GABA uptake transporters (GATs) located on astrocytes and neurons. However, whether striatal GATs and astrocytes determine DA output are unknown. We reveal that DA release in mouse dorsolateral striatum, but not nucleus accumbens core, is governed by GAT-1 and GAT-3. These GATs are partly localized to astrocytes, and are enriched in dorsolateral striatum compared to accumbens core. In a mouse model of early parkinsonism, GATs are downregulated, tonic GABAergic inhibition of DA release augmented, and nigrostriatal GABA co-release attenuated. These data define previously unappreciated and important roles for GATs and astrocytes in supporting DA release in striatum, and reveal a maladaptive plasticity in early parkinsonism that impairs DA output in vulnerable striatal regions

    Prediction of acute myeloid leukaemia risk in healthy individuals

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    The incidence of acute myeloid leukaemia (AML) increases with age and mortality exceeds 90% when diagnosed after age 65. Most cases arise without any detectable early symptoms and patients usually present with the acute complications of bone marrow failure(1). The onset of such de novo AML cases is typically preceded by the accumulation of somatic mutations in preleukaemic haematopoietic stem and progenitor cells (HSPCs) that undergo clonal expansion(2,3). However, recurrent AML mutations also accumulate in HSPCs during ageing of healthy individuals who do not develop AML, a phenomenon referred to as age-related clonal haematopoiesis (ARCH)(4-8). Here we use deep sequencing to analyse genes that are recurrently mutated in AML to distinguish between individuals who have a high risk of developing AML and those with benign ARCH. We analysed peripheral blood cells from 95 individuals that were obtained on average 6.3 years before AML diagnosis (pre-AML group), together with 414 unselected age- and gender-matched individuals (control group). Pre-AML cases were distinct from controls and had more mutations per sample, higher variant allele frequencies, indicating greater clonal expansion, and showed enrichment of mutations in specific genes. Genetic parameters were used to derive a model that accurately predicted AML-free survival; this model was validated in an independent cohort of 29 pre-AML cases and 262 controls. Because AML is rare, we also developed an AML predictive model using a large electronic health record database that identified individuals at greater risk. Collectively our findings provide proof-of-concept that it is possible to discriminate ARCH from pre-AML many years before malignant transformation. This could in future enable earlier detection and monitoring, and may help to inform intervention

    Current and emerging developments in subseasonal to decadal prediction

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    Weather and climate variations of subseasonal to decadal timescales can have enormous social, economic and environmental impacts, making skillful predictions on these timescales a valuable tool for decision makers. As such, there is a growing interest in the scientific, operational and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) timescales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) timescales, while the focus remains broadly similar (e.g., on precipitation, surface and upper ocean temperatures and their effects on the probabilities of high-impact meteorological events), understanding the roles of internal and externally-forced variability such as anthropogenic warming in forecasts also becomes important. The S2S and S2D communities share common scientific and technical challenges. These include forecast initialization and ensemble generation; initialization shock and drift; understanding the onset of model systematic errors; bias correct, calibration and forecast quality assessment; model resolution; atmosphere-ocean coupling; sources and expectations for predictability; and linking research, operational forecasting, and end user needs. In September 2018 a coordinated pair of international conferences, framed by the above challenges, was organized jointly by the World Climate Research Programme (WCRP) and the World Weather Research Prograame (WWRP). These conferences surveyed the state of S2S and S2D prediction, ongoing research, and future needs, providing an ideal basis for synthesizing current and emerging developments in these areas that promise to enhance future operational services. This article provides such a synthesis

    Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

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    Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

    Use of sequenom sample ID plus® SNP genotyping in identification of FFPE tumor samples

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    Short tandem repeat (STR) analysis, such as the AmpFlSTR® Identifiler® Plus kit, is a standard, PCR-based human genotyping method used in the field of forensics. Misidentification of cell line and tissue DNA can be costly if not detected early; therefore it is necessary to have quality control measures such as STR profiling in place. A major issue in large-scale research studies involving archival formalin-fixed paraffin embedded (FFPE) tissues is that varying levels of DNA degradation can result in failure to correctly identify samples using STR genotyping. PCR amplification of STRs of several hundred base pairs is not always possible when DNA is degraded. The Sample ID Plus® panel from Sequenom allows for human DNA identification and authentication using SNP genotyping. In comparison to lengthy STR amplicons, this multiplexing PCR assay requires amplification of only 76-139 base pairs, and utilizes 47 SNPs to discriminate between individual samples. In this study, we evaluated both STR and SNP genotyping methods of sample identification, with a focus on paired FFPE tumor/normal DNA samples intended for next-generation sequencing (NGS). The ability to successfully validate the identity of FFPE samples can enable cost savings by reducing rework
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