5 research outputs found

    Mutation in the FUS nuclear localisation signal domain causes neurodevelopmental and systemic metabolic alterations

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    Variants in the ubiquitously expressed DNA/RNA-binding protein FUS cause aggressive juvenile forms of amyotrophic lateral sclerosis (ALS). Most FUS mutation studies have focused on motor neuron degeneration; little is known about wider systemic or developmental effects. We studied pleiotropic phenotypes in a physiological knock-in mouse model carrying the pathogenic FUSDelta14 mutation in homozygosity. RNA sequencing of multiple organs aimed to identify pathways altered by the mutant protein in the systemic transcriptome, including metabolic tissues, given the link between ALS-frontotemporal dementia and altered metabolism. Few genes were commonly altered across all tissues, and most genes and pathways affected were generally tissue specific. Phenotypic assessment of mice revealed systemic metabolic alterations related to the pathway changes identified. Magnetic resonance imaging brain scans and histological characterisation revealed that homozygous FUSDelta14 brains were smaller than heterozygous and wild-type brains and displayed significant morphological alterations, including a thinner cortex, reduced neuronal number and increased gliosis, which correlated with early cognitive impairment and fatal seizures. These findings show that the disease aetiology of FUS variants can include both neurodevelopmental and systemic alterations

    The value of open-source clinical science in pandemic response: lessons from ISARIC

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    The value of open-source clinical science in pandemic response: lessons from ISARIC

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    ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

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    The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use
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