Data challenges for international health emergencies: lessons learned from ten international COVID-19 driver projects

The COVID-19 pandemic highlighted the importance of international data sharing and access to improve health outcomes for all. The International COVID-19 Data Alliance (ICODA) programme enabled 12 exemplar or driver projects to use existing health-related data to address major research questions relating to the pandemic, and developed data science approaches that helped each research team to overcome challenges, accelerate the data research cycle, and produce rapid insights and outputs. These approaches also sought to address inequity in data access and use, test approaches to ethical health data use, and make summary datasets and outputs accessible to a wider group of researchers. This Health Policy paper focuses on the challenges and lessons learned from ten of the ICODA driver projects, involving researchers from 19 countries and a range of health-related datasets. The ICODA programme reviewed the time taken for each project to complete stages of the health data research cycle and identified common challenges in areas such as data sharing agreements and data curation. Solutions included provision of standard data sharing templates, additional data curation expertise at an early stage, and a trusted research environment that facilitated data sharing across national boundaries and reduced risk. These approaches enabled the driver projects to rapidly produce research outputs, including publications, shared code, dashboards, and innovative resources, which can all be accessed and used by other research teams to address global health challenges

mHTT Seeding Activity:A Marker of Disease Progression and Neurotoxicity in Models of Huntington's Disease

Self-propagating, amyloidogenic mutant huntingtin (mHTT) aggregates may drive progression of Huntington's disease (HD). Here, we report the development of a FRET-based mHTT aggregate seeding (FRASE) assay that enables the quantification of mHTT seeding activity (HSA) in complex biosamples from HD patients and disease models. Application of the FRASE assay revealed HSA in brain homogenates of presymptomatic HD transgenic and knockin mice and its progressive increase with phenotypic changes, suggesting that HSA quantitatively tracks disease progression. Biochemical investigations of mouse brain homogenates demonstrated that small, rather than large, mHTT structures are responsible for the HSA measured in FRASE assays. Finally, we assessed the neurotoxicity of mHTT seeds in an inducible Drosophila model transgenic for HTTex1. We found a strong correlation between the HSA measured in adult neurons and the increased mortality of transgenic HD flies, indicating that FRASE assays detect disease-relevant, neurotoxic, mHTT structures with severe phenotypic consequences in vivo. Ast et al. present the development of a FRET-based aggregate seeding (FRASE) assay that facilitates the detection and quantification of mHTT seeding activity (HSA) in complex biosamples. They show that HSA is detectable in brains of presymptomatic Huntington's disease (HD) mice and correlates with disease progression and neurotoxicity in HD transgenic flies