A Hybrid Architecture (CO-CONNECT) to Facilitate Rapid Discovery and Access to Data Across the United Kingdom in Response to the COVID-19 Pandemic: Development Study.

BACKGROUND: COVID-19 data have been generated across the United Kingdom as a by-product of clinical care and public health provision, as well as numerous bespoke and repurposed research endeavors. Analysis of these data has underpinned the United Kingdom's response to the pandemic, and informed public health policies and clinical guidelines. However, these data are held by different organizations, and this fragmented landscape has presented challenges for public health agencies and researchers as they struggle to find relevant data to access and interrogate the data they need to inform the pandemic response at pace. OBJECTIVE: We aimed to transform UK COVID-19 diagnostic data sets to be findable, accessible, interoperable, and reusable (FAIR). METHODS: A federated infrastructure model (COVID - Curated and Open Analysis and Research Platform [CO-CONNECT]) was rapidly built to enable the automated and reproducible mapping of health data partners' pseudonymized data to the Observational Medical Outcomes Partnership Common Data Model without the need for any data to leave the data controllers' secure environments, and to support federated cohort discovery queries and meta-analysis. RESULTS: A total of 56 data sets from 19 organizations are being connected to the federated network. The data include research cohorts and COVID-19 data collected through routine health care provision linked to longitudinal health care records and demographics. The infrastructure is live, supporting aggregate-level querying of data across the United Kingdom. CONCLUSIONS: CO-CONNECT was developed by a multidisciplinary team. It enables rapid COVID-19 data discovery and instantaneous meta-analysis across data sources, and it is researching streamlined data extraction for use in a Trusted Research Environment for research and public health analysis. CO-CONNECT has the potential to make UK health data more interconnected and better able to answer national-level research questions while maintaining patient confidentiality and local governance procedures.

VarioML framework for comprehensive variation data representation and exchange.

BACKGROUND: Sharing of data about variation and the associated phenotypes is a critical need, yet variant information can be arbitrarily complex, making a single standard vocabulary elusive and re-formatting difficult. Complex standards have proven too time-consuming to implement. RESULTS: The GEN2PHEN project addressed these difficulties by developing a comprehensive data model for capturing biomedical observations, Observ-OM, and building the VarioML format around it. VarioML pairs a simplified open specification for describing variants, with a toolkit for adapting the specification into one's own research workflow. Straightforward variant data can be captured, federated, and exchanged with no overhead; more complex data can be described, without loss of compatibility. The open specification enables push-button submission to gene variant databases (LSDBs) e.g., the Leiden Open Variation Database, using the Cafe Variome data publishing service, while VarioML bidirectionally transforms data between XML and web-application code formats, opening up new possibilities for open source web applications building on shared data. A Java implementation toolkit makes VarioML easily integrated into biomedical applications. VarioML is designed primarily for LSDB data submission and transfer scenarios, but can also be used as a standard variation data format for JSON and XML document databases and user interface components. CONCLUSIONS: VarioML is a set of tools and practices improving the availability, quality, and comprehensibility of human variation information. It enables researchers, diagnostic laboratories, and clinics to share that information with ease, clarity, and without ambiguity.

HB-GAM (pleiotrophin) reverses inhibition of neural regeneration by the CNS extracellular matrix.

Chondroitin sulfate (CS) glycosaminoglycans inhibit regeneration in the adult central nervous system (CNS). We report here that HB-GAM (heparin-binding growth-associated molecule; also known as pleiotrophin), a CS-binding protein expressed at high levels in the developing CNS, reverses the role of the CS chains in neurite growth of CNS neurons in vitro from inhibition to activation. The CS-bound HB-GAM promotes neurite growth through binding to the cell surface proteoglycan glypican-2; furthermore, HB-GAM abrogates the CS ligand binding to the inhibitory receptor PTPσ (protein tyrosine phosphatase sigma). Our in vivo studies using two-photon imaging of CNS injuries support the in vitro studies and show that HB-GAM increases dendrite regeneration in the adult cerebral cortex and axonal regeneration in the adult spinal cord. Our findings may enable the development of novel therapies for CNS injuries.

Heparan sulfate proteoglycan syndecan-3 is a novel receptor for GDNF, neurturin, and artemin.

Glial cell line-derived neurotrophic factor (GDNF) family ligands (GFLs) are potent survival factors for dopaminergic neurons and motoneurons with therapeutic potential for Parkinson's disease. Soluble GFLs bind to a ligand-specific glycosylphosphatidylinositol-anchored coreceptor (GDNF family receptor α) and signal through the receptor tyrosine kinase RET. In this paper, we show that all immobilized matrix-bound GFLs, except persephin, use a fundamentally different receptor. They interact with syndecan-3, a transmembrane heparan sulfate (HS) proteoglycan, by binding to its HS chains with high affinity. GFL-syndecan-3 interaction mediates both cell spreading and neurite outgrowth with the involvement of Src kinase activation. GDNF promotes migration of cortical neurons in a syndecan-3-dependent manner, and in agreement, mice lacking syndecan-3 or GDNF have a reduced number of cortical γ-aminobutyric acid-releasing neurons, suggesting a central role for the two molecules in cortical development. Collectively, syndecan-3 may directly transduce GFL signals or serve as a coreceptor, presenting GFLs to the signaling receptor RET.