COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms.

We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.

Neurologic manifestations in 1760 COVID-19 patients admitted to Papa Giovanni XXIII Hospital, Bergamo, Italy.

OBJECTIVES: Evidences from either small series or spontaneous reporting are accumulating that SARS-CoV-2 involves the Nervous Systems. The aim of this study is to provide an extensive overview on the major neurological complications in a large cohort of COVID-19 patients. METHODS: Retrospective, observational analysis on all COVID-19 patients admitted from February 23rd to April 30th, 2020 to ASST Papa Giovanni XXIII, Bergamo, Italy for whom a neurological consultation/neurophysiological assessment/neuroradiologic investigation was requested. Each identified neurologic complication was then classified into main neurologic categories. RESULTS: Of 1760 COVID-19 patients, 137 presented neurologic manifestations that manifested after COVID-19 symptoms in 98 pts and was the presenting symptom in 39. Neurological manifestations were classified as: (a) cerebrovascular disease [53 pts (38.7%)] including 37 ischemic and 11 haemorrhagic strokes, 4 transient ischemic attacks, 1 cerebral venous thrombosis; (b) peripheral nervous system diseases [31 (22.6%)] including 17 Guillain-Barrè syndromes; (c) altered mental status [49 (35.8%)] including one necrotizing encephalitis and 2 cases with RT-PCR detection of SARS-Cov-2 RNA in CSF; (d) miscellaneous disorders, among whom 2 patients with myelopathy associated with Ab anti-SARS-CoV-2 in CSF. Patients with peripheral nervous system involvement had more frequently severe ARDS compared to patients with cerebrovascular disease (87.1% vs 42%; difference = 45.1% 95% CI 42.0-48.2; χ2= 14.306; p < 0.0002) and with altered mental status (87.1% vs 55.6%; difference = 31.5% 95% CI 27.5-37.5%; χ2= 7.055; p < 0.01). CONCLUSION: This study confirms that involvement of nervous system is common in SARS-CoV-2 infection and offers clinicians useful information for prevention and prompt identification in order to set the adequate therapeutic strategies.