Dataset Information

Estimating the severity of COVID-19: Evidence from the Italian epicenter.

ABSTRACT: We provide results on the level of COVID-19 excess mortality in the Italian region of Lombardy and in the province of Bergamo using official and original data sources. Since February 2020 Lombardy and in particular the province of Bergamo have been severely hit by the novel COVID-19 infectious disease. Combining official statistics, retrospective data and original data (i.e., obituaries and death notices) we provide a tentative estimate of the number of deaths either directly or indirectly, associated with COVID-19 as well as the total number of persons infected. Our findings suggest that the reported number of deaths attributable to COVID-19 identified by public authorities accounts only for one half of the observed excess mortality between March 2020 and previous years.

SUBMITTER: Buonanno P

PROVIDER: S-EPMC7529188 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Estimating the severity of COVID-19: Evidence from the Italian epicenter.

Buonanno Paolo P Galletta Sergio S Puca Marcello M

PloS one 20201001 10

We provide results on the level of COVID-19 excess mortality in the Italian region of Lombardy and in the province of Bergamo using official and original data sources. Since February 2020 Lombardy and in particular the province of Bergamo have been severely hit by the novel COVID-19 infectious disease. Combining official statistics, retrospective data and original data (i.e., obituaries and death notices) we provide a tentative estimate of the number of deaths either directly or indirectly, asso ...[more]

PMID: 33002036

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Project description:Using RNA-seq and high-resolution mass spectrometry we performed a comprehensive systems analysis on 128 plasma and leukocyte samples from hospitalized patients with or without COVID-19 (n=102 and 26 respectively) and with differing degrees of disease severity. We generated abundance measurements for over 17,000 transcripts, proteins, metabolites, and lipids and compiled them with clinical data into a curated relational database. This resource offers the unique opportunity to perform systems analysis and cross-ome correlations to both molecules and patient outcomes. In total 219 molecular features were mapped with high significance to COVID-19 status and severity, including those involved in processes such as complement system activation, dysregulated lipid transport, and B cell activation. In one example, we detected a trio of covarying molecules – citrate, plasmenyl-phosphatidylcholines, and gelsolin (GSN) – that offer both pathophysiological insight and potential novel therapeutic targets. Further, our data revealed in some cases, and supported in others, that several biological processes were dysregulated in COVID-19 patients including vessel damage, platelet activation and degranulation, blood coagulation, and acute phase response. For example, we observed that the coagulation-related protein, cellular fibronectin (cFN), was highly increased within COVID-19 patients and provide new evidence that the upregulated proteoform stems from endothelial cells, consistent with endothelial injury as a major activator of the coagulation cascade. The abundance of prothrombin, which is cleaved to form thrombin during clotting, was significantly reduced and correlated with severity and might help to explain the hyper coagulative environment of SARS-CoV-2 infection. From transcriptomic analysis of leukocytes, we concluded that COVID-19 patients with acute respiratory distress syndrome (ARDS) demonstrated a phenotype that overlapped with, but was distinct from, that found in patients with non-COVID-19-ARDS. To aid in the global efforts toward elucidation of disease pathophysiology and therapeutic development, we created a web-based tool with interactive visualizations allowing for easy navigation of this systems-level compendium of biomolecule abundance in relation to COVID-19 status and severity. Finally, we leveraged these multi-omic data to predict COVID-19 patient outcomes with machine learning, which highlighted the predictive power of these expansive molecular measurements beyond the standardized clinical estimate of 10-year survival Charlson score.

Dataset Information

Estimating the severity of COVID-19: Evidence from the Italian epicenter.

Publications

Estimating the severity of COVID-19: Evidence from the Italian epicenter.

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