Evidence map›Paper›PMID 32908997›Full record

ArticlemedRxiv : the preprint server for health sciences2020

Serological Responses to Human Virome Define Clinical Outcomes of Italian Patients Infected with SARS-CoV-2.

Limin Wang, Julián Candia, Lichun Ma, Yongmei Zhao, Luisa Imberti, Alessandra Sottini, Kerry Dobbs, NIAID-NCI COVID Consortium, Andrea Lisco, Irini Sereti and 3 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Limin WangLaboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland 20892.
Julián CandiaLaboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland 20892.
Lichun MaLaboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland 20892.
Yongmei ZhaoCCR-SF Bioinformatics Group, Advanced Biomedical and Computational Sciences, Frederick National Laboratory for Cancer Research, 8560 Progress Drive, Frederick, Maryland 21701.
Luisa ImbertiCREA Laboratory, Diagnostic Department, ASST Spedali Civili di Brescia, Brescia, Italy.
Alessandra SottiniCREA Laboratory, Diagnostic Department, ASST Spedali Civili di Brescia, Brescia, Italy.
Kerry DobbsLaboratory of Clinical Immunology and Microbiology, National Institute of Allergy and Infectious Diseases, Bethesda, Maryland 20892.
NIAID-NCI COVID Consortium
Andrea LiscoLaboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, Bethesda, Maryland 20892.
Irini SeretiLaboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, Bethesda, Maryland 20892.
Helen C SuLaboratory of Clinical Immunology and Microbiology, National Institute of Allergy and Infectious Diseases, Bethesda, Maryland 20892.
Luigi D NotarangeloLaboratory of Clinical Immunology and Microbiology, National Institute of Allergy and Infectious Diseases, Bethesda, Maryland 20892.
Xin Wei WangLaboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland 20892.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the pandemic respiratory infectious disease COVID-19. However, clinical manifestations and outcomes differ significantly among COVID-19 patients, ranging from asymptomatic to extremely severe, and it remains unclear what drives these disparities. Here, we studied 159 hospitalized Italian patients with pneumonia from the NIAID-NCI COVID-19 Consortium using a phage-display method to characterize circulating antibodies binding to 93,904 viral peptides encoded by 1,276 strains of human viruses. SARS-CoV-2 infection was associated with a marked increase in individual's immune memory antibody repertoires linked to trajectories of disease severity from the longitudinal analysis also including anti-spike protein antibodies. By applying a machine-learning-based strategy, we developed a viral exposure signature predictive of COVID-19-related disease severity linked to patient survival. These results provide a basis for understanding the roles of memory B-cell repertoires in COVID-19-related symptoms as well as a predictive tool for monitoring its clinical severity.

Identifiers

PMID32908997
PMCPMC7480049

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.