Longitudinal Analysis of Biologic Correlates of COVID-19 Resolution: Case Report

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1. Version published to 10.3389/fmed.2022.915367

   Jun 15, 2022
2. 

   ScreenIT

   Feb 6, 2022

   SciScore for 10.1101/2022.02.03.22269612: (What is this?)

   Please note, not all rigor criteria are appropriate for all manuscripts.

   Table 1: Rigor

   Ethics	IRB: Subject Recruitment: All study activities were approved by the Rutgers Institutional Review Board (Pro2020000655). Consent: Informed consent was obtained from the patient in her 50’s (51-55 age range, Caucasian, female) and a relative in their 46-50 age range (Caucasian, male).
   Sex as a biological variable	Informed consent was obtained from the patient in her 50’s (51-55 age range, Caucasian, female) and a relative in their 46-50 age range (Caucasian, male).
   Randomization	not detected.
   Blinding	not detected.
   Power Analysis	not detected.
   Cell Line Authentication	not detected.

   Table 2: Resources

   Antibodies
   Sentences	Resources
   HRP-conjugated mouse anti-human IgG1, IgG2, IgG3, and IgG4 (Southern Biotech, …

   SciScore for 10.1101/2022.02.03.22269612: (What is this?)

   Please note, not all rigor criteria are appropriate for all manuscripts.

   Table 1: Rigor

   Ethics	IRB: Subject Recruitment: All study activities were approved by the Rutgers Institutional Review Board (Pro2020000655). Consent: Informed consent was obtained from the patient in her 50’s (51-55 age range, Caucasian, female) and a relative in their 46-50 age range (Caucasian, male).
   Sex as a biological variable	Informed consent was obtained from the patient in her 50’s (51-55 age range, Caucasian, female) and a relative in their 46-50 age range (Caucasian, male).
   Randomization	not detected.
   Blinding	not detected.
   Power Analysis	not detected.
   Cell Line Authentication	not detected.

   Table 2: Resources

   Antibodies
   Sentences	Resources
   HRP-conjugated mouse anti-human IgG1, IgG2, IgG3, and IgG4 (Southern Biotech, Birmingham, AL, USA) secondary antibodies were used at 1:2,000 dilution.	anti-human IgG1 suggested: None IgG2, IgG3 suggested: None IgG4 suggested: None
   To monitor depletion of antigen-specific antibodies prior to use in neutralization assays, antigen-specific IgG titers of untreated and absorbed samples were determined as described above.	antigen-specific suggested: None antigen-specific IgG suggested: None
   Experimental Models: Cell Lines
   Sentences	Resources
   Cell lines: Vero E6 were obtained from the American Type Culture Collection (ATCC) (Manassas, VA, USA); HeLa cells stably expressing ACE2 (HeLa-ACE2) were obtained from Dennis Burton at the Scripps Research Institute 57.	HeLa suggested: None
   Propagation of viral stocks was performed with Vero E6 cells using DMEM supplemented with 2% FBS.	Vero E6 suggested: RRID:CVCL_XD71)
   SARS-CoV-2 neutralization assay: HeLa-Ace2 cells were seeded in 96-well black optical-bottom plates at a density of 1 × 104 cells/well in FluoroBrite DMEM (Thermo Fisher Scientific, Waltham, MA, USA) containing 4% FBS (Seradigm, Radnor, PA, USA), 2mM L-glutamine, and 1% penicillin/streptomycin (Corning, NY, USA), and incubated overnight at 37°C with 5% CO2.	HeLa-Ace2 suggested: JCRB Cat# JCRB1845, RRID:CVCL_B3LW)
   The Human Premixed Multi-Analyte Kits were used to detect 48 cytokine/chemokines (CD40L, EGF, Eotaxin, FGF-2, LT-3L, Fractalkine, G-CSF, GROa, IFNα2, IFNγ, IL-1α, IL-1β, IL-1RA, IL-2, IL3, IL-4, IL-5, IL-6, IL-7, IL8, IL-9, IL-10, IL-12 (p40), IL-12 (p70), IL-13, IL-15, IL17A, IL-17E, IL-17F, IL-18, IL-22, IL-27, IP-10, MCP-1, MCP3, M-CSF, MDC, MIG, MIP-1α, MIP-1β, PDGF-AA, PDGF-AB, RANTES, TGFα, TNFα, TNFβ, VEGF-A) according to the manufacturer’s recommendations.	MCP-1 suggested: None
   Software and Algorithms
   Sentences	Resources
   Proteomics: Proteomic analysis was performed by the Rutgers Biological Mass Spectrometry Facility.	Rutgers Biological suggested: None
   Peak lists were generated using Proteome Discoverer 2.2 and data were searched using a local implementation of the Global Proteome Machine 62.	Proteome Discoverer suggested: (Proteome Discoverer, RRID:SCR_014477)
   Hierarchical clustering analysis and principal component analysis were performed in MATLAB on the standardized cytokine and protein expression measurements using custom scripts.	MATLAB suggested: (MATLAB, RRID:SCR_001622)
   MAST package (version 1.8.2) 67 were to identify differential expressing genes across different cell populations.	MAST suggested: (MAST, RRID:SCR_016340)

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   Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

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   Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:

   Our case study has limitations. One is the study of a single patient. The particular characteristics of the case patient, including the underlying immune dysfunction, undoubtedly played a role in both the clinical outcome of the convalescent plasma donation and the ways in which disease resolution occurred. However, most of our findings are corroborated by the rapidly evolving knowledge of the pathways associated with COVID-19 disease and its severity. Thus, we are reasonably confident that our findings are applicable beyond the particular patient under study. Moreover, our report of COVID-19 resolution in a patient unable to generate humoral responses to SARS-CoV-2 infection, together with a previous report of convalescent plasma-associated resolution of COVID-19 in a patient with humoral immunodeficiency 18, strongly supports the use of well-characterized convalescent plasma for therapeutic use in COVID-19 patients who are immunocompromised due to underlying defects or immunosuppressive therapies. A second limitation of our work lies in our inability -- despite multiple attempts -- to access the plasma obtained from the first, anonymous donor, which had no beneficial effect on the recipient’s disease. A comparison between the two sets of convalescent plasma samples might have shed light on key therapeutic properties of convalescent plasma for COVID-19. Thirdly, we do not know which organ/cell(s) the viral transcripts we detected in plasma are derived from. Care of the patie...

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   Results from TrialIdentifier: We found the following clinical trial numbers in your paper:
   

   Identifier	Status	Title
   NCT04391309	Recruiting	COVID-19 and Anti-CD14 Treatment Trial

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   Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

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   Results from JetFighter: We did not find any issues relating to colormaps.

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   Results from rtransparent:

   • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
   • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
   • No protocol registration statement was detected.

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   Results from scite Reference Check: We found no unreliable references.

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3. 

   Version published to 10.1101/2022.02.03.22269612 on medRxiv

   Feb 3, 2022