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Authors: Hou et al.

Link to paper: https://www.medrxiv.org/content/10.1101/2020.05.08.20095836v1

Journal/ Pre-Print: Pre-Print (medrxiv)

Tags: Immunology/Immunity, Proteomics

Research Highlights

1. Protein microarray performed to evaluate protein expression in patients with SARS-CoV-2 infection vs patients with similar symptoms that were negative

2. Differential expression of 125 proteins in the two groups, 88 up-regulated and 37 down-regulated

3. Pathway analysis demonstrated enrichment of CCL2- and CXCL10-mediated cytokine signalling pathways

Summary

The study involved patients who were SARS-CoV-2 positive (n=15) or negative (n=13), but displayed similar symptoms. Serum samples were analysed using a protein microarray to detect expression of 532 proteins, demonstrating 125 differential expression proteins (88 up-regulated and 37 down-regulated), part of which may serve as biomarkers for COVID-19 diagnosis. Further biological processes analysis showed an enrichment in immune responses upon infection, revealing the dysregulation of cytokine-mediated signalling. Differentially-expressed proteins were also correlate with clinical indices, adding knowledge to the prognosis of COVID-19.

Impact for SARS-CoV2/COVID19 research efforts

Understand the immune response to SARS-CoV2/COVID19

Understand the virology and/or cell biology of SARS-CoV2/COVID19

Study Type

· Clinical Cohort study (e.g. drug trials) & Proteomics

Antibody microarray to test patient serum

Strengths and limitations of the paper

Novelty: Microarray to investigate proteomics of patients with SARS-CoV-2

Standing in the field: Relatively consistent with expected results and previous data

Appropriate statistics:

No sample size calculation. Protein expression in the two groups compared by a t test, however in such a small group a Mann Whitney test, or other tests not based on normal distribution, would have been better, and there should have been an adjustment for multiple hypothesis testing. Statistical methods for the correlation of proteins with clinical indices are not reporte.

Viral model used: N/a

Translatability:

Needs confirmation in further studies, but could the biomarkers may have potential for clinical use, either in diagnostics or prognostics.

Main limitations:

· Limitations in stats as reported above. Small sample size.

· The study involved targeted proteomics. This type of study would be more useful if there were patients with mild vs severe disease, in a large cohort, to use these biomarkers as prognostic indicators.

· Lastly, the method suggests that the ‘influenza group’ were patients that were negative for SARS-CoV-2 RNA, however it is not clear if they were tested for influenza. Also, as it has mentioned in the discussion, the study needs more comprehensive comparison to healthy subjects and COVID-19 patients over the entire course of infection.