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Authors: Wei. et al.

Link to paper:

Journal/ Pre-Print: CellPress

Tags: Bioinformatics, Immunology/Immunity, Clinical, Inflammation

Research Highlight

1. Single-cell RNA sequencing and immunophenotype profiling of COVID-19 patient peripheral blood mononuclear cells (PBMCs) pre-ICU, during ICU and post-ICU.

2. ICU stage was marked by a strong antiviral response, IFN-I response and cytokine signalling and showed an increase in monocyte expansion and a decrease in T and B cells.


In this study, PBMCs from four patients with confirmed COVID-19 infection were isolated for single-cell RNA sequencing. Patient samples were taken either before (N=2), during (N=4), and/or after (N=4) ICU admission. Three out of four patients in ICU were found to have increased monocyte expansion but reduced T and B cell levels. Likewise, viral RNA sensors, type I interferon signature genes and IFN-a (but not IFN- β) serum levels were found to be elevated during ICU stage. Out of 42 cytokines and cytokine receptors detected, none showed significantly higher RNA levels during ICU admission, and serum IL-6 was not elevated

Impact for SARS-CoV2/COVID19 Research Efforts

· Understand the immune response to SARS-CoV2/COVID19:

Strong monocyte signature and lymphopenia at the peak of the disease

Induction of type-I IFN

· Clinical symptoms and pathogenesis of SARS-Cov2/COVID19

Heightened IFN-a at the ICU stage of treatment

IFN-b levels stable throughout the disease course

Study Type

· In silico study / bioinformatics study

· Patient Case study

Strengths and Limitations of the Paper

Novelty: A number of papers have used scRNA-sequencing for immune cell profiling of COVID-19 patients, but few have looked at expression levels of intracellular sensors linked to the type I interferon response with patient samples pre-ICU, ICU, and post-ICU.

Standing in the field: Supports the growing body of evidence showing the importance of IFN-I in anti-SARS-CoV2 response as well as the expanded innate immune response in severe cases with concomitant lymphocytopenia.

Appropriate statistics: Difficult to judge without having access to quality control metrics but commonly used scRNA-sequencing and downstream analysis libraries were used: Seurat and pheatmap.

Viral model used: N/A

Translatability: Gives insight into the immunopathogenesis of COVID-19 but is not directly translatable to the clinic.

Main limitations:

· Underlying data not yet deposited in public databases

· No controls - patients not treated in ICU/milder cases

· Patients had different medication regimes

· No viral load measured to correlate with IFN-I levels and treatment stage

· Researchers debate the elevation of cytokines in severe disease based on expression data from PBMCs without serum level measurements and without mild case controls. Three of the patients were given arbidol and two chloroquine, both drugs modulate cytokine production.

· Cytokine response ontology enriched in ICU stage but only IL-6 and type I IFN were measured in the serum.

· Constrained by number of patients (4)

· Missing pre-ICU data for patients 3 and 4 Cross-patient comparison is constrained by patient underlying conditions, age and sex. Subjects were:

· Elderly female – no co-existing medical condition

· Elderly male – gout

· Young female – no co-existing medical condition

· Elderly male – co-existing conditions include hypertension and hyperglycaemia

· Use of obscure terminology such as “inactivated monocyte” (one of the clusters in scRNAseq)