Reappearance of Effector T Cells Predicts Successful Recovery from COVID-19

Authors: Odak et al.

Link to paper: https://doi.org/10.1101/2020.05.11.20096263

Journal/ Pre-Print: MedRxiv

Tags: Clinical, Immunology/Immunity

Research Highlights

1. Compared to healthy controls (HC), both mild-disease (MD) and severe-disease (SD) COVID19 patients show general lymphopenia and a reduced Treg cell numbers. Lower numbers of NK, NKT, γδ-, and CD8+ T cells in the blood of COVID-19 patients with SD but not in MD

2. Decrease in the proportion of memory/effector CD4 T cells in SD compared to MD patients

3. Convalescing patients (comprised of both MD and SD patients) show decrease in naïve and increase in effector/memory and central memory CD4 and CD8 T cell

Summary 

The authors assess T cell responses in the blood of COVID-19 patients, which they propose to be used as a potential prognostic biomarker. A general lymphopenia was observed with reduced numbers of Treg cells. They observed low numbers of NK, NKT, γδ-, and CD8+ cells in SD but not MD patients. SD patients showed reduced memory/effector CD4 T cells; MD patients, however, had increased effector/memory CD8 T cell frequencies. Both groups showed increased frequencies of naïve gdT cells. By comparing to a follow-up sample, convalescing patients (comprised of both MD and SD patients) showed a decrease in naïve and increase in effector/memory and central memory CD4 and CD8 T cells.

Impact for SARS-CoV2/COVID19 research efforts

The findings help us to understand the immune response to SARS-CoV2/COVID19, and provide further confirmation of reduced T cell numbers in COVID-19.

Study Type

· Clinical Cohort study

Strengths and limitations of the paper

Novelty:

· Authors probe γδ T cells which haven’t been widely studied and follow up some patients to check recovery. They also split T cells into naïve/effector and central memory

· Reasonable number of patients and attempts to match controls

· Use of 11-color flow cytometric panels approved for clinical diagnostics

Standing in the field: d ecrease in lymphocyte cell counts in the blood of COVID-19 patients has been described. The authors have previously published on T cells and viral infection.

Appropriate statistics:

· Two-tailed student t test or Mann-Whitney U test were used to analyse the different groups, not clear which tests were used for which data.

· Did not state whether they check for normal distribution in order to perform a two-tailed student t test.

· No correction for multiple comparisons was performed.

· No statistical analysis performed comparing variables (e.g. co-morbidities) between the healthy, mild and severe groups (but do state no statistical difference in age and gender in SD vs MD patients)

Viral model used: Blood of SARS-CoV-2 positive patients

Translatability: Currently hard to translate; spread of data makes it hard to use the determined parameters to classify patients into severity groups upon admission

Main limitations:

· Study was performed on blood samples and did not include tissue-derived and antigen-specific T cell responses

· Very varied time of sampling after symptom onset and convalescence follow-up (first sampling 2-32 days after symptom onset)

· In the flow cytometry panel: no report of an Fc block as well as live-dead marker in counts panel according to table of Abs and gating strategy. It would have been informative to see plots side-by-side for comparison of healthy vs mild vs severe and/or paired samples for recovery. It appears that the comparison between memory and naïve T cells was performed on non-Tregs only.

· Th subsets are not classified according to chemokine receptors and/or transcription factors and cytokine expression and no functional readouts or activation status of T cells

· It would be useful to compare counts from cytometer to diagnostic counts used in other studies, especially since they claim to be proving biomarker utility

· No follow up samples on healthy controls, so difficult to know natural variability caused by sampling on different days, and differing duration between the 2 samples from one patient

· Non-convalescing group seems to be very skewed by a couple of patients, with many looking the same as convalescing patients