Relationship of SARS-CoV-2–specific CD4 response to COVID-19 severity and impact of HIV-1 and tuberculosis coinfection
Catherine Riou, … , Robert J. Wilkinson, on behalf of the HIATUS consortium
Catherine Riou, … , Robert J. Wilkinson, on behalf of the HIATUS consortium
Published May 4, 2021
Citation Information: J Clin Invest. 2021;131(12):e149125. https://doi.org/10.1172/JCI149125.
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Research Article AIDS/HIV COVID-19

Relationship of SARS-CoV-2–specific CD4 response to COVID-19 severity and impact of HIV-1 and tuberculosis coinfection

Abstract

T cells are involved in control of coronavirus disease 2019 (COVID-19), but limited knowledge is available on the relationship between antigen-specific T cell response and disease severity. Here, we used flow cytometry to assess the magnitude, function, and phenotype of SARS coronavirus 2–specific (SARS-CoV-2–specific) CD4+ T cells in 95 hospitalized COVID-19 patients, 38 of them being HIV-1 and/or tuberculosis (TB) coinfected, and 38 non–COVID-19 patients. We showed that SARS-CoV-2–specific CD4+ T cell attributes, rather than magnitude, were associated with disease severity, with severe disease being characterized by poor polyfunctional potential, reduced proliferation capacity, and enhanced HLA-DR expression. Moreover, HIV-1 and TB coinfection skewed the SARS-CoV-2 T cell response. HIV-1–mediated CD4+ T cell depletion associated with suboptimal T cell and humoral immune responses to SARS-CoV-2, and a decrease in the polyfunctional capacity of SARS-CoV-2–specific CD4+ T cells was observed in COVID-19 patients with active TB. Our results also revealed that COVID-19 patients displayed reduced frequency of Mycobacterium tuberculosis–specific CD4+ T cells, with possible implications for TB disease progression. These results corroborate the important role of SARS-CoV-2–specific T cells in COVID-19 pathogenesis and support the concept of altered T cell functions in patients with severe disease.

Authors

Catherine Riou, Elsa du Bruyn, Cari Stek, Remy Daroowala, Rene T. Goliath, Fatima Abrahams, Qonita Said-Hartley, Brian W. Allwood, Nei-Yuan Hsiao, Katalin A. Wilkinson, Cecilia S. Lindestam Arlehamn, Alessandro Sette, Sean Wasserman, Robert J. Wilkinson, on behalf of the HIATUS consortium

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Figure 1

Measures of COVID-19 disease severity.

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Measures of COVID-19 disease severity. (A) An unsupervised 2-way hierarc...
(A) An unsupervised 2-way hierarchical cluster analysis (HCA, Ward’s method) was employed to grade COVID-19 disease, using the WHO ordinal scale scoring, Roche Elecsys anti–SARS-CoV-2 antibody cutoff index, WCC, CRP, D-dimer, ferritin, LDH, and radiographic evidence of disease extent expressed as percentage of unaffected lung. COVID-19 status (COVID-19 cases in red and SARS-CoV-2–uninfected hospitalized controls in blue) and outcome (survived in white and deceased in black) of each patient is indicated at the top of the dendrogram. Data are depicted as a heatmap colored from minimum to maximum values detected for each parameter. (B) Constellation plot-cluster analysis based on all measured parameters. Each dot represents a participant and is color-coded according to his or her COVID-19 status. Each cluster obtained for the HCA is identified by a number. (C) Principal component analysis (PCA) on correlations, based on the 8 clinical parameters, was used to explain the variance of the data distribution in the cohort. Each dot represents a participant. The 2 axes represent principal components 1 (PC1) and 2 (PC2). Their contribution to the total data variance is shown as a percentage. (D) Loading plot showing how each parameter influences PC1 and PC2 values. (E) Comparison of PC1 score values between COVID-19 cases who survived and those who died. Bars represent medians. Statistical comparisons were calculated using the nonparametric Mann-Whitney U test. Only participants with complete clinical data were included in the analysis (n = 79 COVID-19 patients and n = 25 hospitalized controls).