Virological and immunological features of SARS-CoV-2-infected children who develop neutralizing antibodies

Abstract

As the global COVID-19 pandemic progresses, it is paramount to gain knowledge on adaptive immunity to SARS-CoV-2 in children to define immune correlates of protection upon immunization or infection. We analyzed anti-SARS-CoV-2 antibodies and their neutralizing activity (PRNT) in 66 COVID-19-infected children at 7 (±2) days after symptom onset. Individuals with specific humoral responses presented faster virus clearance and lower viral load associated with a reduced in vitro infectivity. We demonstrated that the frequencies of SARS-CoV-2-specific CD4⁺CD40L⁺ T cells and Spike-specific B cells were associated with the anti-SARS-CoV-2 antibodies and the magnitude of neutralizing activity. The plasma proteome confirmed the association between cellular and humoral SARS-CoV-2 immunity, and PRNT⁺ patients show higher viral signal transduction molecules (SLAMF1, CD244, CLEC4G). This work sheds lights on cellular and humoral anti-SARS-CoV-2 responses in children, which may drive future vaccination trial endpoints and quarantine measures policies.

Keywords: Ab-mediated neutralization activity; COVID-19; SARS-CoV-2; anti-SARS-CoV-2 antibodies; antigen-specific B cells; antigen-specific CD4 T cells; pediatric COVID-19; proteomic profiling.

Graphical abstract

Figure 1

SARS-CoV-2-specific IgG and Ab neutralization activities were inversely associated with viral load, virus clearance, and infectivity (A–E) Correlation plots show in (A) association between ddPCR and SARS-CoV-2 IgG titers (n = 21); (B) association between ddPCR and PRNT (n = 29); (C) association between infectivity in vitro (FFU) and SARS-CoV-2 IgG titers (n = 17); (D) association between infectivity in vitro (FFU) and PRNT (n = 24); and (E) association between SARS-CoV-2 IgG and SARS-CoV-2 RNA copies/mL (AUC) (n = 16). Solid lines define linear regression, and grey areas show 95% confidence interval. Non-parametric Spearman correlation was used in (A)–(E). Non-parametric Mann-Whitney test was used in (F), means with SD are shown in the plot. AUC, area under the curve; ddPCR, digital droplet PCR; FFU, foci forming unit; NP, nasopharyngeal swab. Light purple triangles, SARS-CoV-2 IgG⁺; light green triangles, SARS-CoV-2 IgG⁻; light purple solid circle, PRNT⁺; light green solid circle, PRNT⁻.

Figure 2

SARS-CoV-2-specific B cells are positively associated with anti-SARS-CoV-2 IgG and Ab neutralization activity (A) Gating strategy for antigen-specific B cells. (B and C) SARS-CoV-2 Mann-Whitney test (n = 28); means and SD are shown in the plots. Light purple triangles, SARS-CoV-2 IgG⁺; light green triangles, SARS-CoV-2 IgG⁻; light purple solid circle, PRNT⁺; light green solid circle, PRNT⁻.

Figure 3

SARS-CoV-2-specific CD4 T cells are positively associated with SARS-CoV-2-specific IgG and Ab-neutralization activity (A) Gating strategy for antigen-specific T cells (CD40L⁺). Left-side panels show CD40L⁺CD4⁺ T cells for unstimulated (UN) and stimulated (STIM) samples in a healthy control (HC). Right-side panels show the same conditions for a SARS-CoV-2-infected patient. (B and C) Twenty-eight patients split according to SARS-CoV-2 IgG (B) and PRNT (C) were compared by the Mann-Whitney test; means and SD are shown in the plots. Light purple triangles, SARS-CoV-2 IgG⁺; light green triangles, SARS-CoV-2 IgG⁻; light purple solid circle, PRNT⁺; light green solid circle, PRNT⁻.

Figure 4

Proteomic analysis revealing distinct patterns in patients with differential anti-SARS-CoV-2 Ab-neutralization activity (A–D) Non-parametric Mann-Whitney test was used to compare proteomics analysis of 7 PRNT⁻, 21 PRNT, and 15 HC; means and SD are shown in the plots. (E and F) Correlation analysis between PRNT (E) and SARS-CoV-2 IgG versus SLAMF1 (F, n = 28). Non-parametric Spearman correlation test was used in (E) and (F); solid lines define linear regression, and grey area shows 95% confidence interval. Light purple solid circle, PRNT⁺; light green solid circle, PRNT⁻; gray solid circle, HC.

Figure 5

Multiomics factor analysis (MOFA) showing clusterization factors of patients with Ab-neutralization activity (A) Fraction of variance explained by 7 latent factors is shown for 28 patients. (B) Samples distributed across the top 6 latent factors. (C and D) Top contributing features and loading direction (+ and −) for factor 3 in B cell (C) and T cell (D) populations. AM, activated memory; CM, central memory; DN, double negative; EM, effector memory; RM, resting memory; TEMRA, terminally differentiated effector memory; TLM, tissue-like memory.