RESUMO
Despite tremendous efforts by the international research community to understand the pathophysiology of SARS-CoV-2 infection, the reasons behind the clinical variability, ranging from asymptomatic infection to lethal disease, are still unclear. Existing inter-individual variations of the immune responses, due to environmental exposures and genetic factors, may be critical to the development or not of symptomatic disease after infection with SARS-CoV-2, and transcriptomic differences marking such responses may be observed even later, after convalescence. Herein, we performed genome-wide transcriptional whole-blood profiling to test the hypothesis that immune response-related gene signatures may differ between healthy individuals with prior entirely asymptomatic versus clinical SARS-CoV-2 infection, all of which developed an equally robust antibody response. Among 12.789 protein-coding genes analyzed, there were only six and nine genes with significantly decreased or increased expression, respectively, in those with prior asymptomatic infection (n=17, mean age 34 years) relatively to those with clinical infection (n=15, mean age 37 years). All six genes with decreased expression (IFIT3, IFI44L, RSAD2, FOLR3, PI3, ALOX15), are involved in innate immune response while the first two are interferon-induced proteins. Among genes with increased expression six are involved in immune response (GZMH, CLEC1B, CLEC12A), viral mRNA translation (GCAT), energy metabolism (CACNA2D2) and oxidative stress response (ENC1). Notably, 8/15 differentially expressed genes are regulated by interferons. Our results suggest that an intrinsically weaker expression of some innate immunity-related genes may be associated with an asymptomatic disease course in SARS-CoV-2 infection. Whether a certain gene signature predicts, or not, those who will develop a more efficient immune response upon exposure to SARS-CoV-2, with implications for prioritization for vaccination, warrant further study.
RESUMO
More than 300 SARS-COV-2 serological tests have recently been developed using either the nucleocapsid phosphoprotein (N), the spike glycoprotein subunit (S1), and more recently the receptor binding domain (RBD). Most of the assays report very good clinical performance characteristics in well-controlled clinical settings. However, there is a growing belief that good performance characteristics that are obtained during clinical performance trials might not be sufficient to deliver good diagnostic results in population-wide screens that are usually characterized with low seroprevalence. In this paper, we developed a serological assay against N, S1 and RBD using a bead-based multiplex platform and a rules-based computational approach to assess the performance of single and multi-antigen readouts in well-defined clinical samples and in a population-wide serosurvey from blood donors. Even though assays based on single antigen readouts performed similarly well in the clinical samples, there was a striking difference between the antigens on the population-wide screen. Asymptomatic individuals with low antibody titers and sub-optimal assay specificity might contribute to the large discrepancies in population studies with low seroprevalence. A multi-antigen assay requiring partial agreement between RBD, N and S1 readouts exhibited enhanced specificity, less dependency on assay cut-off values and an overall more robust performance in both sample settings. Our data suggest that assays based on multiple antigen readouts combined with a rules-based computational consensus can provide a more robust platform for routine antibody screening. One Sentence SummaryClinical and Population-level performance of single and multiplex SARS-CoV-2 serological assays.
