ABSTRACT
Variants of concern (VOC) of SARS-CoV2 and waning immunity pose a serious global problem. Overall, vaccination and prior infection appear to provide significant protection to the majority of individuals, but some remain susceptible to infection and severe disease. Rigorously identifying a broad spectrum of correlates of protection (COP) is necessary to identify these susceptible populations. The extent to which additional booster doses provide protection is also poorly understood. To address this need, we conducted a multicenter prospective study assessing the association between serological profiles and the risk for SARS-CoV-2 infection, comparing those vaccinated with three to four doses of Pfizer BNT162b2 vaccine. Of 608 healthy adults, 365 received three doses and 243 received four doses. During the first 90 days of followup, 239 (39%) were infected, of whom 165/365 (45%) received 3 doses and 74/243 (30%) four doses. We found that the fourth dose elicited a significant rise in antibody binding and neutralizing titers against multiple variants, and reduced the risk of symptomatic infection by 37% [95% I, 15% - 54%]. We identified several parameters based on IgG and IgA binding that were COPs. The strongest association with infection risk was reduced IgG levels to RBD mutants and IgA levels to VOCs, which was a COP in the three-dose group (HR=6.34, p=0.008) and in the four-dose group (HR=8.14, p=0.018). A combination of two commercially available ELISA assays were also associated with protection in both groups (HR = 1.84, p = 0.002; HR = 2.01, p = 0.025, respectively). Most importantly, we identified a subset of individuals with low antibody levels after three doses of vaccine that responded with a significant boost in neutralizing antibody titers after a fourth dose, but were still at significantly increased susceptibility to infection when compared to those who had pre-existing high levels of neutralizing antibodies. Thus, we identify a highly susceptible population that remains susceptible despite apparent responsiveness to vaccines. Further, we develop several specific and sensitive COPs that show dramatic effect sizes and may be utilized to identify individuals most at risk from future exposures.
ABSTRACT
The COVID-19 pandemic is rapidly spreading throughout the world. Recent reports suggest that 10-30% of SARS-CoV-2 infected patients are asymptomatic. Other studies report that some subjects have significant viral shedding prior to symptom onset. Since both asymptomatic and pre-symptomatic subjects can spread the disease, identifying such individuals is critical for effective control of the SARS-CoV-2 pandemic. Therefore, there is an urgent need to increase diagnostic testing capabilities in order to also screen asymptomatic carriers. In fact, such tests will be routinely required until a vaccine is developed. Yet, a major bottleneck of managing the COVID-19 pandemic in many countries is diagnostic testing, due to limited laboratory capabilities as well as limited access to genome-extraction and Polymerase Chain Reaction (PCR) reagents. We developed P-BEST - a method for Pooling-Based Efficient SARS-CoV-2 Testing, using a non-adaptive group-testing approach, which significantly reduces the number of tests required to identify all positive subjects within a large set of samples. Instead of testing each sample separately, samples are pooled into groups and each pool is tested for SARS-CoV-2 using the standard clinically approved PCR-based diagnostic assay. Each sample is part of multiple pools, using a combinatorial pooling strategy based on compressed sensing designed for maximizing the ability to identify all positive individuals. We evaluated P-BEST using leftover samples that were previously clinically tested for COVID-19. In our current proof-of-concept study we pooled 384 patient samples into 48 pools providing an 8-fold increase in testing efficiency. Five sets of 384 samples, containing 1-5 positive carriers were screened and all positive carriers in each set were correctly identified. P-BEST provides an efficient and easy-to-implement solution for increasing testing capacity that will work with any clinically approved genome-extraction and PCR-based diagnostic methodologies.
