Probabilistic approaches for classifying highly variable anti-SARS-CoV-2 antibody responses

Antibody responses vary widely between individuals1, complicating the correct classification of low-titer measurements using conventional assay cut-offs. We found all participants in a clinically diverse cohort of SARS-CoV-2 PCR+ individuals (n=105), and n=33 PCR+ hospital staff, to have detectable IgG specific for pre-fusion-stabilized spike (S) glycoprotein trimers, while 98% of persons had IgG specific for the receptor-binding domain (RBD). However, anti-viral IgG levels differed by several orders of magnitude between individuals and were associated with disease severity, with critically ill patients displaying the highest anti-viral antibody titers and strongest in vitro neutralizing responses. Parallel analysis of random healthy blood donors and pregnant women (n=1,000) of unknown serostatus, further demonstrated highly variable IgG titers amongst seroconverters, although these were generally lower than in hospitalized patients and included several measurements that scored between the classical 3 and 6SD assay cut-offs. Since the correct classification of seropositivity is critical for individual- and population-level metrics, we compared different probabilistic algorithms for their ability to assign likelihood of past infection. To do this, we used tandem anti-S and -RBD IgG responses from our PCR+ individuals (n=138) and a large cohort of historical negative controls (n=595) as training data, and generated an equal-weighted learner from the output of support vector machines and linear discriminant analysis. Applied to test samples, this approach provided a more quantitative way to interpret anti-viral titers over a large continuum, scrutinizing measurements overlapping the negative control background more closely and offering a probability-based diagnosis with potential clinical utility. Especially as most SARS-CoV-2 infections result in asymptomatic or mild disease, these platform-independent approaches improve individual and epidemiological estimates of seropositivity, critical for effective management of the pandemic and monitoring the response to vaccination.