Abstract
PURPOSE: The human antibody repertoire forms in response to infections, the microbiome, vaccinations, and environmental exposures. The specificity of such antibody responses was compared among a cohort of toddlers to identify differences between seropositive versus seronegative responses. METHODS: An assessment of the serum IgM and IgG antibody reactivities in 197 toddlers of 1- and 2-years of age was performed with a microfluidic array containing 110 distinct antigens. Longitudinal profiling was done from years 1 to 2. Seropositivity to RNA and DNA viruses; bacteria; live attenuated, inactive, and subunit vaccines; and autoantigens was compared. A stratification was developed based on quantitative variations in the IgG responses. Clinical presentations and previously known genetic risk alleles for various immune system conditions were investigated in relation to IgG responses. RESULTS: IgG reactivities stratified toddlers into low, moderate, and high responder groups. The high group (17%) had elevated IgG responses to multiple RNA and DNA viruses (e.g., respiratory syncytial virus, Epstein-Barr virus, adenovirus, Coxsackievirus) and this correlated with increased responses to live attenuated viral vaccines and certain autoantigens. This high group was more likely to be associated with gestational diabetes and an older age. Genetic analyses identified polymorphisms in the IL2RB, TNFSF4, and INS genes in two high responder individuals that were associated with their elevated cytokine levels and clinical history of eczema and asthma. CONCLUSION: Serum IgG profiling of toddlers reveals correlations between the magnitude of the antibody responses towards viruses, live attenuated vaccines, and certain autoantigens. A low responder group had much weaker responses overall, including against vaccines. The serum antibody screen also identifies individuals with IgG responses to less common infections (West Nile virus, parvovirus, tuberculosis). The characterization of the antibody responses in combination with the identification of genetic risk alleles provides an opportunity to identify children with increased risk of clinical disease.