Anti-glycan antibodies are an abundant subpopulation of serum antibodies with critical functions in many immune processes. Changes in the levels of these antibodies can occur with the onset of disease, exposure to pathogens, or vaccination. As a result, there has been significant interest in exploiting anti-glycan antibodies as biomarkers for many diseases. The serum contains a mixture of anti-glycan antibodies that can recognize the same antigen, and competition for binding can potentially influence the detection of antibody subpopulations that are more relevant to disease processes.
The most abundant antibody isotypes in serum are IgG, IgM, and IgA, but little is known about how these different isotypes compete for the same glucan antigen. In this study, we developed a multiplexed glucan microarray assay and applied it to assess how different isotypes of anti-glucan antibodies (IgA, IgG, and IgM) compete for the imprinted glycan antigens. While IgG and IgA antibodies generally outperform IgM for peptide or protein antigens, we found that IgM outperformed IgG and IgA on many glucan antigens.
To illustrate the importance of this effect, we provide evidence that IgM competition may explain the unexpected observation that IgG of certain antigenic specificities appears to be preferentially transported from mothers to fetuses. We show that IgM in maternal serum competes with IgG resulting in lower than expected IgG signals. Since cord blood contains very low levels of IgM, competition only affects maternal IgG signals, making it appear that certain IgG antibodies are higher in cord blood than matched maternal blood. Taken together, the results highlight the importance of competition for studies involving anti-glycan antibodies.
Human serum contains a wide variety of carbohydrate-binding antibodies that play a critical role in human health and provide a rich pool of potential biomarkers for many biomedical applications and diseases. For example, the detection of anti-glycan antibodies against blood group A and B antigens provides a simple and reliable strategy to predict which individuals are suitable for transfusion and transplantation. Anti-glycan antibodies are also crucial in other areas of immunology, such as tumor surveillance, autoimmunity, defense against pathogens, and response to vaccines.
These broader immune functions have stimulated interest in exploring the potential use of circulating anti-glycan antibodies as biomarkers for a wide variety of diseases. Detection of antiglycan antibodies in serum is typically carried out by immobilizing a carbohydrate of interest, capturing specific antibodies, and then measuring the amounts of bound antibodies.
This process is complicated by the fact that serum often contains a mixture of antibodies that recognize the same antigen, and certain antibodies within the mixture may be more relevant to immune protection or disease processes than others. Antibodies against a particular glycan can vary in terms of affinity, specificity, concentration, and/or isotype, but they can all compete to bind to the same antigen. As a result, the binding of one can influence the detection of the others, and it can be difficult to reliably measure a subpopulation of target antibodies of interest.
Our approach to assessing competence involved the use of purified IgG, IgA, and IgM antibodies from pooled human serum. Each polyclonal antibody sample would be profiled on our glycan microarray individually and in the presence of other isotypes. In addition, changes in IgG and IgM anti-glycan antibody signals would be assessed in whole serum after the addition of IgG, IgA, and IgM. Although IgD and IgE are also present in serum at low concentrations and capable of competing, this study focused on the most abundant antibodies in serum.