Obesity Is Associated with an Impaired Baseline Repertoire of Anti-Influenza Virus Antibodies.

Obesity is a risk factor for severe disease and mortality for both influenza and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. While previous studies show that individuals with obesity generate antibody responses following influenza vaccination, infection rates within the obese group were twice as high as those in the healthy-weight group. The repertoire of antibodies raised against influenza viruses following previous vaccinations and/or natural exposures is referred to here as baseline immune history (BIH). To investigate the hypothesis that obesity impacts immune memory to infections and vaccines, we profiled the BIH of obese and healthy-weight adults vaccinated with the 2010-2011 seasonal influenza vaccine in response to conformational and linear antigens. Despite the extensive heterogeneity of the BIH profiles in both groups, there were striking differences between obese and healthy subjects, especially with regard to A/H1N1 strains and the 2009 pandemic virus (Cal09). Individuals with obesity had lower IgG and IgA magnitude and breadth for a panel of A/H1N1 whole viruses and hemagglutinin proteins from 1933 to 2009 but increased IgG magnitude and breadth for linear peptides from the Cal09 H1 and N1 proteins. Age was also associated with A/H1N1 BIH, with young individuals with obesity being more likely to have reduced A/H1N1 BIH. We found that individuals with low IgG BIH had significantly lower neutralizing antibody titers than individuals with high IgG BIH. Taken together, our findings suggest that increased susceptibility of obese participants to influenza infection may be mediated in part by obesity-associated differences in the memory B-cell repertoire, which cannot be ameliorated by current seasonal vaccination regimens. Overall, these data have vital implications for the next generation of influenza virus and SARS-CoV-2 vaccines. IMPORTANCE Obesity is associated with increased morbidity and mortality from influenza and SARS-CoV-2 infection. While vaccination is the most effective strategy for preventing influenza virus infection, our previous studies showed that influenza vaccines fail to provide optimal protection in obese individuals despite reaching canonical correlates of protection. Here, we show that obesity may impair immune history in humans and cannot be overcome by seasonal vaccination, especially in younger individuals with decreased lifetime exposure to infections and seasonal vaccines. Low baseline immune history is associated with decreased protective antibody responses. Obesity potentially handicaps overall responses to vaccination, biasing it toward responses to linear epitopes, which may reduce protective capacity. Taken together, our data suggest that young obese individuals are at an increased risk of reduced protection by vaccination, likely due to altered immune history biased toward nonprotective antibody responses. Given the worldwide obesity epidemic coupled with seasonal respiratory virus infections and the inevitable next pandemic, it is imperative that we understand and improve vaccine efficacy in this high-risk population. The design, development, and usage of vaccines for and in obese individuals may need critical evaluation, and immune history should be considered an alternate correlate of protection in future vaccine clinical trials.

Obesity is associated with an altered baseline and post-vaccination influenza antibody repertoire.

As highlighted by the ongoing COVID-19 pandemic, vaccination is critical for infectious disease prevention and control. Obesity is associated with increased morbidity and mortality from respiratory virus infections. While obese individuals respond to influenza vaccination, what is considered a seroprotective response may not fully protect the global obese population. In a cohort vaccinated with the 2010-2011 trivalent inactivated influenza vaccine, baseline immune history and vaccination responses were found to significantly differ in obese individuals compared to healthy controls, especially towards the 2009 pandemic strain of A/H1N1 influenza virus. Young, obese individuals displayed responses skewed towards linear peptides versus conformational antigens, suggesting aberrant obese immune response. Overall, these data have vital implications for the next generation of influenza vaccines, and towards the current SARS-CoV-2 vaccination campaign.

Understanding differences between synthetic and natural antibodies can help improve antibody engineering.

Synthetic libraries are a major source of human-like antibody (Ab) drug leads. To assess the similarity between natural Abs and the products of these libraries, we compared large sets of natural and synthetic Abs using "CDRs Analyzer," a tool we introduce for structural analysis of Ab-antigen (Ag) interactions. Natural Abs, we found, recognize their Ags by combining multiple complementarity-determining regions (CDRs) to create an integrated interface. Synthetic Abs, however, rely dominantly, sometimes even exclusively on CDRH3. The increased contribution of CDRH3 to Ag binding in synthetic Abs comes with a substantial decrease in the involvement of CDRH2 and CDRH1. Furthermore, in natural Abs CDRs specialize in specific types of non-covalent interactions with the Ag. CDRH1 accounts for a significant portion of the cation-pi interactions; CDRH2 is the major source of salt-bridges and CDRH3 accounts for most hydrogen bonds. In synthetic Abs this specialization is lost, and CDRH3 becomes the main sources of all types of contacts. The reliance of synthetic Abs on CDRH3 reduces the complexity of their interaction with the Ag: More Ag residues contact only one CDR and fewer contact 3 CDRs or more. We suggest that the focus of engineering attempts on CDRH3 results in libraries enriched with variants that are not natural-like. This may affect not only Ag binding, but also Ab expression, stability and selectivity. Our findings can help guide library design, creating libraries that can bind more epitopes and Abs that better mimic the natural antigenic interactions.

Large-scale analysis of somatic hypermutations in antibodies reveals which structural regions, positions and amino acids are modified to improve affinity.

The principles of affinity maturation of antibodies (Abs), which underlies B cell-mediated immunity, are still under debate. It is unclear whether the antigen (Ag) binding site is a preferred target for mutations, and what the role of activation-induced deaminase (AID) hotspots is in this process. Here we report a structural analysis of 3495 residues that have been replaced through somatic hypermutations (SHMs) in 196 Abs. We show that there is no correlation between the propensity of an amino acid to be in AID hotspot and the probability that it is replaced during the SHM process. Although AID hotspots may be necessary to enable SHMs, they are not a major driving force in determining which residues are mutated. We identified Ab positions that are highly mutated and significantly affect binding. The effect of mutation on binding energy is a major factor in determining which structural regions of the Ab are mutated. There is a clear preference for mutations at the Ag-binding site. However, positions outside this region that also affect binding are often preferred targets for SHMs. As for amino acid preferences, a general trend during SHM is to make Ab-Ag interfaces more similar to protein-protein interfaces in general. In different regions of the Ab, there are different sets of preferences for amino acid substitution. This mapping improves our understanding of Ab affinity maturation and may assist in Ab engineering.

Computational identification of antigen-binding antibody fragments.

Determining which parts of the Ab are essential for Ag recognition and binding is crucial for understanding B cell-mediated immunity. Identification of fragments of Abs that maintain specificity to the Ag will also allow for the development of improved Ab-based therapy and diagnostics. In this article, we show that structural analysis of Ab-Ag complexes reveals which fragments of the Ab may bind the Ag on their own. In particular, it is possible to predict whether a given CDR is likely to bind the Ag as a peptide by analyzing the energetic contribution of each CDR to Ag binding and by assessing to what extent the interaction between that CDR and the Ag depends on other CDRs. To demonstrate this, we analyzed five Ab-Ag complexes and predicted for each of them which of the CDRs may bind the Ag on its own as a peptide. We then show that these predictions are in agreement with our experimental analysis and with previously published experimental results. These findings promote our understanding of the modular nature of Ab-Ag interactions and lay the foundation for the rational design of active CDR-derived peptides.