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.

FLU-LISA (fluorescence-linked immunosorbent assay): high-throughput antibody profiling using antigen microarrays.

Vaccination and natural infection both elicit potent humoral responses that provide protection from subsequent infections. The immune history of an individual following such exposures is in part encoded by antibodies. While there are multiple immunoassays for measuring antibody responses, the majority of these methods measure responses to a single antigen. A commonly used method for measuring antibody responses is ELISA-a semiquantitative assay that is simple to perform in research and clinical settings. Here, we present FLU-LISA (fluorescence-linked immunosorbent assay)-a novel antigen microarray-based assay for rapid high-throughput antibody profiling. The assay can be used for profiling immunoglobulin (Ig) G, IgA and IgM responses to multiple antigens simultaneously, requiring minimal amounts of sample and antigens. Using several influenza and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antigen microarrays, we demonstrated the specificity and sensitivity of our novel assay and compared it with the traditional ELISA, using samples from mice, chickens and humans. We also showed that our assay can be readily used with dried blood spots, which can be collected from humans and wild birds. FLU-LISA can be readily used to profile hundreds of samples against dozens of antigens in a single day, and therefore offers an attractive alternative to the traditional ELISA.

Efficient high-throughput SARS-CoV-2 testing to detect asymptomatic carriers.

Recent reports suggest that 10 to 30% of severe acute respiratory syndrome coronavirus 2 (SARS- CoV-2) infected patients are asymptomatic and that viral shedding may occur before symptom onset. Therefore, there is an urgent need to increase diagnostic testing capabilities to prevent disease spread. We developed P-BEST, a method for Pooling-Based Efficient SARS-CoV-2 Testing, which identifies all positive subjects within a set of samples using a single round of testing. Each sample is assigned into multiple pools using a combinatorial pooling strategy based on compressed sensing. We pooled sets of 384 samples into 48 pools, providing both an eightfold increase in testing efficiency and an eightfold reduction in test costs, while identifying up to five positive carriers. We then used P-BEST to screen 1115 health care workers using 144 tests. P- BEST provides an efficient and easy-to-implement solution for increasing testing capacity that can be easily integrated into diagnostic laboratories.