Mapping disparities in viral infection rates using highly multiplexed serology

Despite advancements in medical interventions, the disease burden caused by viral pathogens remains large and highly diverse. This burden includes the wide range of signs and symptoms associated with active viral replication as well as a variety of clinical sequelae of infection. Moreover, there is growing evidence supporting the existence of sex- and ethnicity-based health disparities linked to viral infections and their associated diseases. Despite several well-documented disparities in viral infection rates, our current understanding of virus-associated health disparities remains incomplete. This knowledge gap can be attributed, in part, to limitations of the most commonly used viral detection methodologies, which lack the breadth needed to characterize exposures across the entire virome. Additionally, virus-related health disparities are dynamic and often differconsiderably through space and time. In this study, we utilize PepSeq, an approach for highly multiplexed serology, to broadly assess an individual's history of viral exposures, and we demonstrate the effectivenessof this approach for detecting infection disparities through a pilot study of 400 adults aged 30-60 in Phoenix, AZ. Using a human virome PepSeq library, we observed expected seroprevalence rates for several common viruses and detected both expected and previously undocumented differencesin inferred rates of infection between our male/female and Hispanic/non-Hispanic White individuals.