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 differ considerably 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 effectiveness of 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 differences in inferred rates of infection between our Hispanic White and non-Hispanic White individuals. Importance Our understanding of population-level virus infection rates and associated health disparities is incomplete. In part, this is because of the high diversity of human-infecting viruses and the limited breadth and sensitivity of traditional approaches for detecting infection events. Here, we demonstrate the potential for modern, highly-multiplexed antibody detection methods to greatly increase our understanding of disparities in rates of infection across subpopulations (e.g., different sexes or ethnic groups). The use of antibodies as biomarkers allows us to detect evidence of past infections over an extended period of time, and our approach for highly-multiplexed serology (PepSeq) allows us to measure antibody responses against 100s of viruses in an efficient and cost-effective manner. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work was supported by the National Institute on Minority Health and Health Disparities of the National Institutes of Health under Award Number U54MD012388 and the State of Arizona Technology and Research Initiative Fund (TRIF, administered by the Arizona Board of Regents, through Northern Arizona University). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This study was reviewed and approved by the Valleywise Health and NAU Institutional Review Boards (approval number 1545420). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes