mSphere (Sep 2024)

Mapping disparities in viral infection rates using highly multiplexed serology

  • Alejandra Piña,
  • Evan A. Elko,
  • Rachel Caballero,
  • Morgan Metrailer,
  • Mary Mulrow,
  • Dan Quan,
  • Lora Nordstrom,
  • John A. Altin,
  • Jason T. Ladner

DOI
https://doi.org/10.1128/msphere.00127-24
Journal volume & issue
Vol. 9, no. 9

Abstract

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ABSTRACT 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 male/female and Hispanic/non-Hispanic White individuals.IMPORTANCEOur 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, and our approach for highly multiplexed serology (PepSeq) allows us to measure antibody responses against hundreds of viruses in an efficient and cost-effective manner.

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