The Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, Arizona, USA.
Valleywise Health, Phoenix, Arizona, USA.
mSphere. 2024 Sep 25;9(9):e0012724. doi: 10.1128/msphere.00127-24. Epub 2024 Aug 20.
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.
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, 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.
尽管医学干预措施取得了进步,但由病毒病原体引起的疾病负担仍然很大且高度多样化。这种负担包括与病毒复制有关的广泛的体征和症状,以及感染的各种临床后果。此外,越来越多的证据支持与病毒感染及其相关疾病有关的基于性别的健康差异和种族差异的存在。尽管病毒感染率存在一些有据可查的差异,但我们对与病毒相关的健康差异的认识仍然不完整。这一知识差距部分归因于最常用的病毒检测方法存在局限性,这些方法缺乏全面描述整个病毒组暴露情况的广度。此外,与病毒相关的健康差异是动态的,通常在空间和时间上有很大的不同。在这项研究中,我们利用 PepSeq (一种高度多重化的血清学方法)广泛评估个体的病毒暴露史,并通过在亚利桑那州凤凰城的 400 名 30-60 岁成年人中进行的一项试点研究,展示了这种方法检测感染差异的有效性。使用人类病毒组 PepSeq 文库,我们观察到几种常见病毒的预期血清阳性率,并检测到我们的男性/女性和西班牙裔/非西班牙裔白人个体之间感染率推断的预期和以前未记录的差异。
我们对人群中病毒感染率和相关健康差异的理解并不完整。部分原因是感染人类的病毒高度多样化,以及传统检测感染事件的方法的广度和灵敏度有限。在这里,我们展示了现代、高度多重化的抗体检测方法有很大的潜力,可以大大提高我们对亚人群(例如不同性别或种族群体)感染率差异的理解。抗体作为生物标志物可以让我们检测到过去感染的证据,并可以在很长一段时间内检测到,我们的高度多重化血清学方法( PepSeq )可以以高效和具有成本效益的方式测量针对数百种病毒的抗体反应。