The UNC Chapel Hill Superfund Research Program (UNC-SRP)

摘要

ABSTRACT The Data Management and Analysis Core (DMAC) provides critical support for University of North Carolina (UNC)-Superfund Research Program (SRP) researchers to manage and analyze data related to the theme, “Identifying novel methods to reduce inorganic arsenic (iAs) exposure and elucidating mechanisms underlying iAs-induced metabolic dysfunction with a vision for disease prevention.” Across the globe and in the United States, there is an urgent need to identify the factors that increase susceptibility to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-induced coronavirus disease (COVID-19) and interventions to reduce disease. We propose herein a study which will begin to address some of these questions as well as build capacity to answer further questions regarding environmental contributions to viral-induced disease. In this administrative supplement, we build upon the activities in the DMAC and propose to address the fundamental knowledge gap in understanding environmental contributions to the COVID-19 burden in both NC and the US more generally as well as build tools to address these questions. In NC, communities are at risk of exposure to toxic substances known to affect the immune system. As an example, with millions of individuals on private wells in NC, there is significant concern that communities are exposed to toxic levels of inorganic arsenic (iAs), a known immunosuppressant. In addition to exposure to these chemical toxicants, communities are faced with exposure to social stressors such as neighborhood violence, unemployment, and poverty. These social stressors have also been shown to have physiologic effects on the immune system. Additionally, the synergistic effects of chemical and social stressors is becoming increasingly clear. These combined exposures may disproportionately impact the health of individuals who have reduced immune system function such as those suffering with obesity, those with chronic medical conditions, and the elderly. As a major output of this study, we propose the development of the NC Environmental Scan web portal (NC ENVIRO-SCAN) that will integrate key datasets of iAs, social stressors, and COVID-19 information to be able to identify communities with increased risk of infection and disease outcome. The central hypothesis of this research is that individuals living in areas where exposure to iAs and social stressors are high will have increased COVID-19 disease burden. This hypothesis is based on findings in our laboratories as well as the published literature. The three aims in the supplement include: (1) Evaluate the association between exposure to iAs, social stressors and COVID-19 disease risk in NC; (2) Identify resiliency factors that protect against COVID-19 disease risk; (3) Develop the NC ENVIRO-SCAN web portal and disseminate results to key stakeholders in NC. This study is novel in its investigation of combined effects of toxic substances (iAs), social stressors, and COVID-19 disease risk. It has the potential to improve public health in NC and protect populations from the harms of chemically-enhanced disease risk.