Prevalence of SARS-CoV-2 in hemoglobinopathies is modified by age and race

• Type of Material: Article
• Authors: Jennifer Frediani, Emory University; Ezra Pak-Harvey, Emory University; Richard Parsons, Emory University; Adrianna L. Westbrook, The Atlanta Center for Microsystems-Engineered Point-of-Care Technologies; William O'Sick, Emory University; Gregory Martin, Emory University; Wilbur Lam, Emory University; Joshua Levy, Emory University
• Language: English
• Date: 2023-09-01
• Publisher: Elsevier
• Publication Version: Final Published Version
• Copyright Statement: © 2023 Elsevier Inc. All rights reserved.
• Final Published Version (URL): http://dx.doi.org/10.1016/j.bcmd.2023.102756
• Title of Journal or Parent Work: Blood Cells, Molecules, and Diseases
• Volume: 102
• Start Page: 102756
• End Page: 102756
• Grant/Funding Information: This work was supported by RADx [Grant/Award Number: U54 EB027690 02S1, U54 EB027690 03S1, U54EB027690 03S2 UL1 TR002378].
• Keywords: Humans; Sickle cell disease; Prevalence; COVID-19 Testing; Adolescent; United States; COVID-19; SARS-CoV-2; Hemoglobinopathies; Cross-Sectional Studies; Anemia, Sickle Cell; Hemoglobinopathy
• Research Categories: Biology, Virology; Biology, Cell

Abstract

Prior literature has established a positive association between sickle cell disease and risk of contracting SARS-CoV-2. Data from a cross-sectional study evaluating COVID-19 testing devices (n = 10,567) was used to examine the association between underlying health conditions and SARS-CoV-2 infection in an urban metropolis in the southern United States. Firth's logistic regression was used to fit the model predicting SARS-CoV-2 positivity using vaccine status and different medical conditions commonly associated with COVID-19. Another model using the same method was built using SARS-CoV-2 positivity as the outcome and hemoglobinopathy presence, age (<16 Years vs. ≥16 Years), race/ethnicity and comorbidities, including hemoglobinopathy, as the factors. Our first model showed a significant association between hemoglobinopathy and SARS-CoV-2 infection (OR: 2.28, 95 % CI: (1.17,4.35), P = 0.016). However, in the second model, this association was not maintained (OR: 1.35, 95 % CI: (0.72,2.50), P = 0.344). We conclude that the association between SARS-CoV-2 positivity and presence of hemoglobinopathies like sickle cell disease is confounded by race, age, and comorbidity status. Our results illuminate previous findings by identifying underlying clinical/demographic factors that confound the reported association between hemoglobinopathies and SARS-CoV-2. These findings demonstrate how social determinants of health may influence disease manifestations more than genetics alone.