Abstract
Early life respiratory microbiota may increase risk for future pulmonary disease. Associations between respiratory microbiota and lung health in children from low- and middle-income countries are not well-described. Leveraging the Ghana Randomized Air Pollution and Health Study (GRAPHS) prospective pregnancy cohort in Kintampo, Ghana, we collected nasopharyngeal swabs in 112 asymptomatic children aged median 4.3 months (interquartile range (IQR) 2.9, 7.1) and analyzed 22 common bacterial and viral pathogens with MassTag polymerase chain reaction (PCR). We prospectively followed the cohort and measured lung function at age four years by impulse oscillometry. First, we employed latent class analysis (LCA) to identify nasopharyngeal microbiota (NPM) subphenotypes. Then, we used linear regression to analyze associations between subphenotype assignment and lung function. LCA suggest that a two-class model best described the infant NPM. We identified a higher diversity subphenotype (N = 38, 34%) with more pathogens (median 4; IQR 3.25, 4.75) and a lower diversity subphenotype (N = 74, 66%) with fewer pathogens (median 1; IQR 1, 2). In multivariable linear regression models, the less diverse NPM subphenotype had higher small airway resistance (R5-R20 β = 17.9%, 95% CI 35.6, 0.23; p = 0.047) compared with the more diverse subphenotype. Further studies are required to understand the role of the microbiota in future lung health.