ABSTRACT Chronic obstructive pulmonary disease (COPD) affects 300 million people and is the third leading cause of death globally, with >80% of these deaths occurring in low- and middle-income countries (LMICs). LMICs, particularly those in sub-Saharan Africa, are also home to over two thirds of the global population of people with HIV (PWH). HIV increases the risk of COPD and COPD-associated mortality, but the mechanisms underlying this risk are incompletely understood, which in turn limits our ability to identify PWH at the highest risk of developing COPD. Elucidating mechanisms that lead to COPD in PWH in LMICs is particularly important, as an estimated one third of COPD cases in LMICs are not attributable to known COPD risk factors. Systemic inflammation is associated with disease severity in COPD and impaired lung function in PWH, but it is unknown if inflammatory pathways affecting lung function in PWH are distinct from those in people without HIV. Furthermore, most data on inflammation in PWH and impaired lung function were generated by measuring a limited number of cytokines, which yields an incomplete picture of the inflammatory pathways involved. Microbial communities in the lung, gut, and oral cavity are also altered in patients with COPD and data from the US suggest a causal link between the microbiome and COPD among PWH. Host-microbe interactions likely explain the association between microbiome alterations and COPD in PWH, but these interactions are not fully understood, particularly in LMIC populations that face the greatest COPD-associated morbidity and mortality. Using my experience with microbiome analysis and the pulmonary research infrastructure I built in Botswana, I will incorporate shotgun metagenomic sequencing of multiple microbial communities (saliva, sputum, stool), host transcriptomics, and untargeted metabolomics to characterize the effect of host-microbiome interactions on pulmonary function in a longitudinal cohort of adults with and without HIV in Botswana. I will collect clinical, demographic, and spirometry data from 500 adults with chronic respiratory symptoms (250 PWH, 250 HIV-uninfected) and will then collect specimens and spirometry every six months for 24 months in a stratified random sample of 200 adults. Specimens will be shipped to Duke University for DNA and RNA sequencing and mass-spectrometry based metabolomics in advanced core facilities. I will use advanced statistical methods that incorporate machine learning to identify unique host pathways associated with microbiome composition in PWH and COPD and develop and validate a predictive model to identify PWH and COPD. This proposal will advance our understanding of how host-microbiome interactions affect inflammation and pulmonary function in PWH, thus addressing a key priority for the National Heart, Lung, and Blood Institute. Furthermore, this proposal will establish a clinical cohort and robust biorepository that, coupled with our findings, will supp...