ABSTRACT Sleep disordered breathing (SDB), which includes sleep apnea and related disorders, is a highly prevalent disorder that increases the risk of cardiopulmonary, metabolic, and other diseases. Continuous positive airway pressure (CPAP), the most common treatment for SDB, remains suboptimal with poor patient adherence. Identifying genes contributing to physiologically relevant pathways will increase our understanding and aid in the discovery of improved countermeasures and more personalized treatments. As part of the PI’s ongoing K01 project, we assembled the largest known genetic study of objectively measured SDB and identified the first common- and rare-frequency genetic associations with SDB at genome-level significance. Literature searches indicate that many of our suspected genes in multiple associated regions are involved with pulmonary inflammation, suggesting that genes implicated in pulmonary inflammation may have an important but unmeasured causal role for the development of SDB (in addition to the known effects of SDB on inflammation). Simultaneously, our collaborators have identified associations between SDB and subclinical measures of interstitial lung disease defined by abnormalities in computed tomography images. SDB affects up to 88% of adults with idiopathic pulmonary fibrosis (IPF), and many of our suspected SDB genes are also implicated in IPF. The broad overlap of these genes suggests that pulmonary inflammation and injury may contribute to SDB through a common biological mechanism. The next logical steps in translating these genetic findings into broader biological insights are to systematically investigate the impact of inflammation on SDB and clarify if these potential effects are mediated by pulmonary or other effects. Candidate traits that influence SDB will be identified using polygenic risk scores derived from existing studies. The potential impact of these significant traits at specific genetic loci will be investigated using genetic colocalization. We will also identify genes that may be mediating these interactions using externally derived gene expression data in candidate tissues. Our specific aims are to: 1) to identify potential inflammation-related predictors of sleep disordered breathing severity; and 2) to identify potential pulmonary predictors of sleep disordered breathing severity. The proposed project is a natural extension of the PI’s K01 and will improve our understanding of the potential physiological and molecular mechanisms of sleep disordered breathing, a common disorder impacting millions of individuals.