ABSTRACT Inhalation of electronically aerosolized vapors, or vaping, has grown substantially in the past decade. A recent outbreak of e-cigarette or vaping product use associated lung injury (EVALI) has raised concern for the public health impact of the behavior. Effects on the lung both acutely and chronically are not well-understood, and mechanisms of lung damage have not been fully elucidated. EVALI cases are in part thought to be due to in- halation of toxic chemicals, such as vitamin E acetate, contained within the diluent of the product; however, factors determining individual susceptibility to EVALI are unclear. Changes in the metabolic milieu of the lung could also alter the structure and function of the lung microbiome, further perpetuating injury. In preliminary studies, we have demonstrated alterations in the lung metabolome in EVALI patients compared to individuals with lung injury from other causes and to a healthy control and an HIV-infected individual with chronic vape use as well as alterations in pulmonary function with chronic vaping. In the current proposal, we will measure multi- ple parallel molecular and clinical datasets to test the hypothesis that interactions of the metabolome, microbi- ome, and the host are critical in development of injury secondary to e-vapor exposure. We will build a compre- hensive, systems-level model of the cellular and microbial milieu in the lung of subjects with chronic e-vapor exposure and from inpatients with acute EVALI to understand the transition from chronic exposure to acute injury. We will apply supervised and unsupervised machine learning algorithms to better understand and clas- sify features distinguishing acute vaping induced lung injury from non-vaping associated lung injury and from chronic lung injury related to e-vapor exposure. In addition, we will develop a novel ex vivo lung perfusion model that can be used for future mechanistic studies arising from our investigations. Leveraging the infra- structure within the Systems Biology of Diffusion Impairment in HIV study (R01HL140963), we have the oppor- tunity to examine a continuum of vaping and lung impairment including chronic vaping in a healthy population, chronic vaping in HIV+ individuals who may have enhanced susceptibility to vaping, and in patients with EVALI through the following aims: Aim 1: To identify causal molecular pathways underlying the host response to chronic e-vapor exposure by integrating clinical features and -omics data from ambulatory individuals. Aim 2: To identify predictive signatures of respiratory impairment from clinical features, transcriptomic, microbiome, and metabolomic data using clinical specimens from hospitalized individuals with EVALI. Aim 3: To develop a clinically relevant ex-vivo model of ENDD exposure to facilitate mechanistic investigation and evaluation of novel therapeutic interventions. This project will leverage existing resources to identify complex associations and causal relations...