PROJECT SUMMARY Further characterization of longitudinal lung function (LLF) throughout adulthood in asthmatics is critically important, as low lung function correlates with increased exacerbations, morbidity, and mortality. Precise genomic and metabolomic profiling of the biological mechanisms underlying LLF trajectories will be instrumental in understanding and ameliorating lung function deterioration. MicroRNAs (miRs; short non-coding RNAs) exhibit broad impact on inflammatory cascades, leading to airway remodeling and chronic airway obstruction, and specific metabolites provide a measure of real-time inflammatory changes that reflect both genetic and environmental influences. Therefore, the combined use of miRs and metabolites has great potential to provide critical insight into disease physiology and identify mechanisms to regulate, diagnose, and prognosticate LLF. The objective of this proposal is to identify miRNA and metabolomic determinants of LLF patterns, classified using longitudinal spirometry measures from electronic medical records (EMRs), that accurately identify individuals with asthma at the greatest risk of progression to more serious chronic lung obstruction. Our central hypothesis is that LLF trajectories are regulated by specific sets of genes, miRNAs, and metabolites that can 1) inform on underlying biological dysregulation and 2) serve as biomarkers to distinguish clinically actionable patterns of LLF, enabling personalized medicine approaches through the identification of multiomic therapeutic targets. We will explore this hypothesis by generating the novel and unique Biobank of Asthmatics with Longitudinal Lung Function (BALLF) cohort; which includes rigorous LLF phenotyping generated from electronic medical records (Aim 1a) and global metabolomics profiling and miRNA sequencing (Aim 1b) supplementing existing genetic and phenotypic data. We will identify metabolites (Aim2a) and miRNAs (Aim2b) associated with these LLF; capitalizing on our rich preliminary data implicating sphingolipid and eicosanoid biosynthesis to guide our analyses. Finally, we will leverage our extensive systems biology expertise to integrate this multiomic data to improve our biological understanding of LLF (Aim3a) and to develop clinically translatable biomarkers (Aim 3b). Crucially, we have the ability to both validate these findings and to assess their generalizability in two existing independent cohorts of asthmatics. This will represent the first integrative omic study of LLF trajectories in asthma focusing on the unique combination of miRs, metabolites, and genes; as such the findings of this innovative proposal have tremendous potential to elucidate the biological mechanisms of lung function decline and to influence the management of asthmatics at risk of this devastating complication.