An Investigation of Omics for Bronchopulmonary Dypslasia

PROJECT SUMMARY Bronchopulmonary dysplasia (BPD) is the most common and serious complication of prematurity. Disruptions in lipid metabolism may be associated with respiratory complications in preterm infants but remain incompletely characterized. The lack of reproducible biochemical markers for BPD has limited the translational application of established and novel therapies. To address this gap, Aim 1 will identify distinct lipid and metabolomic profiles associated with the respiratory severity score at birth. Aim 2 will conduct longitudinal metabolomic profiling in preterms as part of the prospective Longitudinal Omics in Neonates (LION) study. Here we will identify metabolic trajectories over time in association with BPD cases and controls. Aim 3 will examine a subset of LION study patients at risk for severe BPD and receiving mechanical ventilation. Longitudinal tracheal aspirate samples obtained from this subcohort will be interrogated in multi-omic fashion for single-cell RNA sequencing and targeted lipidomics. Correlation and multi-omic analyses will link cellular programming events with lipidomic profiles. All aims rely on targeted and agnostic machine learning-based approaches while leveraging known biochemical mechanisms. Dr. Reiss is supported by a world-class mentoring and scientific advisory committee including experts in omics for maternal-child health (David K. Stevenson, Michael P. Snyder, Karl G. Sylvester), epidemiology (Gary M. Shaw), machine learning (Nima Aghaeepour), lipid biochemistry (Jonathan Z. Long, Camilia Martin), and developmental pulmonary biology and immunology (Lawrence S. Prince). The career development plan will complement the proposed scientific investigations by examining 1) Epidemiologic Methods & Analytic Approaches for Omics; 2) Lipid Metabolism and Biochemistry for Newborn Lung Health and Disease and 3) Single-cell RNA sequencing (scRNA-seq) in BPD. This award will leverage Dr. Reiss’s expertise in clinical metabolomics and machine learning for neonatal disease and build towards his long-term goal of becoming an independent physician-scientist using omic approaches to identify novel biomarkers and pathways for translational discovery in BPD.