[K08] Metabolomic and multi-omic predictors of inhaled corticosteroid response in obese and non-obese asthma

Ente: National Heart Lung and Blood Institute

Scadenza: 2031-05-31

Importo max: $163,414

Paese: US

Descrizione

PROJECT SUMMARY Inhaled corticosteroids (ICS) are the backbone of asthma therapy, however as many as 35% of patients do not have adequate treatment response to ICS. Poor ICS response is most prevalent in high-risk groups including non-White populations and those with obesity. These groups also experience the highest morbidity and exacerbation rates among those with asthma. Because mechanisms driving treatment response are unknown, we cannot prospectively develop optimal treatment regimens for patients. Understanding metabolomic differences in treatment response is a powerful tool to disentangle complex genetic and environmental processes in populations that are disproportionately affected by treatment non-response and increased asthma burden. The goal of this project is to identify metabolite profiles that predict ICS response and understand genetic contributions of these metabolic traits in a high-risk, understudied asthma population. I hypothesize that there will be distinct metabolite profiles that include arginine, oxylipin, and other oxidative stress pathways associated with ICS response and that ICS response in patients with increasing BMI will be associated with proline and polyamines, and that these metabolites will colocalize with known loci associated with ICS response. This project will be accomplished in three specific aims: Specific Aim 1: Identify metabolite profiles associated with ICS response. Specific Aim 2: Integrate genetic and metabolomic data to identify metabolite quantitative trait loci (mtQTL) to understand the genetic basis of metabolites associated with ICS response. Specific Aim 3: Develop a metabolite prediction model for ICS response using machine learning approaches in a diverse asthma population. I will use metabolomic, oxylipin, and genetic data from the Best African American Response to Asthma Drugs (BARD) clinical trial, a four-way randomized crossover trial in adults and children with asthma and self-identified Black race. I will perform targeted metabolomic analysis of arginine metabolites and oxylipins and untargeted metabolomics serum to identify pathways associated with ICS response. Using existing genetic data, I will identify mtQTLs to understand the genetic contribution to novel and pre-specified metabolites associated with ICS treatment response. I will examine how obesity modifies these metabolite profiles and mtQTLs to identify mechanisms in this high-risk group. Finally, I will quantify novel and pre-specified metabolites in the BARD cohort and two additional asthma clinical trials, SIENA and STICS. I will use machine learning approaches to develop a prediction model for ICS response using metabolites and clinical data with stratification by cohort to evaluate for heterogeneity of prediction model by cohort composition. The anticipated outcomes of this project are (1) to gain a deeper understanding of the metabolic pathways and genetic factors that affect ICS response, and (2) to complete a rigorous Istituzione: UNIVERSITY OF COLORADO DENVER PI: Meghan Dolan Althoff Progetto: 1K08HL183790-01

Settori: National Heart Lung and Blood Institute

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