Chen, Y

Dahlin, A

Hawcutt, DB

Hecker, J

Lasky-Su, JA

Mcgeachie, M

Pirmohamed, M

Tantisira, K

Tran, DT

Weiss, ST

Wu, AC

University of Liverpool Repository

Urinary metabolite signatures are associated with low cortisol levels in children taking inhaled corticosteroids (ICS).  Dung Tran, MS, PhD1, Yulu Chen PhD1, Daniel B Hawcutt MD2, Munir Pirmohamed MD2, Jessica Lasky-Su, PhD1, Ann C. Wu, MD1,3, Kelan Tantisira, MD, MPH4, Michael McGeachie PhD1, Scott T.Weiss, MD, MS1, and Amber Dahlin, PhD, MMSc1.Author Affiliations1Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA USA2University of Liverpool, Liverpool, UKFunding: NHLBI R01 HL152244 HL 155742RationaleAsthma is among the most common chronic diseases routinely treated with inhaled corticosteroids (ICS). Over 30% of asthma patients taking ICS are at increased risk of adrenal suppression, a potentially serious side effect of long-term glucocorticoid exposure; however, this relationship is not well understood. We performed a metabolomics study to identify molecular factors related to cortisol levels in asthma patients taking ICS.MethodsMetabolomic profiling was performed on 200 urine samples from the Pharmacogenetics of Adrenal Suppression with Inhaled Steroids (PASS) cohort (114 males, 86 females), comprising pediatric asthma patients on ICS. Samples were grouped according to plasma cortisol levels, based on peak plasma cortisol measurement following Synacthen test, as normal (>350 nmol/L) or low (≦350 nmol/L). Untargeted metabolomics profiling, conducted by Metabolon Inc., identified 984 metabolites of which 571 metabolites were selected for analysis. Logistic regression was utilized to evaluate associations between metabolites and cortisol levels, then Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) were performed to validate the results. Synthetic Minority Over-sampling Technique (SMOTE) was utilized to improve balance between comparison groups. Classification models were fitted by 1000 SMOTE runs and model statistics (p-values or variable importance in projection (VIP)) were aggregated using their medians. Network analysis was conducted to quantify relationships among metabolites. ResultsNinety metabolites (45.6% lipids; 31.1% amino acids) demonstrated significant associations (FDR < 0.05) with cortisol levels in logistic regression models. OPLS-DA models clearly separated low vs. normal cortisol groups with 57 metabolites (VIP >1.5), among which 56 confirmed results from logistic regression models. Twenty-six of the 90 metabolites present at significantly lower levels in the low cortisol subjects were annotated to major adrenal steroid hormone biosynthesis sub-pathways. Fourteen metabolites were significantly elevated in low cortisol subjects; the top metabolite, mannitol/sorbitol, was previously associated with exacerbations in asthma patients on ICS. Network analyses also identified two highly correlated clusters of steroid and nucleoside metabolites, respectively; N4-acetylcytidine, carnitine, and pregnen-diol-sulfate represented hubs within the unique clusters.ConclusionsUrinary metabolite profiles differ among asthma patients with low vs. normal cortisol levels. We identified a potential link between circulating cortisol levels and urine metabolites participating in amino acid, nucleoside, and lipid metabolism. Multiple adrenal corticosteroids and their metabolites exhibited significant decreases in the low cortisol group, consistent with reduced adrenal function. Ongoing work to replicate and integrate metabolite signatures with other ‘omic’ data will help clarify the impact of ICS exposure on adrenocortical function in asthma patients.

Urinary Metabolite Signatures Are Associated With Low Cortisol Levels in Children Taking Inhaled Corticosteroids

http://livrepository.liverpool.ac.uk/3176613/1/ATS_abstract_TRAN_revised.docx

Urinary Metabolite Signatures Are Associated With Low Cortisol Levels in Children Taking Inhaled Corticosteroids

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