Dung T. Tran, Yulu Chen, Yi Zheng, Julian Hecker, Daniel B. Hawcutt, Munir Pirmohamed, Jessica Lasky-Su, Ann C. Wu, Kelan G. Tantisira, Michael J. McGeachie, Scott T. Weiss, Amber Dahlin
{"title":"尿液代谢组学特征揭示了吸入皮质类固醇控制哮喘症状的儿童肾上腺抑制的新决定因素","authors":"Dung T. Tran, Yulu Chen, Yi Zheng, Julian Hecker, Daniel B. Hawcutt, Munir Pirmohamed, Jessica Lasky-Su, Ann C. Wu, Kelan G. Tantisira, Michael J. McGeachie, Scott T. Weiss, Amber Dahlin","doi":"10.1002/iid3.1315","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>Asthma is routinely treated with inhaled corticosteroids (ICS). Asthma patients on ICS are at increased risk of adrenal suppression, a potentially serious effect of long-term glucocorticoid exposure; however, this relationship is poorly understood. Therefore, this study aims to identify metabolite biomarkers related to adrenal suppression in asthma patients taking ICS.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>A total of 571 urine metabolites from 200 children with asthma on ICS in the Pharmacogenetics of Adrenal Suppression with Inhaled Steroids (PASS) cohort were profiled. Samples were grouped by peak plasma cortisol measurement as adrenal sufficient (>350 nmol/L) or insufficient (≤350 nmol/L) (outcome). Regression and discriminant-based statistical models combined with network analyses were utilized to assess relationships between metabolites and the outcome. Finally, prioritized metabolites were validated using data from an ancillary study of the Childhood Asthma Management (CAMP) cohort with similar characteristics to PASS.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>Ninety metabolites were significantly associated with adrenal suppression, of which 57 also could discriminate adrenal status. While 26 metabolites (primarily steroids) were present at lower levels in the adrenal insufficient patients, 14 were significantly elevated in this group; the top metabolite, mannitol/sorbitol, was previously associated with asthma exacerbations. Network analyses identified unique clusters of metabolites related to steroids, fatty acid oxidation, and nucleoside metabolism, respectively. Four metabolites including urocanic acid, acetylcarnitine, uracil, and sorbitol were validated in CAMP cohort for adrenal suppression.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>Urinary metabolites differ among asthma patients on ICS, by adrenal status. While steroid metabolites were reduced in patients with poor adrenal function, our findings also implicate previously unreported metabolites involved in amino acid, lipid, and nucleoside metabolism.</p>\n </section>\n </div>","PeriodicalId":13289,"journal":{"name":"Immunity, Inflammation and Disease","volume":null,"pages":null},"PeriodicalIF":3.1000,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/iid3.1315","citationCount":"0","resultStr":"{\"title\":\"Urine metabolomics signature reveals novel determinants of adrenal suppression in children taking inhaled corticosteroids to control asthma symptoms\",\"authors\":\"Dung T. Tran, Yulu Chen, Yi Zheng, Julian Hecker, Daniel B. Hawcutt, Munir Pirmohamed, Jessica Lasky-Su, Ann C. Wu, Kelan G. Tantisira, Michael J. McGeachie, Scott T. Weiss, Amber Dahlin\",\"doi\":\"10.1002/iid3.1315\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>Asthma is routinely treated with inhaled corticosteroids (ICS). Asthma patients on ICS are at increased risk of adrenal suppression, a potentially serious effect of long-term glucocorticoid exposure; however, this relationship is poorly understood. Therefore, this study aims to identify metabolite biomarkers related to adrenal suppression in asthma patients taking ICS.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>A total of 571 urine metabolites from 200 children with asthma on ICS in the Pharmacogenetics of Adrenal Suppression with Inhaled Steroids (PASS) cohort were profiled. Samples were grouped by peak plasma cortisol measurement as adrenal sufficient (>350 nmol/L) or insufficient (≤350 nmol/L) (outcome). Regression and discriminant-based statistical models combined with network analyses were utilized to assess relationships between metabolites and the outcome. Finally, prioritized metabolites were validated using data from an ancillary study of the Childhood Asthma Management (CAMP) cohort with similar characteristics to PASS.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>Ninety metabolites were significantly associated with adrenal suppression, of which 57 also could discriminate adrenal status. While 26 metabolites (primarily steroids) were present at lower levels in the adrenal insufficient patients, 14 were significantly elevated in this group; the top metabolite, mannitol/sorbitol, was previously associated with asthma exacerbations. Network analyses identified unique clusters of metabolites related to steroids, fatty acid oxidation, and nucleoside metabolism, respectively. Four metabolites including urocanic acid, acetylcarnitine, uracil, and sorbitol were validated in CAMP cohort for adrenal suppression.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusions</h3>\\n \\n <p>Urinary metabolites differ among asthma patients on ICS, by adrenal status. 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Urine metabolomics signature reveals novel determinants of adrenal suppression in children taking inhaled corticosteroids to control asthma symptoms
Background
Asthma is routinely treated with inhaled corticosteroids (ICS). Asthma patients on ICS are at increased risk of adrenal suppression, a potentially serious effect of long-term glucocorticoid exposure; however, this relationship is poorly understood. Therefore, this study aims to identify metabolite biomarkers related to adrenal suppression in asthma patients taking ICS.
Methods
A total of 571 urine metabolites from 200 children with asthma on ICS in the Pharmacogenetics of Adrenal Suppression with Inhaled Steroids (PASS) cohort were profiled. Samples were grouped by peak plasma cortisol measurement as adrenal sufficient (>350 nmol/L) or insufficient (≤350 nmol/L) (outcome). Regression and discriminant-based statistical models combined with network analyses were utilized to assess relationships between metabolites and the outcome. Finally, prioritized metabolites were validated using data from an ancillary study of the Childhood Asthma Management (CAMP) cohort with similar characteristics to PASS.
Results
Ninety metabolites were significantly associated with adrenal suppression, of which 57 also could discriminate adrenal status. While 26 metabolites (primarily steroids) were present at lower levels in the adrenal insufficient patients, 14 were significantly elevated in this group; the top metabolite, mannitol/sorbitol, was previously associated with asthma exacerbations. Network analyses identified unique clusters of metabolites related to steroids, fatty acid oxidation, and nucleoside metabolism, respectively. Four metabolites including urocanic acid, acetylcarnitine, uracil, and sorbitol were validated in CAMP cohort for adrenal suppression.
Conclusions
Urinary metabolites differ among asthma patients on ICS, by adrenal status. While steroid metabolites were reduced in patients with poor adrenal function, our findings also implicate previously unreported metabolites involved in amino acid, lipid, and nucleoside metabolism.
期刊介绍:
Immunity, Inflammation and Disease is a peer-reviewed, open access, interdisciplinary journal providing rapid publication of research across the broad field of immunology. Immunity, Inflammation and Disease gives rapid consideration to papers in all areas of clinical and basic research. The journal is indexed in Medline and the Science Citation Index Expanded (part of Web of Science), among others. It welcomes original work that enhances the understanding of immunology in areas including:
• cellular and molecular immunology
• clinical immunology
• allergy
• immunochemistry
• immunogenetics
• immune signalling
• immune development
• imaging
• mathematical modelling
• autoimmunity
• transplantation immunology
• cancer immunology