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Metabolomic profiling reveals extensive adrenal suppression due to inhaled corticosteroid therapy in asthma

Abstract

The application of large-scale metabolomic profiling provides new opportunities for realizing the potential of omics-based precision medicine for asthma. By leveraging data from over 14,000 individuals in four distinct cohorts, this study identifies and independently replicates 17 steroid metabolites whose levels were significantly reduced in individuals with prevalent asthma. Although steroid levels were reduced among all asthma cases regardless of medication use, the largest reductions were associated with inhaled corticosteroid (ICS) treatment, as confirmed in a 4-year low-dose ICS clinical trial. Effects of ICS treatment on steroid levels were dose dependent; however, significant reductions also occurred with low-dose ICS treatment. Using information from electronic medical records, we found that cortisol levels were substantially reduced throughout the entire 24-hour daily period in patients with asthma who were treated with ICS compared to those who were untreated and to patients without asthma. Moreover, patients with asthma who were treated with ICS showed significant increases in fatigue and anemia as compared to those without ICS treatment. Adrenal suppression in patients with asthma treated with ICS might, therefore, represent a larger public health problem than previously recognized. Regular cortisol monitoring of patients with asthma treated with ICS is needed to provide the optimal balance between minimizing adverse effects of adrenal suppression while capitalizing on the established benefits of ICS treatment.

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Fig. 1: Overall study design.
Fig. 2: Plasma steroid metabolite associations in EPIC-Norfolk cohort and MGBB-Asthma cohort.
Fig. 3: Quantification of cortisol in the EMR-Cortisol cohort.

Data availability

The EPIC-Norfolk data can be requested by bona fide researchers for specified scientific purposes via the study website (https://www.mrc-epid.cam.ac.uk/research/studies/epic-norfolk/). Requests for the other datasets can be made by researchers via a data use agreement for specific scientific inquiries. Datasets for the other cohorts are subject to controlled access. These restrictions apply because of the sensitive nature of patient data and the possibility of identifying individuals via the use of electronic medical records in conjunction with omic data. To create a data use agreement, contact the corresponding author. The corresponding author will respond to requests within 10 days.

Code availability

All code for data processing and analyses are available via GitHub at:

https://github.com/CDNMBioinformatics/PartnersBiobank_asthma_metabolomics

https://github.com/CDNMBioinformatics/RPDR

https://github.com/CDNMBioinformatics/RPDR_ACTH

https://github.com/CDNMBioinformatics/PEGASUS_Scripts

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Acknowledgements

The external funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Effort from P.K., J.A.L.S. and S.T.W. is supported by P01HL132825 from the National Heart, Lung, and Blood Institute, National Institutes of Health (NIH/NHLBI). I.D.S. is funded by the Medical Research Council (MC_UU_00006/1-Etiology and Mechanisms). Effort from R.K., D.I.S., M.C., K.M., M.S. and J.A.L.S. is supported by R01HL123915 from the NIH/NHLBI and W81XWH-17-1-0533 from the US Department of Defense. Effort from R.S.K. is supported by K01HL146980 from the NIH/NHLBI. Effort from S.H.C. is supported by K01HL153941 from the NIH/NHLBI. Effort from M.H. and J.A.L.S. is supported by R01HL141826 from the NIH/NHLBI. Effort from A.D. is supported by K01HL130629 from the NIH/NHLBI. Effort from A.D. and J.A.L.S. is supported by 1R01HL152244 from the NIH/NHLBI. Effort from M.M. and J.A.L.S. is supported by R01HL155742 from the NIH/NHLBI. Effort from H.K. is supported by the Jane and Aatos Erkko Foundation, the Paulo Foundation and the Pediatric Research Foundation. Effort from K.L.S. is supported by K08HL148178 from the NIH/NHLBI. Effort from M.M. is supported by R01HL139634 from the NIH/NHLBI. Effort from A.W. is supported by K23HL151819 from the NIH/NHLBI and the Thrasher Research Fund Award (15115). Effort from A.C.W. is supported by 1R01HD085993 from the National Institute of Child Health and Human Development. Effort from Y.V. is supported by K23AI130408 from the National Institute of Allergy and Infectious Diseases. Effort from J.A.L.S., S.T.W. and E.W.K. is supported by NIH U01HG008685. Effort from P.Z. and C.E.W. was supported by the Japan Society for the Promotion of Science KAKENHI Grant (JP19K21239), the Japanese Environment Research and Technology Development Fund (5-1752), the Gunma University Initiative for Advanced Research, the Japan-Sweden Research Cooperative Program between the Japan Society for the Promotion of Science and the Swedish Foundation for International Cooperation in Research and Higher Education (JPJSBP-1201854), the Swedish Heart Lung Foundation (HLF 20180290 and HLF 20200693) and the Swedish Research Council (2016-02798). The EPIC-Norfolk study (https://doi.org/10.22025/2019.10.105.00004) has received funding from the Medical Research Council (MR/N003284/1 MC-UU_12015/1 and MC_UU_00006/1) and Cancer Research UK (C864/A14136). Metabolite measurements in the EPIC-Norfolk study were supported by the MRC Cambridge Initiative in Metabolic Science (MR/L00002/1) and the Innovative Medicines Initiative Joint Undertaking under European Medical Information Framework grant agreement number 115372. We are grateful to all the participants who have been part of the project and to the many members of the study teams at the University of Cambridge who have enabled this research. We thank the staff and participants of the EPIC-Norfolk, Mass General Brigham Biobank and Childhood Asthma Management Program studies for their contributions. Figure 1 was created with BioRender (https://biorender.com/).

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Authors

Contributions

P.K. and I.D.S. had full access to the data and take responsibility for the data integrity and accuracy of the analysis. J.A.L.S. and C.L. contributed to conceptualization of the study. P.K. performed the quality control and statistical downstream data analyses for Mass General Brigham Biobank (MGBB) cohorts and comparison to the EPIC-Norfolk datasets. P.K. also performed the replication in the Childhood Asthma Management Program. I.D.S. performed the quality control and regression analysis for the EPIC-Norfolk cohort. M.S. contributed to the data pulls and acquisition from MGBB. A.W. contributed to ascertainment of the inhaled medications in MGBB. K.M. contributed to the downstream analyses. D.I.S. performed the cost-effectiveness analysis. P.K. and J.A.L.S. prepared the original draft of the manuscript. P.K., J.A.L.S., R.S.K., I.D.S., C.L., K.M., A.D., S.H.C., M.H., M.M., M.C., H.M.K., K.L.S., A.W., A.C.W., Y.V. and C.E.W. contributed to the statistical interpretation and critical revision of the manuscript. P.Z., C.E.W. and C.C. contributed to the metabolomic data generation. J.A.L.S., S.T.W., C.L., N.J.W. and E.W.K. contributed to funding acquisition. All authors reviewed the final manuscript.

Corresponding author

Correspondence to Jessica A. Lasky-Su.

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Nature Medicine thanks Daniel Hawcutt, Warwick Dunn, Mohsen Sadatsafavi and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Michael Basson was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

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Extended data

Extended Data Fig. 1 Plasma metabolites in EPIC-Norfolk cohort.

a. Manhattan plot of metabolites sorted by their pathways on x-axis and negative log10 of P-value on the y-axis. The cut off horizontal lines on the y-axis highlight the metabolites significantly associated with asthma outcome at a P-value <0.05 and at the Bonferroni threshold (n = 35 metabolites, P-value<5.14 × 10-5). The legend key shape and color show the direction of effect for the metabolites and the main pathway they belong to, respectively. b. Volcano Plot showing the effect size of the metabolites with OR on the x-axis and negative log10 of P-value on the y-axis. The metabolites colored in red are significant at a Bonferroni threshold of P-value<5.14 × 10-5. Multivariable logistic regression models were used to obtain odds ratio and p-values comparing asthma cases with controls (A, B).

Extended Data Fig. 2 Principal steroid hormone biosynthesis pathways with mineralocorticoid, glucocorticoid and androgen metabolites highlighting the replicated metabolites between EPIC-Norfolk cohort and Mass General Brigham Biobank.

Our annotated metabolites colored in red have been mapped to these pathways with their precursors or intermediates. Abbreviations: CRH: Corticotropin releasing hormone; ACTH: Adrenocorticotropic hormone.

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Supplementary Tables 1–6. Extended Data figures have been uploaded as separate files through the online portal as required in the checklist.

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Kachroo, P., Stewart, I.D., Kelly, R.S. et al. Metabolomic profiling reveals extensive adrenal suppression due to inhaled corticosteroid therapy in asthma. Nat Med 28, 814–822 (2022). https://doi.org/10.1038/s41591-022-01714-5

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