Identification of human glucocorticoid response markers using integrated multi-omic analysis from a randomized crossover trial
Background: Glucocorticoids are among the most commonly prescribed drugs, but there is no biomarker that can quantify their action. The aim of the study was to identify and validate circulating biomarkers of glucocorticoid action. Methods: In a randomized, crossover, single-blind, discovery study, 1...
| Main Authors: | , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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eLife Sciences Publications Ltd
2021-04-01
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| Series: | eLife |
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| Online Access: | https://elifesciences.org/articles/62236 |
| _version_ | 1811235775878004736 |
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| author | Dimitrios Chantzichristos Per-Arne Svensson Terence Garner Camilla AM Glad Brian R Walker Ragnhildur Bergthorsdottir Oskar Ragnarsson Penelope Trimpou Roland H Stimson Stina W Borresen Ulla Feldt-Rasmussen Per-Anders Jansson Stanko Skrtic Adam Stevens Gudmundur Johannsson |
| author_facet | Dimitrios Chantzichristos Per-Arne Svensson Terence Garner Camilla AM Glad Brian R Walker Ragnhildur Bergthorsdottir Oskar Ragnarsson Penelope Trimpou Roland H Stimson Stina W Borresen Ulla Feldt-Rasmussen Per-Anders Jansson Stanko Skrtic Adam Stevens Gudmundur Johannsson |
| author_sort | Dimitrios Chantzichristos |
| collection | DOAJ |
| description | Background: Glucocorticoids are among the most commonly prescribed drugs, but there is no biomarker that can quantify their action. The aim of the study was to identify and validate circulating biomarkers of glucocorticoid action.
Methods: In a randomized, crossover, single-blind, discovery study, 10 subjects with primary adrenal insufficiency (and no other endocrinopathies) were admitted at the in-patient clinic and studied during physiological glucocorticoid exposure and withdrawal. A randomization plan before the first intervention was used. Besides mild physical and/or mental fatigue and salt craving, no serious adverse events were observed. The transcriptome in peripheral blood mononuclear cells and adipose tissue, plasma miRNAomic, and serum metabolomics were compared between the interventions using integrated multi-omic analysis.
Results: We identified a transcriptomic profile derived from two tissues and a multi-omic cluster, both predictive of glucocorticoid exposure. A microRNA (miR-122-5p) that was correlated with genes and metabolites regulated by glucocorticoid exposure was identified (p=0.009) and replicated in independent studies with varying glucocorticoid exposure (0.01 ≤ p≤0.05).
Conclusions: We have generated results that construct the basis for successful discovery of biomarker(s) to measure effects of glucocorticoids, allowing strategies to individualize and optimize glucocorticoid therapy, and shedding light on disease etiology related to unphysiological glucocorticoid exposure, such as in cardiovascular disease and obesity.
Funding: The Swedish Research Council (Grant 2015-02561 and 2019-01112); The Swedish federal government under the LUA/ALF agreement (Grant ALFGBG-719531); The Swedish Endocrinology Association; The Gothenburg Medical Society; Wellcome Trust; The Medical Research Council, UK; The Chief Scientist Office, UK; The Eva Madura’s Foundation; The Research Foundation of Copenhagen University Hospital; and The Danish Rheumatism Association.
Clinical trial number: NCT02152553. |
| first_indexed | 2024-04-12T11:57:49Z |
| format | Article |
| id | doaj.art-2fd4e8ec41fc4f27b347cd69da834ac2 |
| institution | Directory Open Access Journal |
| issn | 2050-084X |
| language | English |
| last_indexed | 2024-04-12T11:57:49Z |
| publishDate | 2021-04-01 |
| publisher | eLife Sciences Publications Ltd |
| record_format | Article |
| series | eLife |
| spelling | doaj.art-2fd4e8ec41fc4f27b347cd69da834ac22022-12-22T03:33:57ZengeLife Sciences Publications LtdeLife2050-084X2021-04-011010.7554/eLife.62236Identification of human glucocorticoid response markers using integrated multi-omic analysis from a randomized crossover trialDimitrios Chantzichristos0https://orcid.org/0000-0002-1660-1973Per-Arne Svensson1Terence Garner2Camilla AM Glad3Brian R Walker4https://orcid.org/0000-0002-2416-1648Ragnhildur Bergthorsdottir5Oskar Ragnarsson6Penelope Trimpou7Roland H Stimson8https://orcid.org/0000-0002-9002-6188Stina W Borresen9Ulla Feldt-Rasmussen10Per-Anders Jansson11Stanko Skrtic12Adam Stevens13https://orcid.org/0000-0001-8335-4143Gudmundur Johannsson14Department of Internal Medicine and Clinical Nutrition, Institute of Medicine at Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Endocrinology, Diabetology and Metabolism, Sahlgrenska University Hospital, Gothenburg, SwedenDepartment of Molecular and Clinical Medicine, Institute of Medicine at Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Institute of Health and Care Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, SwedenDivision of Developmental Biology & Medicine, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United KingdomDepartment of Internal Medicine and Clinical Nutrition, Institute of Medicine at Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Endocrinology, Diabetology and Metabolism, Sahlgrenska University Hospital, Gothenburg, SwedenClinical and Translational Research Institute, Newcastle University, Newcastle upon Tyne, United Kingdom; BHF/University Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, United KingdomDepartment of Internal Medicine and Clinical Nutrition, Institute of Medicine at Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Endocrinology, Diabetology and Metabolism, Sahlgrenska University Hospital, Gothenburg, SwedenDepartment of Internal Medicine and Clinical Nutrition, Institute of Medicine at Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Endocrinology, Diabetology and Metabolism, Sahlgrenska University Hospital, Gothenburg, SwedenDepartment of Internal Medicine and Clinical Nutrition, Institute of Medicine at Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Endocrinology, Diabetology and Metabolism, Sahlgrenska University Hospital, Gothenburg, SwedenBHF/University Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, United KingdomDepartment of Medical Endocrinology and Metabolism, Copenhagen University Hospital, Copenhagen, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, DenmarkDepartment of Medical Endocrinology and Metabolism, Copenhagen University Hospital, Copenhagen, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, DenmarkWallenberg Laboratory, Department of Molecular and Clinical Medicine, Institute of Medicine at Sahlgrenska Academy, University of Gothenburg, Gothenburg, SwedenDepartment of Internal Medicine and Clinical Nutrition, Institute of Medicine at Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Innovation Strategies and External Liaison, Pharmaceutical Technologies and Development, Gothenburg, SwedenDivision of Developmental Biology & Medicine, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United KingdomDepartment of Internal Medicine and Clinical Nutrition, Institute of Medicine at Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Endocrinology, Diabetology and Metabolism, Sahlgrenska University Hospital, Gothenburg, SwedenBackground: Glucocorticoids are among the most commonly prescribed drugs, but there is no biomarker that can quantify their action. The aim of the study was to identify and validate circulating biomarkers of glucocorticoid action. Methods: In a randomized, crossover, single-blind, discovery study, 10 subjects with primary adrenal insufficiency (and no other endocrinopathies) were admitted at the in-patient clinic and studied during physiological glucocorticoid exposure and withdrawal. A randomization plan before the first intervention was used. Besides mild physical and/or mental fatigue and salt craving, no serious adverse events were observed. The transcriptome in peripheral blood mononuclear cells and adipose tissue, plasma miRNAomic, and serum metabolomics were compared between the interventions using integrated multi-omic analysis. Results: We identified a transcriptomic profile derived from two tissues and a multi-omic cluster, both predictive of glucocorticoid exposure. A microRNA (miR-122-5p) that was correlated with genes and metabolites regulated by glucocorticoid exposure was identified (p=0.009) and replicated in independent studies with varying glucocorticoid exposure (0.01 ≤ p≤0.05). Conclusions: We have generated results that construct the basis for successful discovery of biomarker(s) to measure effects of glucocorticoids, allowing strategies to individualize and optimize glucocorticoid therapy, and shedding light on disease etiology related to unphysiological glucocorticoid exposure, such as in cardiovascular disease and obesity. Funding: The Swedish Research Council (Grant 2015-02561 and 2019-01112); The Swedish federal government under the LUA/ALF agreement (Grant ALFGBG-719531); The Swedish Endocrinology Association; The Gothenburg Medical Society; Wellcome Trust; The Medical Research Council, UK; The Chief Scientist Office, UK; The Eva Madura’s Foundation; The Research Foundation of Copenhagen University Hospital; and The Danish Rheumatism Association. Clinical trial number: NCT02152553.https://elifesciences.org/articles/62236glucocorticoidsbiomarkersmulti-omicsmicroRNAgene expressionmetabolites |
| spellingShingle | Dimitrios Chantzichristos Per-Arne Svensson Terence Garner Camilla AM Glad Brian R Walker Ragnhildur Bergthorsdottir Oskar Ragnarsson Penelope Trimpou Roland H Stimson Stina W Borresen Ulla Feldt-Rasmussen Per-Anders Jansson Stanko Skrtic Adam Stevens Gudmundur Johannsson Identification of human glucocorticoid response markers using integrated multi-omic analysis from a randomized crossover trial eLife glucocorticoids biomarkers multi-omics microRNA gene expression metabolites |
| title | Identification of human glucocorticoid response markers using integrated multi-omic analysis from a randomized crossover trial |
| title_full | Identification of human glucocorticoid response markers using integrated multi-omic analysis from a randomized crossover trial |
| title_fullStr | Identification of human glucocorticoid response markers using integrated multi-omic analysis from a randomized crossover trial |
| title_full_unstemmed | Identification of human glucocorticoid response markers using integrated multi-omic analysis from a randomized crossover trial |
| title_short | Identification of human glucocorticoid response markers using integrated multi-omic analysis from a randomized crossover trial |
| title_sort | identification of human glucocorticoid response markers using integrated multi omic analysis from a randomized crossover trial |
| topic | glucocorticoids biomarkers multi-omics microRNA gene expression metabolites |
| url | https://elifesciences.org/articles/62236 |
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