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Identification of human glucocorticoid response markers using integrated multi-omic analysis from a randomized crossover trial

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Harvard

Chantzichristos, D, Svensson, P-A, Garner, T, Glad, CA, Walker, BR, Bergthorsdottir, R, Ragnarsson, O, Trimpou, P, Stimson, RH, Borresen, SW, Feldt-Rasmussen, U, Jansson, P-A, Skrtic, S, Stevens, A & Johannsson, G 2021, 'Identification of human glucocorticoid response markers using integrated multi-omic analysis from a randomized crossover trial', eLife, vol. 10, e62236. https://doi.org/10.7554/ELIFE.62236

APA

Chantzichristos, D., Svensson, P-A., Garner, T., Glad, C. A., Walker, B. R., Bergthorsdottir, R., Ragnarsson, O., Trimpou, P., Stimson, R. H., Borresen, S. W., Feldt-Rasmussen, U., Jansson, P-A., Skrtic, S., Stevens, A., & Johannsson, G. (2021). Identification of human glucocorticoid response markers using integrated multi-omic analysis from a randomized crossover trial. eLife, 10, [e62236]. https://doi.org/10.7554/ELIFE.62236

CBE

Chantzichristos D, Svensson P-A, Garner T, Glad CA, Walker BR, Bergthorsdottir R, Ragnarsson O, Trimpou P, Stimson RH, Borresen SW, Feldt-Rasmussen U, Jansson P-A, Skrtic S, Stevens A, Johannsson G. 2021. Identification of human glucocorticoid response markers using integrated multi-omic analysis from a randomized crossover trial. eLife. 10:Article e62236. https://doi.org/10.7554/ELIFE.62236

MLA

Vancouver

Chantzichristos D, Svensson P-A, Garner T, Glad CA, Walker BR, Bergthorsdottir R et al. Identification of human glucocorticoid response markers using integrated multi-omic analysis from a randomized crossover trial. eLife. 2021 Apr 6;10. e62236. https://doi.org/10.7554/ELIFE.62236

Author

Chantzichristos, Dimitrios ; Svensson, Per-Arne ; Garner, Terence ; Glad, Camilla Am ; Walker, Brian R ; Bergthorsdottir, Ragnhildur ; Ragnarsson, Oskar ; Trimpou, Penelope ; Stimson, Roland H ; Borresen, Stina W ; Feldt-Rasmussen, Ulla ; Jansson, Per-Anders ; Skrtic, Stanko ; Stevens, Adam ; Johannsson, Gudmundur. / Identification of human glucocorticoid response markers using integrated multi-omic analysis from a randomized crossover trial. In: eLife. 2021 ; Vol. 10.

Bibtex

@article{0867d50e7cef4d0f9eb6d4b4f51edb9b,
title = "Identification of human glucocorticoid response markers using integrated multi-omic analysis from a randomized crossover trial",
abstract = "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.",
author = "Dimitrios Chantzichristos and Per-Arne Svensson and Terence Garner and Glad, {Camilla Am} and Walker, {Brian R} and Ragnhildur Bergthorsdottir and Oskar Ragnarsson and Penelope Trimpou and Stimson, {Roland H} and Borresen, {Stina W} and Ulla Feldt-Rasmussen and Per-Anders Jansson and Stanko Skrtic and Adam Stevens and Gudmundur Johannsson",
note = "{\textcopyright} 2021, Chantzichristos et al.",
year = "2021",
month = apr,
day = "6",
doi = "10.7554/ELIFE.62236",
language = "English",
volume = "10",
journal = "eLife",
issn = "2050-084X",
publisher = "eLife Sciences Publications",

}

RIS

TY - JOUR

T1 - Identification of human glucocorticoid response markers using integrated multi-omic analysis from a randomized crossover trial

AU - Chantzichristos, Dimitrios

AU - Svensson, Per-Arne

AU - Garner, Terence

AU - Glad, Camilla Am

AU - Walker, Brian R

AU - Bergthorsdottir, Ragnhildur

AU - Ragnarsson, Oskar

AU - Trimpou, Penelope

AU - Stimson, Roland H

AU - Borresen, Stina W

AU - Feldt-Rasmussen, Ulla

AU - Jansson, Per-Anders

AU - Skrtic, Stanko

AU - Stevens, Adam

AU - Johannsson, Gudmundur

N1 - © 2021, Chantzichristos et al.

PY - 2021/4/6

Y1 - 2021/4/6

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85103995127&partnerID=8YFLogxK

U2 - 10.7554/ELIFE.62236

DO - 10.7554/ELIFE.62236

M3 - Journal article

C2 - 33821793

VL - 10

JO - eLife

JF - eLife

SN - 2050-084X

M1 - e62236

ER -

ID: 66209853