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Identification of glucocorticoid-related molecular signature by whole blood methylome analysis

OBJECTIVE: Cushing’s syndrome represents a state of excessive glucocorticoids related to glucocorticoid treatments or to endogenous hypercortisolism. Cushing’s syndrome is associated with high morbidity, with significant inter-individual variability. Likewise, adrenal insufficiency is a life-threate...

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Autores principales: Armignacco, Roberta, Jouinot, Anne, Bouys, Lucas, Septier, Amandine, Lartigue, Thomas, Neou, Mario, Gaspar, Cassandra, Perlemoine, Karine, Braun, Leah, Riester, Anna, Bonnet-Serrano, Fidéline, Blanchard, Anne, Amar, Laurence, Scaroni, Carla, Ceccato, Filippo, Rossi, Gian Paolo, Williams, Tracy Ann, Larsen, Casper K, Allassonnière, Stéphanie, Zennaro, Maria-Christina, Beuschlein, Felix, Reincke, Martin, Bertherat, Jérôme, Assié, Guillaume
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Bioscientifica Ltd 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8789024/
https://www.ncbi.nlm.nih.gov/pubmed/34914631
http://dx.doi.org/10.1530/EJE-21-0907
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author Armignacco, Roberta
Jouinot, Anne
Bouys, Lucas
Septier, Amandine
Lartigue, Thomas
Neou, Mario
Gaspar, Cassandra
Perlemoine, Karine
Braun, Leah
Riester, Anna
Bonnet-Serrano, Fidéline
Blanchard, Anne
Amar, Laurence
Scaroni, Carla
Ceccato, Filippo
Rossi, Gian Paolo
Williams, Tracy Ann
Larsen, Casper K
Allassonnière, Stéphanie
Zennaro, Maria-Christina
Beuschlein, Felix
Reincke, Martin
Bertherat, Jérôme
Assié, Guillaume
author_facet Armignacco, Roberta
Jouinot, Anne
Bouys, Lucas
Septier, Amandine
Lartigue, Thomas
Neou, Mario
Gaspar, Cassandra
Perlemoine, Karine
Braun, Leah
Riester, Anna
Bonnet-Serrano, Fidéline
Blanchard, Anne
Amar, Laurence
Scaroni, Carla
Ceccato, Filippo
Rossi, Gian Paolo
Williams, Tracy Ann
Larsen, Casper K
Allassonnière, Stéphanie
Zennaro, Maria-Christina
Beuschlein, Felix
Reincke, Martin
Bertherat, Jérôme
Assié, Guillaume
author_sort Armignacco, Roberta
collection PubMed
description OBJECTIVE: Cushing’s syndrome represents a state of excessive glucocorticoids related to glucocorticoid treatments or to endogenous hypercortisolism. Cushing’s syndrome is associated with high morbidity, with significant inter-individual variability. Likewise, adrenal insufficiency is a life-threatening condition of cortisol deprivation. Currently, hormone assays contribute to identify Cushing’s syndrome or adrenal insufficiency. However, no biomarker directly quantifies the biological glucocorticoid action. The aim of this study was to identify such markers. DESIGN: We evaluated whole blood DNA methylome in 94 samples obtained from patients with different glucocorticoid states (Cushing’s syndrome, eucortisolism, adrenal insufficiency). We used an independent cohort of 91 samples for validation. METHODS: Leukocyte DNA was obtained from whole blood samples. Methylome was determined using the Illumina methylation chip array (~850 000 CpG sites). Both unsupervised (principal component analysis) and supervised (Limma) methods were used to explore methylome profiles. A Lasso-penalized regression was used to select optimal discriminating features. RESULTS: Whole blood methylation profile was able to discriminate samples by their glucocorticoid status: glucocorticoid excess was associated with DNA hypomethylation, recovering within months after Cushing’s syndrome correction. In Cushing’s syndrome, an enrichment in hypomethylated CpG sites was observed in the region of FKBP5 gene locus. A methylation predictor of glucocorticoid excess was built on a training cohort and validated on two independent cohorts. Potential CpG sites associated with the risk for specific complications, such as glucocorticoid-related hypertension or osteoporosis, were identified, needing now to be confirmed on independent cohorts. CONCLUSIONS: Whole blood DNA methylome is dynamically impacted by glucocorticoids. This biomarker could contribute to better assessment of glucocorticoid action beyond hormone assays.
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spelling pubmed-87890242022-01-28 Identification of glucocorticoid-related molecular signature by whole blood methylome analysis Armignacco, Roberta Jouinot, Anne Bouys, Lucas Septier, Amandine Lartigue, Thomas Neou, Mario Gaspar, Cassandra Perlemoine, Karine Braun, Leah Riester, Anna Bonnet-Serrano, Fidéline Blanchard, Anne Amar, Laurence Scaroni, Carla Ceccato, Filippo Rossi, Gian Paolo Williams, Tracy Ann Larsen, Casper K Allassonnière, Stéphanie Zennaro, Maria-Christina Beuschlein, Felix Reincke, Martin Bertherat, Jérôme Assié, Guillaume Eur J Endocrinol Clinical Study OBJECTIVE: Cushing’s syndrome represents a state of excessive glucocorticoids related to glucocorticoid treatments or to endogenous hypercortisolism. Cushing’s syndrome is associated with high morbidity, with significant inter-individual variability. Likewise, adrenal insufficiency is a life-threatening condition of cortisol deprivation. Currently, hormone assays contribute to identify Cushing’s syndrome or adrenal insufficiency. However, no biomarker directly quantifies the biological glucocorticoid action. The aim of this study was to identify such markers. DESIGN: We evaluated whole blood DNA methylome in 94 samples obtained from patients with different glucocorticoid states (Cushing’s syndrome, eucortisolism, adrenal insufficiency). We used an independent cohort of 91 samples for validation. METHODS: Leukocyte DNA was obtained from whole blood samples. Methylome was determined using the Illumina methylation chip array (~850 000 CpG sites). Both unsupervised (principal component analysis) and supervised (Limma) methods were used to explore methylome profiles. A Lasso-penalized regression was used to select optimal discriminating features. RESULTS: Whole blood methylation profile was able to discriminate samples by their glucocorticoid status: glucocorticoid excess was associated with DNA hypomethylation, recovering within months after Cushing’s syndrome correction. In Cushing’s syndrome, an enrichment in hypomethylated CpG sites was observed in the region of FKBP5 gene locus. A methylation predictor of glucocorticoid excess was built on a training cohort and validated on two independent cohorts. Potential CpG sites associated with the risk for specific complications, such as glucocorticoid-related hypertension or osteoporosis, were identified, needing now to be confirmed on independent cohorts. CONCLUSIONS: Whole blood DNA methylome is dynamically impacted by glucocorticoids. This biomarker could contribute to better assessment of glucocorticoid action beyond hormone assays. Bioscientifica Ltd 2021-12-16 /pmc/articles/PMC8789024/ /pubmed/34914631 http://dx.doi.org/10.1530/EJE-21-0907 Text en © The authors https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License. (https://creativecommons.org/licenses/by/4.0/)
spellingShingle Clinical Study
Armignacco, Roberta
Jouinot, Anne
Bouys, Lucas
Septier, Amandine
Lartigue, Thomas
Neou, Mario
Gaspar, Cassandra
Perlemoine, Karine
Braun, Leah
Riester, Anna
Bonnet-Serrano, Fidéline
Blanchard, Anne
Amar, Laurence
Scaroni, Carla
Ceccato, Filippo
Rossi, Gian Paolo
Williams, Tracy Ann
Larsen, Casper K
Allassonnière, Stéphanie
Zennaro, Maria-Christina
Beuschlein, Felix
Reincke, Martin
Bertherat, Jérôme
Assié, Guillaume
Identification of glucocorticoid-related molecular signature by whole blood methylome analysis
title Identification of glucocorticoid-related molecular signature by whole blood methylome analysis
title_full Identification of glucocorticoid-related molecular signature by whole blood methylome analysis
title_fullStr Identification of glucocorticoid-related molecular signature by whole blood methylome analysis
title_full_unstemmed Identification of glucocorticoid-related molecular signature by whole blood methylome analysis
title_short Identification of glucocorticoid-related molecular signature by whole blood methylome analysis
title_sort identification of glucocorticoid-related molecular signature by whole blood methylome analysis
topic Clinical Study
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8789024/
https://www.ncbi.nlm.nih.gov/pubmed/34914631
http://dx.doi.org/10.1530/EJE-21-0907
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