Whole blood methylome-derived features to discriminate endocrine hypertension

Roberta Armignacco; Parminder S. Reel; Smarti Reel; Anne Jouinot; Amandine Septier; Cassandra Gaspar; Karine Perlemoine; Casper K. Larsen; Lucas Bouys; Leah Braun; Anna Riester; Matthias Kroiss; Fidéline Bonnet-Serrano; Laurence Amar; Anne Blanchard; Anne-Paule Gimenez-Roqueplo; Aleksander Prejbisz; Andrzej Januszewicz; Piotr Dobrowolski; Eleanor Davies; Scott M. MacKenzie; Gian Paolo Rossi; Livia Lenzini; Filippo Ceccato; Carla Scaroni; Paolo Mulatero; Tracy A Williams; Alessio Pecori; Silvia Monticone; Felix Beuschlein; Martin Reincke; Maria-Christina Zennaro; Jérôme Bertherat; Emily Jefferson; Guillaume Assié

doi:10.1186/s13148-022-01347-y

Whole blood methylome-derived features to discriminate endocrine hypertension

Roberta Armignacco, Parminder S. Reel, Smarti Reel, Anne Jouinot, Amandine Septier, Cassandra Gaspar, Karine Perlemoine, Casper K. Larsen, Lucas Bouys, Leah Braun, Anna Riester, Matthias Kroiss, Fidéline Bonnet-Serrano, Laurence Amar, Anne Blanchard, Anne-Paule Gimenez-Roqueplo, Aleksander Prejbisz, Andrzej Januszewicz, Piotr Dobrowolski, Eleanor DaviesScott M. MacKenzie, Gian Paolo Rossi, Livia Lenzini, Filippo Ceccato, Carla Scaroni, Paolo Mulatero, Tracy A Williams, Alessio Pecori, Silvia Monticone, Felix Beuschlein, Martin Reincke, Maria-Christina Zennaro, Jérôme Bertherat, Emily Jefferson, Guillaume Assié (Lead / Corresponding author)

Research output: Contribution to journal › Article › peer-review

5 Citations (Scopus)

86 Downloads (Pure)

Abstract

Background: Arterial hypertension represents a worldwide health burden and a major risk factor for cardiovascular morbidity and mortality. Hypertension can be primary (primary hypertension, PHT), or secondary to endocrine disorders (endocrine hypertension, EHT), such as Cushing's syndrome (CS), primary aldosteronism (PA), and pheochromocytoma/paraganglioma (PPGL). Diagnosis of EHT is currently based on hormone assays. Efficient detection remains challenging, but is crucial to properly orientate patients for diagnostic confirmation and specific treatment. More accurate biomarkers would help in the diagnostic pathway. We hypothesized that each type of endocrine hypertension could be associated with a specific blood DNA methylation signature, which could be used for disease discrimination. To identify such markers, we aimed at exploring the methylome profiles in a cohort of 255 patients with hypertension, either PHT (n = 42) or EHT (n = 213), and at identifying specific discriminating signatures using machine learning approaches.

Results: Unsupervised classification of samples showed discrimination of PHT from EHT. CS patients clustered separately from all other patients, whereas PA and PPGL showed an overall overlap. Global methylation was decreased in the CS group compared to PHT. Supervised comparison with PHT identified differentially methylated CpG sites for each type of endocrine hypertension, showing a diffuse genomic location. Among the most differentially methylated genes, FKBP5 was identified in the CS group. Using four different machine learning methods-Lasso (Least Absolute Shrinkage and Selection Operator), Logistic Regression, Random Forest, and Support Vector Machine-predictive models for each type of endocrine hypertension were built on training cohorts (80% of samples for each hypertension type) and estimated on validation cohorts (20% of samples for each hypertension type). Balanced accuracies ranged from 0.55 to 0.74 for predicting EHT, 0.85 to 0.95 for predicting CS, 0.66 to 0.88 for predicting PA, and 0.70 to 0.83 for predicting PPGL.

Conclusion: The blood DNA methylome can discriminate endocrine hypertension, with methylation signatures for each type of endocrine disorder.

Original language	English
Article number	142
Number of pages	11
Journal	Clinical Epigenetics
Volume	14
Issue number	1
DOIs	https://doi.org/10.1186/s13148-022-01347-y
Publication status	Published - 3 Nov 2022

Keywords

Humans
Epigenome
DNA Methylation
Pheochromocytoma/complications
Hypertension/diagnosis
Adrenal Gland Neoplasms/diagnosis
Biomarkers
Circulating biomarker
Whole blood methylome
Endocrine hypertension

ASJC Scopus subject areas

Genetics(clinical)
Genetics
Molecular Biology
Developmental Biology

Access to Document

10.1186/s13148-022-01347-yLicence: CC BY

Final Published VersionFinal published version, 1.33 MBLicence: CC BY

Cite this

Armignacco, R., Reel, P. S., Reel, S., Jouinot, A., Septier, A., Gaspar, C., Perlemoine, K., Larsen, C. K., Bouys, L., Braun, L., Riester, A., Kroiss, M., Bonnet-Serrano, F., Amar, L., Blanchard, A., Gimenez-Roqueplo, A.-P., Prejbisz, A., Januszewicz, A., Dobrowolski, P., ... Assié, G. (2022). Whole blood methylome-derived features to discriminate endocrine hypertension. Clinical Epigenetics, 14(1), Article 142. https://doi.org/10.1186/s13148-022-01347-y

@article{0cfe44a3d66043638376a8a0cf3d731b,

title = "Whole blood methylome-derived features to discriminate endocrine hypertension",

abstract = "Background: Arterial hypertension represents a worldwide health burden and a major risk factor for cardiovascular morbidity and mortality. Hypertension can be primary (primary hypertension, PHT), or secondary to endocrine disorders (endocrine hypertension, EHT), such as Cushing's syndrome (CS), primary aldosteronism (PA), and pheochromocytoma/paraganglioma (PPGL). Diagnosis of EHT is currently based on hormone assays. Efficient detection remains challenging, but is crucial to properly orientate patients for diagnostic confirmation and specific treatment. More accurate biomarkers would help in the diagnostic pathway. We hypothesized that each type of endocrine hypertension could be associated with a specific blood DNA methylation signature, which could be used for disease discrimination. To identify such markers, we aimed at exploring the methylome profiles in a cohort of 255 patients with hypertension, either PHT (n = 42) or EHT (n = 213), and at identifying specific discriminating signatures using machine learning approaches.Results: Unsupervised classification of samples showed discrimination of PHT from EHT. CS patients clustered separately from all other patients, whereas PA and PPGL showed an overall overlap. Global methylation was decreased in the CS group compared to PHT. Supervised comparison with PHT identified differentially methylated CpG sites for each type of endocrine hypertension, showing a diffuse genomic location. Among the most differentially methylated genes, FKBP5 was identified in the CS group. Using four different machine learning methods-Lasso (Least Absolute Shrinkage and Selection Operator), Logistic Regression, Random Forest, and Support Vector Machine-predictive models for each type of endocrine hypertension were built on training cohorts (80% of samples for each hypertension type) and estimated on validation cohorts (20% of samples for each hypertension type). Balanced accuracies ranged from 0.55 to 0.74 for predicting EHT, 0.85 to 0.95 for predicting CS, 0.66 to 0.88 for predicting PA, and 0.70 to 0.83 for predicting PPGL.Conclusion: The blood DNA methylome can discriminate endocrine hypertension, with methylation signatures for each type of endocrine disorder.",

keywords = "Humans, Epigenome, DNA Methylation, Pheochromocytoma/complications, Hypertension/diagnosis, Adrenal Gland Neoplasms/diagnosis, Biomarkers, Circulating biomarker, Whole blood methylome, Endocrine hypertension",

author = "Roberta Armignacco and Reel, {Parminder S.} and Smarti Reel and Anne Jouinot and Amandine Septier and Cassandra Gaspar and Karine Perlemoine and Larsen, {Casper K.} and Lucas Bouys and Leah Braun and Anna Riester and Matthias Kroiss and Fid{\'e}line Bonnet-Serrano and Laurence Amar and Anne Blanchard and Anne-Paule Gimenez-Roqueplo and Aleksander Prejbisz and Andrzej Januszewicz and Piotr Dobrowolski and Eleanor Davies and MacKenzie, {Scott M.} and Rossi, {Gian Paolo} and Livia Lenzini and Filippo Ceccato and Carla Scaroni and Paolo Mulatero and Williams, {Tracy A} and Alessio Pecori and Silvia Monticone and Felix Beuschlein and Martin Reincke and Maria-Christina Zennaro and J{\'e}r{\^o}me Bertherat and Emily Jefferson and Guillaume Assi{\'e}",

note = "Copyright: {\textcopyright} 2022. The Author(s).",

year = "2022",

month = nov,

day = "3",

doi = "10.1186/s13148-022-01347-y",

language = "English",

volume = "14",

journal = "Clinical Epigenetics",

issn = "1868-7075",

publisher = "BioMed Central Ltd.",

number = "1",

}

Armignacco, R, Reel, PS , Reel, S, Jouinot, A, Septier, A, Gaspar, C, Perlemoine, K, Larsen, CK, Bouys, L, Braun, L, Riester, A, Kroiss, M, Bonnet-Serrano, F, Amar, L, Blanchard, A, Gimenez-Roqueplo, A-P, Prejbisz, A, Januszewicz, A, Dobrowolski, P, Davies, E, MacKenzie, SM, Rossi, GP, Lenzini, L, Ceccato, F, Scaroni, C, Mulatero, P, Williams, TA, Pecori, A, Monticone, S, Beuschlein, F, Reincke, M, Zennaro, M-C, Bertherat, J, Jefferson, E & Assié, G 2022, 'Whole blood methylome-derived features to discriminate endocrine hypertension', Clinical Epigenetics, vol. 14, no. 1, 142. https://doi.org/10.1186/s13148-022-01347-y

TY - JOUR

T1 - Whole blood methylome-derived features to discriminate endocrine hypertension

AU - Armignacco, Roberta

AU - Reel, Parminder S.

AU - Reel, Smarti

AU - Jouinot, Anne

AU - Septier, Amandine

AU - Gaspar, Cassandra

AU - Perlemoine, Karine

AU - Larsen, Casper K.

AU - Bouys, Lucas

AU - Braun, Leah

AU - Riester, Anna

AU - Kroiss, Matthias

AU - Bonnet-Serrano, Fidéline

AU - Amar, Laurence

AU - Blanchard, Anne

AU - Gimenez-Roqueplo, Anne-Paule

AU - Prejbisz, Aleksander

AU - Januszewicz, Andrzej

AU - Dobrowolski, Piotr

AU - Davies, Eleanor

AU - MacKenzie, Scott M.

AU - Rossi, Gian Paolo

AU - Lenzini, Livia

AU - Ceccato, Filippo

AU - Scaroni, Carla

AU - Mulatero, Paolo

AU - Williams, Tracy A

AU - Pecori, Alessio

AU - Monticone, Silvia

AU - Beuschlein, Felix

AU - Reincke, Martin

AU - Zennaro, Maria-Christina

AU - Bertherat, Jérôme

AU - Jefferson, Emily

AU - Assié, Guillaume

PY - 2022/11/3

Y1 - 2022/11/3

N2 - Background: Arterial hypertension represents a worldwide health burden and a major risk factor for cardiovascular morbidity and mortality. Hypertension can be primary (primary hypertension, PHT), or secondary to endocrine disorders (endocrine hypertension, EHT), such as Cushing's syndrome (CS), primary aldosteronism (PA), and pheochromocytoma/paraganglioma (PPGL). Diagnosis of EHT is currently based on hormone assays. Efficient detection remains challenging, but is crucial to properly orientate patients for diagnostic confirmation and specific treatment. More accurate biomarkers would help in the diagnostic pathway. We hypothesized that each type of endocrine hypertension could be associated with a specific blood DNA methylation signature, which could be used for disease discrimination. To identify such markers, we aimed at exploring the methylome profiles in a cohort of 255 patients with hypertension, either PHT (n = 42) or EHT (n = 213), and at identifying specific discriminating signatures using machine learning approaches.Results: Unsupervised classification of samples showed discrimination of PHT from EHT. CS patients clustered separately from all other patients, whereas PA and PPGL showed an overall overlap. Global methylation was decreased in the CS group compared to PHT. Supervised comparison with PHT identified differentially methylated CpG sites for each type of endocrine hypertension, showing a diffuse genomic location. Among the most differentially methylated genes, FKBP5 was identified in the CS group. Using four different machine learning methods-Lasso (Least Absolute Shrinkage and Selection Operator), Logistic Regression, Random Forest, and Support Vector Machine-predictive models for each type of endocrine hypertension were built on training cohorts (80% of samples for each hypertension type) and estimated on validation cohorts (20% of samples for each hypertension type). Balanced accuracies ranged from 0.55 to 0.74 for predicting EHT, 0.85 to 0.95 for predicting CS, 0.66 to 0.88 for predicting PA, and 0.70 to 0.83 for predicting PPGL.Conclusion: The blood DNA methylome can discriminate endocrine hypertension, with methylation signatures for each type of endocrine disorder.

AB - Background: Arterial hypertension represents a worldwide health burden and a major risk factor for cardiovascular morbidity and mortality. Hypertension can be primary (primary hypertension, PHT), or secondary to endocrine disorders (endocrine hypertension, EHT), such as Cushing's syndrome (CS), primary aldosteronism (PA), and pheochromocytoma/paraganglioma (PPGL). Diagnosis of EHT is currently based on hormone assays. Efficient detection remains challenging, but is crucial to properly orientate patients for diagnostic confirmation and specific treatment. More accurate biomarkers would help in the diagnostic pathway. We hypothesized that each type of endocrine hypertension could be associated with a specific blood DNA methylation signature, which could be used for disease discrimination. To identify such markers, we aimed at exploring the methylome profiles in a cohort of 255 patients with hypertension, either PHT (n = 42) or EHT (n = 213), and at identifying specific discriminating signatures using machine learning approaches.Results: Unsupervised classification of samples showed discrimination of PHT from EHT. CS patients clustered separately from all other patients, whereas PA and PPGL showed an overall overlap. Global methylation was decreased in the CS group compared to PHT. Supervised comparison with PHT identified differentially methylated CpG sites for each type of endocrine hypertension, showing a diffuse genomic location. Among the most differentially methylated genes, FKBP5 was identified in the CS group. Using four different machine learning methods-Lasso (Least Absolute Shrinkage and Selection Operator), Logistic Regression, Random Forest, and Support Vector Machine-predictive models for each type of endocrine hypertension were built on training cohorts (80% of samples for each hypertension type) and estimated on validation cohorts (20% of samples for each hypertension type). Balanced accuracies ranged from 0.55 to 0.74 for predicting EHT, 0.85 to 0.95 for predicting CS, 0.66 to 0.88 for predicting PA, and 0.70 to 0.83 for predicting PPGL.Conclusion: The blood DNA methylome can discriminate endocrine hypertension, with methylation signatures for each type of endocrine disorder.

KW - Humans

KW - Epigenome

KW - DNA Methylation

KW - Pheochromocytoma/complications

KW - Hypertension/diagnosis

KW - Adrenal Gland Neoplasms/diagnosis

KW - Biomarkers

KW - Circulating biomarker

KW - Whole blood methylome

KW - Endocrine hypertension

UR - http://www.scopus.com/inward/record.url?scp=85141171757&partnerID=8YFLogxK

U2 - 10.1186/s13148-022-01347-y

DO - 10.1186/s13148-022-01347-y

M3 - Article

C2 - 36329530

SN - 1868-7075

VL - 14

JO - Clinical Epigenetics

JF - Clinical Epigenetics

IS - 1

M1 - 142

ER -

Whole blood methylome-derived features to discriminate endocrine hypertension

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Omics-Based Strategies for Improved Diagnosis and Treatment of Endocrine Hypertension (ENSAT-HT) (Joint with Inserm, University of Torino, University of Padua, University of Glasgow, University of Birmingham, Radboud University Medical Centre, SleekIT Limited and Inserm Transfert)

Health Informatics Centre

Cite this

Whole blood methylome-derived features to discriminate endocrine hypertension

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Projects

Omics-Based Strategies for Improved Diagnosis and Treatment of Endocrine Hypertension (ENSAT-HT) (Joint with Inserm, University of Torino, University of Padua, University of Glasgow, University of Birmingham, Radboud University Medical Centre, SleekIT Limited and Inserm Transfert)

Equipment

Health Informatics Centre

Cite this