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)

Connell, John (Investigator)
Doney, Alexander (Investigator)
Jefferson, Emily (Investigator)
Zhou, Kaixin (Investigator)

Status	Finished
Effective start/end date	1/05/15 → 31/12/21

Funding

COMMISSION OF THE EUROPEAN COMMUNITIES: £724,921.00

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

SDG 3 Good Health and Well-being

Additional file 2 of Whole blood methylome-derived features to discriminate endocrine hypertension
Armignacco, R. (Creator), Reel, P. S. (Creator), Reel, S. (Creator), Jouinot, A. (Creator), Septier, A. (Creator), Gaspar, C. (Creator), Perlemoine, K. (Creator), Larsen, C. K. (Creator), Bouys, L. (Creator), Braun, L. (Creator), Riester, A. (Creator), Kroiss, M. (Creator), Bonnet-Serrano, F. (Creator), Amar, L. (Creator), Blanchard, A. (Creator), Gimenez-Roqueplo, A.-P. (Creator), Prejbisz, A. (Creator), Januszewicz, A. (Creator), Dobrowolski, P. (Creator), Davies, E. (Creator), MacKenzie, S. M. (Creator), Rossi, G. P. (Creator), Lenzini, L. (Creator), Ceccato, F. (Creator), Scaroni, C. (Creator), Mulatero, P. (Creator), Williams, T. A. (Creator), Pecori, A. (Creator), Monticone, S. (Creator), Beuschlein, F. (Creator), Reincke, M. (Creator), Zennaro, M.-C. (Creator), Bertherat, J. (Creator), Jefferson, E. (Creator) & Assié, G. (Creator), figshare, 4 Nov 2022
DOI: 10.6084/m9.figshare.21500752
Dataset

Health Informatics Centre
Health and Clinical Services
Facility/equipment: Facility

Researchers develop new system to classify endocrine hypertension
Reel, P., Reel, S. & Jefferson, E.
12/10/22
1 item of Media coverage
Press/Media: Research

2 Invited talk
1 Membership of network

Machine Learning Approaches for Multi-Omics Data Analysis
Reel, P. (Speaker)
18 Oct 2022
Activity: Talk or presentation types › Invited talk
Machine learning for classification of hypertension subtypes using multi-omics
Reel, P. (Speaker)
12 Oct 2022
Activity: Talk or presentation types › Invited talk

File
european network for the study of adrenal tumors (External organisation)
Reel, P. (Member)
1 Mar 2016 → 15 Jan 2026
Activity: Membership types › Membership of network

8 Article
2 Poster
1 Meeting abstract
1 Review article

Targeted Metabolomics to Distinguish Primary from Endocrine Hypertension: Results from the Prospective ENSAT-HT Study
Reel, P. S., Reel, S., Amar, L., Parente, B., Deinum, J., Timmers, H. J. L. M., Prehn, C., Adamski, J., Ceccato, F., Monticone, S., Buffolo, F., Mulatero, P., Peitzsch, M., Cole, C., Stüfchen, I., Schneider, H., Reincke, M., Rossi, G. P., Lenzini, L. & Cosentino, T. & 6 others, Assié, G., Blanchard, A., Zennaro, M. C., Jefferson, E., Beuschlein, F. & Erlic, Z., 9 May 2026.
Research output: Contribution to conference › Poster › peer-review

Open Access
File
12 Downloads (Pure)
Identification of hypertension subtypes using microRNA profiles and machine learning
Reel, S., Reel, P. S., Van Kralingen, J., Larsen, C. K., Robertson, S., MacKenzie, S. M., Riddell, A., McClure, J. D., Lamprou, S., Connell, J. M. C., Amar, L., Pecori, A., Tetti, M., Pamporaki, C., Kabat, M., Ceccato, F., Kroiss, M., Dennedy, M. C., Stell, A. & Deinum, J. & 11 others, Mulatero, P., Reincke, M., Gimenez-Roqueplo, A.-P., Assié, G., Blanchard, A., Beuschlein, F., Rossi, G.-P., Eisenhofer, G., Zennaro, M. C., Jefferson, E. & Davies, E. (Lead / Corresponding author), Mar 2025, In: European Journal of Endocrinology. 192, 4, p. 418-428 11 p., lvaf052.
Research output: Contribution to journal › Article › peer-review

Open Access
File
10 Link opens in a new tab Citations (Scopus)

106 Downloads (Pure)
Classifying hypertension subtypes using multi-omics: A multi-centre machine learning based retrospective study
Reel, P. S., Reel, S., Cole, C., Zennaro, M. C. & Jefferson, E., 31 Oct 2023. 1 p.
Research output: Contribution to conference › Poster › peer-review

Open Access

ENSAT Scientific Award
Reel, P. (Recipient) & Reel, S. (Recipient), 2023
Prize: Prize (including medals and awards)

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)

Project Details

Funding

UN Sustainable Development Goals

Fingerprint

Additional file 2 of Whole blood methylome-derived features to discriminate endocrine hypertension

Health Informatics Centre

Researchers develop new system to classify endocrine hypertension

Machine Learning Approaches for Multi-Omics Data Analysis

Machine learning for classification of hypertension subtypes using multi-omics

european network for the study of adrenal tumors (External organisation)

Targeted Metabolomics to Distinguish Primary from Endocrine Hypertension: Results from the Prospective ENSAT-HT Study

Identification of hypertension subtypes using microRNA profiles and machine learning

Classifying hypertension subtypes using multi-omics: A multi-centre machine learning based retrospective study

ENSAT Scientific Award

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)

Project Details

Funding

UN Sustainable Development Goals

Fingerprint

Datasets

Equipment

Press/Media

Activities

Research output

Prizes