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)

2022

Analyse du profil de méthylation du sang total pour discriminer l’hypertension endocrine

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., Rossi, G. P., & 12 othersLenzini, L., Ceccato, F., Scaroni, C., Mulatero, P., Pecori, A., Monticone, S., Beuschlein, F., Reincke, M., Zennaro, M. C., Bertherat, J., Jefferson, E. & Assié, G., 24 Sept 2022, In: Annales d'Endocrinologie. 83, 5, p. 297 1 p.

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

Machine learning for classification of hypertension subtypes using multi-omics: A multi-centre, retrospective, data-driven study

Reel, P. S., Reel, S., van Kralingen, J. C., Langton, K., Lang, K., Erlic, Z., Larsen, C. K., Amar, L., Pamporaki, C., Mulatero, P., Blanchard, A., Kabat, M., Robertson, S., MacKenzie, S. M., Taylor, A. E., Peitzsch, M., Ceccato, F., Scaroni, C., Reincke, M., Kroiss, M., & 22 othersDennedy, M. C., Pecori, A., Monticone, S., Deinum, J., Rossi, G. P., Lenzini, L., McClure, J. D., Nind, T., Riddell, A., Stell, A., Cole, C., Sudano, I., Prehn, C., Adamski, J., Gimenez-Roqueplo, A. P., Assié, G., Arlt, W., Beuschlein, F., Eisenhofer, G., Davies, E., Zennaro, M. C. & Jefferson, E., Oct 2022, In: EBioMedicine. 84, 16 p., 104276.

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

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11 Citations (Scopus)

28 Downloads (Pure)

Preanalytical Pitfalls in Untargeted Plasma Nuclear Magnetic Resonance Metabolomics of Endocrine Hypertension

Bliziotis, N. G., Kluijtmans, L. A. J., Tinnevelt, G. H., Reel, P., Reel, S., Langton, K., Robledo, M., Pamporaki, C., Pecori, A., Van Kralingen, J., Tetti, M., Engelke, U. F. H., Erlic, Z., Engel, J., Deutschbein, T., Nölting, S., Prejbisz, A., Richter, S., Adamski, J., Januszewicz, A., & 18 othersCeccato, F., Scaroni, C., Dennedy, M. C., Williams, T. A., Lenzini, L., Gimenez-Roqueplo, A-P., Davies, E., Fassnacht, M., Remde, H., Eisenhofer, G., Beuschlein, F., Kroiss, M., Jefferson, E., Zennaro, M-C., Wevers, R. A., Jansen, J. J., Deinum, J. & Timmers, H. J. L. M., 24 Jul 2022, In: Metabolites. 12, 8, 21 p., 679.

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

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2 Citations (Scopus)

12 Downloads (Pure)

Predicting Hypertension Subtypes with Machine Learning Using Targeted Metabolites and Their Ratios

Reel, S., Reel, P. S., Erlic, Z., Amar, L., Pecori, A., Larsen, C. K., Tetti, M., Pamporaki, C., Prehn, C., Adamski, J., Dennedy, M. C., Deinum, J., Eisenhofer, G., Langton, K., Mulatero, P., Reincke, M., Rossi, G. P., Lenzini, L., Davies, E., Zennaro, M. C., & 2 othersBeuschlein, F. & Jefferson, E., 16 Aug 2022, In: Metabolites. 12, 8, 20 p., 755.

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3 Citations (Scopus)

22 Downloads (Pure)

Whole blood methylome-derived features to discriminate endocrine hypertension

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., Davies, E., & 15 othersMacKenzie, S. M., Rossi, G. P., Lenzini, L., Ceccato, F., Scaroni, C., Mulatero, P., Williams, T. A., Pecori, A., Monticone, S., Beuschlein, F., Reincke, M., Zennaro, M-C., Bertherat, J., Jefferson, E. & Assié, G., 3 Nov 2022, In: Clinical Epigenetics. 14, 1, 11 p., 142.

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3 Citations (Scopus)

30 Downloads (Pure)

2021

Targeted metabolomics as a tool in discriminating endocrine from primary hypertension

Erlic, Z., Reel, P., Reel, S., Amar, L., Pecori, A., Larsen, C. K., Tetti, M., Pamporaki, C., Prehn, C., Adamski, J., Prejbisz, A., Ceccato, F., Scaroni, C., Kroiss, M., Dennedy, M. C., Deinum, J., Langton, K., Mulatero, P., Reincke, M., Lenzini, L., & 6 othersGimenez-Roqueplo, A-P., Assié, G., Blanchard, A., Zennaro, M. C., Jefferson, E. & Beuschlein, F., Apr 2021, In: Journal of Clinical Endocrinology and Metabolism. 106, 4, p. 1111-1128 18 p.

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14 Citations (Scopus)

50 Downloads (Pure)

Using machine learning approaches for multi-omics data analysis: A review

Reel, P. S., Reel, S., Pearson, E., Trucco, E. & Jefferson, E., Jul 2021, In: Biotechnology Advances. 49, 24 p., 107739.

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170 Citations (Scopus)

2373 Downloads (Pure)

2018

The Research Data Management Platform (RDMP): A novel, process driven, open-source tool for the management of longitudinal cohorts of clinical data

Nind, T., Galloway, J., McAllister, G., Scobbie, D., Bonney, W., Hall, C., Tramma, L., Reel, P., Groves, M., Appleby, P., Doney, A., Guthrie, B. & Jefferson, E., 22 May 2018, In: Giga Science. 7, 7, 12 p., giy060.

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10 Citations (Scopus)

253 Downloads (Pure)

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)

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