Targeted metabolomics as a tool in discriminating endocrine from primary hypertension

Zoran Erlic, Parminder Reel, Smarti Reel, Laurence Amar, Alessio Pecori, Casper K. Larsen, Martina Tetti, Christina Pamporaki, Cornelia Prehn, Jerzy Adamski, Aleksander Prejbisz, Filippo Ceccato, Carla Scaroni, Matthias Kroiss, Michael C. Dennedy, Jaap Deinum, Katharina Langton, Paolo Mulatero, Martin Reincke, Livia LenziniAnne-Paule Gimenez-Roqueplo, Guillaume Assié, Anne Blanchard, Maria Christina Zennaro, Emily Jefferson, Felix Beuschlein (Lead / Corresponding author)

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)
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Context: Identification of patients with endocrine forms of hypertension (EHT) (primary hyperaldosteronism [PA], pheochromocytoma/paraganglioma [PPGL], and Cushing syndrome [CS]) provides the basis to implement individualized therapeutic strategies. Targeted metabolomics (TM) have revealed promising results in profiling cardiovascular diseases and endocrine conditions associated with hypertension.

Objective: Use TM to identify distinct metabolic patterns between primary hypertension (PHT) and EHT and test its discriminating ability.

Methods: Retrospective analyses of PHT and EHT patients from a European multicenter study (ENSAT-HT). TM was performed on stored blood samples using liquid chromatography mass spectrometry. To identify discriminating metabolites a "classical approach" (CA) (performing a series of univariate and multivariate analyses) and a "machine learning approach" (MLA) (using random forest) were used.

The study included 282 adult patients (52% female; mean age 49 years) with proven PHT (n = 59) and EHT (n = 223 with 40 CS, 107 PA, and 76 PPGL), respectively.#

Results: From 155 metabolites eligible for statistical analyses, 31 were identified discriminating between PHT and EHT using the CA and 27 using the MLA, of which 16 metabolites (C9, C16, C16:1, C18:1, C18:2, arginine, aspartate, glutamate, ornithine, spermidine, lysoPCaC16:0, lysoPCaC20:4, lysoPCaC24:0, PCaeC42:0, SM C18:1, SM C20:2) were found by both approaches. The receiver operating characteristic curve built on the top 15 metabolites from the CA provided an area under the curve (AUC) of 0.86, which was similar to the performance of the 15 metabolites from MLA (AUC 0.83).

Conclusion: TM identifies distinct metabolic pattern between PHT and EHT providing promising discriminating performance.

Original languageEnglish
Pages (from-to)1111-1128
Number of pages18
JournalJournal of Clinical Endocrinology and Metabolism
Issue number4
Early online date31 Dec 2020
Publication statusPublished - Apr 2021


  • Cushing syndrome
  • arterial hypertension
  • pheochromocytoma
  • primary aldosteronism
  • screening
  • targeted metabolomics

ASJC Scopus subject areas

  • Endocrinology, Diabetes and Metabolism
  • Biochemistry
  • Endocrinology
  • Clinical Biochemistry
  • Biochemistry, medical


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