ArticleThe Journal of clinical endocrinology and metabolism2021
Targeted Metabolomics as a Tool in Discriminating Endocrine From Primary Hypertension.
Article in The Journal of clinical endocrinology and metabolism, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it, 36 citations in OpenAlex.
- Usefulness of steroid profiling in the diagnosis of primary Aldosteronism a systematic review.Endocrine · 2026Pooled it
- Primary aldosteronism.Nature reviews. Disease primers · 2026Review
- The role of arachidonic acid metabolites in the subtype classification and pathogenesis of primary aldosteronism.iScience · 2026Article
- Metabolomics and Precision Medicine in Resistant Hypertension: Pathophysiological Insights, Biomarker Discovery, and Translational Strategies.International journal of hypertension · 2026Review
- Article
- Mendelian Randomization Analysis Reveals Causal Effects of Circulating Metabolites on Hyperaldosteronism.Food science & nutrition · 2025Article
- A multi-stage metabolic pattern of adrenocortical adenomas offers diagnostic potential of uric acid, isocitric acid, and proline.Metabolomics : Official journal of the Metabolomic Society · 2025Article
- Preliminary investigations of plasma lipidome and selenium levels in adults with treated hypothyroidism and in healthy individuals without selenium deficiency.Scientific reports · 2024Article
- Identification of novel hypertension biomarkers using explainable AI and metabolomics.Metabolomics : Official journal of the Metabolomic Society · 2024Article
- Mild autonomous cortisol secretion: pathophysiology, comorbidities and management approaches.Nature reviews. Endocrinology · 2024Review
- Treating Primary Aldosteronism-Induced Hypertension: Novel Approaches and Future Outlooks.Endocrine reviews · 2024Article
- Association of adrenal steroids with metabolomic profiles in patients with primary and endocrine hypertension.Frontiers in endocrinology · 2024Article
- Metabolic and inflammatory parameters in relation to baseline characterization and treatment outcome in patients with prolactinoma: insights from a retrospective cohort study at a single tertiary center.Frontiers in endocrinology · 2024Article
- O tempora, o mores: The Age We Live In, Machine Learning, Hypertension, and Primary Aldosteronism.JACC. Asia · 2023Article
- Article
- Whole blood methylome-derived features to discriminate endocrine hypertension.Clinical epigenetics · 2022Article
- Adrenal venous sampling in primary aldosteronism: Experience of a Spanish multicentric study (Results from the SPAIN-ALDO Register).Endocrine · 2022Article
- Predicting Hypertension Subtypes with Machine Learning Using Targeted Metabolites and Their Ratios.Metabolites · 2022Article
- Preanalytical Pitfalls in Untargeted Plasma Nuclear Magnetic Resonance Metabolomics of Endocrine Hypertension.Metabolites · 2022Article
- Review
Corrections and comments
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Authors and funding
26 authors at 14 institutions in 9 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
contextIdentification 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.
objectiveUse TM to identify distinct metabolic patterns between primary hypertension (PHT) and EHT and test its discriminating ability.
methodsRetrospective 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.
resultsFrom 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).
conclusionTM identifies distinct metabolic pattern between PHT and EHT providing promising discriminating performance.
Indexed as
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.