TY - JOUR A1 - Bliziotis, Nikolaos G. A1 - Kluijtmans, Leo A. J. A1 - Tinnevelt, Gerjen H. A1 - Reel, Parminder A1 - Reel, Smarti A1 - Langton, Katharina A1 - Robledo, Mercedes A1 - Pamporaki, Christina A1 - Pecori, Alessio A1 - Van Kralingen, Josie A1 - Tetti, Martina A1 - Engelke, Udo F. H. A1 - Erlic, Zoran A1 - Engel, Jasper A1 - Deutschbein, Timo A1 - Nölting, Svenja A1 - Prejbisz, Aleksander A1 - Richter, Susan A1 - Adamski, Jerzy A1 - Januszewicz, Andrzej A1 - Ceccato, Filippo A1 - Scaroni, Carla A1 - Dennedy, Michael C. A1 - Williams, Tracy A. A1 - Lenzini, Livia A1 - Gimenez-Roqueplo, Anne-Paule A1 - Davies, Eleanor A1 - Fassnacht, Martin A1 - Remde, Hanna A1 - Eisenhofer, Graeme A1 - Beuschlein, Felix A1 - Kroiss, Matthias A1 - Jefferson, Emily A1 - Zennaro, Maria-Christina A1 - Wevers, Ron A. A1 - Jansen, Jeroen J. A1 - Deinum, Jaap A1 - Timmers, Henri J. L. M. T1 - Preanalytical pitfalls in untargeted plasma nuclear magnetic resonance metabolomics of endocrine hypertension JF - Metabolites N2 - Despite considerable morbidity and mortality, numerous cases of endocrine hypertension (EHT) forms, including primary aldosteronism (PA), pheochromocytoma and functional paraganglioma (PPGL), and Cushing’s syndrome (CS), remain undetected. We aimed to establish signatures for the different forms of EHT, investigate potentially confounding effects and establish unbiased disease biomarkers. Plasma samples were obtained from 13 biobanks across seven countries and analyzed using untargeted NMR metabolomics. We compared unstratified samples of 106 PHT patients to 231 EHT patients, including 104 PA, 94 PPGL and 33 CS patients. Spectra were subjected to a multivariate statistical comparison of PHT to EHT forms and the associated signatures were obtained. Three approaches were applied to investigate and correct confounding effects. Though we found signatures that could separate PHT from EHT forms, there were also key similarities with the signatures of sample center of origin and sample age. The study design restricted the applicability of the corrections employed. With the samples that were available, no biomarkers for PHT vs. EHT could be identified. The complexity of the confounding effects, evidenced by their robustness to correction approaches, highlighted the need for a consensus on how to deal with variabilities probably attributed to preanalytical factors in retrospective, multicenter metabolomics studies. KW - confounders KW - metabolomics KW - multicenter KW - plasma NMR KW - preanalytical conditions Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-282930 SN - 2218-1989 VL - 12 IS - 8 ER - TY - JOUR A1 - Reel, Smarti A1 - Reel, Parminder S. A1 - Erlic, Zoran A1 - Amar, Laurence A1 - Pecori, Alessio A1 - Larsen, Casper K. A1 - Tetti, Martina A1 - Pamporaki, Christina A1 - Prehn, Cornelia A1 - Adamski, Jerzy A1 - Prejbisz, Aleksander A1 - Ceccato, Filippo A1 - Scaroni, Carla A1 - Kroiss, Matthias A1 - Dennedy, Michael C. A1 - Deinum, Jaap A1 - Eisenhofer, Graeme A1 - Langton, Katharina A1 - Mulatero, Paolo A1 - Reincke, Martin A1 - Rossi, Gian Paolo A1 - Lenzini, Livia A1 - Davies, Eleanor A1 - Gimenez-Roqueplo, Anne-Paule A1 - Assié, Guillaume A1 - Blanchard, Anne A1 - Zennaro, Maria-Christina A1 - Beuschlein, Felix A1 - Jefferson, Emily R. T1 - Predicting hypertension subtypes with machine learning using targeted metabolites and their ratios JF - Metabolites N2 - Hypertension is a major global health problem with high prevalence and complex associated health risks. Primary hypertension (PHT) is most common and the reasons behind primary hypertension are largely unknown. Endocrine hypertension (EHT) is another complex form of hypertension with an estimated prevalence varying from 3 to 20% depending on the population studied. It occurs due to underlying conditions associated with hormonal excess mainly related to adrenal tumours and sub-categorised: primary aldosteronism (PA), Cushing’s syndrome (CS), pheochromocytoma or functional paraganglioma (PPGL). Endocrine hypertension is often misdiagnosed as primary hypertension, causing delays in treatment for the underlying condition, reduced quality of life, and costly antihypertensive treatment that is often ineffective. This study systematically used targeted metabolomics and high-throughput machine learning methods to predict the key biomarkers in classifying and distinguishing the various subtypes of endocrine and primary hypertension. The trained models successfully classified CS from PHT and EHT from PHT with 92% specificity on the test set. The most prominent targeted metabolites and metabolite ratios for hypertension identification for different disease comparisons were C18:1, C18:2, and Orn/Arg. Sex was identified as an important feature in CS vs. PHT classification. KW - metabolomics KW - machine learning KW - hypertension KW - primary aldosteronism KW - pheochromocytoma/paraganglioma KW - Cushing syndrome KW - biomarkers Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-286161 SN - 2218-1989 VL - 12 IS - 8 ER - TY - JOUR A1 - Rogowski-Lehmann, Natalie A1 - Geroula, Aikaterini A1 - Prejbisz, Aleksander A1 - Timmers, Henri J. L. M. A1 - Megerle, Felix A1 - Robledo, Mercedes A1 - Fassnacht, Martin A1 - Fliedner, Stephanie M. J. A1 - Reincke, Martin A1 - Stell, Anthony A1 - Januszewicz, Andrzej A1 - Lenders, Jacques W. M. A1 - Eisenhofer, Graeme A1 - Beuschlein, Felix T1 - Missed clinical clues in patients with pheochromocytoma/paraganglioma discovered by imaging JF - Endocrine Connections N2 - Background: Pheochromocytomas and paragangliomas (PPGLs) are rare but potentially harmful tumors that can vary in their clinical presentation. Tumors may be found due to signs and symptoms, as part of a hereditary syndrome or following an imaging procedure. Objective: To investigate potential differences in clinical presentation between PPGLs discovered by imaging (iPPGLs), symptomatic cases (sPPGLs) and those diagnosed during follow-up because of earlier disease/known hereditary mutations (fPPGL). Design: Prospective study protocol, which has enrolled patients from six European centers with confirmed PPGLs. Data were analyzed from 235 patients (37 iPPGLs, 36 sPPGLs, 27% fPPGLs) and compared for tumor volume, biochemical profile, mutation status, presence of metastases and self-reported symptoms. iPPGL patients were diagnosed at a significantly higher age than fPPGLs (P<0.001), found to have larger tumors (P=0.003) and higher metanephrine and normetanephrine levels at diagnosis (P=0.021). Significantly lower than in sPPGL, there was a relevant number of self-reported symptoms in iPPGL (2.9 vs 4.3 symptoms, P< 0.001). In 16.2% of iPPGL, mutations in susceptibility genes were detected, although this proportion was lower than that in fPPGL (60.9%) and sPPGL (21.5%). Patients with PPGLs detected by imaging were older, have higher tumor volume and more excessive hormonal secretion in comparison to those found as part of a surveillance program. Presence of typical symptoms indicates that in a relevant proportion of those patients, the PPGL diagnosis had been delayed. Precis: Pheochromocytoma/paraganglioma discovered by imaging are often symptomatic and carry a significant proportion of germline mutations in susceptibility genes. KW - pheochromocytoma KW - paraganglioma KW - imaging KW - signs and symptoms KW - prospective KW - Biochemical-Diagnosis KW - Plasma KW - MASS KW - Normetanephrine KW - Metanephrine KW - Paraganglioma KW - Society KW - Utility Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-226481 VL - 7 IS - 11 ER -