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 - Bliziotis, Nikolaos G. A1 - Kluijtmans, Leo A. J. A1 - Soto, Sebastian A1 - Tinnevelt, Gerjen H. A1 - Langton, Katharina A1 - Robledo, Mercedes A1 - Pamporaki, Christina A1 - Engelke, Udo F. H. A1 - Erlic, Zoran A1 - Engel, Jasper A1 - Deutschbein, Timo A1 - Nölting, Svenja A1 - Prejbisz, Aleksander A1 - Richter, Susan A1 - Prehn, Cornelia A1 - Adamski, Jerzy A1 - Januszewicz, Andrzej A1 - Reincke, Martin A1 - Fassnacht, Martin A1 - Eisenhofer, Graeme A1 - Beuschlein, Felix A1 - Kroiss, Matthias A1 - Wevers, Ron A. A1 - Jansen, Jeroen J. A1 - Deinum, Jaap A1 - Timmers, Henri J. L. M. T1 - Pre- versus post-operative untargeted plasma nuclear magnetic resonance spectroscopy metabolomics of pheochromocytoma and paraganglioma JF - Endocrine N2 - Purpose Pheochromocytomas and Paragangliomas (PPGL) result in chronic catecholamine excess and serious health complications. A recent study obtained a metabolic signature in plasma from PPGL patients; however, its targeted nature may have generated an incomplete picture and a broader approach could provide additional insights. We aimed to characterize the plasma metabolome of PPGL patients before and after surgery, using an untargeted approach, and to broaden the scope of the investigated metabolic impact of these tumors. Design A cohort of 36 PPGL patients was investigated. Blood plasma samples were collected before and after surgical tumor removal, in association with clinical and tumor characteristics. Methods Plasma samples were analyzed using untargeted nuclear magnetic resonance (NMR) spectroscopy metabolomics. The data were evaluated using a combination of uni- and multi-variate statistical methods. Results Before surgery, patients with a nonadrenergic tumor could be distinguished from those with an adrenergic tumor based on their metabolic profiles. Tyrosine levels were significantly higher in patients with high compared to those with low BMI. Comparing subgroups of pre-operative samples with their post-operative counterparts, we found a metabolic signature that included ketone bodies, glucose, organic acids, methanol, dimethyl sulfone and amino acids. Three signals with unclear identities were found to be affected. Conclusions Our study suggests that the pathways of glucose and ketone body homeostasis are affected in PPGL patients. BMI-related metabolite levels were also found to be altered, potentially linking muscle atrophy to PPGL. At baseline, patient metabolomes could be discriminated based on their catecholamine phenotype. KW - PPGL KW - metabolomics KW - NMR KW - paired KW - plasma KW - operation Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-326574 VL - 75 IS - 1 ER -