@article{BliziotisKluijtmansTinneveltetal.2022,
  author    = {Bliziotis, Nikolaos G. and Kluijtmans, Leo A. J. and Tinnevelt, Gerjen H. and Reel, Parminder and Reel, Smarti and Langton, Katharina and Robledo, Mercedes and Pamporaki, Christina and Pecori, Alessio and Van Kralingen, Josie and Tetti, Martina and Engelke, Udo F. H. and Erlic, Zoran and Engel, Jasper and Deutschbein, Timo and N{\"o}lting, Svenja and Prejbisz, Aleksander and Richter, Susan and Adamski, Jerzy and Januszewicz, Andrzej and Ceccato, Filippo and Scaroni, Carla and Dennedy, Michael C. and Williams, Tracy A. and Lenzini, Livia and Gimenez-Roqueplo, Anne-Paule and Davies, Eleanor and Fassnacht, Martin and Remde, Hanna and Eisenhofer, Graeme and Beuschlein, Felix and Kroiss, Matthias and Jefferson, Emily and Zennaro, Maria-Christina and Wevers, Ron A. and Jansen, Jeroen J. and Deinum, Jaap and Timmers, Henri J. L. M.},
  title     = {Preanalytical pitfalls in untargeted plasma nuclear magnetic resonance metabolomics of endocrine hypertension},
  series = {Metabolites},
  volume    = {12},
  journal   = {Metabolites},
  number    = {8},
  issn      = {2218-1989},
  doi       = {10.3390/metabo12080679},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-282930},
  year      = {2022},
  abstract  = {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.},
  language  = {en}
}
@article{BliziotisKluijtmansSotoetal.2022,
  author    = {Bliziotis, Nikolaos G. and Kluijtmans, Leo A. J. and Soto, Sebastian and Tinnevelt, Gerjen H. and Langton, Katharina and Robledo, Mercedes and Pamporaki, Christina and Engelke, Udo F. H. and Erlic, Zoran and Engel, Jasper and Deutschbein, Timo and N{\"o}lting, Svenja and Prejbisz, Aleksander and Richter, Susan and Prehn, Cornelia and Adamski, Jerzy and Januszewicz, Andrzej and Reincke, Martin and Fassnacht, Martin and Eisenhofer, Graeme and Beuschlein, Felix and Kroiss, Matthias and Wevers, Ron A. and Jansen, Jeroen J. and Deinum, Jaap and Timmers, Henri J. L. M.},
  title     = {Pre- versus post-operative untargeted plasma nuclear magnetic resonance spectroscopy metabolomics of pheochromocytoma and paraganglioma},
  series = {Endocrine},
  volume    = {75},
  journal   = {Endocrine},
  number    = {1},
  doi       = {10.1007/s12020-021-02858-z},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-326574},
  pages     = {254-265},
  year      = {2022},
  abstract  = {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.},
  language  = {en}
}