Preanalytical Pitfalls in Untargeted Plasma Nuclear Magnetic Resonance Metabolomics of Endocrine Hypertension

Nikolaos G. Bliziotis (Lead / Corresponding author), Leo A. J. Kluijtmans (Lead / Corresponding author), Gerjen H. Tinnevelt, Parminder Reel, Smarti Reel, Katharina Langton, Mercedes Robledo, Christina Pamporaki, Alessio Pecori, Josie Van Kralingen, Martina Tetti, Udo F. H. Engelke, Zoran Erlic, Jasper Engel, Timo Deutschbein, Svenja Nölting, Aleksander Prejbisz, Susan Richter, Jerzy Adamski, Andrzej JanuszewiczFilippo Ceccato, Carla Scaroni, Michael C Dennedy, Tracy A. Williams, Livia Lenzini, Anne-Paule Gimenez-Roqueplo, Eleanor Davies, Martin Fassnacht, Hanna Remde, Graeme Eisenhofer, Felix Beuschlein, Matthias Kroiss, Emily Jefferson, Maria-Christina Zennaro, Ron A. Wevers (Lead / Corresponding author), Jeroen J. Jansen, Jaap Deinum, Henri J. L. M. Timmers (Lead / Corresponding author)

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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.
Original languageEnglish
Article number679
Number of pages21
JournalMetabolites
Volume12
Issue number8
DOIs
Publication statusPublished - 24 Jul 2022

Keywords

  • confounders
  • metabolomics
  • multicenter
  • plasma NMR
  • preanalytical conditions

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