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https://doi.org/10.3389/fendo.2021.722656
Title: | Plasma Metabolome Profiling for the Diagnosis of Catecholamine Producing Tumors | Authors: | März, Juliane Kurlbaum, Max Roche-Lancaster, Oisin Deutschbein, Timo Peitzsch, Mirko Prehn, Cornelia Weismann, Dirk Robledo, Mercedes Adamski, Jerzy Fassnacht, Martin Kunz, Meik Kroiss, Matthias |
Keywords: | adrenal catecholamines feature selection machine learning mass spectronomy paraganglioma pheochromocytoma targeted metabolomics |
Issue Date: | 7-Sep-2021 | Publisher: | Frontiers Media S.A. | Citation: | März, Juliane, Kurlbaum, Max, Roche-Lancaster, Oisin, Deutschbein, Timo, Peitzsch, Mirko, Prehn, Cornelia, Weismann, Dirk, Robledo, Mercedes, Adamski, Jerzy, Fassnacht, Martin, Kunz, Meik, Kroiss, Matthias (2021-09-07). Plasma Metabolome Profiling for the Diagnosis of Catecholamine Producing Tumors. Frontiers in Endocrinology 12 : 722656. ScholarBank@NUS Repository. https://doi.org/10.3389/fendo.2021.722656 | Rights: | Attribution 4.0 International | Abstract: | Context: Pheochromocytomas and paragangliomas (PPGL) cause catecholamine excess leading to a characteristic clinical phenotype. Intra-individual changes at metabolome level have been described after surgical PPGL removal. The value of metabolomics for the diagnosis of PPGL has not been studied yet. Objective: Evaluation of quantitative metabolomics as a diagnostic tool for PPGL. Design: Targeted metabolomics by liquid chromatography-tandem mass spectrometry of plasma specimens and statistical modeling using ML-based feature selection approaches in a clinically well characterized cohort study. Patients: Prospectively enrolled patients (n=36, 17 female) from the Prospective Monoamine-producing Tumor Study (PMT) with hormonally active PPGL and 36 matched controls in whom PPGL was rigorously excluded. Results: Among 188 measured metabolites, only without considering false discovery rate, 4 exhibited statistically significant differences between patients with PPGL and controls (histidine p=0.004, threonine p=0.008, lyso PC a C28:0 p=0.044, sum of hexoses p=0.018). Weak, but significant correlations for histidine, threonine and lyso PC a C28:0 with total urine catecholamine levels were identified. Only the sum of hexoses (reflecting glucose) showed significant correlations with plasma metanephrines. By using ML-based feature selection approaches, we identified diagnostic signatures which all exhibited low accuracy and sensitivity. The best predictive value (sensitivity 87.5%, accuracy 67.3%) was obtained by using Gradient Boosting Machine Modelling. Conclusions: The diabetogenic effect of catecholamine excess dominates the plasma metabolome in PPGL patients. While curative surgery for PPGL led to normalization of catecholamine-induced alterations of metabolomics in individual patients, plasma metabolomics are not useful for diagnostic purposes, most likely due to inter-individual variability. © Copyright © 2021 März, Kurlbaum, Roche-Lancaster, Deutschbein, Peitzsch, Prehn, Weismann, Robledo, Adamski, Fassnacht, Kunz and Kroiss. | Source Title: | Frontiers in Endocrinology | URI: | https://scholarbank.nus.edu.sg/handle/10635/232019 | ISSN: | 1664-2392 | DOI: | 10.3389/fendo.2021.722656 | Rights: | Attribution 4.0 International |
Appears in Collections: | Staff Publications Elements |
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