Plasma Metabolome Profiling for the Diagnosis of Catecholamine Producing Tumors

März J, Kurlbaum M, Roche-Lancaster O, Deutschbein T, Peitzsch M, Prehn C, Weismann D, Robledo M, Adamski J, Fassnacht M, Kunz M, Kroiss M (2021)

Publication Language: English

Publication Type: Journal article

Publication year: 2021

Journal

Frontiers in Endocrinology Frontiers Media

Book Volume: 12

Article Number: 722656

DOI: 10.3389/fendo.2021.722656

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.

Authors with CRIS profile

Oisin Roche-Lancaster Department of Paediatrics and Adolescent Medicine Meik Kunz Lehrstuhl für Medizinische Informatik

Involved external institutions

Universitätsklinikum Würzburg DE Germany (DE) Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt (HMGU) / Helmholtz Munich DE Germany (DE) Spanish National Cancer Research Centre / Centro Nacional de Investigaciones Oncológicas (CNIO) ES Spain (ES) Universitätsklinikum Carl Gustav Carus Dresden DE Germany (DE)

How to cite

APA:

März, J., Kurlbaum, M., Roche-Lancaster, O., Deutschbein, T., Peitzsch, M., Prehn, C.,... Kroiss, M. (2021). Plasma Metabolome Profiling for the Diagnosis of Catecholamine Producing Tumors. Frontiers in Endocrinology, 12. https://doi.org/10.3389/fendo.2021.722656

MLA:

März, Juliane, et al. "Plasma Metabolome Profiling for the Diagnosis of Catecholamine Producing Tumors." Frontiers in Endocrinology 12 (2021).

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