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Institute
Phäochromozytome und Paragangliome (PPGL) sind seltene, katecholaminproduzierendeTumore des chromaffinen Gewebes. Die Erkrankung ist durch die Überproduktion von Katecholaminen gekennzeichnet und kann lebensbedrohliche Folgen haben. Die dieser Arbeit zugrunde liegende Studie untersuchte die interindividuellen Unterschiede im Metabolitenprofil bei Patient*innen mit PPGL im Vergleich zu Kontrollen mittels Flüssigchromatographie-Massenspektrometrie und einem Targeted Metabolomic Ansatz. Targeted Metabolomics beschreibt die Messung und Quantifizierung von im Voraus definierten Metaboliten in einer Probe. Von den 188 gemessenen Metaboliten zeigten vier Metabolite eine signifikanten Veränderung zwischen den Gruppen (Histidin, Threonin, LysoPC a C28:0 und Summe der Hexosen). Für alle vier Metabolite wurde ein Zusammenhang mit Katecholaminen im Urin beziehungsweise Metanephrinen im Plasma nachgewiesen. Subgruppenanalysen zeigten weitere Hinweise auf geschlechts- und phänotypspezifische Unterschiede im Metabolitenprofil zwischen Patient*innen mit PPGL und Kontrollen.
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.