Metabolic profiling enables differentiation between acute, chronic and healed myocarditis

Tom Kretzschmar (Jena)1, J. G. Westphal (Jena)1, P. S. Chaw (Jena)1, S. Neugebauer (Jena)2, J. M. Wu (Jena)1, M. Zeller (Jena)1, J. Bogoviku (Jena)1, M. Bekhite (Jena)1, T. Bekfani (Magdeburg)3, M. Kiehntopf (Jena)2, M. Franz (Jena)1, C. Schulze (Jena)1

1Universitätsklinikum Jena Klinik für Innere Medizin I - Kardiologie Jena, Deutschland; 2Universitätsklinikum Jena Institut für Klinische Chemie und Laboratoriumsdiagnostik Jena, Deutschland; 3Universitätsklinikum Magdeburg A.ö.R. Klinik für Kardiologie, Angiologie und Pneumologie Magdeburg, Deutschland


Background: The diagnosis of different pathological phenotypes of myocarditis is clinically challenging and often not possible. Right now, only histological examination of heart tissue is a suitable diagnostic method to determine chronic myocarditis and magnetic resonance imaging for additional assistance. The detection of potential diagnostic and prognostic biomarkers is limited but still has the potential to be a useful tool for the identification and differentiation of various phenotypes of myocarditis.

Aim: To identify metabolic differences and potential new biomarkers for diagnostic and prognostic purpose, we determined the metabolic profiles of acute (AM), chronic (CM) and healed myocarditis (HM) patients.

Methods: Serum metabolites of 20 controls, 26 AM, 6 CM, and 26 HM were analyzed and quantified with the MxP 500 kit.

Results: Compared to control, uniquely and equally altered metabolites were identified in all myocarditis phenotypes. Arachidonic Acid (2.8 ± 0.46, p<0.001, AUC = 0.97) and Fatty Acid (20:2) (2.8 ± 0.42, p<0.001, AUC = 0.96) were equally increased in all patient cohorts and are promising biomarker candidates for the diagnosis of general myocarditis (Figure 1 A). Sarcosine (3.2 ± 0.65, p = 0.04, AUC = 0.98) was uniquely altered in AM and showed the best diagnostic properties (Figure 1 B). TG(16:1_36:4) (0.42 ± 0.61, p=0.02) was only altered in CM and showed the highest AUC (0.88) (Figure 1 C). TG (14:0_36:1) (0.47 ± 1.3, p=0.008) showed the best AUC (0.84) of the uniquely altered metabolites in HM (Figure 1D).

Conclusion: Our study provides an understanding of the metabolic diversity of different myocarditis phenotypes. The generated metabolic profiles and identified metabolites could improve myocarditis diagnosis and prognosis.

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