Analysis of serum NMR metabolomics in fibrotic diseases of the myocardium.

Authors

Mark V Füzesi, Ella J Zhang, Rajshree Ghosh Biswas, Antonia Leist, Anna-Laura M Hasubek, Xiaoyu Wang, Jiashang Chen, Xin Zhou, Angela Rao, Evan Zhang, Isabella H Muti, Piet Habbel, Johannes Nowak, Leo L Cheng

Published in

Metabolomics : Official journal of the Metabolomic Society. Volume 22. Issue 4. Aug 07, 2026. Epub Aug 07, 2026.

Abstract

Heart failure accounts for more than 43% of annual deaths worldwide, and isdriven by widespread pathological remodeling, in which myocardial fibrosis plays an important role. Currently, accurate clinical diagnosis of myocardialfibrosis (MF) remains difficult, with even greater challenges in differentiating among lesser-understood etiologies, such as cardiac sarcoidosis (CS) andcardiac amyloidosis (CA).
To investigate the capability of high-resolution magic angle spinning (HRMAS) nuclear magnetic resonance (NMR)spectroscopy to differentiate amongst patients with MF of different origins (CS, CA) using blood sera.
HRMAS NMR spectroscopy of 10 ìL ofblood sera from three patient groups, with matched controls, was conducted:1)MF due to common causes including hypertension and coronary arterydisease (n = 13),2)transthyretin CA (n = 18), and3)CS (n = 12). NMR spectra were analyzed as regions of interest (ROIs). ROIAL-NMR was used toidentify metabolites present in the determined ROIs. Statistical analysis, such as hierarchical clustering, Wilcoxon/Kruskal-Wallis tests (paired andunpaired), and unsupervised multivariate principal component analyses (PCA), were performed to distinguish diseased individuals from their matchedcontrols.
Analysis of NMR spectra identified 61 ROIs highlighting metabolite alterations such as changes in fatty acids, branched chain aminoacids, and markers of energy and inflammatory states, that may contribute to disease-specific metabolic signatures.
HRMAS NMRmetabolomics results may enhance our understanding of the patho-mechanisms underlying myocardial fibrosis across etiologies and serve as a clinicallypractical tool to improve diagnostic precision and identify new therapeutic targets.

PMID:
42565902
Bibliographic data and abstract were imported from PubMed on 07 Aug 2026.

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