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Published on: February 13, 2019
Metabolic Task Analysis Reveals Distinct Metabotypes in End-Stage Dilated Cardiomyopathy
Bastien S C Nihant1, Job A J Verdonschot1, Sonia Bălan2
1Cardiovascular Research Institute Maastricht (CARIM), The Netherlands (B.S.C.N., J.A.J.V., J.J.F.P.L., M.N., S.H.).
Background:
Dilated cardiomyopathy (DCM) is associated with shifts in cardiac metabolism. However, those shifts vary widely across patients, likely reflecting the diverse underlying causes of the disease. Identifying metabolic subtypes, or metabotypes, in DCM patients could help tailor treatments to patient needs. Hence, having a practical approach to identify these metabotypes would be a significant advance toward precision medicine in DCM.
Methods:
We present a systems biology approach to uncover metabotypes directly from widely available transcriptomic data. We use in silico metabolic modeling methods that we have optimized for cardiac research to predict metabolic function activities from enzyme expression, followed by a hierarchical clustering approach. To demonstrate its power, we applied our method to publicly available cardiac data from end-stage DCM patients (N=164) and nonfailing controls (N=160).
Results:
We identified 2 distinct metabotypes in end-stage DCM patients. These metabotypes are characterized by unique metabolic changes, notably in calcium handling, amino acid oxidation, and the pentose phosphate pathway. Strikingly, 1 DCM metabotype showed greater metabolic divergence from healthy controls, suggesting a greater metabolic contribution to its underlying etiology-even though disease severity was similar between the 2 identified DCM metabotypes. Further transcriptome-wide analysis revealed immune-related differences between metabotypes, suggesting an underlying interplay between inflammation, the immune response, and metabolism.
Conclusions:
Our results imply the presence of distinct metabotypes in end-stage DCM. Our systems biology approach offers an exciting opportunity to uncover novel insights into DCM, paving the way for a deeper understanding of its progression and heterogeneity.
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