Bridging metabolism and immuno-inflammation: a novel framework to characterize dilated cardiomyopathy subtype

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Abstract
The heterogeneous subtypes in dilated cardiomyopathy (DCM) are poorly characterized, thus posing challenges to risk stratification. This study aimed to establish a DCM subtype framework based on metabolic and immunoinflammatory factors. DCM subtypes were identified using unsupervised clustering based on the expression patterns of metabolism-related genes in the left ventricular myocardium of 89 DCM patients. By comparing metabolic pathways, clinical characteristics, immune cell infiltration, inflammatory responses, and immunotherapy efficacy between the subtypes, key metabolic genes were identified through correlation analysis and validated at both bulk and single-cell levels. The alterations in gene expression were verified using the DCM mouse model. Molecular docking was performed to assess the binding affinity between the target protein and potential therapeutic small molecules. Two subtypes were identified; subtypes 1 and 2 were characterized by increased amino acid metabolism and decreased glucose and energy-related metabolisms, respectively. Subtype 2 displayed worse left ventricular structure and function, higher levels of immune and inflammatory activity, and a more favorable response to immunotherapy. The integrative analysis identified DHRS7C as a key regulator of glucose/energy metabolism; its expression was inversely correlated with left ventricular impairment. The DCM mice showed downregulated DHRS7C expression, which positively correlated with cardiac dysfunction. Additionally, molecular docking identified 17beta-estradiol as a potential therapeutic agent targeting DHRS7C. This study suggested two heterogeneous DCM subtypes with different metabolic and immunoinflammatory profiles. Furthermore, DHRS7C was inversely correlated with DCM indices and could be targeted by 17beta-estradiol.
Funding Information
  • Noncommunicable Chronic Diseases-National Science and Technology Major Project (2023ZD0504600)
  • National Natural Science Foundation of China (82470368)

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