Why the study?
Dilated cardiomyopathy is heterogeneous with multiple etiologies, yet most patients receive identical treatment despite transcriptomic differences that could guide targeted therapy.
Transcriptomic, genotypic, and phenotypic clustering identifies distinct pathophysiological subgroups in dilated cardiomyopathy, offering potential pathways for individualized therapy.
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Multi-omic clustering identifies homogeneous DCM subgroups; hypothesis-generating for targeted therapies, requires prospective validation before clinical use.
Dilated cardiomyopathy is a heterogeneous disease characterized by multiple genetic and environmental etiologies. The majority of patients are treated the same despite these differences. The cardiac transcriptome provides information on the patient's pathophysiology, which allows targeted therapy. Using clustering techniques on data from the genotype, phenotype, and cardiac transcriptome of patients with early- and end-stage dilated cardiomyopathy, more homogeneous patient subgroups are identified based on shared underlying pathophysiology. Distinct patient subgroups are identified based on differences in protein quality control, cardiac metabolism, cardiomyocyte function, and inflammatory pathways. The identified pathways have the potential to guide future treatment and individualize patient care.
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Verdonschot et al. (2023) studied this question.
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