Clustering of Cardiac Transcriptome Profiles Reveals Unique
Job A.J. Verdonschot, Ping Wang, Kasper Derks, Michiel Adriaens, Sophie L.V.M. Stroeks, Michiel T.H.M. Henkens, Anne G. Raafs, Maurits A. Sikking, Bart de Koning, Arthur van den Wijngaard, Ingrid P.C. Krapels, Miranda Nabben, Han G. Brunner, Stéphane Heymans
Abstract
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.