Abstract
Dilated cardiomyopathy is a heterogeneous disease characterized by multiple genetic and environmental etiol-ogies. 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 pathophysi-ology. Distinct patient subgroups are identified based on differences in protein quality control, cardiac meta-bolism, cardiomyocyte function, and inflammatory pathways. The identified pathways have the potential to guide future treatment and individualize patient care. (J Am Coll Cardiol Basic Trans Science 2023;8:406-418) (c) 2023 The Authors. Published by Elsevier on behalf of the American College of Cardiology Foundation. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
| Original language | English |
|---|---|
| Pages (from-to) | 406-418 |
| Number of pages | 13 |
| Journal | JACC: Basic to Translational Science |
| Volume | 8 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 1 Apr 2023 |
Keywords
- clustering
- dilated cardiomyopathy
- genetics
- transcriptomics
- TITIN
- DIAGNOSIS
- DEFINITION
- MUTATIONS
- HEALTH
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