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Updated: Aug 18, 2026

Single Cell Transcriptional Profiling of Adult Mouse Cardiomyocytes
Published on: December 28, 2011
Array lessons from the heart: focus on the genome and transcriptome of cardiomyopathies
Despina Sanoudou1, Elizabeth Vafiadaki, Demetrios A Arvanitis
1Molecular Biology Division, Center for Basic Research, Foundation for Biomedical Research of the Academy of Athens, Athens, Greece. dsanoudou@bioacademy.gr
Abstract:
Our understanding of the cardiovascular system has evolved through the years by extensive studies emphasizing the identification of the molecular and physiological mechanisms involved in its normal function and disease pathogenesis. Major discoveries have been made along the way. However, the majority of this work has focused on specific genes or pathways rather than integrative approaches. In cardiomyopathies alone, over 30 different loci have shown mutations with varying inheritance patterns, yet mostly coding for structural proteins. The emergence of microarrays in the early 1990s paved the way to a new era of cardiovascular research. Microarrays dramatically accelerated the rhythm of discoveries by giving us the ability to simultaneously study thousands of genes in a single experiment. In the field of cardiovascular research, microarrays are having a significant contribution, with the majority of work focusing on end-stage cardiomyopathies that lead to heart failure. Novel molecular mechanisms have been identified, known pathways are seen under new light, disease subgroups begin to emerge, and the effects of various drugs are molecularly dissected. This cross-study data comparison concludes that consistent energy metabolism gene expression changes occur across dilated, hypertrophic, and ischemic cardiomyopathies, while Ca2+ homeostasis changes are prominent in the first two cardiomyopathies, and structural gene expression changes accompany mostly the dilated form. Gene expression changes are further correlated to disease genetics. The future of microarrays in the cardiomyopathy field is discussed with an emphasis on optimum experimental design and on applications in diagnosis, prognosis, and drug discovery.
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