Cardiovascular genetic medicine: genomic assessment of prognosis and diagnosis in patients with cardiomyopathy and heart failure.
In the last half century, epidemiologic studies and basic science investigations revealed that hypertension (Kannel et al., Ann Intern Med 55:33-50, 1961), hyperlipidemia (Dawber et al., Am J Public Health Nations Health 49:1349-1356, 1959), diabetes (Kannel et al., Am J Cardiol 34(1):29-34, 1974), smoking (Dawber et al., Am J Public Health Nations Health 49:1349-1356, 1959), and inflammation (Rossmann et al., Exp Gerontol 43(3):229-237, 2008) posed increased risk for cardiovascular disease. These associations served both as risk factors and offered insight into disease pathophysiology. Currently, it is increasingly appreciated that polygenic factors may also play a role as etiologic or risk factors (Chakravarti and Little, Nature 421(6921):412-414, 2003; Dorn and Molkentin, Circulation 109(2):150-158, 2004). Recent technologic advances in genomic screening make the search for these factors possible, and robust technologies are now available for both entire genome screening for expression or single nucleotide polymorphisms. In this paper, we review the basic principles of gene expression and molecular signature analysis in the context of potential clinical applications of transcriptomics.
Heidecker
Bettina
B
Cardiology, Miller School of Medicine, University of Miami, PO Box 019132 C-205, Miami, FL 33101, USA. BHeidecker@med.miami.edu
Hare
Joshua M
JM
D015415:Biomarkers; D002309:Cardiology / Q000379:methods*; D009202:Cardiomyopathies / Q000175:diagnosis* / Q000235:genetics; D020869:Gene Expression Profiling; D023281:Genomics; D017408:Guidelines as Topic; D006333:Heart Failure / Q000175:diagnosis* / Q000235:genetics; D006801:Humans; D005810:Multigene Family; D018579:Patient Selection; D010641:Phenotype; D011379:Prognosis; D012107:Research Design
D015415:Biomarkers