Blood gene expression signatures associate with heart failure outcomes

Gene expression signatures in blood correlate with specific diseases. Such signatures may serve as valuable diagnostic and prognostic tools in disease management. Blood gene expression signatures associated with heart failure may be applied to predict prognosis, monitor disease progression, and opti...

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Bibliographic Details
Published in:Physiological genomics 2011-04, Vol.43 (8), p.392-397
Main Authors: Vanburen, Peter, Ma, Jun, Chao, Samuel, Mueller, Enkhtuyaa, Schneider, David J, Liew, Choong-Chin
Format: Article
Language:English
Subjects:
Adult
Aged
Aged, 80 and over
Cluster Analysis
Disease Progression
Gene Expression Profiling - methods
Heart Failure - blood
Heart Failure - genetics
Heart Failure - mortality
Humans
Microarray Analysis - methods
Middle Aged
Prognosis
Receptors, Antigen, T-Cell - analysis
Receptors, Antigen, T-Cell - blood
Risk Assessment
Survival Analysis
Treatment Outcome
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Summary:Gene expression signatures in blood correlate with specific diseases. Such signatures may serve as valuable diagnostic and prognostic tools in disease management. Blood gene expression signatures associated with heart failure may be applied to predict prognosis, monitor disease progression, and optimize treatment. Blood gene expression profiles were generated for 71 subjects with heart failure and 15 controls without heart failure, using the Affymetrix GeneChip U133Plus2.0. Survival analysis identified 197 "mortality genes" that were significantly associated with patient outcome. Functional categorization showed that genes associated with T cell receptor signaling were most significantly overpresented. Cluster analysis of these T cell receptor signaling genes significantly categorized heart failure patients into three risk groups (P = 0.031) that were distinct from the three risk groups categorized by New York Heart Association (NYHA) Classification (P = 0.0002). By combining the analysis of clinical assessment (NYHA class) with T cell receptor signaling gene expression, we proposed a model that demonstrated an even greater differentiation of patients at risk (P = 0.0001). In this discovery study, we identified blood expression signatures associated with heart failure patient outcomes. Characterization of these mortality genes helped identify a set of T cell receptor signaling genes that may be of utility in predicting survival of heart failure patients. These data raise the possibility of prospectively risk stratifying patients with heart failure by integrating blood gene expression signatures with current clinical assessment.
ISSN:1094-8341
1531-2267
DOI:10.1152/physiolgenomics.00175.2010