|dc.description.abstract||Background Despite our growing understanding of the pathophysiology and
management of heart failure, there exist no strategies to individualize therapy using
predictors of long-term prognosis and response to therapy. Gene expression analysis
using microarray technology provides a phenotypic resolution not possible with standard
clinical criteria and could offer insights into disease mechanisms and also identify
markers useful for diagnostic, prognostic, and therapeutic purposes. Thus, the two major
applications of this technology are gene discovery and molecular signature analysis.
These two applications were explored in studies involving the two major forms of
cardiomyopathy, ischemic and nonischemic (ICM and NICM, respectively).
Methods For a gene discovery analysis, we compared the gene expression of 21 NICM
and 10 ICM samples with that of 6 nonfailing (NF) hearts using Affymetrix U133A
microarrays and Significance Analysis of Microarrays software. For molecular signature
analysis, we identified and validated an etiology signature with Prediction Analysis of
Microarrays software using 48 ICM and NICM myocardial samples obtained from
different institutions and at different clinical stages.
Results The gene discovery analysis demonstrated that compared to NF hearts, 257
genes were differentially expressed in NICM and 72 genes in ICM. Only 41 genes were
shared between the two comparisons and an analysis of the gene subsets revealed shared
and unique disease-specific gene expression between end-stage cardiomyopathy of
different etiologies. The molecular signature analysis demonstrated that an etiology
prediction profile accurately distinguished between ICM and NICM, was generalizable to
samples from separate institutions, specific to disease stage, and unaffected by
differences in clinical characteristics.
Conclusions We have demonstrated that there are shared and distinct genes involved in
the development of heart failure of different etiologies, and that a molecular signature can
accurately identify etiology in cardiomyopathy. These findings highlight the utility of the
two distinct applications of gene expression analysis, and support ongoing efforts to
develop cause-specific therapies and expression profiling-based biomarkers in heart
failure. The ultimate goal is individualized therapy, whereby a heart failure patient could,
through gene expression analysis, be offered an accurate assessment of prognosis, and
how individualized medical therapy could affect his or her outcome.||