Identification of a gene expression profile that differentiates between ischemic and nonischemic cardiomyopathy.
BACKGROUND
Gene expression profiling refines diagnostic and prognostic assessment in oncology but has not yet been applied to myocardial diseases. We hypothesized that gene expression differentiates ischemic and nonischemic cardiomyopathy, demonstrating that gene expression profiling by clinical parameters is feasible in cardiology.


RESULTS
Affymetrix U133A microarrays of 48 myocardial samples from Johns Hopkins Hospital (JHH) and the University of Minnesota (UM) obtained (1) at transplantation or left ventricular assist device (LVAD) placement (end-stage; n=25), (2) after LVAD support (post-LVAD; n=16), and (3) from newly diagnosed patients (biopsy; n=7) were analyzed with prediction analysis of microarrays. A training set was used to develop the profile and test sets to validate the accuracy of the profile. An etiology prediction profile developed in end-stage JHH samples was tested in independent samples from both JHH and UM with 100% sensitivity and 100% specificity in end-stage samples and 33% sensitivity and 100% specificity in both post-LVAD and biopsy samples. The overall sensitivity was 89% (95% CI 75% to 100%), and specificity was 89% (95% CI 60% to 100%) over 210 random partitions of end-stage samples into training and test sets. Age, gender, and hemodynamic differences did not affect the profile's accuracy in stratified analyses. Select gene expression was confirmed with quantitative polymerase chain reaction.


CONCLUSIONS
Gene expression profiling accurately predicts cardiomyopathy etiology, is generalizable to samples from separate institutions, is specific to disease stage, and is unaffected by differences in clinical characteristics. This strongly supports ongoing efforts to incorporate expression profiling-based biomarkers in determining prognosis and response to therapy in heart failure.
Kittleson
Michelle M
MM
Department of Medicine, Division of Cardiology, Johns Hopkins University School of Medicine, Baltimore, Md, USA.
Ye
Shui Q
SQ
Irizarry
Rafael A
RA
Minhas
Khalid M
KM
Edness
Gina
G
Conte
John V
JV
Parmigiani
Giovanni
G
Miller
Leslie W
LW
Chen
Yingjie
Y
Hall
Jennifer L
JL
Garcia
Joe G N
JG
Hare
Joshua M
JM
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D009202:Cardiomyopathies / Q000145:classification / Q000175:diagnosis* / Q000209:etiology / Q000235:genetics*; D002455:Cell Division / Q000235:genetics; D003598:Cytoskeletal Proteins / Q000096:biosynthesis / Q000235:genetics; D003937:Diagnosis, Differential; D005240:Feasibility Studies; D005260:Female; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D006801:Humans; D008297:Male; D008875:Middle Aged; D009124:Muscle Proteins / Q000096:biosynthesis / Q000235:genetics; D017202:Myocardial Ischemia / Q000150:complications* / Q000235:genetics; D020411:Oligonucleotide Array Sequence Analysis; D016133:Polymerase Chain Reaction; D011237:Predictive Value of Tests; D012680:Sensitivity and Specificity; D015398:Signal Transduction / Q000235:genetics
D003598:Cytoskeletal Proteins; D009124:Muscle Proteins