Published online before print August 5, 2004, doi: 10.1161/01.ATV.0000141358.65242.1f
© 2004 American Heart Association, Inc.
Atherosclerosis and Lipoproteins |
Gene Expression Phenotypes of Atherosclerosis
From the Division of Cardiology, Department of Medicine (D.S., T.W., C.D., K.V., R.S., P.J.G.-C.), the Department of Molecular Genetics and Microbiology (H.D., J.N.), the Division of Cardiothoracic Surgery, Department of Surgery (C.A.M.), and the Institute of Statistics and Decision Science (E.I., J.P., F.R., M.W.), Duke University, Durham, NC; and the Biomedical Engineering Center, Ohio State University (E.E.), Columbus, Ohio.
Correspondence to David Seo, Duke University Medical Center, Box 3163, Duke South, Durham, NC 27710. E-mail david.seo{at}duke.edu
Objective— Fulfilling the promise of personalized medicine by developing individualized diagnostic and therapeutic strategies for atherosclerosis will depend on a detailed understanding of the genes and gene variants that contribute to disease susceptibility and progression. To that end, our group has developed a nonbiased approach congruent with the multigenic concept of complex diseases by identifying gene expression patterns highly associated with disease states in human target tissues.
Methods and Results— We have analyzed a collection of human aorta samples with varying degrees of atherosclerosis to identify gene expression patterns that predict a disease state or potential susceptibility. We find gene expression signatures that relate to each of these disease measures and are reliable and robust in predicting the classification for new samples with >93% in each analysis. The genes that provide the predictive power include many previously suspected to play a role in atherosclerosis and additional genes without prior association with atherosclerosis.
Conclusion— Hence, we are reporting a novel method for generating a molecular phenotype of disease and then identifying genes whose discriminatory capability strongly implicates their potential roles in human atherosclerosis.
To improve our understanding of the genetic factors that influence atherosclerosis, we performed a genomic analysis of fresh human aorta. We have identified unique gene expression phenotypes that define disease state and, potentially, disease susceptibility, and we have generated a novel list of candidate genes for further study.
Key Words: clinical human atherosclerosis • genomic • gene expression profile • disease genetic susceptibility • molecular signature
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