Gene Expression Phenotypes of Atherosclerosis

• Published in: Arteriosclerosis, thrombosis, and vascular biology Vol. 24; no. 10; pp. 1922 - 1927
• Main Authors: Seo, David, Wang, Tao, Dressman, Holly, Herderick, Edward E, Iversen, Edwin S, Dong, Chunming, Vata, Korkut, Milano, Carmelo A, Rigat, Fabio, Pittman, Jennifer, Nevins, Joseph R, West, Mike, Goldschmidt-Clermont, Pascal J
• Format: Journal Article
• Language: English
• Published: Philadelphia, PA American Heart Association, Inc 01.10.2004; Hagerstown, MD Lippincott
• Subjects: Aorta, Thoracic - chemistry; Aorta, Thoracic - metabolism; Aorta, Thoracic - pathology; Arteriosclerosis - genetics; Arteriosclerosis - pathology; Associated diseases and complications; Atherosclerosis (general aspects, experimental research); Biological and medical sciences; Blood and lymphatic vessels; Cardiology. Vascular system; Cluster Analysis; Diabetes. Impaired glucose tolerance; Diseases of the peripheral vessels. Diseases of the vena cava. Miscellaneous; Endocrine pancreas. Apud cells (diseases); Endocrinopathies; Gene Expression Profiling - methods; Gene Expression Profiling - statistics & numerical data; Gene Expression Regulation - genetics; Genes - physiology; Humans; Medical sciences; Oligonucleotide Array Sequence Analysis - methods; Oligonucleotide Array Sequence Analysis - statistics & numerical data; Phenotype; Predictive Value of Tests; Vascular disease; Human; Phenotype; clinical human atherosclerosis; disease genetic susceptibility; genomic; Atherosclerosis; Cardiovascular disease; gene expression profile; molecular signature; Gene expression; Genetic disease
• ISSN: 1079-5642; 1524-4636
• DOI: 10.1161/01.ATV.0000141358.65242.1f

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.