Association of a peripheral blood metabolic profile with coronary artery disease and risk of subsequent cardiovascular events.
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2010-04
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Abstract
BACKGROUND: Molecular tools may provide insight into cardiovascular risk. We assessed whether metabolites discriminate coronary artery disease (CAD) and predict risk of cardiovascular events. METHODS AND RESULTS: We performed mass-spectrometry-based profiling of 69 metabolites in subjects from the CATHGEN biorepository. To evaluate discriminative capabilities of metabolites for CAD, 2 groups were profiled: 174 CAD cases and 174 sex/race-matched controls ("initial"), and 140 CAD cases and 140 controls ("replication"). To evaluate the capability of metabolites to predict cardiovascular events, cases were combined ("event" group); of these, 74 experienced death/myocardial infarction during follow-up. A third independent group was profiled ("event-replication" group; n=63 cases with cardiovascular events, 66 controls). Analysis included principal-components analysis, linear regression, and Cox proportional hazards. Two principal components analysis-derived factors were associated with CAD: 1 comprising branched-chain amino acid metabolites (factor 4, initial P=0.002, replication P=0.01), and 1 comprising urea cycle metabolites (factor 9, initial P=0.0004, replication P=0.01). In multivariable regression, these factors were independently associated with CAD in initial (factor 4, odds ratio [OR], 1.36; 95% CI, 1.06 to 1.74; P=0.02; factor 9, OR, 0.67; 95% CI, 0.52 to 0.87; P=0.003) and replication (factor 4, OR, 1.43; 95% CI, 1.07 to 1.91; P=0.02; factor 9, OR, 0.66; 95% CI, 0.48 to 0.91; P=0.01) groups. A factor composed of dicarboxylacylcarnitines predicted death/myocardial infarction (event group hazard ratio 2.17; 95% CI, 1.23 to 3.84; P=0.007) and was associated with cardiovascular events in the event-replication group (OR, 1.52; 95% CI, 1.08 to 2.14; P=0.01). CONCLUSIONS: Metabolite profiles are associated with CAD and subsequent cardiovascular events.
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Shah, Svati H, James R Bain, Michael J Muehlbauer, Robert D Stevens, David R Crosslin, Carol Haynes, Jennifer Dungan, L Kristin Newby, et al. (2010). Association of a peripheral blood metabolic profile with coronary artery disease and risk of subsequent cardiovascular events. Circ Cardiovasc Genet, 3(2). pp. 207–214. 10.1161/CIRCGENETICS.109.852814 Retrieved from https://hdl.handle.net/10161/5964.
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Robert David Stevens
Elizabeth Rebecca Hauser
The incorporation of personalized medicine to all areas of human health represents a turning point for human genetics studies, a point at which the discoveries made have real implications for clinical medicine. It is important for students to gain experience in how human genetics studies are conducted and how results of those studies may be used. As a statistical geneticist and biostatistician my research interests are focused on developing and applying statistical methods to search for genes causing common human diseases. My research programs combine development and application of statistical methods for genetic studies, with a particular emphasis on understanding the joint effects of genes and environment.
These studies I work on cover diverse areas in biomedicine but are always collaborative, with the goal of bringing robust data science and statistical methods to the project. Collaborative studies include genetic and ‘omics studies of cardiovascular disease, health effects of air pollution, genetic analysis of adherence to an exercise program, genetic analysis in evaluating colon cancer risk, genetic analysis of suicide, and systems biology analysis of Gulf War Illness.
Keywords: human genetics, genetic association, gene mapping, genetic epidemiology, statistical genetics, biostatistics, cardiovascular disease, computational biology, diabetes, aging, colon cancer, colon polyps, kidney disease, Gulf War Illness, exercise behavior, suicide
Geoffrey Steven Ginsburg
Dr. Geoffrey S. Ginsburg's research interests are in the development of novel paradigms for developing and translating genomic information into medical practice and the integration of personalized medicine into health care.
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