Atherosclerosis: The Path From Genomics to Therapeutics
Atherosclerosis: The Path From Genomics to Therapeutics
Recent rapid advances in genomic tools and techniques hold great promise for transforming the practice of cardiovascular medicine. Resources including the Human Genome Project and the International HapMap project, major technological advances in high-throughput genotyping and methods of statistical analysis, and methods for high-throughput gene expression and small molecule profiling allow researchers to confront issues that will fundamentally change the practice of cardiovascular medicine during the 21st century. Genomic, proteomic, and metabolomic studies of complex cardiovascular diseases such as atherosclerosis will bridge epidemiology and basic biology, and promise increased understanding of cardiovascular disease processes. Genetic approaches applied to atherosclerosis will continue to identify genes and pathways involved in the predisposition to and pathophysiology of atherosclerosis. Gene expression profiling refines our understanding of the dynamic nature of the atherosclerotic vascular wall and promises discovery and validation of targets for therapeutic intervention. Opportunities to translate genetic, genomic, proteomic, and metabolomic information into cardiovascular clinical practice have never been greater, but their fruition requires validation in large independent cohorts, achieved only through collaborative effort. Their continued success will depend on ongoing cooperation within the cardiovascular research community. (J Am Coll Cardiol 2007;49:1589–99) © 2007 by the American College of Cardiology Foundation
This state-of-the-art review focuses on research that applies major technological developments in genomic medicine to atherosclerotic cardiovascular disease. High-throughput technologies facilitate identification of genetic, genomic, proteomic, and metabolomic markers of coronary artery disease (CAD) risk that may find a place in clinically useful prediction algorithms. Such risk models would augment the utility of established clinical tools such as the Framingham risk score. However, putative genomic, proteomic, and metabolomic markers will require the same rigor in application as other epidemiologic markers. Ultimately, the translation of such information to clinical practice should enhance "personalized medicine." The coupling of information gained through genomic, proteomic, and metabolomic methodologies to traditional tools should sharpen our ability to assess and modify management of cardiovascular disease.
Despite steady progress, atherosclerotic cardiovascular disease remains a growing public health burden in developed countries, and advances in cardiovascular research will not realize their full impact unless translated to care of individual patients. Hope for determining new therapeutic targets in atherosclerosis increasingly rests on research progress in genetic studies, expression profiling, and proteomics. Combining new markers of cardiovascular disease with currently available screening tools promises to promote this translational process.
Before a personalized medicine approach to atherosclerosis based on genomics, proteomics, and metabolomics can become reality, researchers must validate novel markers across different cohorts and in relation to various environmental modifiers. The operation of intricate networks of genes, environmental factors, and gene-by-environment interactions further complicates our understanding of the genetic components of atherosclerosis. Combined genomic approaches, often called genomic convergence, are necessary in atherosclerosis research.
Technological revolutions in genetics and genomics have facilitated 2 major approaches to understanding disease pathogenesis and risk. First, the Human Genome Project and International HapMap Project now allow us to obtain with relative speed vast amounts of deoxyribonucleic acid (DNA)-based information applicable to research subjects with atherosclerotic cardiovascular disease. Second, current technology enables collection of information on expression for thousands of genes in vascular cells and tissues under different conditions. The human DNA sequence laid the groundwork for studies of genetic susceptibility to disease, and expression databases assist definition of disease subtypes and variance related to environmental interactions. Although currently less mature technologies, proteomic and metabolomic studies promise to complement genomic approaches. Table 1 compares advantages and disadvantages of methods for marker identification.
A patient-specific risk profile for cardiovascular disease generated by knowledge of the genetic underpinnings of human disease risk would likely assist the clinician in providing targeted interventions, e.g., drugs that act on only a subset of the population or avoiding particular environmental exposure known to interact with a genetic variant. Both examples illustrate personalized medicine. Although current technology enables researchers to amass huge amounts of genomic data in a relatively short time frame, translation to the clinic will require demonstrated effects on outcomes. Indeed, the bottleneck for translation of genomic medicine to everyday practice lies at that intersection of knowledge.
Recent rapid advances in genomic tools and techniques hold great promise for transforming the practice of cardiovascular medicine. Resources including the Human Genome Project and the International HapMap project, major technological advances in high-throughput genotyping and methods of statistical analysis, and methods for high-throughput gene expression and small molecule profiling allow researchers to confront issues that will fundamentally change the practice of cardiovascular medicine during the 21st century. Genomic, proteomic, and metabolomic studies of complex cardiovascular diseases such as atherosclerosis will bridge epidemiology and basic biology, and promise increased understanding of cardiovascular disease processes. Genetic approaches applied to atherosclerosis will continue to identify genes and pathways involved in the predisposition to and pathophysiology of atherosclerosis. Gene expression profiling refines our understanding of the dynamic nature of the atherosclerotic vascular wall and promises discovery and validation of targets for therapeutic intervention. Opportunities to translate genetic, genomic, proteomic, and metabolomic information into cardiovascular clinical practice have never been greater, but their fruition requires validation in large independent cohorts, achieved only through collaborative effort. Their continued success will depend on ongoing cooperation within the cardiovascular research community. (J Am Coll Cardiol 2007;49:1589–99) © 2007 by the American College of Cardiology Foundation
This state-of-the-art review focuses on research that applies major technological developments in genomic medicine to atherosclerotic cardiovascular disease. High-throughput technologies facilitate identification of genetic, genomic, proteomic, and metabolomic markers of coronary artery disease (CAD) risk that may find a place in clinically useful prediction algorithms. Such risk models would augment the utility of established clinical tools such as the Framingham risk score. However, putative genomic, proteomic, and metabolomic markers will require the same rigor in application as other epidemiologic markers. Ultimately, the translation of such information to clinical practice should enhance "personalized medicine." The coupling of information gained through genomic, proteomic, and metabolomic methodologies to traditional tools should sharpen our ability to assess and modify management of cardiovascular disease.
Despite steady progress, atherosclerotic cardiovascular disease remains a growing public health burden in developed countries, and advances in cardiovascular research will not realize their full impact unless translated to care of individual patients. Hope for determining new therapeutic targets in atherosclerosis increasingly rests on research progress in genetic studies, expression profiling, and proteomics. Combining new markers of cardiovascular disease with currently available screening tools promises to promote this translational process.
Before a personalized medicine approach to atherosclerosis based on genomics, proteomics, and metabolomics can become reality, researchers must validate novel markers across different cohorts and in relation to various environmental modifiers. The operation of intricate networks of genes, environmental factors, and gene-by-environment interactions further complicates our understanding of the genetic components of atherosclerosis. Combined genomic approaches, often called genomic convergence, are necessary in atherosclerosis research.
Technological revolutions in genetics and genomics have facilitated 2 major approaches to understanding disease pathogenesis and risk. First, the Human Genome Project and International HapMap Project now allow us to obtain with relative speed vast amounts of deoxyribonucleic acid (DNA)-based information applicable to research subjects with atherosclerotic cardiovascular disease. Second, current technology enables collection of information on expression for thousands of genes in vascular cells and tissues under different conditions. The human DNA sequence laid the groundwork for studies of genetic susceptibility to disease, and expression databases assist definition of disease subtypes and variance related to environmental interactions. Although currently less mature technologies, proteomic and metabolomic studies promise to complement genomic approaches. Table 1 compares advantages and disadvantages of methods for marker identification.
A patient-specific risk profile for cardiovascular disease generated by knowledge of the genetic underpinnings of human disease risk would likely assist the clinician in providing targeted interventions, e.g., drugs that act on only a subset of the population or avoiding particular environmental exposure known to interact with a genetic variant. Both examples illustrate personalized medicine. Although current technology enables researchers to amass huge amounts of genomic data in a relatively short time frame, translation to the clinic will require demonstrated effects on outcomes. Indeed, the bottleneck for translation of genomic medicine to everyday practice lies at that intersection of knowledge.
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