Peeking Under the Peaks

Abstract

Family studies throughout the 1970s and 1980s documented the role of shared genetic factors in the familial aggregation of cardiovascular disease and its risk factors, including hypertension. These familial aggregation studies, however, do not identify and characterize the role of particular genes. Identification of the genes contributing to interindividual variation in disease risk may facilitate early identification of patients who are at elevated risk of cardiovascular disease before the onset of any clinical symptoms, development of more efficacious treatments by exploiting previously unidentified metabolic and physiological pathways, and the tailoring of particular treatments to patients who are most likely to respond on the basis of their genetic constitution. Cardiovascular disease risk and risk factor levels are controlled by complex interactions among numerous metabolic and physiological systems, as well as demographic and lifestyle factors. Because so many systems are involved, variation in a large number of genes can potentially influence interindividual variation in disease risk, and the impact of any one gene is likely to be small to moderate in size. Before the current revolution in genomic analyses, studies identifying genes contributing to cardiovascular disease risk were of 2 basic types: studies of rare inborn errors of metabolism and association studies of a priori biologic candidate genes. The former have proved very useful for the identification of novel pathways, but the frequencies of these conditions are very rare, so their contribution to the prevalence of disease in the general population is minimal. The latter have proven useful in a few cases, such as the apolipoprotein E polymorphism with plasma cholesterol levels and risk of myocardial infarction, but have been plagued by lack of consistency. Modern genomic analyses have provided 2 additional pathways to identify genes that may be contributing to disease risk: gene expression profiles and genome-wide linkage analyses. Nothing further …