EDITORIAL COMMENT
Gaining Insights in Coronary Disease Genomics*
Sarah S. Murray, PhD* and
Eric J. Topol, MD, FACC
Scripps Genomic Medicine, Scripps Health, and the Scripps Research Institute, La Jolla, California.
* Reprint requests and correspondence: Dr. Sarah S. Murray, Scripps Genomic Medicine, 3344 North Torrey Pines Court, Suite 300, La Jolla, California 92037. (Email: murray.sarah{at}scrippshealth.org).
With coronary artery disease (CAD) being the leading cause of death worldwide, new strategies for prevention are desperately needed (1–3). Although we are still in the early phase of understanding the genomic basis of complex disease traits, there have been meaningful advances in identifying genomic markers of susceptibility for CAD and over 30 diseases in the past year. This explosion of discoveries of low-penetrant, common susceptibility alleles have been gleaned from whole-genome association studies (4). Such studies are hypothesis-free and analyze up to 1 million single nucleotide genomic markers, leading to the potential of statistically incontrovertible associations of disease phenotypes to genetic markers. The greatest benefit to date has been identification of key pathways that underlie disease, which were previously not conceived or known. The incredible pace of discovery continues with anticipated findings for many cancers, cardiovascular, and neurologic diseases. In aggregate, these studies have the potential to radically change medicine (4).
Two genomewide association studies recently identified a common variant in chromosome 9p21 that increased the risk of myocardial infarction (5) and advanced coronary heart disease (defined as disease requiring coronary artery bypass grafting or percutaneous coronary intervention) (6). Later, 2 additional studies also confirmed significant association to this region of the genome for coronary artery disease (7,8). The common variant is located  115 kb from 2 tumor suppressor genes, CDKN2A and CDKN2B, but whether the variant and these genes are related in any way remains unknown. Helgadottir et al. (9) expanded their initial study and investigated the role of 9p21-associated variants to other arterial diseases and determined that the same locus was also associated with abdominal aortic aneurysm and intracranial aneurysm. This finding shed some insight into the possible mechanism of disease and indicated that the variant was not only associated with atherosclerotic diseases but with other vascular diseases characterized by lack of integrity of the vessel wall. A second variant associated with type II diabetes (10–12) is located only 10 kb from the CAD-associated variant. However, it is in a different haplotype block and is not associated with CAD and is hypothesized to have an independent function (9).
In this issue of the Journal, there are 2 studies that have investigated the role of genetic variants to susceptibility and/or progression of cardiovascular disease in large cohorts. In the first study, Ye et al. (13) report on the role of variants in 9p21 on both susceptibility and progression of atherosclerosis in a population-based prospectively collected cohort. Prior to this study, the risk conferred by variants in 9p21 was estimated from cross-sectional studies of disease versus control groups. True risk assessment in the general population is best estimated from large population-based, prospective studies (14), which also enable the investigation risk alleles and disease progression. Ye et al. (13) report, for the first time, that the same 9p21 variant is also associated with progression of atherosclerosis in this cohort and provides additional insight into the mechanism of disease. The study confirms the 9p21 association findings of the genomewide studies and estimates the hazard ratio to be 1.35 for each copy of the risk allele.
In the second study, Stene et al. (15) report on a functional promoter variant in the zinc finger protein 202 (ZNF202) gene and its association with atherosclerosis and ischemic heart disease. ZNF202 is a candidate gene for CAD as it is involved in pathways for blood vessel maintenance and lipid metabolism. Following demonstration of association with atherosclerosis and ischemic heart disease, a large prospective study was undertaken. This demonstrated a hazard ratio of 1.2 for individuals carrying 2 copies of the risk allele. They replicated the association to ischemic heart disease in 2 additional cross-sectional studies and also demonstrated evidence that the associated variant in the promoter region of ZNF202 reduces the functional activity as measured by reduced transcriptional activity.
The flood of new genomic markers associated with diseases has engendered significant challenges. These include the lack of establishing any cause and effect relationship or mechanism for the variant, and the lack of even identifying which particular base pair in a given incriminated bin in the genome is actually the culprit. Because any variant discovered to be associated with complex disease traits, by definition, will not be necessary and sufficient to cause disease by itself, there are many approaches to understanding the role of newly found genetic components to disease. All risk variants found using the genome-wide association study design to date have used cross-sectional data. One approach to gain insight is to use a prospective study design to understand the risk variant's cumulative risk and effect on disease progression. Both studies presented in this issue of the Journal used a prospective study design to better predict population risk and, in the case of the Ye et al. (13) study, to understand a risk variant's role in disease progression. There are very few examples where risk variants have been linked to disease progression. Age-related macular degeneration provides an example of a complex disease where much of the genetic contribution has been elucidated. In 1 of the few examples, Seddon et al. (16) have provided unique insights into age-related macular degeneration and disease progression as a result of 2 risk variants in complement factor H and LOC387115. The discovery of gain-of-function complement factor variants as a root cause of age-related macular degeneration has led to clinical trials testing complement factor inhibitors, which hold considerable promise as a new way to slow the progression of the condition. Another strategy is to look at the interaction of multiple genetic variants on the risk, either in prospective or cross-sectional study designs. Recently, there have been 2 studies that have begun to look at multiple genetic variants to determine aggregate risk factors. Kathiresan et al. (17) used prospective data to determine time to first cardiovascular disease event in relation to genotype score across 9 SNPs associated with low-density lipoprotein or high-density lipoprotein cholesterol. Zheng et al. (18) used cross-sectional data to determine cumulative association with prostate cancer by evaluating 16 SNPs in 5 chromosomal regions. Finally, another direction is to understand the variant's function and influence on the final outcome of disease. Because many of these newly discovered variants are not in coding or even gene regions, this is a challenging prospect. Stene et al. (15) studied a polymorphism in the promoter region of ZFP202 and were able to demonstrate differences in transcriptional activity in vitro. For the numerous risk alleles not in obvious coding or regulatory regions, as is the case in the 9p21 region, the search for the variant's disease etiology has proven to be challenging thus far. For these types of variants, understanding the potential role of these variants in regulatory, structural, or epigenetic mechanisms may be required to get a more complete picture.
These newly discovered risk variants in or near genes can lead to new insights into disease pathology. Type II diabetes provides a good example. Currently there are at least 16 genes with highly associated and replicated variants to this disorder (19). The 16 genes are involved in several different pathways, potentially indicating that perturbations in any of these pathways (or combinations of pathways) can lead to a common outcome. These genes are involved in a variety of mechanisms such as insulin secretion, insulin transport, binding of zinc to insulin, insulin clearance, beta-cell function, and pancreatic development (20).
Ultimately, understanding the multiple mechanisms leading to disease pathologies can lead to new drug targets and more efficacious therapies. In addition, elucidating the disease risk based on a collective set of variants can lead to tools for individual prediction of disease and therapeutic response. Although the work and science that needs to still be done for coronary disease genomics is remarkable, these 2 studies have helped to provide some incremental insights.
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Footnotes
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* Editorials published in the Journal of the American College of Cardiology reflect the views of the authors and do not necessarily represent the views of JACC or the American College of Cardiology. 
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References
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