Genetic Variation and Disease: GWAS

Genome-wide association studies (GWAS) represent a recently developed research technique with many implications on both a global and an individual scale. GWAS seek to identify the single nucleotide polymorphisms (SNPs, pronounced "snips") that are common to the human genome and to determine how these polymorphisms are distributed across different populations. On a broad scale, these studies help scientists uncover associations between individual SNPs and disorders that are passed from one generation to the next in Mendelian fashion. On a small scale, GWAS can be used to determine an individual's risk of developing a particular disorder. Although the impact of GWAS on medical genetics is undeniable, the true usefulness of these studies largely depends upon researchers' understanding of the interacting factors behind common genetic disorders.

With the completion of the Human Genome Project in 2003, researchers began to pinpoint areas of the genome that varied between individuals. Shortly thereafter, they discovered that the most common type of DNA sequence variation found in the genome is the single nucleotide polymorphism; in fact, there are an estimated 10 million SNPs that commonly occur in the human genome. A worldwide effort known as the HapMap Project seeks to identify and localize these and other genetic variants, and to learn how the variants are distributed within and among populations from different parts of the world. To date, the project has identified over 3.1 million SNPs across the human genome that are common to individuals of African, Asian, and European ancestry.

The HapMap information, which is available to the public, has facilitated a new type of research effort: the genome-wide association study (GWAS). In such a study, the distribution of SNPs is determined in hundreds or even thousands of people with and without a particular disease. By tallying which SNPs co-occur with disease symptoms, researchers can make a statistical estimate regarding the level of increased risk associated with each SNP. For instance, in a landmark 2007 study conducted in the United Kingdom, researchers identified people affected by seven common disorders, and they then genotyped 2,000 people in each disease category (for a total of 14,000 individuals studied). Next, these individuals were compared to 3,000 genotyped controls who did not have the disorders in question. As a result of these comparisons, the researchers were able to identify new genetic markers that point to an increased risk for multifactorial disorders such as heart disease and diabetes (Wellcome Trust Case Control Consortium, 2007). It was announced in July 2008 that this study will be expanded to include an additional 36,000 individuals and will focus on examining the genetic contributions to a total of 14 common disorders, as well as to individuals' responses to certain drugs.

Only a few years ago, a robust GWAS that genotyped thousands of individuals would have been prohibitively expensive. However, this is no longer the case thanks to the widespread use of an innovation known as the DNA microarray, which was first developed in the early 1990s. A DNA microarray (sometimes called a DNA chip) is a small glass slide with short DNA probes attached to it in a specific pattern. When a sample of fragmented DNA is washed over the microarray, pieces of this DNA hybridize to the chip and can then be detected by scanning software.

One manufacturer of DNA microarrays, Affymetrix, now offers a chip containing approximately 1.8 million different genetic markers. When a fragment of DNA from a test sample hybridizes to a probe on this microarray, the scanning software can document exactly which genetic marker is present in that DNA sample. This technology allows a single sample to be simultaneously queried for changes at almost 2 million known genetic variants (Figure 1).

The practicality of identifying a correlation between a genetic change and the incidence of a complex disease is limited to statistical estimation of increased risk for developing the disorder, rather than a hard-and-fast prediction. This is due to the significant number of genetic and environmental variables that interact to cause the onset of a complex disease. Therefore, any genetic variant, such as a SNP, makes only a small contribution to an individual's overall risk.

In most cases, findings from a GWAS cannot be directly applied to the prevention or treatment of disease. Rather, before doctors are able to recommend medicinal, behavioral, and environmental interventions based on a SNP profile, the full pathway of disease development and the involvement of all variables must be understood. For example, one situation that makes the link between SNPs and disease difficult to understand is the case in which a SNP is not located within an exon of a gene. In such instances, studies are required to investigate the possibility that the SNP lies in a promoter or enhancer region and somehow affects regulation of the causal gene.

Occasionally, the results of a GWAS seem relatively straightforward; this is often the case when a gene is identified that contains a variant that confers susceptibility to a multifactorial disorder (Steinthorsdottir et al., 2007). However, the effect of that variant or other alleles of the gene is still just one of many factors influencing disease risk; therefore, the predictive power of the various alleles is not absolute. A well-known example of this is the link between certain alleles of the apolipoprotein E (ApoE) gene found on chromosome 19 and the development of Alzheimer's disease. ApoE codes for a protein that helps carry cholesterol in the bloodstream, and it has three common alleles: e2, e3, and e4. Research has shown that having one or two copies of the ApoE e4 allele significantly increases a person's risk for developing Alzheimer's disease, but it does not guarantee development of this disorder. It also remains unclear how certain forms of ApoE influence cerebral plaque formation, the hallmark of Alzheimer's disease (National Institute on Aging, 2008).

Over the past few years, the scientific community has experienced a deluge of knowledge derived from the use of genome-wide association studies. As previously noted, because most SNPs are only partial contributors to an individual's risk for developing a disease, researchers must be cautious about giving too much weight to SNP profiles. Nonetheless, this has not deterred savvy entrepreneurs from capitalizing on existing GWAS research. For example, consumer genomics companies such as 23andMe, deCODE genetics, Navigenics, and Knome now offer a range of personal genotyping and sequencing services to clients who are interested in learning their estimated genome-based risk for developing a number of common disorders. Thus, for about U.S. $1,000, you can have your entire genome scanned for markers that have been identified by GWAS and receive personalized risk calculations that are updated as new knowledge becomes available.

In the coming years, social science research will reveal why people want this information, how well they understand the information they receive, and whether these risk assessments make a difference in patients' lives. One thing is certain, however: Personal genetic profiles will continue to increase in their medical value as researchers cultivate more and more knowledge about the genetic and environmental factors that interact to contribute to the development of common disorders.

Medical genetics has historically been a highly specialized field, and genome-wide association studies have played an important role in research to identify possible connections between SNPs and various disorders. Over time, researchers' knowledge of the genetic risk factors for disease has become more comprehensive, and this has made it possible to apply GWAS research to risk assessments for various disorders. It is important to understand, however, that GWAS are not absolute predictors of disease due to the role of environmental factors in complex disease development. Although the days of personalized medical care predicted by the planners of the Human Genome Project are drawing closer, that dream will only be realized through continued research into all of the many factors that contribute to complex disease susceptibility.