CHICAGO—The outcomes of genome-wide association studies (GWAS) have not been what scientists expected, but researchers are developing new approaches to use revelatory GWAS information to identify genetic causal variants, predictors of treatment response, and future opportunities for genetic insight.
The ability to perform GWAS, developed in the past five years, has allowed the identification of genetic risk factors for systemic diseases. In addition, GWAS have pinpointed biologic constituents and treatment response predictors in the genetic components of both common and rare disorders. However, contrary to what scientists expected, GWAS have identified only a small number of the causal variants for recently identified genetic loci, which, in turn, interpret only a small part of the genetic contribution to these diseases.
The emerging limitations of GWAS are not a reason to halt these studies, however. “The good thing about genome-wide association studies is that they do what they are billed to do—that is, represent common genetic variation in the human genome—and they do it well,” said David B. Goldstein, PhD, Richard and Pat Johnson Distinguished University Professor and director of the Center for Human Genome Variation at Duke University in Durham, N.C. Dr. Goldstein addresses GWAS research and its application at the ACR State-of-the-Art Lecture, “Moving Forward in the Genome Wide Association Studies Era,” here at the 2011 ACR/ARHP Annual Scientific Meeting here in November. [Editor’s note: This session was recorded and is available via ACR SessionSelect at www.rheumatology.org.] On the other hand, “the variation in response, most of which cannot be explained, is motivation for doing serious genetics,” continued Dr. Goldstein.
To this end, researchers are developing new approaches to isolate and define causal variants and explore genetic features that affect disease. These new methods seek to explain the “missing heritability” of the GWAS and generate DNA sequencing approaches to identify causal genetic variants.
Gap between GWAS Findings and Identification of Causal Variants
GWAS use gene chips to scan the human genome, analyzing large amounts of DNA in many people to search for variants that are more common in cases than in controls. One underlying premise is that GWAS detect common variation in specific diseases that lead to genes causing the disease and later to individualized therapies. While GWAS have identified a multitude of single-DNA letter changes, so-called Mendelian disorders, associated with risk of many common diseases, in reality scientists have been unable to discover the specific genetic changes influencing these common conditions. “What we have in the main are signals that we can’t track to causal variants,” Dr. Goldstein said. “When we can’t track signals to causal variants, we have little biology from the signals because we don’t know what is causing the variants.”
