NEW YORK (GenomeWeb News) – Genome-wide association studies over the past five years have identified hundreds of SNPs associated with diseases, but despite these advances few of the SNPs identified have clear functional implications relevant to mechanisms of disease, according to a review article published in the current issue of The New England Journal of Medicine.
According to the author of the article, Teri Manolio, director of the Office of Population Genomics at the National Human Genome Research Institute, nearly 600 genome-wide association studies covering 150 distinct diseases and traits have been published, with around 800 SNP-trait associations deemed significant. But the potential utility of many of these SNPs remains uncertain and questions must be answered before GWAS data can be routinely incorporated into clinical practice, she said.
"Although the approach has proved powerful in identifying robust associations between many SNPs and traits, much additional work is needed to determine the functional basis for the observed associations so that appropriate interventions can be developed," Manolio wrote.
Some GWAS studies have turned up associations that are consistent with the common-disease/common-variant hypothesis, such as in the case of age-related macular degeneration, in which five major variants are associated with a risk of disease that is two to three times the risk for a person without one of these variants. But other common conditions have not been as amenable to genome-wide associations. Manolio cites schizophrenia as an example, in which five GWAS failed to turn up any variants with genome-wide significance.
According to the review, only 12 percent of SNPs associated with traits are located in, or are in tight linkage equilibrium with, protein-coding regions of genes — even though genotyping arrays are "heavily over-represented" with SNPs in protein-coding regions. Roughly 40 percent of trait-associated SNPs have been found in intergenic regions, with another 40 percent found in noncoding introns.
"These two findings have sharpened the focus on the potential roles of intronic, and particularly intergenic, regions in regulating gene expression," Manolio wrote.
A primary challenge for researchers translating GWAS is that while trait-associated SNPs may reveal functional genetic variants, they are unlikely to be the causative variants, based on current understanding of genomic function and regulation. Though fine mapping has shown promise in identifying causal variants, according to Manolio, "its yield has been limited."
She cited the ongoing 1000 Genomes Project as being a potential aid in fine-mapping efforts, as that project is developing a comprehensive catalogue of SNPs with a prevalence of 1 percent to 5 percent. That would make up for a deficiency in current genome-wide association arrays, which lack a good representation of SNPs with a prevalence of less than 5 percent, she said.
Currently, know variants have explained little about the risk of disease occurrence to be of clinically useful predictive value, Manolio wrote, but as sample sizes in studies increase and more risk variants are found, the predictive value of cumulative genotypic scores will increase.
"Possible clinical uses of predictive scores — for example, in deciding which patients should be screened more intensely for breast cancer with the use of mammography or for statin-induced myopathy with the use of muscle enzyme assays — will require rigorous, preferably prospective, evaluation before being accepted into clinical practice," she said.
The uncertainty regarding the clinical utility of currently-known SNPs also should be considered by customers of the direct-to-consumer genomics firms. "Patients inquiring about genome-wide association testing should be advised that at present the results of such testing have no value in predicting risk and are not clinically directive," Manolio wrote.