A recent paper published in Nature by Decode Genetics discussed the discovery of a version of a common SNP correlated with susceptibility to type 2 diabetes.
According to the team, which also included British researchers, the impact of the T2D variant, located on chromosome 11, depends on descent: If the SNP is inherited from the father, the risk of developing type 2 diabetes increases by 30 percent, but if it is inherited maternally, the risk is 10 percent lower compared to the version of the variant that is not associated with the SNP.
The finding highlights the importance of taking parental origin into account when conducting genome-wide association studies, and could provide an approach for doing in other studies based on Illumina microarrays, genealogical data, and statistical tools that Decode has developed, according to the firm.
The issue of what role path-of-descent plays in interpreting GWAS findings has been discussed both in scientific literature and at recent conferences. For instance, several investigators interviewed by BioArray News at the Human Genome Variation and Complex Genome Analysis meeting in September 2009 mentioned parent-of-origin as a factor that needed to be taken into account when conducting association studies (see BAN 9/15/2009).
While researchers are aware of the potential role parent-of-origin plays, many simply do not have access to such data for the sample sets they wish to interrogate. Decode CEO and paper co-author Kari Stefansson told BioArray News this week that this is the primary reason that line-of-descent has not factored as strongly in interpreting GWAS findings.
Taking parent-of-origin into account "requires significant data and know-how to do so, capabilities that most research institutions simply do not have at present," Stefansson said. "One has to have genotypic information not only on a large number of individuals, but also, by definition, to be able to determine which genotypes were inherited through the maternal and paternal lineages. This requires either deep cohorts or the ability to impute the missing data."
For this specific study, Decode and researchers from Landspitali University Hospital in Reykjavik, the University of Iceland, and the University of Cambridge genotyped 38,167 Icelanders using Illumina HumanHap300 or CNV370 BeadChips. To determine the parental origin of most alleles, the researchers used a combination of genealogy and long-range phasing. They then focused on SNPs associated with diseases that are within 500 kilobases of known imprinted genes, according to the paper.
Seven independent SNP associations were examined. Five — one with breast cancer, one with basal-cell carcinoma, and three with type 2 diabetes — have parental-origin-specific associations, the authors wrote. Additionally, an association between the SNP rs2334499 at 11p15 and type 2 diabetes was observed.
According to Stefansson, Decode's access to a large population bank and genealogical records put it in a position where it could account for parent-of-origin in this study.
"Some 60 percent of the adult population of Iceland is taking part in one or more of our gene-discovery projects," he said. "We therefore have very detailed genotypic data on many tens of thousands of individuals whose DNA we have analyzed using high-density arrays.
"But we also have the genealogies that link all of these individuals together, and have developed statistical algorithms for imputing or predicting genotypes back through the genealogies for those for whom we do not have the same level of genotypic data," he said. "We can correlate phenotypes with the parental origin of virtually any marker in the genome."
Using Illumina chips, Decode's technique could conceivably be implemented by other researchers with access to similar sample sets and records. Stefansson noted, however, that he believes the firm will "have an advantage in the discovery and intellectual property areas using this approach, as few other groups now have comparable capabilities."
He also said that the company will make use of the technique to add content to its diagnostic tests and the personal genome scans offered through its DecodeMe direct-to-consumer testing service.
"One of the next big challenges in understanding the genetic risk factors for common diseases, and bringing clinically relevant testing into even wider medical practice, is to build upon GWAS discoveries of common variants contributing relatively modest increases in risk of disease and to identify the rarer variants that substantially increase individual risk," Stefansson said.
He added that in the future it will "likely be necessary to sequence the entire genome of large study cohorts, a task that is still prohibitively expensive. However, because we can impute sequence data using our genealogies, either archival or molecular, we can multiply by approximately 100 times the amount of data we can generate by sequencing one individual. For this reason we believe that we will be able to conduct very large studies to find rare variants before it becomes economically feasible for most others to do so."