A team of genomic researchers has developed a computer program that enables them to screen the masses of data generated by genome-wide association studies (GWASs) in order to isolate specific gene variants (causal variants) linked to specific diseases.

The computational method, which is called the preferential linkage disequilibrium approach, was developed by molecular biologists and bioinformatics specialists at Duke University (Durham, NC, USA) and their collaborators at the Roswell Park Cancer Institute (Buffalo, NY, USA). The program tracks variants reported by GWASs, then cross-references those of interest against a comprehensive variant catalog generated through robust “next-generation” sequencing in order to pinpoint causal variants.

To confirm the validity of the approach the investigators applied it to the GWAS signals of five human traits for which the causal variants were already known. Results detailed in the August 30, 2012, issue of the American Journal of Human Genetics, revealed that they had successfully placed the known causal variants among the top ten candidates in the majority of the cases. Further application of this method to additional GWASs, including those of hepatitis C virus treatment response, plasma levels of clotting factors, and late-onset Alzheimer's disease, has led to the identification of a number of promising candidate causal variants.

“This approach helps to intergrade the large body of data available in GWASs with the rapidly accumulating sequence data,” said senior author Dr. David B. Goldstein, professor of molecular genetics and microbiology at Duke University.

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Roswell Park Cancer Institute