Conference Summary

Clinical Applications for Technological Advances in Genetic Testing

Shelley D. Smith, PhD


December 11, 2009

In This Article

New Uses for GWAS

A number of GWAS analyses have found loci associated with type 2 diabetes, but the genes in those regions and the responsible mutations have not been determined. David Altshuler[7] of the Broad Institute in Cambridge, Massachusetts, emphasized that detection of the genes could identify new biological mechanisms for diabetes and that there may be differences between different populations. His group sequenced regulatory regions of genes in the areas targeted by GWAS and found rare variants that could be deleterious and that tend to occur on consistent haplotypes, which suggests that they come from a founder.

However, this method of using GWAS to identify regions for sequencing is still dependent upon the common SNPs in association with the disorder. As an alternative approach, linkage analysis using family data could be used in combination with association analysis because linkage is not dependent on a common SNP in disequilibrium with a causal mutation.

In another study of type 2 diabetes, Hua Zhong[8] of Rosetta Inpharmatics in Seattle, Washington, used knowledge of gene expression in mouse models of diabetes to select candidate genes highlighted by GWAS. The mouse model led Zhong and colleagues to additional genes in an "adipose network" that showed moderate significance in the GWAS, emphasizing that the most significant results of a GWAS might not be the only genes that are biologically significant. Once genes are selected for sequencing, though, the resulting mutations need to be evaluated, so these studies also brought out the need for better methods for distinguishing between benign and deleterious sequence variations.


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