The recent development of microarray platforms, capable of genotyping hundreds of thousands of single nucleotide polymorphisms (SNPs), has provided an opportunity to rapidly identify novel susceptibility genes for complex phenotypes. Studies employing genotyping microarrays have typically utilized a whole genome association (WGA) approach, in which each SNP is examined individually for association with disease. While this approach has resulted in several important breakthroughs in the past two years, it is biased towards detecting common alleles with additive effects. At the same time, structural properties of WGA datasets, including patterns of linkage disequilibrium (LD), have not yet been exploited in these analyses.

Consequently, Dr. Todd Lencz, Associate Director of Research at The Zucker Hillside Hospital, working in collaboration with Dr. Christophe Lambert of Golden Helix, has developed a novel analytic approach that first identifies patterned clusters of SNPs demonstrating extended homozygosity (runs of homozygosity or "ROHs") and then employs both genome-wide and regionally-specific statistical tests for association to disease. This approach can identify chromosomal segments that may harbor rare, penetrant recessive loci.

In a recent study published in the Proceedings of the National Academy of Sciences¹ (right), Dr. Lencz outlines the runs of homozygosity association methodology and how it was used to identify nine genetic risk loci for schizophrenia. Dr. Lencz used the Affymetrix 500K array for his study and had a modest sample size of approximately 300 case/controls.

This functionality is included with the Whole Genome Analysis Module and can be used in conjunction with HelixTree to identify runs of homozygous markers, create appropriate covariates and then perform necessary statistical tests for association.

References

1. Lencz, T., Lambert, C., DeRosse, D, Burdick, K., Morgan, T., Kane, J., Kucherlapati, R., Malhotra, A.: Runs of Homozygosity Reveal Highly Penetrant Recessive Loci in Schizophrenia. Proceedings of the National Academy of Sciences. Published online December 5, 2007.