Genetic Analysis in Translational Medicine: The 2010 GOLDEN HELIX Symposium

From genes to health - challenges and opportunities

In genome science, the advancement in high-throughput sequencing technologies and bioinformatics analysis is facilitating the better understanding of Mendelian and complex trait inheritance. Charting the genetic basis of complex diseases - including pediatric cancer, and interpreting huge amount of next-generation sequencing data are among the major technical challenges to be overcome in order to understand the molecular basis of various diseases and genetic disorders. In this review, we provide insights into some major challenges currently hindering a better understanding of Mendelian and complex trait inheritance, and thus impeding medical benefits to patients.

Single-variant and multi-variant trend tests for genetic association with next-generation sequencing that are robust to sequencing error

As with any new technology, next-generation sequencing (NGS) has potential advantages and potential challenges. One advantage is the identification of multiple causal variants for disease that might otherwise be missed by SNP-chip technology. One potential challenge is misclassification error (as with any emerging technology) and the issue of power loss due to multiple testing. Here, we develop an extension of the linear trend test for association that incorporates differential misclassification error and may be applied to any number of SNPs. We call the statistic the linear trend test allowing for error, applied to NGS, or LTTae,NGS. This statistic allows for differential misclassification. The observed data are phenotypes for unrelated cases and controls, coverage, and the number of putative causal variants for every individual at all SNPs. We simulate data considering multiple factors (disease mode of inheritance, genotype relative risk, causal variant frequency, sequence error rate in cases, sequence error rate in controls, number of loci, and others) and evaluate type I error rate and power for each vector of factor settings. We compare our results with two recently published NGS statistics. Also, we create a fictitious disease model based on downloaded 1000 Genomes data for 5 SNPs and 388 individuals, and apply our statistic to those data. We find that the LTTae,NGS maintains the correct type I error rate in all simulations (differential and non-differential error), while the other statistics show large inflation in type I error for lower coverage. Power for all three methods is approximately the same for all three statistics in the presence of non-differential error. Application of our statistic to the 1000 Genomes data suggests that, for the data downloaded, there is a 1.5% sequence misclassification rate over all SNPs. Finally, application of the multi-variant form of LTTae,NGS shows high power for a number of simulation settings, although it can have lower power than the corresponding single-variant simulation results, most probably due to our specification of multi-variant SNP correlation values. In conclusion, our LTTae,NGS addresses two key challenges with NGS disease studies; first, it allows for differential misclassification when computing the statistic; and second, it addresses the multiple-testing issue in that there is a multi-variant form of the statistic that has only one degree of freedom, and provides a single p value, no matter how many loci.

Institutional Profile: Golden Helix Institute of Biomedical Research: interdisciplinary research and educational activities in pharmacogenomics and personalized medicine

The Golden Helix Institute of Biomedical Research is an international nonprofit scientific organization with interdisciplinary research and educational activities in the field of genome medicine in Europe, Asia and Latin America. These activities are supervised by an international scientific advisory council, consisting of world leaders in the field of genomics and translational medicine. Research activities include the regional coordination of the Pharmacogenomics for Every Nation Initiative in Europe, in an effort to integrate pharmacogenomics in developing countries, the development of several national/ethnic genetic databases and related web services and the critical assessment of the impact of genetics and genomic medicine on society in various countries. Educational activities also include the organization of the Golden Helix Symposia(®), which are high-profile scientific research symposia in the field of personalized medicine and the Golden Helix Pharmacogenomics Days, an international educational activity focused on pharmacogenomics, as part of its international pharmacogenomics education and outreach efforts.