10 Years Of GWAS Discovery: Biology, Function, And Translation

By Bio-IT World Staff

July 7, 2017 | Researchers have reflected on the 10-year anniversary of the experimental design of genome-wide association studies in a recent article in the American Journal of Human Genetics (DOI: http://dx.doi.org/10.1016/j.ajhg.2017.06.005).

The review was written by seven researchers, led by Peter Visscher from the Institute for Molecular Bioscience, University of Queensland in Brisbane, Australia.

“Application of the experimental design of genome-wide association studies (GWASs) is now 10 years old (young), and here we review the remarkable range of discoveries it has facilitated in population and complex-trait genetics, the biology of diseases, and translation toward new therapeutics,” Visscher and company write. “We predict the likely discoveries in the next 10 years, when GWASs will be based on millions of samples with array data imputed to a large fully sequenced reference panel and on hundreds of thousands of samples with whole-genome sequencing data.”

This is not the first review of the GWASs design. 5 years ago the same authors sought to clear up a few misunderstandings regarding the intentions of the discoveries of the GWASs. “There is now much more acceptance of the experimental design because the empirical results have been robust and overwhelming,” the authors say.

According to the review, GWASs’ results have been reported for hundreds of complex traits. These traits vary across a wide range of domains, from common diseases to quantitative traits. These results have also avoided the ambiguity that might come from the results of studies.

“One unambiguous conclusion from GWASs is that for almost any complex trait that has been studied, many loci contribute to standing genetic variation,” the authors wrote. “In other words, for most traits and diseases studied, the mutational target in the genome appears large so that polymorphisms in many genes contribute to genetic variation in the population. This means that, on average, the proportion of variance explained at the individual variants is small.”

The remainder of the review covers an array of topics, including the utility of GWAS-derived genetic predictors, common variants that tag a substantial proportion of additive genetic variance, and the public availability of GWAS data that has enabled novel research and discoveries.

The authors conclude by addressing the future of GWASs, making several observations and predictions. One such prediction involves GWASs by single nucleotide polymorphisms arrays being replaced by GWASs by whole genome sequencing, “particularly for quantitative traits and very common diseases.”

“For the future, the combination of whole-genome surveys of genetic variation and detailed phenotypic and -omics data on millions of individuals will be a treasure trove for making new fundamental discoveries in human genetics,” the authors write. “Some of those discoveries will be wholly unexpected, and others will detect or unravel biological mechanisms.”