Personalized Medicine and the Genetics of Disease
A trio of commentaries published online by the New England Journal of Medicine tackles an argument that has been heating up among geneticists. It looks at the usefulness of the genome-wide association studies (GWAS) that have become ubiquitous in genetics in the last few years. While such studies have identified more than 300 genetic variations linked to common diseases and other traits, taken together, they account for a relatively small proportion of the genetic risk of disease.
I explored what this might mean for personalized medicine in a feature in our January issue, “Interpreting the Genome.”
The latest data suggest that even the most common heritable illnesses, such as diabetes and heart disease, are linked to many different variants, each of them relatively rare. If that’s true, then practicing personalized medicine could become very complicated–and very expensive. “It would not be good to have a $5,000 genome and a $500,000 analysis,” says Francis Collins, the former director of the National Human Genome Research Institute and a leader of the Human Genome Project.
Thanks to relatively cheap microarrays that allow scientists to quickly scan the genome for specific variations linked to disease, researchers around the globe have been gathering data on tens of thousands of individuals with common genetic diseases, such as diabetes. With huge numbers of people in these studies, scientists can search for genetic variations that have subtler effects on disease.
Some scientists, including David Goldstein, who wrote one of the commentaries in the NEJM, argue that this approach has outlived its utility:
[It’s] hard to have any enthusiasm for conducting genome scans with the use of ever larger cohorts after a study of the first several thousand subjects has identified the strongest determinants among common variants. These initial studies for a given common disease are worth doing, since common variants do appear to explain a sizable fraction of the heritability of certain conditions–notably, exfoliation glaucoma, macular degeneration, and Alzheimer’s disease. Beyond studies of this size, however, we enter the flat or declining part of the effect-size distributions, where there are probably either no more common variants to discover or no more that are worth discovering.
Joel Hirschhorn, author of an opposing commentary, argues that a similar debate took place when GWAS were just getting started, and that the outcome of these studies was much better than naysayers predicted. He also counters arguments that the results of these studies will have little impact on personalized medicine:
The main goal of these studies is not prediction of individual risk but rather discovery of biologic pathways underlying polygenic diseases and traits …
Critically, genomewide association studies have also highlighted pathways whose relevance to a particular disease or trait was previously unsuspected. The genetic variants that are associated with age-related macular degeneration strongly implicate components of the complement system, the loci associated with Crohn’s disease point unambiguously to autophagy and interleukin-23-related pathways, and the height loci include genes encoding chromatin proteins and hedgehog signaling. This clustering into biologic pathways is highly nonrandom (as has been demonstrated by Raychaudhuri and Daly). Already, efforts are under way to translate the new recognition of the role of autophagy in Crohn’s disease into new therapeutic leads. As more pathways are highlighted and additional hypotheses emerge, new projects can be born.
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