More effort and investment needed to reap benefits of genomics, says study

Image courtesy US NHGRI

In addition, there is a need to develop mechanisms of responsible data sharing to accelerate the translation of knowledge into patient benefits.

Genome-wide association studies have become an important new tool for deciphering the role of genetics in human biology and disease. A study of more than 15,000 schizophrenia sufferers published last week, for example, uncovered 35,000 genetic variants that are associated with the condition, and also pointed to similarities with bipolar disease, confounding accepted medical wisdom that the two are not related.

Such findings are having an impact on drug discovery and development, since they highlight that in common, complex diseases it is unlikely that one single target will lead to a one-size-fits-all therapeutic solution.

John Bell, President of the Academy of Medical Sciences, said, “Comparing genetic differences between very large numbers of people is providing a better understanding of health and disease, and identifying important new routes to treatment. To do this work, researchers need access to large collections of tissue samples and patient data.”

“As well as increasing our understanding of many common diseases, Genome Wide Association Studies could identify genetic variations that impact on how individuals respond to drugs, laying the groundwork for an era in which the current ‘one-size-fits-all’ approach to drug treatment will give way to more effective, tailored strategies.”

To fulfill this potential, the report argues that robust mechanisms are needed to promote responsible data sharing amongst researchers in academia, industry and hospitals. Pooling knowledge will maximise the value of GWA studies, prevent duplication of research, and greatly accelerate translation to better healthcare, says the report.

The report also argues that the pace of discovery will accelerate further as the cost of genome sequencing continues to fall and second generation GWA studies are developed. There is an urgent need to build capacity in bioinformatics expertise, statistical methods and computational infrastructure to process the enormous amount of sequence data that will be generated, says the report.

The report also stresses that the biological pictures being revealed by GWA studies are still incomplete. Moving from identifying a genetic association with a disease, to understanding the underlying biology will require much greater integration of the historically distinct approaches of genetic mapping, epidemiology and pathophysiology.