The article nudged me to write a post because it reflects the challenge and opportunities created by two behemoths which like galaxies, are slowly colliding. Its addressing an area of growing interest because organisations are waking up to the value of having information that comes from existing datasets, generating targeted data, and looking within it to drive insight, rather than establishing an hypothesis and finding data to support or refute it.
In parallel, Schizophrenia studies, like the Psychiatric Genomics Consortium (PGC) boast 123,000 samples from people with a diagnosis of schizophrenia, bipolar disorder, ADHD, or autism and 80,000 controls collected by over 300 scientists from 80 institutions in 20 countries. Given the magnitude and complexity of these projects, it fast becomes clear that collaboration, data sharing and internal communication are powerful components i.e.: drivers of success in contrast to traditional innovation, insight and raw scientific discovery.
Other diseases are by no means on the sidelines. Although relatively rare, the debilitating and lethal neurodegenerative disorder Amyotrophic Lateral Sclerosis (ALS) is also on the "galactic plane". Combining resources at a global scale, Project Mine has generated over 5000 full genome sequences with a goal of completing another 10 000 within a year. Whole countries are sequencing their populations. Here in the UK the plan is to complete 100 000 genomes by 2017. In Qatar they will sequence 300 000, in USA the plan is to complete 1 million people's whole genomes. The tiniest nations are also on the plane - even the Faero Islands plan to complete 50 000 subjects and Iceland has just published the first 2000 whole genome sequences in their population. Although this sounds like a great deal, the means to adequately process and analyse these, and other large scale datasets is in its infancy. How can we analyse all this data? One way is the obvious route of training and education. We are part of a new National programme to establish graduate training in genome medicine. Offered here at Sheffield, the MSc makes a solid step towards beginning to understand the use of genome data for health.
In my view, Eric Shcadt currently leads the new field at the intersection between big data and genomics and medicine - at least in terms of vision. He has driven the development of multi-scale biological research projects that have captured thousands of genomes, clinical records, related datasets and drug profiles to launch a new form of highly networked big data medicine. The first really broadly accessible application of this is will be the launch of a new app together with Apple's health ecosystem Apple ResearchKit that will help doctors interpret medical data on an iPhone. What data is that? Simply put it's your lifestyle - how many steps you take, how many stairs you climb, your blood pressure, blood oxygen, when and where. Ultimately combining that with genomics and other health data means that apps in the future could have the potential to truly and effectively predict when you and you alone are most likely to die. Schadt calls his adventure the 'death app' - not a name that is likely to live long.
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