‘Omics’ has been a science buzzword for the past few years, as well as the butt of many jokes; a certain genomics center includes a badomics generator on its website, which puts the suffix on random words to create fake but strangely compelling journal publication titles. University of California, Davis professor Jonathan Eisen regularly announces ‘worst new omics word awards’ on his blog, past winners include ‘consciousome,’ nutrimetabonomics,’ and ‘sexome.’ Harvard geneticist Robert C. Green commented on the trend saying, “It sounds futuristic. It sounds computational. When you use the term ‘omics,’ it signals you are a new paradigm guy.”
Yet despite all the ridiculous words and ensuing mockery, the more scientifically validated omics (genomics, proteomics, metabolomics) are currently extremely valuable tools for biomedical research. These technologies are especially well suited for disease applications, as they allow a close study of the human body using many different angles (in this case genes, proteins, and metabolites). While I am particularly biased here, as omics are a fantastic way for attacking biological questions with chemical methods (my own personal favorite corner of science), the field holds true promise for the future of personalized medicine based on genome sequencing. The Human Genome Project was completed in 2003 and in the years following the words ‘personalized medicine’ have been thrown around quite a bit. Defined by the FDA as “providing the right patient with the right drug at the right time,” personalized medicine is most typically linked to the sequencing of an individual’s genome to look for genetic bio-markers. However while much discussed and promoted as the future of medicine, this level of healthcare has yet to reach the mainstream in part due to the cost, but also due to computational efforts needed to sequence genomes on a large scale.
Though for those fortunate enough to have access to the technology as well as advanced knowledge and understanding of complex biochemistry, self-analysis is a viable option. One of the most famous examples is Stanford University School of Medicine geneticist Michael Synder, who published his personal genomic sequence as well as an abundance of other personal omics data, termed as ‘integrative personal omics profile’ (iPOP), in a 2012 Cell paper. Contributing to what Baylor College of Medicine’s Richard Gibbs has jokingly called the ‘narciss-ome,’ Snyder took his blood approximately 20 times over the course of 14 months and diagnosed himself with Type 2 diabetes before he started to display obvious symptoms, and was also able to recognize the changes that occurred in his iPOP at the onset of viral infections. This required analyzing 3.2 billion DNA nucleotides to assess his genome during the time period and more than 3 billion blood molecules, clearly no easy feat. Yet the massive influx of personal data that Snyder’s iPOP yielded highlights the true strength of omics as a clinical diagnostics tool, and Snyder and others are working to make the platform more accessible to the public. Snyder himself commented in 2012, “Clinical interpretations are a lot of effort. People talk about the $1,000 genome. We’re not there yet—but we’ll get there. But it costs $20,000 or $30,000 to interpret that same genome properly, to go in and look at all of the variants and understand what they are doing. That’s the real bottleneck, as I see it, for personalized medicine right now.”
As of 2014 we are still quite far from the $1,000 genome and the level of healthcare envisioned by Snyder as he undertook his project, however we are slowly but definitely making the transition from narciss-omics to greater-good-omics (sorry, Professor Eisen). There are still ethical/privacy considerations, and data storage and structures to be contended with, but patient databases are slowly coming about. This year, a Chicago health system dipped its toe into genomic medicine, using online application Health Heritage to cull genetic information and match it with patient family history. It is not quite the ultimate omics profile that Snyder showed us to be capable of generating, but it’s a step in the right direction.
