Is The Quest For A Cheaper Genome Putting The Cart Before The Horse?

The genomic revolution is at hand. Since the human genome project was completed two decades ago for $2.7 billion, the cost of sequencing the human genome – reading (almost) every ‘genetic letter’ of a person’s DNA code – has dropped to around $560. Soon, it may cost as little as $100. This is largely thanks to advances in next-generation sequencing, which involves splitting the DNA into an ever-increasing number of tiny fragments, reading them in parallel, and then piecing the full sequence back together.

Such a cheap genome could make genome sequencing affordable or even free for most people. In much the same way that investing in disease prevention (such as vaccination programs and screening) can save money later down the line, so too could genome sequencing. According to famed Harvard geneticist George Church, preconception genetic screening (to determine a couple’s risk of having a child with a genetic disease) would pay for itself. He also argues that it’s in the best interest of health insurance companies to cover the costs of genome sequencing.

The term ‘$100 genome’ may be somewhat misleading, because while the sequencing of the genome itself may only cost $100, this genetic data by alone is not useful to the patient. Someone has to interpret the data, then someone has to communicate that interpretation to the patient so that they can make properly informed decisions in the case where genetic risk factors are detected. There may then be further costs of medical care, whether in the form of close monitoring or preventative treatments. This is all assuming that time is not of the essence. Sometimes, a doctor might need answers immediately to help save a critically ill patient, in which case the sequencing will be considerably more expensive.

Another problem is that we are still rather limited in what we can actually do with a person’s genome. Sometimes, a single genetic variant can dramatically increase the risk or even guarantee the development of certain diseases. Classic examples include mutations in the BRCA1 and BRCA2 genes, which can dramatically increase the risk of multiple cancers. In such cases, genome sequencing can be life-saving.

Unfortunately, the vast majority of diseases are linked with many genes that interact with each other and with the environment in complex ways. Schizophrenia, for example, has been associated with over 100 different genes. It is estimated that 22% of the population have at least one such mutation, but show no signs of the disorder. Meanwhile, if an identical twin has schizophrenia, the other twin only has it around 50% of the time. Currently, we don’t really understand how these genetic and environmental factors come together to determine someone’s risk of developing most diseases – at least, not well enough to make effective use of their genome sequence.

Tools such as machine learning may eventually help us solve this problem, but this will take time. Until then, we’re going to be stuck with a lot of genetic data that we don’t know how to use. That raises some ethical concerns as well: what information lies buried in our genetic code now that we might uncover 10, 20 or 30 years down the line? Who stores and guards that information, and for how long?

More affordable genome sequencing isn’t a bad thing – as already discussed, there will be some immediate applications. It also means that as soon as we do figure out how to use our genetic information more effectively, many people will already have had their genomes sequenced, or will be able to do so relatively quickly and cheaply. Nevertheless, the genomics revolution may turn out to be a longer and bumpier ride than we hoped.