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Genome Technology Explained, Part Three – What’s the Big Deal?

by Bradley Miller on October 23, 2009

In two previous posts I highlighted some of the coming changes in DNA sequencing and some of the up and coming companies that will help us with the onslaught of data. But I’ve neglected to begin to explain why these technologies will be so transformative and why that matters for biomedicine.  Back in 2003 both the National Institutes of Health and Celera made a big splash as they announced that the human genome had been decoded.  While true – we had the basic sequence of the human genome – the A-T-G-Cs of it all, we didn’t really know what we were looking at.  Just because we have all 3 billion letters of the human genome sequence, doesn’t mean we know what it actually does. (Image above of a DNA strand courtesy Richards Center, Yale University)

Sicklecells

Well, that’s only partially true – we do have lots of scientific research and understanding of certain genetic mechanisms and functions of genes.  But as of yet that knowledge has been somewhat limited and pretty elementary with respect to actual impact on clinical medicine and human health.  Very few diseases, like sickle cell anemia, can be traced back to only one mutation – a relatively simple genetic explanation (Picture at right: regular red blood cells with sickled disease red blood cells, courtesy NIDDK).  We know that multiple genes are linked to heart disease or cancer or arthritis and we’re discovering new links every day.  However, most of the the connections are still pretty weak and don’t fully explain the true genetic nature of some diseases.

And, one more thing, I’d be pretty skeptical of the commercial genetic tests that are available from companies like 23&me and Navigenics (among others).  While they have strong people behind the company, the data they’re using is still pretty weak with respect to predicting disease.  Take those tests as a novelty, not as a sure thing diagnosis – please feel free to write me and I’d be happy to explain more.

For another example, let’s take a look at cancer and its genetic root.  Scientists used to search for a single “cancer gene” – when we found one, we realized it was only a small fraction of the story and there were many other genes that had related effects that contributed to cancer.  The same thing applies to heart disease and even seemingly simple traits like eye color.  In a way, the more we learn, the more we discover we didn’t know as much as we thought we did.  It got more complicated.

To complicate the public’s understanding, the genetic model we all learn in school is Mendel and his peas.  It’s a good educational example because one gene leads to either smooth or wrinkled peas; another gene confers either green or yellow color – making the peas a really simple and useful example to explain basic genetics.  However, very, very few genes and phenotypes work this way in human genetics.

One reason the human genome, as we know it today, is not as quite as useful as all the hype in the media is that what we call the human genome project is really the genome of just two people.  It’s a roadmap of sorts to help with genetic research – it, by itself, explains very little in the way of human variation and disease (I’d like to say though, that much like the moon landing, there was a certain gravitas to actually completing the genome – it has inspired scientists and has certainly aided with scientific progress).  The genome map doesn’t have all of the gene variants figured out – it’s a raw map and it’s up to us to figure out where those genetic variants are.  More over, diseases like cancer and heart disease have many, many genetic components, making it even harder to figure out which gene has which function.  In other words, biomedical genomics is very different than the genomics lay people learn and understand.

To understand where cancer related and heart disease related genes are and what roles they play in disease, we’re going to need breakthrough technologies to not only sequence DNA, but also handle all the information that comes out of that process.  Each human genome, depending on how it’s sequenced, is between 250 gigabytes and 2 terabytes of information and costs between $100K-$500K.  That’s a lot of data and moolah, especially considering the hard drive in your computer is probably 250 gigabytes or smaller!  Each cell in your body contains more information than the disk drive in your computer.  Not too shabby of a machine, eh?  I digress.  As we progress, new models of sequencing and data solutions will become much more economically feasible, making it possible to do the necessary research.

An example of how genomics will change medicine was published last year in a New England Journal of Medicine article.  In it researchers describe how they obtained two complete genetic sequences from a person – one of a leukemia cell and the other of a healthy skin cell.  Essentially the researchers compared the cancer genome with the healthy genome and analyzed the genetic differences. When they compared the cancer genome to the healthy genome they found 3 mutations that they expected to find based off of prior leukemia research.  However, they also found 7 genes that they had no idea were involved in leukemia – the researchers arguably tripled the genetic understanding of leukemia with just this one study.  Now, with these new gene targets, researchers and doctors will have a better understanding of leukemia as a disease, which will shed insight in to next generation therapies and maybe even a cure someday.

Now, that study cost approximately $500,000 for the genomes alone – $250,000 for each genome.  With new sequencing technologies we’ll be able to get that cost down to under $100 in a matter of a couple of years. The leukemia study mentioned above was just a proof of concept that illustrated our ability to better understand disease genetics and pathophysiology  by comparing only two different genomes. To get a full and accurate understanding, these same scientists will need thousands of genomes to compare – and that’s just for each, individual disease!

Over time this genomic research will become common place and will yield great advances in biomedicine.  At this point we need more cost effective technology that will make it affordable to perform the necessary research with enough genomes to really matter.  To close this post, though, I strongly caution that this work may not directly lead to a cure.  My bet is that the research will help us to better understand that which we don’t know we don’t know.  It is a leap in to the right direction and will prove incredibly helpful.  It’s an exciting time.  In future articles I’ll dive deeper in to the genetic mechanisms of cancer and then other, new breakthroughs in genomic technologies.

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