Scientists will never find a single gene for depression—nor two, nor 20. But among the 20,000 human genes and the hundreds of thousands of proteins and molecules that switch on those genes or regulate their activity in some way, there are clues that point to the roots of depression. Tools to identify biological pathways that are instrumental in either inducing depression or protecting against it have recently debuted—and hold the promise of providing leads for new drug therapies for psychiatric and neurological diseases.
A recent paper in the journal Neuronillustrates both the dazzling complexity of this approach and the ability of these techniques to pinpoint key genes that may play a role in governing depression. Scientific American talked with the senior author on the paper—neuroscientist Eric Nestler from the Icahn School of Medicine at Mt. Sinai in New York. Nestler spoke about the potential of this research to break the logjam in pharmaceutical research that has impeded development of drugs to treat brain disorders.
Scientific American: The first years in the war on cancer met with a tremendous amount of frustration. Things look like they're improving somewhat now for cancer. Do you anticipate a similar trajectory may occur in neuroscience for psychiatric disorders?
Eric Nestler: I do. I just think it will take longer. I was in medical school 35 years ago when the idea that identifying a person's specific pathophysiology was put forward as a means of directing treatment of cancer. We're now three decades later finally seeing the day when that’s happening. I definitely think the same will occur for major brain disorders. The brain is just more complicated and the disorders are more complicated so it will take longer.
SA:Do you have any estimates of how long it might take?
EN: I don't think it will be 30 years because we’ve learned a lot from cancer and other fields like immunology. That will guide us and teach us as we make progress for the brain so I would say between five or 10 years. There are already insights—specific genes and biochemical pathways—that have been identified now for brain disorders that are being followed up on. If we get lucky and some of those prove to be useful, we can start to see some clinical advances within about five years.
SA:There have been a lot of genetic studies that have looked for links between genes and psychiatric disorders but they turn up hundreds of genes of interest. How do you actually proceed to use that information to do something useful to both understand disease and to treat it?
EN: This is a major question of our time. One approach is to determine how differences in hundreds of genes would affect key biochemical pathways inside the brain. Although there are hundreds of genes, the expectation is that there's just a handful of altered biochemical pathways. Now if we could find those pathways and how they're altered and figure out ways to reverse those changes, we might be able to come up with new therapeutics. That is our working hypothesis now.
SA: Can you take information from one of these large genetic studies of recent years and use a technique to find either a key gene or pathway?
EN: Doing that is complicated because we're dealing with literally tens of thousands of gene products—proteins or RNAs (the latter are molecules that, along with DNA, encode the making of proteins). And so we must sift through how a few hundred out of tens of thousands of these gene products are altered. How they influence biochemical pathways is a complicated process in and of itself. But this process is tractable and it is work that can be done now.
SA: Aren’t you using multiple techniques to try to deal with this complexity?
EN:We use several approaches. First we identify the tens of thousands of RNAs present in different brain areas and put that information together with direct measures of how different brain areas function abnormally in an animal model of depression.
Chief Analytics Officer Spring 2017
15% off with code MP15
Big Data and Analytics for Healthcare Philadelphia
$200 off with code DATA200
10% off with code 7WDATASMX
Data Science Congress 2017
20% off with code 7wdata_DSC2017
20% off with code AIP17-7WDATA-20