When the UCLA Medical School created the Department of Human Genetics two years ago, a crucial element in securing the success of the new department was to recruit one of the world’s foremost genetic scientists to head it.
To that end, the university brought in Leena Peltonen, a native of Finland and formerly professor of medical genetics at the University of Helsinki and professor of molecular biology at Finland’s National Public Health Institute.
Peltonen has published 308 scientific reports and 95 reviews and chapters, and she serves on the editorial boards of a number of medical journals. Her research has focused on the genetic underpinnings of human disease, and she has localized genes associated with schizophrenia and multiple sclerosis.
As chair of the department, Peltonen will lead UCLA’s efforts to “translate” the recently compiled human genetic code into knowledge that will bring us closer to understanding the causes of human diseases. This effort will combine the resources of computer science, statistics, mathematics, biology and genetics. And obviously, the commercial potential of drugs and therapies coming out of such research is phenomenal.
Question:
With what purpose in mind was the Department of Human Genetics created at UCLA?
Answer:
UCLA missed the first wave of human genetics and it was not one of the key players when the genome was read through. There were lots of genetic researchers, but the focus was not on human genetics, and that’s what we’ve been trying to build up. This is a very disease-oriented department and the research programs focus on the identification of the genes behind human diseases.
Q:
Are there any specific diseases or types of diseases that the department concentrates on?
A:
The research is either targeted to what we call trivial or simple genetic diseases, meaning that there is one disease gene and mistakes in that particular gene always cause the disease. However, an increasing number of programs are also targeted at what we call more complex diseases, and those are the common diseases everybody is interested in, like schizophrenia or multiple sclerosis. More and more genetic research is targeted to those common diseases and they are more challenging because they involve a spectrum of genes, and so we have to identify multiple genes and multiple different variants of those genes.
Q:
Given that the program is only two years old, what will it take to move to the forefront of human genetic research?
A:
We were fortunate in the sense that everybody has to start from scratch now. Basically the genome has been read through everybody knows that’s not quite true but it’s almost there so we are in a totally new situation and you can’t rely on earlier skills or earlier knowledge. It will require a totally new spectrum of skills. “Bioinformatics” or “functional genomics” are often-used terms which refer simply to the idea that you have to develop novel strategies that will help you translate the information in the databases into actual knowledge.
Q:
Can you give us an idea of what is involved in these strategies?
A:
These programs are based on the idea that you have to develop novel bio-computing strategies. Actually some of these programs will also be of very high commercial interest, just as in information technology, because there is a wealth of genetic information and we have no clue how to access this information. That is why bio-computing is a very important part of the research programs.
Q:
Is there a lot of collaboration between your department and other university departments?
A:
Oh yes. We also have joint faculty members who were recruited jointly with other departments. There are several faculty members that can read both the computer science literature and basic genetic material, and those individuals are in very high demand. Pharmaceutical companies try to recruit them with triple the salaries that we can offer them.
A:
Q:
Is it difficult to keep faculty members here under such circumstances?
A:
We can provide them with a pleasant and stimulating environment. I don’t think you can force talent, you have to attract them with something beyond economic incentives. The problem is that there are too few of these individuals out there, and all the academic institutions are trying to recruit them. That’s why we have to start from scratch and start training new experts, and that’s why we have a bioinformatics training program at UCLA to train more of these individuals.
Q:
What kind of commercial applications can we expect to come out of your department?
A:
If you take the immediate commercial applications, much of the genetic or molecular innovations have been very technological, as for example the “DNA chip” (a device that enables researchers to perform a large number of genetic experiments), and there are now multiple companies established on the basis of this idea. The next wave, beyond these technology-oriented applications, will be the data transfer and interpretation part, meaning new computer programs that can read simultaneously 30,000 mutations in the human genome. It’s technically doable or feasible to monitor 30,000 genes simultaneously, but to understand what it actually means is the challenge, and that’s why the next wave will be these interpretation programs and tools that extract information and translate it. How we understand the human genome information is what will dramatically change during the next decade.
Q:
Should we be thinking about software programs?
A:
To some extent, but software programs are only tools. They need novel mathematical algorithms which can take into account the effect of multiple genes and which can also take into account environmental effects, like your surroundings and your lifestyle. It’s not just developing software or computer programs; you really have to develop totally new views toward this information.
Q:
There will be presumably different models coming out of different research institutes for interpreting genetic information. Is there any way of saying which ones are going to be the more widely accepted ones?
A:
There are more multiple ways to test which model is the best, and UCLA is actually in a good position for some of these. Assume we have a hypothesis that there are 10 genes behind high blood pressure, and one highly meaningful way to evaluate how essentially important these genes are is to study large population samples. L.A. is a wonderful place for this because there is such a diverse population, so there are multiple populations you can monitor to see if all these hypothetical 10 genes are equally important in, let’s say, Mexican Americans or in African Americans. It’s a tremendous challenge but also a unique possibility for UCLA.
Q:
Los Angeles has been lagging behind Silicon Valley in terms of university research generating new start-up companies. Do you expect that to improve in the realm of biotechnology?
A:
Biotechnology has not been as efficiently capitalized in Los Angeles as it has been in Silicon Valley and San Francisco, because it requires a very strong information technology component which was already present there and which attracted biotechnology companies. Also the local universities (in Northern California) did something right, and perhaps UCLA did not do something right. UCLA should really pay close attention and there should be very easy data exchange and intellectual confidence exchange between the university and the industry. It should be made very, very easy. We have some success stories, but we have too few.
Q:
The availability of an individual’s genetic information creates some thorny privacy questions, because insurance companies may not want to insure someone whose genetic code shows a predisposition for a given disease. What’s your view on privacy concerns?
A:
I feel very strongly that all an individual’s health care information, including your genome profile, should be private and that you decide personally who you want to have access to it. It is possible that questions about the privacy of genetic information, in that it may be used to deny a person health insurance, could create opposition to genetic research in the U.S. and may delay research here. In Finland, where there is socialized health care and people do not have to fear losing their health care insurance, there is very little concern about genetic research.
