EPI Atlanta Conference
December 5 - 7, 2006
Genetic Epidemiology, Genetics, and MCH
CYNTHIA MOORE: Thank you. It’s very nice to be here. I want to give you a brief and somewhat rapid overview of Public Health Genomics, and talk to you a little bit about our collaborative efforts for using genomic knowledge for population and health. And I think that all of us will agree that almost all diseases are caused by gene-environment interaction. Of course, there are disorders that fall on either end of the extremes, even though we know that there are still both components involved. But we believe that the vast majority of diseases, those that we have termed common complex diseases, actually have a more equal contribution from both genes and environment. And in this category, we place heart disease, asthma, diabetes. And more recently, we’ve added to the list, pre-term birth, and we’re going to hear more about that a little bit later.
Now some of you may be saying sort of, “What in the heck is genomics?” And so I thought I’d start off with a little bit of definitions. Doctors Goodmacher and Collins from NIH have given us these definitions: that genetics is the study of single genes and their effects; whereas genomics is the study of not just the single genes, but of the functions and the interactions of all genes in the genome. Dr. Khoury, from our office--I’m sorry, I’m popping my piece, talked about genetics to genomics or continuum from genetic diseases to genetic information. And what does this mean in health practice? When we look at genetic diseases, I think this is what we’ve traditionally known in maternal and child health, and been involved within programs like newborn screening. These are the single gene disorders, Mandelian disorders—. And that they really contribute in disease birth; develop five percent of disease. We’re usually dealing with mutations: one gene, one disease. They have a--confer a high disease risk. The environment may be involved, but to the lesser degree. In the model of medical practice or health practice that we’re talking about is genetic services, whereas genetic information involves all diseases. We’re talking about a high disease burden, 95 percent. Here we’re talking about not so much these deleterious mutations, but we’re talking about a common variance in genes. And we’re talking as Juan mentioned about multiple genes being involved in a disease, and each of them conferring a low disease risk, the environment playing a much more--a significant role in the disease process. And now we’re talking about general practice, pediatrics and family practice in internal medicine being our health model.
So today, I’m going to talk about four areas very briefly: the global emergence of Public Health Genomics; role of population perspective and expansion of population-based research in this area; what does this genomic applications mean for real populations; the really crucial role of knowledge synthesis integration; where do we find--how do we find these needles in a haystack when we start doing this research; and the real need for public health assessment of genomic-based test and technologies, evidence-based health care.
So just another definition, Public Health Genomics. This came out of the Bellagio Report in 2006. This was an expert workshop that I didn’t get to attend unfortunately. But they defined Public Health Genomics as a multidisciplinary field concerned with the effective and responsible translation of genome-based knowledge and technologies to improve population health. Now, they developed what they call the Public Health Genomics Enterprise. And they’re--the basis of this was to try to set out a model for moving from genome-based science and technology, and that’s basically where we are now. We have the results of the Human Genome Project. We have the sequence of the human genome. And we have the promise, and then many ways or many times what Juan showed us on all the magazine covers. We have a lot of the hype of improvement in population health. But how do we get there? And this is the slide actually Dr. Khoury has used a lot. The Grand Canyon sort of is between those and how do we move across that Grand Canyon to improvements in population health. This is the enterprise that they developed. These are basically in major pathways that they think that we need to follow to get there. And of course, this is in many ways, quite simple because each of these pathways, in itself, is very complex.
Now at our CDC and in our office we’ve been focusing in on several of these particular areas. One, of course, is in population research or the population sciences. So I just want to give you a few examples of some of that work.
For an audience like this as a non-epidemiologist, I sort of hesitate to put a slide up like this. But I will anyway. Just the importance of the epidemiologic approach to genetic information beyond gene discovery. And, of course, again we all know that gene discovery is just the start. We need prevalence information, associations, interaction and--but one thing that you may not know, and I think it’s surprising to a lot of people, when we start our work and look for information, basic information just on the prevalence of genotypes of a lot of these variants is not available from a representative population. Yet some of the very basic work that has not been done and is needed, and is the focus of some of the research from our office at CDC. Also, to put a focus on the need for this information, Dr. Khoury and his associates have coined the term “Human Genome Epidemiology”. This is from a textbook that they wrote, and defined it as the systematic application of epidemiologic methods and approaches to assess the impact of human genetic variation on health and disease. And coined this is being a huge problem. We have about 25,000 genes, their combinations, and their interactions with the risk factors. So it is, in fact, as Juan alluded to, a huge problem. Now there is, again, a lot of population health research in the genomics area. And this is research following the sequencing of the human genome. You can see sort of the house that’s been built by NIH, their model of how they would like to proceed to--from the basic sequence to health impact. One of the, I think, challenges that we have now is that we’re moving from research that’s based in looking at single genes or at candidate genes for research, to research that’s looking at for genome wide studies. And in this research we’re now able to get data on 500,000 or a million variants. And the, of course challenge, as you all know, is trying to figure out how we will actually analyze those data and how we will interpret those data. And, I guess, what we’ll be able to--how we will be able to make those data available to other researchers given the issues around confidentiality that exist. Because putting that amount of data out in a data set to share has certain major issues around confidentiality. There are also, of course you have to have populations or study groups to do these investigations in. There’s emergence of global biobanks and cohort studies that you’re all probably aware of. One that is in progress right now is the UK Biobank which is an adult study. Also the National Children Study, which many in this room may have contributed to. The UK Biobank has funded the National Children Study has started with some initial funds, but long term funding is still in doubt. But longitudinal studies in cohorts like this are very important for us to collect the data that are needed to answer some of the questions that Juan mentioned.
So moving on to knowledge integration which is another area that’s important. There are collaborative efforts in this area to those with Human Genome Epidemiology Network out of CBC. Another is the Public Population Project in Genomics, which is out of Canada. HugeNet is a global collaboration of individuals and organizations that try to assess population impact of this human genomic variation. And the idea here is not just to pull together what’s already been done, or research that’s been done, but it’s also to impact what’s done in the future to set standards for reporting so that there can be this integration of information, and it can be interpreted. And also to build networks of researchers who can pull together both their data sets that they have now, and perhaps even their biological specimen banks, and collaborate to make the future research even better.
So finally, I guess as an endpoint of all of this will be genetic tests or genomic tests, where we’ll use the information that comes and hopefully to impact on health. And it has the potential to affect many people, especially for pharmacogenomics. It has a potential for enhancing and targeting prevention efforts. But there are a lot of issues: implementation issues and access for individuals, how we’ll educate providers in the public, how we’ll monitor the impact on population health. And this picture, or this figure, is from gene test database showing the increase in a number of diseases for which testing is available. But these diseases mainly are single-gene diseases or tests for which only one, for which there is just a single gene tested. And as we discussed in the future, it will be likely that we’ll be looking at genomic profiles or multiple genes being tested. And what we’re seeing now is, I think, and we’ll see more of is a gene discovery followed almost immediately by the suggestion that there should be a gene test developed. This reporting of an association between a genetic variant and Type II Diabetes was followed by an article that an immediate practical consequence of the discovery would be to develop a diagnostic test to identify people who carry the variant, that people who knew of their extra risk they would have an incentive to stay thin and exercise. Maybe, maybe not. But that immediate leap to develop a test is sending that we’re seeing more and more without really an assessment in between.
Now there have been several groups like the Secretary’s Advisory Committee on Genetic Testing, who have called for pre-imposed testing or genetic tests. And we have worked with groups such as the Foundation for Blood Research to develop this process. And certainly I invite you to go to our website and look at those processes. One of them, which was called ACE, called for four components for evaluation and looking at the analytic validity, clinical validity, clinical utility and ethical, legal and social implications of testing. That is morphed into a pilot project from CDC, which is called EGAT, which is a non-federal, non-regulatory working group which is evidence-based and is evaluating several genetic tests at the moment using this evidence-based practice centers. This is a scheme of the EGAT process. This working group considers different topics, evidence-based practice centers, let’s see if I’ve got a pointer here, do the reviews and bring that back to the working group.
There are many stakeholders that interact with the working group. And at some point these--our recommendations will be disseminated out to consumers, health care providers, policymakers and payers. But as the number of genetic tests increase, you can see that there is a need for a process, an ongoing process and there’s a lot of work to be done in this area. Again, I invite you to come to our website and look at the EGAT progress.
Finally, very quickly, sort of circumventing that whole round of, any sort of assessment are direct to consumer. Genetic testing is going on, especially genomic profiling that’s being marketed mainly through the web. And there really has been no evaluation of this testing now, but this activity continues to grow.
So we hope that we’ll be able to close the gap between gene discovery and population health through these processes. We do have a long way to go. We think that the basic pathways are there and I would again invite you to visit our website, collaborate with us on some of our projects. And I think at the end we’re going to have a time for questions. Great. Thank you.