Good morning everyone. My name is Carol Kovac. I'm from IBM and I'm going to be your moderator this morning. I guess there's the old saying that says today is the first day of the rest of your life. And so after yesterday's announcement, I'm glad to see that you're all back here ready to start sort of the first day of the rest of our lives after we now have kind of declared the genome complete. I don't know about all of you, but yesterday I found it, you know, fascinating, fascinating retrospective looking back over the last 50 years of discovery, referring back to my own times in graduate school and marveling at how far we have come in just the last few decades. But by the end of yesterday, I think, you know, one of the things that I was ready for was what we started to talk about yesterday was the look ahead. Where are we going? What comes next? How are we going to handle the new data and how are we going to bring information out of that data? From my perspective, in the information technology industry, we are fascinated by the questions of how will the convergence of progress in information technology, which continues to proceed for another 10 years at least along that, you know, exponential growth curve we call Moore's Law, you know, how will the convergence of that with the equivalent exponential scaling laws in biology, which we have just begun to see, they are just at the very beginning of their sort of Moore's Law growth. How will that fundamentally and remarkably change the world over the next decade? And so I think what we're going to talk about all through today is very much more about what comes next. This morning I'm very pleased to moderate a panel, which will begin by talking about the implication of genomics for human disease. And we have with us today four speakers. Unfortunately, Fernando Martinez is unable to be with us this morning. So we will have four speakers. You will have a little bit more leisurely discussion from each of our four. We will have questions and answers, unlike yesterday. So I hope that you will prepare some lively questions and answers for this group of people. Our first speaker this morning is Janet Rowley. Janet is from the University of Chicago, and her work is in the area of, she is a distinguished service professor of medicine, bloom rice, distinguished service professor of medicine at University of Chicago. She has worked on chronic myeloid leukemia and is the recipient of the last award for medical research in 1998. This morning she will speak to us from the genome to successful treatment in leukemia. Well, thank you, Carolyn, for introducing this session. It is a great pleasure for me to be here amongst the speakers on this very auspicious occasion as we look to the future, having now most of the human genome accessible to us. And as I thought about what I would like to talk about this morning, I decided that I would go very, very quickly through the portion of the title that talks about successful treatment and really emphasize the kinds of things that we can now do with the genome in hand. And I will speak in part from the standpoint of leukemia, which is a very small segment of cancer. But I think the analysis of leukemia and research in leukemia has led the way for many of the studies and many of the paradigms developed in cancer. This is a quick overview of that from chromosome abnormalities, the discovery of Peter Knoll and David Hungerford in 1960, that there was a unique abnormality in chronic myeloid leukemia called the Philadelphia chromosome to the discovery that it was really a translocation, cloning of the translocation breakpoints and identifying the genes as BCR-Able. And finally here to successful treatment, and you notice that this is a period of 40 years. This shows you the karyotype of a patient with CML. Here's the Philadelphia chromosome, normal chromosome 22, and you see how much smaller it is. And I discovered that the piece wasn't missing, but rather was moved over here to the end of chromosome nine. And then with heister camp and grofin it was shown that the Abel gene and the BCR gene were involved. And in fact this is the critical new gene that's formed by the translocation, namely the fusion of five prime BCR and three prime Abel. And this leads to the activation of the Abelson gene, which David Baltimore had shown was a tyrosine chymase. This shows you a very schematic drawing of the BCR Abel fusion gene. And Abelson has a pocket that binds ATP and is involved in the enzymatic transfer of a phosphate to tyrosine on a substrate. And this is the beginning of the pathway that leads to activation of all of the target genes resulting in chronic myeloid leukemia. The miraculous thing of STI 571 is it binds to this same pocket, preventing, unfortunately you can't see it over here, but this is ATP here, prevents the binding of ATP and therefore this activation of the pathway does not occur. This shows you the data upon which the approval of Gleevec or Imantanib is now called. This was based where 532 patients who had failed interferon, which was the best therapy available at the time of these patients. And there's anyway, I think this margin of all the slides is clearly going to be cut off. This is 88% of the patients showed a complete hematologic response and almost half of them excited genetic response. And so this was actually approved in 72 days, which is obviously a record for the Food and Drug Administration. So this is the good news, but I should point out that this success occurred with relatively little input from DNA. Clearly DNA was used to clone the breakpoint and identify the genes and identify the fusion gene, but it was sort of a peripheral accomplishment, if you will, or had a peripheral input. Now when you look at the future, here we have a number of karyotypes of both hematologic diseases and solid tumors. The number of recurring rearrangements is greater than 300 in the hematologic diseases and greater than 100 in the solid tumor. We've cloned many of the genes here at the translocation breakpoints, but except for the treatment of acute promyelocytic leukemia with a drug that targets retinoic acid, we have no genotypic specific therapy. So the challenge for the future is to get a GLEVAC for each one of these different rearrangements. And how we're going to go about that is obviously a matter of using a number of strategies. One that you heard about extensively yesterday is to look at microarrays. This is an example from acute lymphoblastic leukemia published from St. Jude's Hospital. Here, as you will recall from yesterday, patient samples are on the vertical, genes are on the horizontal, and they're segregated by particular chromosome abnormalities. And as was emphasized yesterday, there is a unique fingerprint for each of these translocations and rearrangements in patients that have similar rearrangements. The concern is that the genes or the oligonucleotides on the chip are more only those that we know about. So it doesn't tell you anything about what you do not know. And it's difficult to quantitate and compare from one experiment to another. So, Simon Wang in the lab decided that he would try a different strategy that's using SAGE. This was developed by Ken Kinsler and Bert Vogelstein at Hopkins, and we select only poly A plus RNA, select the 3 prime end, use restriction enzyme to cut at the last C-A-T-G site, and then it cuts 10 base pairs downstream so that in our selection we're getting the last C-A-T-G site before the poly A tail from all these different transcripts. And of course you're not selecting for the transcripts except they have to be polyadenylated. Here you have the individual SAGE tags, you ligate them and sequence them. Then based on sequence information of each tag, you can go back and match it to the genome. And again, this is where a public database is so extremely important. And you can sequence multiple SAGE tags in a single lane so that we do 30 to 40 as compared with doing CDNAs one at a time. This is a summary of the work that has been done in the laboratory. These are normal human cells, both hematopoietic stem cells, myeloid progenitor cells as well as lymphoid cells. And then we're in the process of looking at leukemia, the most common chromosome translocations in acute myelogenous leukemia. And here we're looking at five patients each one selected for CD15 positive. You'll notice that we've done more than 100,000 SAGE tags in most of these libraries, that is individual SAGE tags. When you look at the origin of the SAGE tags, you can see for the normal 34 and 15 positive cells that 12 and 14 percent are known genes, roughly 40 percent are ESTs, but almost half are novel transcripts, that is they're not present in any database, either GenBank or ESTs. And therefore, of course, none of these will be on a microarray. Just in summary as to where we are with the leukemias, we have compared the level of expression of the various SAGE tags with the normal CD15 positive libraries. And you can see that for the different translocations, a number are present or up-regulated, absent or down-regulated. And one of the things that's astonishing to me is that the 1517, which is the translocation associated with acute promyelocytic leukemia is distinctly different in its pattern of transcripts than the other two types of leukemia. And clearly we will be involved in analysis of this in more detail when we finish the study, which includes the 821 translocation. There are also some transcripts that are common in all of them. Five of them are up-regulated and 82 are either absent or down-regulated so that these would appear to be transcripts that may be more directly related to the leukemic condition and less related to the specific subtype of leukemia. I want to come back to the novel SAGE tags. And here you can see that there are 50,000 SAGE tags. I didn't point, a novel SAGE tags, I didn't point out in the earlier slide, but this is out of more than a million and a half total SAGE tags that have been identified. These are novel SAGE tags that are unique. And of interest we have been studying Drosophila as well. And here you can see that though the Drosophila genome is well studied there are more than 22,000 unique novel SAGE tags in Drosophila from a total analysis of 350,000. So this is an image of a nucleus stained with DAPI. So the DNA in this nucleus is what is stained blue on the screen. And as you heard yesterday, 1 to 2% of the DNA, roughly 30,000 genes or so, though this is a number that is in some dispute, but 1 to 2% codes for protein. So the question is, what does the other 98% do? And I've always been fascinated with astronomy, cosmology and the wonderful images that they can show and the terms they use, black holes and supernova and of course dark matter or dark energy. And I submit to you that we've got our own dark matter. What's the 98% doing here? And I thought the comment of the quote yesterday from Sidney Brenner, there is a distinction between junk and garbage. And so I assume that this 98% is junk, not garbage. And the challenge to us is to figure out its function. And clearly the genome is going to be, and the accessibility of the DNA sequence is going to be an extraordinarily powerful tool to help us with that challenge. So why are there so many novel sage tags? They can be novel genes not identified using current algorithms, and that's certainly going to be the case for some. Transcripts derived from alternative splicing, and we heard an example yesterday of one with 38,000 possible splice variants. Transcripts of non-coding RNA, both antisense, intergenic transcripts involved in imprinting. And I want to emphasize this, the transcripts are present often at very low levels, and they won't be detected by many of the present techniques that we are using to identify transcripts. So the transcripts may be novel genes. And this is an example from the laboratory. So Jin Jin Chen and individuals in the laboratory did a great deal of sequencing, and here was a particular sequence they found, which they could then go and interrogate the database using BLAT, again emphasizing why it is so important for the scientific community to have free access to all of the genomic information. And the sequence here you see in the black bars clearly looks like exons with entronic sequence. It codes for an open reading frame of 79 amino acids, and the direction of transcription, as you can see from the arrows, is from left to right. You also see using all of the programs and the known ESTs that there are no matches, so it does look to be a novel gene. I'll skip over the alternative splicing, though that's a fascinating area, and move on to transcripts of non-coding RNA, anti-sense RNA. So again, taking a sage tag and through strategies that we have of extending them so we get far more sequence information. Here is another example of sequence mapped back using BLAT. This one is on the long arm of chromosome 15, and you'll notice that the arrows in the direction of transcription are from right to left. You'll also notice that it matches a known gene precisely. This is the beta 2 microglobulin gene. So this is an example of expression of anti-sense to beta 2 microglobulin. It's of interest that as we have done our studies in Drosophila, 38% of all of the novel transcripts in Drosophila are anti-sense, so that I think this is a whole area of biology which we have not been aware before. So what might anti-sense be doing? I thought this was a marvelous example from a paper from Kramer in Nature this year showing the reciprocal expression of sense in anti-sense RNA in Neurospora. This shows you part of the map of the frequency gene, it's a circadian rhythm gene in Drosophila, the sense and the anti-sense strand. And this shows you the level of expression of sense transcripts and anti-sense transcripts over time. Anti-sense transcripts are induced when Neurospora is in light. And so that they're very high in light and as the Neurospora are put in dark, they reduce. And the authors propose that the anti-sense strands are annealing to the sense RNA and regulating the transcription of that gene. So this is endogenous RNAI functioning, and this is one of the first examples which I'm aware of showing that anti-sense is a very critical component of gene regulation, and one that I think we haven't gotten into. So I think we've reached a new frontier. And that new frontier is a change in the paradigm. Now this is an example from a paper from the classical paradigm, or as we heard yesterday, classical dogma with DNA to RNA to protein and protein regulating DNA and RNA. And we now have to add in the role that RNA is playing within the nucleus, regulating not only itself, but also regulating DNA through imprinting and other of the regulatory processes. So I think in terms of the relevance to cancer, the question is are we focusing on the right targets? We've been focusing on protein coding genes. Are there other things we should be paying attention to? And if there are other things, are we using the right strategies to find them? Because ultimately our goal is really to come back to the adequate management of cancer patients in the year 2000, whatever. And I'm not going to say I have a crystal ball that knows how long we're going to get there, or at least for every patient. But we're certainly going to be genotyping the involved tissues and being much more precise in our assessment, even the breast cancer dividing it into multiple things and looking at gains and losses and translocations. We'll also then institute genotypic specific therapy, such as GLIVAC. And the hope is that this will lead to less toxicity and improve survival. And I've already commented on the colleagues in the laboratory, particularly San Ming Lang, who were very much involved in the SAGE project, long-term colleagues in the laboratory. I want to acknowledge that this, in version 16, analysis and functional assessment is being carried out with Pupol Yu here at NIH with support from Jeff Trent, Eric Green, and Gerard Buffard. And I acknowledge the support both of NIH as well as a number of foundations and the University of Chicago. Thank you very much. Thank you very much, Janet. Our next speaker is Richard Lifton from Howard Hughes Medical Institute, and Richard is chair of the Department of Genetics at Yale University. And he will be speaking to us today. His research is in the area of cardiovascular disease, hypertension, stroke, osteoporosis. And he will speak to us today about genetic and genomic insights into cardiovascular disease. Thank you, Carolyn. It's a real pleasure to be here today, and I'd like to add my congratulations to NHGRI and the sequencers for a remarkable set of achievements. Having served on the External Advisory Board for the project for the last five years, it's really been a remarkable opportunity to see this unfold. And given all of the opportunities for failure that presented themselves along the way, I think it's really testimony to all involved to have accomplished this goal in such a remarkable fashion. So my task this morning is to talk about cardiovascular disease. And if I could have the first slide on, please. Cardiovascular disease remains the leading cause of deaths in the industrialized world, including the United States. About a third of all people in this room will ultimately die of heart disease or stroke, indicating that we have a lot of work to do. The pathophysiology of heart disease has been defined in rather gross terms by epidemiologic studies, which have succeeded in identifying a number of risk factors for the development of atherosclerosis. These risk factors include hypertension, hyperlipidemia, smoking, and diabetes. These result in atherosclerosis, leading to narrowing of the arteries that supply blood to the heart, resulting in their closure in myocardial infarction, which then results in heart failure, cardiac arrhythmias, and ultimately death. Well, the specific causes that result in these epidemiologic risk factors, we now have the opportunity to begin to identify by genetic approaches. So Brown and Goldstein have pointed out that even the most ardent proponent of the healthy lifestyle proposal would have a hard time explaining the paradox of Jim Ficks and Winston Churchill. Jim Ficks, 5'10", 150-pound marathon runner, healthy lifestyle promoter on the one hand, Winston Churchill on the other, 5'8", 270, slothful, legendary for his gluttony, a heavy smoker. Nonetheless, Ficks died at age 52 while running, and Churchill lived to the ripe old age of 90. And of course, one possible contribution to this explanation for this paradox is that Ficks had a remarkable family history of early coronary artery disease. And we expect that the risk factors for cardiovascular disease will in large part have genetic underlying components. And the opportunity then that presents itself is to use genetics to try to identify these underlying causal factors. We specifically can identify causal relationships between genes and pathways and health outcomes, can identify new targets and pathways for early diagnosis and therapeutic intervention, and ultimately may be able to identify individuals with increased likelihood of benefit and minimize risk of adverse effects from the treatment with specific agents. So that broadly speaking, the genetic contributions to disease causation, Mendelian traits, typically rare, single genes with large effect on the one hand, on the other hand, multifactorial traits where there are multiple inputs from genes and environmental factors. This is where the bulk of disease burden lies. Going forward, the optimal strategies for tackling these genes and identifying them is not well understood because we don't know how many genes influence the trait nor the magnitude of the effect imparted by any single locus. And we also don't know whether they're common or independent alleles. Most of the progress to date has been made in the understanding of these rare Mendelian traits, but I would make the specific pitch that understanding these rare diseases may be of critical importance because it may point us to key gene products and pathways that can be manipulated for health benefit. And importantly, the treatments that arise from these may be highly applicable to the general population and need not be confined to the rare patients with these diseases. So trying to put a molecular face on these epidemiologic risk factors is one of the major enterprises of the last decade, and there have been a number of striking successes. You're all familiar with the work of Brown and Goldstein who identified mutations in the LDL receptor underlying homozygous familial hypercholesterolemia. This is a disease that affects one in a million in the general population, but it established in a formal way the causal relationship between elevated cholesterol and early coronary artery disease and validated the approach of attempting to antagonize the cholesterol biosynthetic pathway by identifying specific antagonists of the rate limiting step in cholesterol biosynthesis, leading ultimately to the development and use of HMG CoA reductase inhibitors. These are drugs that have been demonstrated by randomized controlled trials to have a dramatic impact on reduction of cardiovascular risk, and we're now treating tens of millions of individuals worldwide with drugs that were validated from the understanding of a disease that affects one in a million in the general population. In the last several years there have been dramatic advances in understanding other aspects of the cholesterol homeostasis pathway. Again, from the understanding of very rare diseases. For example, Michael Hayden and colleagues identified mutations underlying tangier disease as being in a specific member of the ABC transporter pathway that is involved in the export of cholesterol out of cells, the so-called the reverse cholesterol transport pathway, getting cholesterol out of cells and into HDL, understanding of a new pathway underlying hypercholesterolemia. Similarly, Helen Hobbs and colleagues have identified mutations underlying another rare disease, testosteroneemia, as members of a related gene family of ABC transporters that are involved in secreting plant sterols out of the liver into the bile, and in the absence of these plant sterols which are abundant in our diet are abnormally absorbed and can't be secreted, resulting again in another form of hypercholesterole of high sterol levels and early coronary artery disease. These are nice examples of rare diseases that are leading us to new understanding of basic human physiology. Our own work has been involved in understanding the pathogenesis of hypertension. This is the most common disease of the industrialized world. It affects more than 20% of the adult population and is a major risk factor for death from heart attack, stroke, end stage renal disease and congestive heart failure. Its pathogenesis has been unknown and its treatment has been inadequate. Part of the reason for the difficulty in understanding its fundamental causation is the complexity of the regulation of blood pressure. This is Arthur Guyton's model of the regulation of blood pressure in humans, and as you can see this is a rather complicated schematic and it's difficult to reduce to more simple terms because unlike cancer this is a phenotype you can only measure in an intact living organism. So as a consequence, hypertension has variously been proposed to be a disease of the brain or of the heart or of the kidney or of the adrenal gland or of the vasculature, and our approach has been to try to settle this using genetic approaches, looking for rare families segregating single genes with very large effect. This has succeeded in identifying mutations in a number of genes that affect blood pressure in humans, and the intriguing aspect of this work is that all of these genes act in a single, final, common pathway that regulates how the kidney handles salt. Every day the kidney filters one and a half kilos of salt on a typical Western diet. We have to reabsorb all but about a half to one percent of the filtered load in order to maintain salt balance. The kidney does this by a highly coordinated pathway of regulated co-transporters, exchangers, and channels. And this whole process is regulated by the renin angiotensin system, whose output angiotensin 2 causes increased secretion of a steroid hormone aldosterone, which interalic corticoid receptor, whose activity regulates the activity of this epithelial sodium channel. To date, all of the mutations that affect blood pressure in humans act in this final common pathway, mutations that raise blood pressure act by increasing net salt reabsorption in the kidney, mutations that raise blood pressure do the opposite. And the pathophysiologic sequence is increased salt reabsorption, results in increased plasma volume due to water following the sodium to maintain isogenicity of blood. This expands plasma volume, increases venous blood return to the heart. The heart obligingly pumps out more blood, and by Ohm's law this raises blood pressure. So all of the mutations act in this fashion. And I'll give you an example of a few of these following this pathway down, the mineralic corticoid receptor and the epithelial sodium channel. So by studying one-of-a-kind family, we identified mutations in the mineralic corticoid receptor in which substitution of a single amino acid in helix 5 of the receptor substituting leucine for serine results in severe hypertension. We've been able to demonstrate at the atomic level that the mechanism of this is that this leucine substitution creates a new Vanderwall's interaction that eliminates the requirement for steroids having 21 hydroxyl group to interact at this portion of helix 3. And so as a consequence this single amino acid substitution changes the specificity of the receptor such that steroids that normally would bind but fail to activate the receptor are now potent agonists. Similarly, mutations just downstream of this receptor, the epithelial sodium channel itself, mutations in this channel cause an early severe form of human hypertension. And the mechanism of this is that these mutations that either modify or chop off this cytoplasmic tail of subunits of the epithelial sodium channel, eliminate the ability of the channel to be cleared from the cell surface by endocytosis via clathrin coated pits. And as a consequence, these channels accumulate at high levels on the cell surface, mediate increased sodium reabsorption and result in hypertension in humans. Most recently we've identified by positional cloning an entirely new signaling pathway not previously recognized by physiologic study. This turns out to be a negative regulator of sodium transport and it's a serine threonine kinase and there are two of them that are involved in the regulation of salt reabsorption. They normally antagonize the reabsorption of salt by a specific co-transporter, the sodium chloride co-transporter and mutations that eliminate just the function that regulates the sodium chloride co-transporter result in hypertension in humans as well. And this has identified a new signaling pathway that we're still trying to understand what its general role is in human homeostasis. Having identified a bunch of these genes, we can begin to test the proposition that this matters in terms of clinical applications. Some of the genes we have identified are autosomal dominant in action and we can identify extended pedigrees based simply on the identification of an index case and genotyping through the extended families. These patients are typically diagnosed with severe hypertension that is refractory to treatment but knowing the specific underlying diagnosis we can begin to treat these patients with selective agents that are tailored to their underlying diagnosis. A nice example of tailored therapy. I'd like to turn now to some of the outcomes of cardiovascular disease. One that I mentioned is congestive heart failure. This shows a massively enlarged left ventricle caused by a specific mutation in sarcomere genes and this is the work of John and Cricket Seidman who have taken a comparable approach to what we have done in hypertension to understanding left ventricular hypertrophy. By collection of rare families from around the world, they have demonstrated that this disease is largely the result of mutations in genes involved in force production in the myocardial cells. As a result of these mutations, force generation is impaired and this is their proposal that the ultimate mechanism by which this results in cardiac hypertrophy is altered regulation of intracellular calcium. These are beginning to flesh out the specific pathway by which the heart adapts to both normal and abnormal force generation and how this common phenotype of cardiac hypertrophy which contributes both to heart failure as well as cardiac arrhythmia arises. Similarly on the outcome side, cardiac arrhythmia is one of the major causes of death in the setting of heart attack. The reasons for this are that the electrical impulses that normally flow through the heart in a coordinated fashion to lead to contraction in a coordinated way become abnormal and the normal depolarization and repolarization goes awry resulting in ventricular fibrillation and that is ultimately leading to inability to propel blood through the body and death. Mark Keating and his colleagues again have taken this approach of looking for rare families with abnormal heart rhythms and have identified a number of genes that underlie these traits and intriguingly all of these genes fall into the pathway of being the specific mediators of components of the cardiac action potential. So mutations that impair, that prolong the influx of sodium at the beginning of cardiac excitation cause cardiac arrhythmia and similarly mutations in a series of potassium channels that normally mediate the specific repolarization of myocardial cells also cause cardiac arrhythmias. Importantly these have already begun to have impact on our understanding of pharmaceutical complications. Long QT syndrome induced by drugs is a common mode of failure of drugs in clinical trials and the Keating lab has identified one of the specific potassium channels that appears to be the target through which this acts and virtually all drugs are now being tested for their ability to antagonize the specific potassium channel. So thinking about the future of genetics and cardiovascular disease, we have come a very short way but we have done it I think quite rapidly. We have begun to identify new genes and pathways and I think going forward we need to continue to pursue all of the known Mendelian traits recognizing that these might provide very key insights that we hadn't in understanding human physiology that might identify key targets that can be manipulated for health benefit. It goes without saying that there are likely to be many of these that we haven't yet recognized because we haven't looked carefully enough and we need to have eyes wide open. Similarly there's another area, genes with large effect but reduced penetrance which has up to now been systematically underexplored. I think there are opportunities to find these genes, both autosomal dominant and recessive forms and then the granddaddy problems, the multifactorial susceptibility genes where as we heard about yesterday from David Bentley we will have the opportunity hopefully in the future, in the not too distant future to be able to do genome wide linkage disequilibrium studies that may help us identify these multifactorial genes that are common in the population but have small incremental effects on traits and in addition, as we heard about from Pat Brown, genomic approaches to identifying of the identification of these pathways will likely also be of critical importance. And then at the end of course there's a critical need to translate these validated targets and pathways into new types of gene that are most likely to be developed by the gene of the Peter Goodfellow. Among the challenges that we face going forward is that there's a paucity of clinical investigators and we need to improve this pipeline. We need larger and better phenotype cohorts, the tools that are being developed by the genome project are going to be most readily applicable to very large well phenotype cohorts. We're woefully unprepared for this task in most investigations. It would be tragic if the fruits of the labors of the genome project are thwarted in their application because we are unable to overcome some of the regulatory barriers that we now face and ultimately we need a better handoff from academia to the pharmaceutical industry. However, based upon the optimism that carried the genome project over the last 15 years to where we are today, I confess that even a hardened pessimist would be very rapid and stunning pace. Thanks very much for your attention. Our next speaker is Nancy Cox. Nancy is a quantitative human geneticist and professor of human genetics and medicine at the University of Chicago. She'll speak to us today about her research in diabetes and the title of her talk is Paradigms for the Genetic Component of Diabetes. Thank you and it's really exciting to be here as part of this terrific celebration. I'm particularly excited to be here to talk about what I always call a poster child for complex disorder, complex disorders, diabetes. Diabetes is not really a single disorder, but many heterogeneous disorders, all of which are characterized by high blood glucose levels. Diabetes is common as are many complex disorders affecting large numbers of individuals in the United States, more than 15 million, and worldwide more than 150 million. Diabetes arises collectively as the consequence of the actions and interactions of many different genetic and non-genetic risk factors. Some forms of diabetes result from mutations in single genes, so there are monogenic forms of diabetes, similar to those for other complex phenotypes as Rick Lifton discussed. But the majority of diabetes is multifactorial polygenic in origin. And as with most complex disorders, we all hope that the identification of genetic risk factors for diabetes will lead to improved diagnosis, treatment and prevention strategies that address the underlying molecular defects rather than just the broad symptoms of the disorder. And there are already indications that this will in fact be the case for diabetes. Preliminary studies indicate that some of the rare monogenic forms of diabetes, maturity onset diabetes, the young, has at least if not more effective treatment strategies, at least some that are more easily tolerated by patients. So genetic identification of particular disorders is already paying off in terms of treatment strategies for individuals with diabetes. Diabetes is increasing epidemically worldwide now. What is shown in the top box is the number of individuals in the millions affected with diabetes in the year 2000. In the second box, the projections for the year 2010 and the last box, the percentage increase. And I would draw your attention to several aspects of this epidemic. One is that ironically, as developing nations adopt the modern western diet and lifestyle, their per capita rates of diabetes actually exceed those of the western societies. And therefore the percentage increases that are projected for many parts of the world will have really catastrophic implications for public health care in areas that can least afford to deal with these problems. It was also horrifying to me to learn at a recent meeting that these projections were made largely without reference to epidemic increases in obesity that are also projected. So as bad as these increases look for the increase in prevalence of diabetes over the next ten years, they are probably underestimates based on the increasing prevalence of obesity. What I want to try to go over today are some of the paradigms that have been used for gene identification in diabetes, some of the traditional paradigms such as candidate gene studies and linkage mapping and positional cloning, but also some of the novel paradigms that are already being used in studies on diabetes, some of which were brought up yesterday in presentations by Eric Lander and others. And I also want to focus on how what we are learning about diabetes susceptibility loci are changing our perceptions, shaping our perceptions about what we ought to be looking for and how that is modifying the paradigms for susceptibility locus identification going forward. So candidate gene studies have been successful in diabetes. This is a very abbreviated list of the genes that have been identified through candidate gene studies and designed not to be exhaustive, but just to illustrate some key points. And unfortunately the first point I would make is that based on my own unscientific survey, the success rate of candidate gene studies thus far has been about one in a thousand. That's true not just for diabetes, but for complex disorders in general. And I think a key point to remember going forward is that we will get smarter about what the right candidates are. So while candidate gene studies have not been tremendously successful so far, the success of the Human Genome Initiative and the biology that will follow that will improve our ability to do intelligent candidate gene studies. And those will probably be the most efficient ways of identifying susceptibility genes in the not too distant future. Points that I'd like to make from the candidate gene studies in the maturity onset diabetes of the young, which is a rare monogenic form of type 2 diabetes, is the observation that many of these candidate genes were identified as a consequence of original linkage mapping studies. So for example, the first transcription factor identified for maturity onset diabetes of the young was a result of a regular, fairly brute force positional cloning study. But once the first transcription factor was identified, many additional transcription factors have been shown to give rise to maturity onset diabetes of the young. And so we have a much more effective candidate gene strategy there. The candidate genes for identified in type 1 diabetes, HLA, was identified in the 1970s in classical case control studies and really helped to clarify the nature of the genetic heterogeneity in diabetes by distinguishing type 1 diabetes from type 2 diabetes. So most, most diabetics have a later onset form of diabetes, termed type 2 diabetes, where there's a relative insufficiency of insulin leading to elevated blood glucose levels. About 7 to 10 percent of diabetics have this form of autoimmune diabetes, type 1 diabetes, and only about 3 percent of individuals with diabetes have monogenic forms such as modi or mutations in the insulin or insulin receptor locus. So HLA was identified in classic case control studies and is a major risk factor for type 1 diabetes. The insulin gene region, the insulin gene region VNTR was also first identified in case control candidate gene studies, but was the first and perhaps best success of the family-based methods for association studies. The TDT was developed and applied first to the insulin gene region in type 1 diabetes. Both of these loci can be detected in linkage studies. So the insulin gene region takes about, takes more than 700 families to detect significant evidence for linkage. The HLA locus in type 1 diabetes takes about 50 families to detect significant evidence for linkage. So you can see that there's a real disparity in terms of the magnitude of the familiarity contributed by these two loci. But in fact, in large-scale linkage studies where the LOD score at HLA and more than 700 families was 65, the next, the locus with the next highest LOD score was in fact the insulin region which had a LOD score just over four. So that gives you a sense of the frustration that we have in type 1 diabetes because of the linkage mapping of the susceptibility loci after collecting many, many families, the linkage mapping identified two loci, two regions that we already knew about from candidate gene studies. Again, for type 2 diabetes, these particular candidate genes that I'm focusing on are not meant to encompass all of those that have been identified in candidate gene studies for type 2 diabetes, but rather to illustrate the evolution in our understanding of the underlying pathways. So in the early days, when we understood much less about the pathways involved in glucose homeostasis, the insulin gene, insulin receptor gene were the obvious candidates. Now as we understand better the pathways of glucose homeostasis, loci like P par gamma come to the forefront, again illustrating that as we understand the pathways better, we will get smarter about the candidate genes. So what have we learned from these candidate genes? Do these studies inform our understanding of diabetes? How do they help us to generate new hypotheses about what to look for, utilizing the data emerging from the human genome initiative? I think a key point is thinking about what we have learned from the genes that can give rise to this complex metabolic phenotype through single gene mutations. And in particular the paradigms that emerge from the study of the identification of transcription factors as genetic susceptibility loci for maturity onset diabetes of the young offer some interesting and important hypotheses for the kinds of loci that may generate linkage signals in diabetes in general. So if we think about these loci, they're higher level regulatory genes. They regulate the expression of many other genes important in glucose homeostasis. With the new data that will be emerging from the human genome initiative with the description, fuller description of pathways involved in metabolism and glucose homeostasis, it would be possible to test the hypothesis that higher level regulatory genes, whether we mean regulatory at the level of at the level of the DNA or regulatory at the level of proteins or as Dr. Raleigh referred, RNA, the hypothesis that the higher level regulatory genes will be the ones that generate linkage signal while those genes and proteins that they regulate will be the polygenic background is one that we'll be able to test in a systematic way going forward. Regulation at a different level, I think is illustrated by the emerging understanding of how the insulin gene region variation affects susceptibility to type 1 diabetes. So in contrast to the very rare mutations that give rise to susceptibility to monogenic forms of type of diabetes including maturity onset diabetes of the young, the allele increasing the risk to type 1 diabetes at the insulin, the NTR has a frequency of 0.75 in populations of European descent. That is a very common risk factor. This variation leads to different, differential expression of insulin in different tissues in the body. So in the beta cells of the pancreas the protective class 3 VNTR alleles are associated with lower insulin mRNA levels than the diabetes predisposing class 1 alleles. Whereas in the thymus the protective class 3 VNTR alleles are associated with higher insulin mRNA levels. These results are consistent with the model in which high level expression of insulin in the thymus facilitates immune tolerance induction resulting in dominant protection for type 1 diabetes. The association of this variation at the insulin locus with type 1 diabetes has been known for more than 15 years and has been essentially universally believed certainly since the studies using the TDT. It took a very long time to generate these observations and this hypothesis. And I think even with the biology that will come out of the human genome initiative we will need to be patient in understanding how variation at susceptibility loci for complex disorders actually generates the differences in risk that we see. And I think another point that we maybe need to keep in mind going forward is that we won't always need to understand or even identify with certainty the exact variation that affects susceptibility to disease. If we can provide enough evidence that the loci are actually the key susceptibility loci and disease that alone will help us understand pathways better and open up new understanding of the disease processes. Another traditional paradigm for identifying genetic variation for monogenic and complex disorders is the linkage mapping followed by positional cloning. The strategy has been spectacularly successful for the monogenic subtypes of diabetes as it has for hypertension and cardiovascular disease and other forms of cancer. The monogenic subtypes of complex diseases were very amenable to this strategy. And in many cases the linkage mapping was followed by immediate gene identification because of the location of a candidate gene directly under the linkage signal. So this was true for example for glucokinase in the linkage mapping for one of the MODI genes. In other cases linkage mapping requires more brute force positional cloning as with the first transcription factor identified for MODI. In complex disorders there's a lot of additional complications to using this general approach. In the first place the linkage mapping has been far less universally successful. In general our signals are much more modest even in very large data sets and the resolution of linkage mapping is very broad. So we are looking for genes in a very large physical region for the complex multifactorial polygenic components to type 1 and type 2 diabetes. One of the responses to these difficulties has been the establishment of consortia for linkage mapping in both type 1 and type 2 diabetes. These consortia involve virtually all of the world's investigations for linkage mapping and these disorders encompassing investigators from academia and industry and I think it allows us to consider not just the very large scale pooling of data to facilitate linkage mapping but a key strategy will be to use more phenotypically homogeneous subsets of families for example defined on the basis of BMI or aged onset to increase both the power and the resolution of linkage mapping. The advantages of this sort of strategy the linkage mapping followed by the positional cloning is the ability to identify genes and pathways outside of our current understanding of the pathophysiology of disease. This will also be true for the newer approaches that will be based on genome-wide association mapping or linkage disequilibrium mapping that we all foresee as an outcome of the studies from the Human Genome Initiative. So the advantage of being able to identify new genes will be new pathways will be really important. This was one of the outcomes of our own studies in type 2 diabetes identifying variation at CalPain 10 as being associated with type 2 diabetes. CalPains are processing proteases that cleave proteins usually at a single site to either inactivate or activate the protein. And so in some ways the general take-home message from CalPain 10 as a diabetes susceptibility locus is analogous to what was observed for the transcription factors in Modi. This is regulation of proteins rather than regulation of genes at the level of the DNA but it's still about regulation at a relatively high level. The models that we characterized for how CalPain 10 variation affects susceptibility to type 2 diabetes are now while they were fairly radical departures from expectations when we first proposed them they're now pretty mainstream and characterized in positional cloning studies for other complex disorders. So we identified primarily non-coating sequence variation as necessary to characterize risk and multiple polymorphisms need to be considered simultaneously. These sorts of models have now been similarly identified in genes positionally cloned for schizophrenia for asthma for stroke and I think this is raises the importance of understanding functional elements in the DNA that we have not previously recognized as functional. So non-coating sequence variation I think will continue to be very important in understanding the risk for complex disorders certainly type 1 and type 2 diabetes for complex disorders as well. I'd like to talk now about some of the novel paradigms that were discussed yesterday including evolutionary approaches so there's a long-standing hypothesis in diabetes that the same variation that now increases risk for diabetes once had an evolutionary advantage for diabetes it's easy to the original hypothesis from Jim Neil the expression of variation that optimized glucose homeostasis. So broadly speaking the same hypothesis is relevant for perhaps relevant for type 1 diabetes another autoimmune and inflammatory disorders in the sense that the environment has changed with respect to exposure to pathogens and the development of the immune system. So I think evolutionary studies have some really interesting possibilities for an independent identification of regions that may be implicated in disease susceptibility. Studies in Anna DiRienza's lab on CalPain10 have led her to focus on a region within the gene where she believes there's a signature of natural selection these observations are coinciding with observations in my own lab looking at the difference in the magnitude of linkage disequilibrium between cases and controls that also localize susceptibility to this particular region of an intron and both of those are converging with studies initiated by others looking at expression as a phenotype with respect to CalPain10 so studies in Graham Bell's lab are focusing on this variation that seems to affect expression of CalPain10 and again these studies are localizing this variation to the 3 prime half of the gene with further investigations necessary to know whether it's going to localize within this same intronic region so those are the kinds of studies that I think will be important in complex disease studies in general closed by with reference to some of the things Shirley said yesterday as a quantitative as one of the more quantitative of the biological sciences genetics has always drawn a lot of purely theoretical interest but I think one of the lasting legacies of the original Watson and Crick discoveries and the the legacy of the progeny of Watson and Crick theory and genetics will not be done in a vacuum you all have generated so much data that we will never be able to use to have theory that is not responsive to all of the data that's been generated I just like to close by thanking my colleagues from both the theoretical and the molecular who keep us grounded thanks thank you very much Nancy our last speaker Adrian is professor of human genetics at the welcome trust center for human genetics at Oxford he is going to be speaking to us today about gene identification for infectious disease resistance the first 50 years thank you very much and I'd like to thank very much the organizers for inviting me to this superb celebration it's an honor and a privilege I could have the slides on please thank you I must say I found yesterday both entertaining and very enlightening and was particularly interested in the talks on comparative genomics which clearly is making huge strides very rapidly and it was clear that evolution is really conserving selecting for prioritizing certain types of genes over millions of years and those can be summarized as genes involved in immunity resistance and in reproduction so the way I would summarize that is that evolution really only cares about two things infectious disease resistance and sex and I would submit to you that if you're going to be interested in just two things in life that's not a bad selection it certainly works for me but thinking about sex I'm afraid the problem here is I've only got time to talk about some of the subjects and you're not going to get any well I see that Peter Goodfellow is up a little later just after lunch and maybe you'll be lucky then so what I'm going to talk about is this and this is really a problem infectious disease mortality and this is what happened in the last decade 1990 to 2000 TB winning the prize at the top of this gory list for the most deaths 30 million deaths but the point really is we haven't cracked these diseases there's a huge amount more we need to know about them we need new interventions we need many new vaccines and we need to understand more about their pathophysiology and of more fundamental interest we need to know more about what they have done to us and to our genomes and this field as I try to suggest in my title some events happened in the other place in Cambridge in England that lead to us being here today now for those of us well many of you will be aware that for those of us in Oxford in England there has been a certain amount of rivalry between these ancient universities over the last 700 or 800 years or so and I guess if that event happened today there would be university vice-chancellors and what we would do in 1953 life was a little simpler so what actually happened was that a young research fellow by the name of Tony Allison finishing his D. Phil studies set out for the tropics he spent most of 1953 in East Africa and did some studies that were summarized in his publication submitted by the end of the year that appeared in the British Medical Journal in February of 1954 for the Cichl hemoglobin and malaria and what Tony did with characteristically was a characteristically direct study where he identified 30 Luo individuals in Nairobi and gave them malaria these 30 were not randomly selected half of them were heterozygous for Cichl hemoglobin the others were not and he showed very dramatically and very clearly that there was a difference in susceptibility between malaria on malaria administration arguably the first demonstration of a polygene in a complex disease he also did an epidemiological type study one of many since showing that there are lower parasite rates in individuals heterozygous for Cichl hemoglobin and lower parasite densities as well so that started a bit of a cottage industry which has grown since and I think this slide shows that the hit rate in malaria and even though I wouldn't stake my life on maybe more than half of these certainly eight or nine of them are definitely right and arguably this is the best summary of many genes being involved in any complex disease you can see on the far side that there are genes involved mainly in red cell invasion and parasite growth and then of more interest to me over the years genes that affect the immune response to malaria including our own work on HLA are associated with resistance to severe malaria this we feel is more important in that we can think more easily about interventions that you might develop looking at the immunologically relevant genes like HLA B and we have tried to develop vaccines following that strategy TNF the work of Dominic Kodkowski's lab has led to another type of intervention the use of anti-TNF in African children with severe malaria but we need to see more genes we need new interventions the candidate gene approach has worked in other diseases as well this is just a brief and incomplete summary of genes identified by case control analysis in TB pneumocouple disease, HIV largely worked from NCI and other units in America and hepatitis B but the point I want to make about all of these is these are not genes with effects of the magnitude of sickle hemoglobin that gives you around about 90% of these small effects and by and large I think this is what you will find and what we do find in the study of infectious disease resistance which makes the exceptions all the more exciting there are only four I know of I've talked about one already sickle hemoglobin then Lou Miller's work on the Duffy blood group and vivax malaria most sub-Saharan Africans are Duffy negative there are 32 mutation in the chemokine receptor 5 C-C chemokine receptor and then many of you will be aware that there's a kind of long-running experiment in progress in Britain at the moment those of us who meet in the 1980s are being followed up a hundred or thereabouts of us have developed the human equivalent of mad cow disease due to a pion that also in humans gives new variant tritial Yakov disease developed new variant all had exactly the same genotype at the prion protein gene a genotype that's found in only 40% of the population so a clear absolute association with susceptibility for that genotype whether the rest of us are protected or just going to get disease later remains to be seen so given those four examples of major gene effects what tantalized us a few years ago was whether instead of carrying analyses in different diseases we could apply linkage analysis in families to pull out a few more big genes in complex infectious diseases we've taken the effect of Zipair analysis route and the first success we had really was in a rather unique disease leprosy leprosy is pretty horrible it's reducing in prevalence but not an incidence in the world two forms of interest to immunologists tuberculoid with stronger cellular immune responses more of a skin disease and leprosy was once actually considered a familial disease in the mid 19th century but then it was the first emilepre the first pathogenic to be seen down a microscope probably the first disease with the defined HLA association using family based association analysis in the early 1980s and now I'll show you the first disease where we think and this involved collecting literally hundreds of families in southern India with our collaborators a classical affected Zipair analysis on 245 Zipair's showed a peak of linkage lot score of over 4 on 10 p13 and luckily there was an obvious positional candidate gene in that region encoding the macrophage manus receptor MRC1 this is a C type lectin an entry receptor one of many and also has a key immunological role in micropanocytosis by dendritic cells leading to antigen presentation so Kerry Tosh in the lab defined lots of new slips and markers in that gene of over a hundred kb and intriguingly there was a cluster of polymorphism shown there in red which in fact are a cluster of three amino acid changes within 12 amino acids in CRD2 carbohydrate recognition domain too showed clear evidence of association within families in fact the strongest association is with the haplotype but most of the effect is due to SNP74 shown there a glycine to serine change and some elegant analysis by Long Carden in our center at Oxford showed that you could attribute essentially all of the linkage to these variants within this one gene and in fact some molecular modeling and some thermostability destabilizes this carbohydrate recognition domain interestingly from an evolutionary point of view this is a variant that is common in Caucasians if you like in Indians and in Europeans much less frequent in Africa the opposite of the geographic distribution of the malarial resistance gene sickle hemoglobin and perhaps relating to the fact that there's been far more mycobacterial disease over the centuries and hepatitis B virus infection a good illustration of a dichotomy in immune responses in humans with 15% of people failing to clear that virus those who become persistent carriers are at high risk of a paracelular carcinoma the commonest cancer in Africa and some evidence of a genetic association including intriguingly a high rate of persistence in those with trisomy 21 intriguing because that's where we found the linkage curve Q 21 Q 22 and again we were relatively lucky in that close to the peak of that linkage curve is a set of cytokine receptor type two genes including the two chains of the interferon alpha receptor interferon is a treatment for hepatitis B the second chain of the gamma receptor and the IL-10 receptor beta and again we were able to show within families this time that actually two of these genes can be used in infectious disease and can probably account for most of that linkage the IFNA R2 and the IL-10 RB gene and functional workers in progress so where we've got to is four diseases have been looked at these are chronic diseases most infections are acute so in the chronic diseases you can collect families you can do linkage studies in leprosy a gene has been identified in hepatitis B interestingly we see different genes like the Gambia the loci I talked about but Angela Fraudson's work in Italy suggesting that a quite different gene at a different location on the long arm of chromosome 6 that she's mapped and identified is the major susceptibility locus in that European population so clearly in our view genetic susceptibility to infectious diseases is polygenic mainly is accounted for by an accumulation of small effects from multiple polygenes but exceptionally you can find in linkage analysis and to finish I just want to reiterate the importance of these studies for evolution most people who work on evolution these days work with VDUs and computers looking at if you like the bodies in the evolutionary battlefield if you're looking at infectious disease and doing studies in the field where infection is still killing millions of people every year you have a chance to watch the battle and recognize the residue of the dead if you like so by looking at genes that are of key evolutionary importance I'll give you one more example you can get a flavor of what's going on these are tall receptor genes identified only in the last few years there are 10 of them scattered throughout the genome and these recognize PAMPs pathogen associated molecular patterns which are central to the recognition of pathogens and to the innate immune system tall receptor 4 and the pathway of endotoxin or lipopolysaccharide that's all been worked out very quickly and there is an amino acid change at position 299 of TLR4 which again in some interesting human challenge studies was shown to be a hypo functional allele when you give people inhaled endotoxin this variant therefore is hypo functional both in those clinical and transfection studies and other people's workers is hypo functional so why have we got a hypo functional variant in a key innate immune system receptor the answer again is probably malaria here in a study of about 4,500 children from three different countries in Africa Gambia, Kenya and Malawi we see modest but clear protection odds ratios of about 0.7 0.6 again severe manifestation of malaria in these African children so what we have is a hyper responsive allele of TLR4 that's interestingly found at higher frequencies in sub-Saharan Africa than elsewhere and malaria may have provided the counter selective force for this partially active allele in other words we may have a balanced polymorphism of the innate immune system with that variant being good for malaria but bad for gram negative bacterial infections so clearly infectious disease associations have been defined with many genes using a variety this is almost certainly just the tip of the iceberg in tuberculosis we know there's a major human susceptibility component these are four early twin studies each showing much higher concordance rates in identical to non identical twins two genome scans in western South Africa by linkage have been negative in TB as there have been in many other diseases so clearly the genes that must be there are not big enough other people do is to genome wide association studies I would argue that these are more likely to be productive in complex diseases that have selected our genome than in many other diseases simply because these are highly polygenic diseases you need to do this sort of study because the odds ratios are small you need to do big studies because almost certainly epistasis will be important that's been shown in HIV very recently by Mary Carrington's group genetic interaction so I'll leave you with the thought that there's a huge amount to do now we finally have the tools to do this with genome wide association studies in infectious disease and close by acknowledging the many people around the world who've been collaborators as well as actively involved in this research thank you very much so I'd now like to call all of our speakers for this panel up here and you can your microphone and please if you have a question in the audience there are two microphones in the aisles and I'd like to ask you to come up to the microphone and ask your questions we do have plenty of time for questions and so I want to see some people up there with your questions because I'm not asking all the questions for this panel wonderful I'd actually be curious to hear from either each of you or a subset of you you've covered broad areas of biomedical research each case illustrating quite nicely how things are about to change or just starting to change in the past couple years you've seen evidence and I would be curious to hear how since all of you have been so wildly successful doing things up until your laboratory staff in terms of their levels of expertise what they need to be doing say five years for now your programs and your respective areas what are the new tools and skill sets that are going to be needed in your laboratory that are different than what you've seen over the past say three to four years so did you want to direct your question to I mean I would actually encourage you to direct your question to oh but I like them all but I'll pick on Rick how's that okay good I think it's really boring when everybody feels obligated to answer the same question but you have to find the answer the the challenge I think is very clear the we will need to be doing much higher throughput genotyping if you imagine doing linkage disequilibrium studies will be need to be doing typical studies with millions of genotypes rather than tens of thousands of genotypes we need to be mining data we need to have much better informatics expertise is we tend to lose the idea that at the end of the day there needs to be a cortex at the end that can get around all of the data and actually interpret it and decide what it means I think there is the mistaken notion probably best exemplified in the biotechnology industry that if you simply generate a lot of data it will answer its own questions and I think that is something that clearly won't be easy to make sure that we don't build these notions that it's going to be easy if we just generate a lot of data Rick can I have one follow up because I suddenly and I guess I will point this back at you because I know it's something you're very interested in you've been so successful at getting clinically trained researchers involved in the problems that you're studying and certainly at NIH there's a tremendous amount of interest now in thinking and you raise it even yourself about you know we don't have enough clinical investigators how are we going to train what recommendations would you make for training clinical investigators who are already burdened with needing to learn clinical medicine and face all the challenges just being a clinician and being a clinical researcher but now on top of it having to gain additional skill sets to take advantage of this new genomic era. Yeah I think it's clearly among the multifactorial problems that we encounter this is one of them. The barriers I think are relatively low clinicians really come to genetics quite well the idea that you're starting with a top down strategy of a disease that they already know something about from their clinical experience is a very natural one for most clinicians and the barriers I think are creating environments where they feel comfortable and know that they actually have a career future if they follow a particular career path and work hard and are successful. Some of the barriers that we have now are clinical investigation looks enormously unattractive to many investigators given how hard it is to simply get IRB approval to start a study these days. So these I think are among the challenges that we face also loan forgiveness programs. Most clinicians finishing their training are an enormous personal debt and trying to figure out how to encourage physician scientists to take this road is a continuing challenge. The good news is this work is enormously appealing to any physician who has the faintest interest in investigation because there's nothing more satisfying than wrestling a disease that's been on the planet since the evolution of man to the ground and understanding it at a fundamental level. If I could just also echo some of what Rick said I think that there has always been something of a partnership between the scientists at NIH and the academic community and I think that's even more important now and in the future just as I illustrated our dependence on being able to go to a well curated database to then match our sequences to what was already known. I think that the efforts as outlined in the genome strategic plan for the future of trying to move as rapidly as possible to understand the complexities of the pathways within cells and the interaction of pathways is going to be critical because the more information you can have at your fingertips when you identify a gene or a sequence and go into the databases to see what's known about that and what is its functional role the more quickly you can generate some hypotheses about why that particular sequence might be affected in whatever disease it is that you find so I think that's important and I can't emphasize enough Rick's comments about clinical research and the increasing difficulty of trying to link samples from cancer patients with their clinical outcomes so that you can immediately see which genetic changes are associated with poor outcomes or aggressive disease and which ones are associated with a more response with a greater response to treatment and this is going to kill not just hamper but kill clinical research unless this is dealt with and since many of the regulations are coming from the government and from HHS it is absolutely critical that those who have some voice within that particular government program act to have people responsible for the generation of these rules understand the enormous detrimental impact that has on clinical research. This being the difficulty of getting IRB approvals for clinical research. That's right and the rules that are now out there is that if you do not have approval from a patient to use a sample for genetic studies you have to go back and get the approval and in leukemia these patients are by and large dead so you have to go find relatives to get the approval. It's catastrophic. Next question. David Valli Baltimore before I ask my question I might take my speak from my position as President of the American Society of Human Genetics the major research organization for human geneticists to second what Dr. Rowley just said. Then I have a question for Dr. Hill which I was very intrigued with his report of discovery of genes of both minor and major effect in terms of resistance to infectious disease and I wonder if he could just tell us a minute of his thoughts about how this will lead to drug development and especially to preventative approaches based on individualized risk. Thanks. As I hope I made clear that there are many reasons for doing infectious disease genetics and many reasons for doing genomics as we heard yesterday and only one of those is to try and develop new interventions but having said that that is one of the most important goals. I think the problem with most infectious diseases is that we need to move from understanding the concept of simple pathogen causing disease as being a one to one relationship to understanding the complex pathophysiology that determines why I say only 10% of people who are infected by mycobacterium tuberculosis end up with disease. So clearly there are a huge number of environmental and genetic factors along that pathway that determine whether you get a unnoticed subclinical infection or you end up dying from TB. And the tantalizing thing is that most of us can deal with most of these infections most of the time. Only 15% of people become carriers of hepatitis, only a fraction get TB, only a smaller fraction get leprosy. So we have the immune mechanisms and defense mechanisms to deal with these diseases. And it's only a small proportion that are failing. And the key question is how do we identify those people and identify what's different about those. So I think the chances of being able to modulate that subtle change in susceptibility by understanding the pathways in principle are very good. The problem is that most of the interventions we've tried like anti-TNF antibodies in severe malaria so far, and that's an intervention that came from the genetics of TNF polymorphisms, promoter polymorphisms and malaria, are applied too late. So I think the most important interventions will be preventive ones, particularly in developing countries in low cost settings. And clearly we're looking at immunomodulation, we're looking at vaccines, and the challenge now with our new tools and new vaccines that we can make is to target the right sort of immune response to prevent these particular diseases or particular manifestations or particular infections. So the short answer is an understanding of pathophysiology. And from that perspective, the more genes there are, the better off you are because the more pathways you can interrogate with millions or hundreds of polygens, then if there's only two or three genes, that's all you can learn about. Thank you. This is Bob Nussbaum from the NHGRI. Before I ask my question, I just wanted to echo Dr. Valley's comments as the President-elect of the American Society of Human Genetics, I'll be receiving the baton from his hand next year, the importance of IRB regulations and HIPAA regulations being interpreted in a way that maximizes protection at the same time that it does not interfere with the societal good that can come from this kind of research. I had actually a specific question for Drs. Cox and Hill, and that is if they wanted to comment on the importance of genome efforts in animals and animal models for disorders like infectious diseases and glucose homeostasis and how much that has helped or not helped in furthering our understanding of the human disorders. Yeah, very briefly. Mass genetics in particular has made important contributions in my own area of tuberculosis. One of the genes that has been shown to be relevant in human TB came out of mass genetics that was the NRAM gene worked on in Montreal for many years. That unfortunately is not the only example, but it's one of few, and the difficulties you have is that very often the pathogen has evolved as much as the human host. So the mouse malaria, for example, separated from the human malaria is around about the same time that mice separated from humans 50 to 100 million years ago. So there are substantial differences, and of course there are differences between different strains of mice and between other animals. So it's often hard to find the right model, particularly with the same pathogen, where you can use mouse models to identify key susceptibility genes. On the other hand, you could argue that what you're really after is pathways rather than the genes, and that will often be the case that new pathways can be identified by genome scanning in mice, and we're beginning to see more of that in malaria in TB and other infectious diseases. But if your pathogen doesn't infect mice, you have a problem. Yes, I echo that with respect to glucose homeostasis. So it's very reminiscent of the monogenic genes that have been identified in humans. Most of the genes identified in the mouse to date are not major risk factors in humans, but nevertheless have shed incredible light on new pathways and areas that we had very no knowledge of before they were identified in the mouse. So I think model organism studies will be key, not just in the mouse, but even in model organisms ranging from Drosophila to yeast, I think they'll be useful, but certainly and there are emerging models more polygenic and multifactorial for diabetes in the mouse, for example from Ron Kahn's group, that I think will be very useful in understanding how glucose homeostasis works and testing drug therapies for effectiveness. Jennifer Puck from the NHGRI, many of you, actually all of you have indicated how some of the very rare single gene disorders in humans have illuminated or started out studies of more complex and more common illnesses, but in the case of immunodeficiencies there are over 110 distinct rare single gene disorders known. How do you see these illuminating the more common diseases that we'd like to try to get a handle on? Yeah, just a quick comment on that. Of course those are by and large great candidates for diseases that are dependent on an immune response. Surprisingly, we have almost no examples of a disease where a knockout mutation causes a severe immunodeficiency in humans, and a subtle change in the expression of that gene is a polygene for a complex disease. The nearest is the interferon gamma receptor where knockout mutations of that or the IL-12RB2 gene give you susceptibility to usually non-pathogenic mycobacteria like mycobacterium avium, and there's some preliminary evidence that promoter variants of the interferon gamma receptor 1 are associated with TB susceptibility. But if you take those 100 genes as a standard, it's for common infections and it's interesting to speculate why in evolutionary terms. Certainly in terms of understanding basic biology, these are going to turn out to be enormously illuminating. That's probably not the soul fault of monogenic diseases that we haven't come up with new therapies since the entire field of immunology I think has been rather disappointing up to date in terms of coming up with new therapeutics. But just to cite one recent example, the polyglandular autoimmune disease with the mutation in the air gene. This has clearly I think been one of the spectacular new insights into the fundamental regulation of how we distinguish self from non-self and recent manuscript demonstrating this may be the transcription factor that leads to the expression of genes normally confined to specific organs in the cells that are determining self from non-self. These are I think going to be a fundamental importance. So I think the basic premise remains that understanding these rare diseases is illuminating basic biology, obviously which are going to turn out to have immediate therapeutic interventions I think is always a matter of speculation and largely of chance and you won't know until you get there. And we'll take one last question. I'm afraid it's not so much a question as a comment from Peter Goodfellow. Genetics works by actually you can only see what varies. So if in your population something isn't varying you can't see it by genetics which is another way of saying that pathway expansion is actually crucial. And similarly just because you identify a gene through that's the best point in that pathway for therapeutic intervention. Yes, I would certainly agree with that. And I think the example that I cited of the cholesterol biosynthetic pathway being inferred from mutations in the LDL receptor demonstrate that you do need to bootstrap your way from identifying a specific gene that's mutated to fleshing out the pathway. Now the fact that there are even alleles on the planet most of the genes that can be mutated are mutated but it's very fair to say that many of these will turn out to not be viable so we will never see them. And unless we have the ability to use these genomic approaches to go from understanding a particular gene to what pathway it's operating in we will likely be very unsuccessful in devising new treatments. Very good. Let's thank our panel again and then we have a break. Please be back by 10.30. While people are getting seated I'd like to tell you a little bit about my association with the genome project. I was acting director starting in 1992 when Jim Watson stepped down as director of what was then the National Center for Human Genome Research. And I must say it was a great privilege for me to interact with many of the incredibly talented architects of the genome project who you've been hearing yesterday and today and I was charged with two jobs when I took over which period of about a year. The first of my tasks was obviously to continue the momentum that had been started by Jim Watson and I just want to say that for me that was a relatively easy job because of the incredible support of the then deputy director Elkie Jordan who just retired last year and was deputy director of genome for all those years and many of the other people who were in the office when I arrived Jane Peterson who you've already met, Mark Geyer and many many of the other staff the staff of genome is absolutely fantastic and deserves a great deal of credit for the success of this project. My second job was to recruit somebody to replace Jim Watson not an easy person to replace obviously and it became clear after some searching that Francis Collins was in fact the person for the job based on his interest in human genetics, his intellect his personality and his leadership skills and also the fact that he could sing about DNA not only on key but with enormous enthusiasm and that was a unique quality that I think was the final reason why he was chosen to head the genome project. I also want to point out that I am aware perhaps more than anyone else that it was on April 4th, 1993 that Francis arrived to take the helm and become the steward of the human genome project because I was liberated. I thought at that point to go back to my lab as it turned out I was subsequently tapped for other responsibilities but Francis arrived and it was just 10 years and 11 days ago. So this is also in addition to all the 10th anniversaries that we've been celebrating. This is the 10th anniversary of Francis Collins leadership of the genome project and the modest person that he is, he never mentioned this but I thought I would bring it up and thank him both for relieving me of the job but also an incredibly a terrific job of leading a program which has been so very very successful. Now with those introductory comments some of you may have noticed that we were talking about genetics for parts of the body below the neck earlier in the morning and now we're moving above the neck to various sensory organs including the brain and I think we have some very very exciting talks to come. We have five talks. I have to ask the speakers to keep to the 15 minute time period or we will get into trouble later on in the day. The first speaker is Tony Monaco director of the Welcome Trust Center for Human Genetics. He received his M.D. and Ph.D. from Harvard Medical School and has been working on the basis of both neurological and psychiatric disorders. He will speak today on genetics of speech, language and reading disorders. Tony. For that nice introduction it's very nice to be here. I work at the Welcome Trust Center for Human Genetics and you heard from my colleague Adrian Hill we've been set up since 1994 trying to identify susceptibility genes for common disease and using the fruits of the human genome project every stage and now we look forward to using the variation that will come out of the human genome project in our goal to identify these susceptibility genes. Today I'd like to tell you about work in my own lab which aims to understand the development of the brain through molecular genetic strategies in behavioral and learning disorders in children including autism, specific language impairment, reading disorders like dyslexia and attention deficit hyperactivity disorder. But today I'm going to focus my attention on specific language impairment which affects about 5% of school children and it's really a diagnosis of exclusion where children who have difficulty acquiring expressive and receptive language despite normal nonverbal intelligence and opportunity and also in the absence of any sensory or neurologic other diagnosis. Specific language impairment or SLI is a large comorbidity with other childhood learning disorders including autism, dyslexia and ADHD and children with SLI have difficulties later in adult life with cognitive and social functions and also at increased risk of psychosis. So one of the genetic factors in SLI it's been known for a long time that speech and language problems cluster in families but of course this familial clustering can be to either genetic factors influencing the trait or the fact that individuals within a family share the same environmental factors. However twin studies pioneered by Dorothy Bishop and others have shown quite conclusively that speech and language disorders are very heritable with difficulties in monozygotic twins being much higher rate than dizygotic twins. Also if you treat language impairment as an extremely continuous trait one can get significant estimates of heritability which are over 95%. So how do you find genes for SLI? We've used two strategies one is a quantitative trait loci approach where one selects children who are at the extreme tail end of a measure of language ability and then assesses all the siblings in that family to see how the trait differences between siblings measures up to their genetic similarities across the genome. Another method we have used is to try to find rare multi-generation pedigrees that have severe speech and language problems and I'll tell you about one such family the KE family which is shown here about 50% of the individuals in the family over three generations are affected with a very severe speech and language disorder males and females equally affected it looks like a clear and simple auto-symbol dominant trait so although there's simple inheritance of the trait the phenotype is quite complex probably the most tell-tale sign of their phenotype is what's called verbal dyspraxia and that's a problem with the fine or a facial movement needed to articulate speech however it's not simply a motor problem they have deficits in multiple aspects of language abilities both receptive and expressive including the processing of phonemes and grammatical skills their nonverbal deficits are much reduced compared to the verbal deficits and they are some of the performance IQ affected members is less than you would consider normal however there's a large range of that and one would not consider the nonverbal deficits as characteristic of the phenotype in the affected members of this family and lastly brain imaging studies of the group in Institute of Child Health in London have shown both structural and functional abnormalities in affected members of this family in both cortical and sub-cortical motor related areas especially the basal ganglia and later when we'll see the expression pattern of the resultant gene Simon Fisher in my group in 1998 mapped this gene to a region of chromosome 7 Q31 right near the cystic fibrosis gene and using the first draft of the human genome sequence from that region facilitated with our collaboration with Eric Green we're about to identify a gene called Fox P2 however it was the stroke of identifying a second patient CS Jane Hurst a clinical geneticist in Oxford identified this patient who also has a verbal dyspraxia language impairment but relatively preserved nonverbal IQ and had a translocation, a de novo translocation break point which disrupted this gene of 17 exons right there in that intron that enabled us to sequence then this gene of 17 exons containing a fork head DNA in the K.E. family fork head transcription factors is a large expanding family of over 40 members in human you can see the large collection and relationship of all these fork head transcription factors throughout many species and there are known to be key members of regulators of embryogenesis and have been shown to be mutated in other human disorders including glaucoma, thyroid agenesis, ovarian failure and immune deficiency in particular though the mechanism of mutation is many times where dosage is critical in embryogenesis for the action of these genes and they usually have haploinsufficiency of one copy and are segregating as an autosomal dominant trait in the K.E. family here you can see a three-dimensional structure of the fork head transcription binding domain with the three alpha helices and the two wings and the K.E. mutation was an arginine to histidine missense mutation in an invariant residue that is conserved throughout all fork head transcription factors in all species and we did not find this mutation in any control chromosomes so what questions does the identification of this gene raise? First question is is the Fox P2 gene contributing more widely to common language related disorders such as SLI and autism? One might predict that this gene could have interesting evolutionary aspects if it's truly involved in the development of speech and language so what are the within and between species variation of Fox P2 in humans and primates where is it expressed in the developing brain? What genes as a transcription factor is it turning off or on at what time points and what happens if you disrupt Fox P2 in a mouse would you get the squeak one mouse? The first question we answered by looking at micro satellite markers a large number of them throughout this gene in families with autism or specific language impairment did not find any association we also screened all the 17 exons that we knew at that time in subsets of cases with autism or SLI and revealed no mutations we also looked at a number of SNPs not exhaustive but no significant association was found either in autism families or in SLI so our work and others I think are showing that this gene is not a major susceptibility gene for either of these two disorders and this is particularly relevant for autism because there's a very strong linkage in this same region of chromosome 7 that has been shown by a number of groups what's the expression of Fox P2 here is just a northern block not maybe what you'd expect for a gene involved in speech and language it's ubiquitously expressed but you can see here in fetal brain there's a fairly large transcript signal working with Andy Copp and the Institute of Child Health to see a lie in my group has looked at the Fox P2 expression in embryogenesis and it seems to be expressed in motor related areas here at embryonic stage 16 and a half in the mouse and we also looked at human fetal brain tissue and show that there's strong expression in the cerebellum a different phylamic nuclei the caudate putamen and also the substantia nigra and here in the inferior olivary nucleus in the medulla so it does parallel also what we see with the imaging of the human patients who have this disorder where they had motor related areas such as basal ganglia and cerebellum as being defective so what about the second the third question was what does this gene look like in evolution here just shows a more revised version of the structure of the gene there's a large number of non-coding exons and very large introns at the 5 prime end of the gene here you can see the forkhead transcription binding domain in exons 12, 13 and 14 there's a polyglutamine stretch in this gene which is actually one of the largest non-pathogenic stretcher polyglutamines ever seen in a protein but and here the KE mutation the arginine mutation in this exon the Sante Pabos group has analyzed this gene in between mouse and human there's only three amino acid changes and two of these amino acid changes have occurred since the split of chimps to human they're both in exon 7 function unknown however Sante's group has sequenced about 14 kilobases and so is another group and found similar findings that there's a lot of rare variants in these introns but very few common variants and using this information there's evidence that this gene has been highly selected in recent human history and also that this is compatible with the emergence of spoken language in the last 200,000 years so in summary FoxP2 is mutated with a rare development sort of speech and language and we think it's the insufficient functional FoxP2 copy during neurogenesis which leads to this abnormal development of the motor related neural structures that are important for speech for language as an analogy the muscurgistrophy gene is not the gene for walking we think that FoxP2 is not the gene for talking however it is for the first time an entry point into the neural pathways important for the development of speech and language if FoxP2 is not a major susceptibility gene for common forms of SLI how can we define genes for common forms of SLI if they affect several percent of school children here we've used that quantitative trait loci approach with large samples from both an epidemiologic sample from Cambridge and also a clinic sample from Guy's Hospital in London and we've used various measures of expressive and receptive language ability called the CELF the non-word repetition which is a highly heritable trait which is a measure of phonologic short-term memory various measures of reading ability and of course a full IQ measurement we've used quantitative trait loci linkage approaches as I showed you earlier that Sib pair trait difference approach but also partitioning trait variability using variance components on chromosome doing a genome wide scan in these two samples we have shown a very strong linkage a whopping LOD score here on chromosome 16Q and interestingly both the epidemiologic and the clinic based sample are contributing to this linkage which is the strongest for non-word repetition more interesting the same region of chromosome 16 shows quantitative trait linkage with various reading measures in the same families here measures of reading spelling or reading comprehension are also showing up in the same region however the expressive language and receptive language test show any strong linkage in this region however there are problems with multiple phenotypes and univariate linkage analysis of course if you're doing 8 to 10 different measures and 300 different markers across the genome there are large problems of multiple testing there's issues of power if you analyze linkage results based on independent univariate measures are you getting all the power out of your sample there's also problems with the interpretation of linkage findings so the replication of linkage findings if you find linkage to non-word repetition in this region but not expressive language does that mean you found the gene for non-word repetition and we think this is a very dangerous area where people try to look at regions where they found linkage and correlate them with only that univariate measure to overcome this problem we've worked with Angela Marlowe and Lon Kardon at the Welcome Trust Center to do a full multivariate genetic analysis here these traits are multiple correlated traits one can actually simultaneously look at the co-variation of these traits at the genetic locus that you're interested in and here you can see for that chromosome 16 locus here are all the univariate traits and then a full multivariate analysis and you can see that one can actually get a significant LOD score which is not only picking up the large LOD score we saw with non-word repetition but also many of the reading scores and also showing some co-variation we're now with expressive language and receptive language that we did not see when we looked at those as univariate traits one can also in this model drop individually each of the univariate traits and ask whether they're contributing significantly and at least at the 5% level all six measures are contributing to the linkage in this region so I'll end here with my conclusions that FoxP2 has been identified as a gene mutated in a rare monogenic speech and language disorder genetic analysis of families with common language and reading disorders has identified significant QTL linkages and we're now using the variation in the genome to look for linkage disequilibrium to identify candidate genes and associated variants the goal of this research is a knowledge of the biological pathways in the brain that are important and hopefully this will provide better diagnosis and potential results. And just quickly some acknowledges Cecilia Lai, Simon Fisher who did all the work on FoxP2 Diane Newberry, James Cleak on the SLI Genome Scan our collaborators on the statistical analysis Angela Marlowe, Lon Carden Andy Kopp's group for the study of FoxP2 Farinay Varga, Caddium and Marcus Pembrey who have been our long standing collaborators on the KE family Slanti Pabbo's group on the evolution of the genetic gene Eric Green for his help in facilitating the analysis of the chromosome 7 region and my clinical collaborators not only in the autism consortium but Patrick Bolton and Gilliam Barrett especially in the SLI consortium. Thank you there and I'll stop for it. Our next speaker is Tom Friedman chief of the laboratory molecular genetics at the National Institute of Deafness and other communication disorders. This is Tom Friedman, hereditary disorders of hearing while on faculty at Michigan State. He was recruited several years ago to the NIH and we'll talk about hereditary hearing disorders in the genomics era. Thank you very much. It's a privilege to be here and I thank the organizers for inviting me. In 1994 I was just 10 years old living in Detroit and I read an article in Scientific American reporting the discovery and although I didn't know it at the time this probably marks the beginning of my interest and an entire generations interest in the nascent field of molecular genetics. Today I work on the genetics of hearing and deafness in humans. About one in a thousand children are born with a significant hearing impairment and it's thought that about half of that has a hereditary underpinning and the other half an environmental. About 50% of older individuals have a significant hearing impairment and we really don't know what the contribution of genetics is to that. It's significantly understudied. Most inherited forms of deafness usually segregate as monogenic traits and hearing loss due to oligogenic traits or complex modes of adherence are rare and difficult to document. There are literally hundreds of syndromes that include hearing loss as one of their features and this isn't surprising since some of the steps involved in hearing are shared by other systems. In contrast there are many novel processes and structures involved in hearing and therefore it's not unexpected that there are many genes that cause isolated hearing loss as the sole clinical sign and this isolated deafness is referred to as non-syndromic deafness and I'm going to present an example of each one example of non-syndromic deafness and an example of syndromic deafness. There are predicted to be a hundred different genes which when mutated can cause non-syndromic hearing loss and in a few moments I'm going to discuss an example. It's counterintuitive but non-syndromic deafness is not a simple diagnosis to make and should be considered tentative even after the gene has been identified. Hearing loss is often detected at the stations of other organ system pathology and young children with one of these syndromes may be incompletely diagnosed with non-syndromic hearing loss. For instance, individuals who have recessively inherited Gervle and Lang Nielsen syndrome have congenital auditory dysfunction together with a heart conduction problem that is easily overlooked. I'll present a second example in a few minutes. Therefore the role of clinicians in mapping and studying the function of deafness genes is fundamental and crucial throughout these studies. In competition and in collaboration, several research together are engaged in a saturating search for genes that are necessary in humans and mice for hearing. The continuing discovery of a large number of common and rare mutations associated with deafness in humans has provided many serendipitous amounts of entry into the biology of hearing. This high degree of genetic heterogeneity of deafness reflects the great diversity of specialized proteins that are required to make sense of sound. I now want to briefly tell you how the ear makes sense of sound. Sound waves enter the external ear and the an ear drum, vibrates and the ossicles of the middle ear vibrate. One ossicle is connected to the ear drum and movement of the stapes which is attached to the oval window causes movement of the fluid that fills the cochlea or this snail shaped organ. The cochlear duct has three chambers. This image shows a cross section and this middle chamber is the organ of cordy which I'll tell you more about in a moment. The red ball represents the direction that sound waves is traveling back in the oval window in the scale of vestibule. And the blue ball is the direction the sound wave is traveling back in the scale of tympani. Fluid wave that is created in the cochlea causes an up and down movement of the basilar membrane of the organ of cordy and this movement of the basilar membrane produces a shearing force between the tips of the stereocilia these projections from the outer and inner hair cell. In an animated fashion at the stereocilia a few nanometers of deflection of these organelles the stereocilia bundle towards the tallest stereocilia and through an angle that can be less than one degree opens within a few microseconds a channel which is thought to be located either at both ends of these tip links or one or the other perhaps at the top. This mechanically gated ion channel has not been identified the molecular correlate is unknown as are the gene or genes that encode these tip links. When these channels open potassium in the endolymph flows down an electrochemical gradient into the hair cell and through a complex process which is obviously oversimplified here depolarizes the membrane. The acoustic nerve sends a neural signal to the brain that the brain interprets as sound. It is the inner hair cell that transduces hydromechanical signal to an electrochemical signal and it is the outer hair cells that further affect this signal by amplifying it in a complex way which I won't discuss. Sensor neural hearing loss occurs when the inner ear fails to send a nerve signal to the brain in response to a sound stimulus in the cochlea. The two genes that I want to discuss are involved in this process. One is involved its thought in the recycling of potassium back to the endolymph and the other one is involved in the integrity maintaining the integrity and probably important during the development of the stereocilia. This rapid progress which I'll tell you about briefly in understanding hereditary deafness has paralleled the ability of genetic maps with highly polymorphic markers the physical maps, the genomic sequence the instrumentation and bioinformatics and the transcript-owned databases as well as very important models because once you identify a gene for hereditary deafness in humans you need an animal model. The first thing that we do is to ascertain families segregating hearing loss and we ascertain them in North America and you're looking for large families in this case one that's segregating dominant disorder and in this case probably a recessive disorder. These are children of a consanguinous marriage and it's important then to obtain comprehensive clinical data and determine the mode of inheritance. In 1996 some genes for hereditary deafness had been mapped but not a single one had for non-syndromic recessive deafness but not a single one had been cloned at that point. But the next year in parallel with the ramping up of these resources, these wonderful resources, three genes had been identified or cloned in 1998 10 genes, a total of 10 in 99-15 in 2016 in 2001-23 in 2002-32 in 2003 and the orange tags represent deafness loci for which the gene has not yet been identified. In addition, on chromosome one there's a dominant modifier which acts as a suppressor of deafness for a locus on chromosome 4 DFNB-26. So you ascertain families you map the genes and you find mutations and often these mutations are private mutations or rare mutations but nevertheless they give you an entry point into studying the biology all the way from the histopathology to the structure of these proteins and their function and that leads to an integrated understanding of the biology and the pathophysiology of the auditory system and eventually to inform clinical applications one of which of course is a cochlear implant. So when common mutations are identified in these genes there are immediate benefits. I want to now tell you just about two loci one on chromosome 13 and one on chromosome 10. So in 1994 in Dr. Petit's lab at the Pasteur the first recessive non-syndromic profound congenital deafness locus was mapped to chromosome 13 and this locus was designated DFNB-1. Three years later in Kelsel's lab the gene underlying this was identified and it encodes a gap junction connexin-26. There are about 20 members of the connexin family which are phylogenetically ancient proteins found in all metazoans. Gap junctions are involved in intercellular exchange of small molecules and ions between adjacent cells as well as forming channels on the surface of cells. Also this gene has a very simple architecture there's just one coding X on. Nevertheless, mutations in this gene account for about 30 to 60% of non-syndromic autosomal recessive hearing loss in Europe and the United States in one particular mutant allele 35 del G, a deletion of a G base, accounts for the majority of mutant alleles of JGV2 in southern Europeans. Rob Morel showed that another mutant allele of this gene 167 del T is responsible for about 40 to 60% of non-syndromic deafness in the Ashkenazi Jewish population and there's a carrier frequency of about 4%. I now want to switch to the second gene that I want to tell you about and give you a little bit of introductory information about Usher's syndrome. Usher's syndrome is characterized by bilateral congenital sensorineural deafness and it's often profound at birth for the most severe form of Usher's syndrome there are two other types which I'm not going to discuss. While the loss of vision occurs perhaps at age 15 to 18 to 20 so children who are born with Usher's syndrome are thought oftentimes to have non-syndromic deafness. They also have vestibular problems which is characterized by lane ambulation. There are seven loci, there are more than seven loci but seven published loci and five of these genes have been identified. Usher 1b, 1c, 1d, 1f, and 1g one of them encodes an unconventional myosin two of them encode proteins that are involved in macromolecular complexes and two of them encode adhesion proteins catherin-23 and proto catherin-15. I just want to briefly tell you a little bit about catherin-23. In 1996 families segregating non-syndromic deafness were mapped to chromosome 10 and shortly thereafter a couple of families with Usher's syndrome were also mapped to this very same interval and it was hypothesized by this group that mutations of the same gene could be responsible for both non-syndromic and syndromic form of deafness. Julie Bork now Julie Schultz positionally cloned a gene in which he found mutations in families that were segregating non-syndromic deafness and also mutations that were responsible for Usher 1d. There's also a mouse model originally mapped by Breida and positionally cloned by Federica de Palma at the same time that the human gene was discovered. There are now 20 mutant alleles which are associated with non-syndromic deafness in this gene catherin-23 which encodes catherin-23 and there are about 21 mutant alleles which are responsible for Usher's syndrome. So what's the difference? Turns out that the mutations that are responsible or associated with non-syndromic deafness appear to be hypermorphs or amino acid substitutions which we believe do not entirely disable this protein. While truncating mutations of catherin-23 are associated with Usher's syndrome so what are the emerging possibilities? Well there are many of them but I've just listed three here. One is improved diagnostic accuracy and genetic counseling which will make it possible which will be possible when we understand more about this genotype-phenotype relationship for each of the genes that have been identified which means ascertaining their families and having many different mutant alleles. The molecular correlates of interior structures and novel processes will continue to be identified by map-based and functional identification of genes for hereditary hearing impairment in humans, mice and zebrafish and as I mentioned many of those specialized functions in the auditory system do not yet have molecular correlates. And finally an increased understanding of the function of deafness genes should facilitate better healthcare for hearing impaired individuals. So I want to thank my colleagues in the section on human genetics for their clever and hard work and I particularly want to thank Dr. Andrew Griffith who has been the clinician scientist because it is his work which represents the underpinnings of the molecular genetics that we do and our collaborator in Pakistan as well. So thank you very much. Our next speaker is Val Sheffield, Professor of Pediatrics and Director of Medical Genetics at the University of Iowa College of Medicine. Dr. Sheffield received his MD and PhD from the University of Chicago and his talk is entitled Impact of the Human Genome Project on Hereditary Blindness, Simple and Complex. So some genetic conditions are lethal whereas other conditions lead to loss of quality of life. Hereditary blindness certainly falls into the latter category. The Pulitzer Prize winning sports writer Jim Murray who I used to read his articles as a youth who later went blind in life made the express the opinion that without vision there is no quality of life. He of course was speaking of his physical loss of the sensation of vision however it would also apply to the global vision and certainly we've seen the vision of the Human Genome Project and the impact it will have on quality of life. Hereditary blindness like other types of genetic disorders can be roughly categorized into categories, single gene or monogenic Mendelian disorders of which there are many and then common complex disorders which are fewer but they are common so there's many patients. I'm going to limit my talk to age-related macular degeneration or AMD. The macula is a part of the retina in which you have the highest concentration of photoreceptor cells and hence it accounts for your central vision your most acute area of vision where you use for reading and driving and other functions. In AMD you get a degeneration of the macula. This is the most normal macula here that's shown although these lesions you don't have to be an ophthalmologist to pick out that there's abnormal lesions here that result in the photoreceptor cell death. The disorder is both clinically heterogeneous as well as genetically heterogeneous. I think you can recognize that these retina look different from one another but they would all be categorized as AMD. There's many studies that have shown that AMD increases with age hence the component of the term age related. As the population in our society increases it's becoming a bigger problem. In the year 2000 there were 16.6 million people with the disorder but it is projected that in 2025 there will be 27 million people with this disorder. Age related however does not mean aged caused. Certainly we do not want to a third of us do not want to look forward to losing our vision later in life if we escape the cardiovascular disorders and their lethal effects. And so it should not be accepted that this will become the fate of one third of the aging population. AMD in fact does have a significant genetic component as has been demonstrated by multiple different studies. So we and others have come up with hypotheses being that perhaps we studied the Mendelian monogenic forms of macular generation. They may be an allelic variant of AMD hence we could possibly get clues to which genes are involved in the late onset disorder or at least identify some of the pathologic mechanisms of AMD by studying these monogenic forms. The first goal of the human genome project is actually the high density development of a high density genetic map. This made possible the mapping of many disease loci and certainly now that we have the complete human sequence not only are we able to put phenotypes on the map using the genetic markers but we are able to now correlate that with the one base resolution physical map and identify genes that cause various macular and retinal disorders. This has been done in many laboratories across the world and as you can see here there's been a rapid increase in the number of loci that have been mapped as well as the number of genes that have been identified. This in our own lab has occurred with a worldwide collaboration. One of my favorite to point out is this collaboration we've had in Israel with both the Israeli and the Arab population. This shows a truck here says this is a University of Iowa logo here. This is a very talented Bedouin physician that was trained in Israeli hospitals and it shows the potential for breaking down political barriers by science and hopefully science will continue to be a leader in the breakdown of political barriers through these collaborations. Now we are at a point where we can test this hypothesis are some of these Mendelian disorders allelic to the common form of the disease and we selected candidate genes based on the fact that we had either mapped or cloned some of these genes and they appeared to resemble the phenotype of the age-related macular degeneration. The bottom line is that after surveying hundreds of AMD families or AMD patients for mutations in these various genes there was really no evidence that they played any role in age-related macular degeneration. This would appear to be a failure of the strategy but I would point out that there are actually many successes in that they have pointed out mechanisms they've pointed out really the genetic complexity of the disorders we've learned about basic biology and some clinical applications and I'll show an example of each of these. At the level of mechanisms one point was controversial as to which cell types in the retina are actually involved in the disorder whether it was the photoreceptor cells or the underlying retinal pigmented epithelium or numerous other cells including the vasculature of the retina and indeed there's now examples of genes expressed solely in the photoreceptor as well as genes expressed in the RPE that are involved in this disorder. Unlike the nice hypertension work that Rick Lifton showed where you could easily point to a unifying pathway such as not the case with AMD and the mechanisms as genes of different function are involved in the disorder. It's also given us clues to genetic complexity. One of the examples I like to show is illustrated in this slide where we have a single gene ELOV-L4 which is involved in fatty acid metabolism. There's a five base pair deletion mutation of this gene which multiple patients have and here we have a 62 year old patient with nearly normal retina certainly normal vision who has this deletion and here we have an 11 year old patient that has severely impaired vision with the same mutation and the abnormal retina indicating there must be modifiers to this primary gene defect be they genetic which is my guess or environmental defects but finding either the environmental or the genetic modifiers will be is a great goal and should have an impact on the understanding of this disease. The human genome project has also allowed us to come up with different strategies or paradigms for finding disease genes and here's an example of something that we're doing in our lab is that we're taking sort of a microarray approach of human DNA samples where what we can do is really take multiple DNA samples collected from individuals that have been very carefully clinically phenotyped and then instead of choosing individuals that have the same phenotype to fill up the microtider plates we select individuals that have very different phenotypes and then we can screen candidate genes in these DNA samples, identify potential mutations, go back and look at the phenotype, refine the hypothesis to select this specific phenotype to see if a given gene does play a role in the disorder. We selected one gene, the NR2e3 gene or a PNR gene which is a nuclear receptor gene on chromosome 15 and when we did the initial survey of 400 diverse patients with this disorder we identified two patients with putative mutations we could then refine our hypothesis and go back and look at mutations in individuals with the same phenotype where we found in 25 of the 29 patients with that particular phenotype they had mutations. The phenotype was particularly interesting as shown by this cartoon of the macula this shows an artist rendition of the multiple types of different photoreceptors that you see in the macula where there's red, green and the most rare type of photoreceptor, the blue photoreceptor in a normal macula however in this particular disease which is called enhanced S cone syndrome the macula is packed solely with blue cones the exclusion of the red and the green cones and this can be shown electrophysiologically here is a normal response to blue light which is this small electrophysiological response whereas these patients with enhanced S cone syndrome have this massive response this can be confirmed histologically on one disease patient that they do in fact have cones packed with blue photoreceptors this suggests then that the progenitor cells that gives rise to cones have a default pathway to the S cone type of photoreceptor so what about therapy many think that the goal is gene therapy but the goal is really the proper application of the proper therapy to the correct individual patient I like to give here is that in studying the Bedouin population we initially studied three different kindreds that we initially thought had the same genetic condition as we identified the loci and the genes it became clear that they all had different molecular causes of this disorder we could then go back and ask the question well do they really differ phenotypically and it turned out that two of the kindreds had severe retinal degeneration but the other kindred had mild retinal degeneration but they had myopia on top of that and so they were being treated as if they could not be as if their vision could not be corrected with eyeglasses but indeed they could be corrected by eyeglasses and it made a big impact on these children just having the lion's society donate eyeglasses another example of this is a disorder Sorsby's macular dystrophy which is caused by mutations in the TMP3 gene now that you can molecularly determine molecularly diagnose individuals with this disorder by finding mutations in the TMP3 gene then you can ask the question what do their phenotype what does our phenotype look like one of our collaborators Sam Jacobson noticed that these patients look like they had a phenotype similar to people with vitamin A deficiency a drastic vitamin A deficiency so we treated these people with vitamin A and indeed their sensitivity to light improved so here it shows a baseline when we give them over this period of time high dose vitamin A their light sensitivity increases five orders of magnitude you take away the vitamin A and it gradually falls off you give it back it improves and here you write the paper not that gene therapy won't be possible in these disorders that it may be there's one nice article by Gene Bennett's group showing gene therapy in the dog model of a severe childhood form of blindness in summary AMD has a significant genetic component disease gene discovery has led to macular disease mechanisms but not yet to a major AMD gene and there's real value in identifying clinical subtypes and identification of genetic modifiers and I think novel treatments will be a focus of future work thank you our next speaker is John Hardy chief of the laboratory neuro genetics at the national institute on aging at the NIH he received his PhD from imperial college in London and he's well known for studying the genetic basis of dementia his talk is entitled genetic analysis reveals unexpected connections between neurodegenerative diseases thanks I remember a couple of things from 1964 to I remember performing she loves you help and twist and shout for my parents with my younger brother and I also remember reading children's encyclopedia of knowledge which was a weekly magazine and trying to understand the basis of the code on usage in DNA and it's really nice for me it's all to be able to give a talk at this 50th anniversary almost as nice as if I had actually managed to get onto a Beatles reunion tour so that's how thrilled I am so why my intention is to my intention is to convey a little bit of the excitement in neurology and your neurological neurodegenerative disease research because we're really in the third golden era in my view of the study of neurodegenerative disease the first golden era really came about also because of technological improvements of course with the description of the diseases the descriptions of Lewy bodies tangles, plaques and the description of these diseases as clinical pathological entities the second golden era really I think the high point of the second golden era really came with the transmitter based treatments for these diseases Eldopa therapy I think is the perhaps the best the most really dramatic therapy understanding the transmitter basis of the phenotypes in the disease I think that was a wonderful era and now the genetics based understanding of diseases and understanding of the etiology really offers the hope that we'll have knowledge based therapies close of course the key in my view the key findings were the Huntingdon's linkage I remember that really influencing my career decisions the cloning of the prion gene by a couple of groups and the amyloid gene by Bayreuter's group of course the triplet repeat diseases I remember being told that human genetics wasn't worth studying because you could do everything much better in mice because you could organise the breeding but of course we would never have found triplet repeats diseases so I think this is a great time this is a great time to be doing research and it's a great time because of the genome project in its broader sense now the usefulness of genetics you know pity the poor pathologist all the pathologist gets to see and this is how diseases were looked at is the credits of a movie all he gets to see is that Schwartz and Egger starred in the movie but he doesn't know for sure and the nice thing about genetics is it tells you exactly the opposite it tells you where the movie starts so at least now you've got to see where the movie starts when you find the mutations you know where it ends and then you trust the molecular biologist to fill in the gaps it's a great time now these are the diseases I'm going to try and skip through very quickly Alzheimer's disease, 4 million Americans although this is a slightly prejudiced thing for me to say as an English guy to say 4 million Americans with Alzheimer's disease but of course it's all over the world the pathology there is a plaques made up of a beta I'll show you some of those in a minute in mice tangles made up of a protein called tau and I'll also say that there's often Lewy bodies I'll try and get back to that at my last slide if I have time because the pathology is a little more complex pre on diseases I'll talk very briefly about perhaps in my last slide you know pre on diseases sometimes have tangles and very interestingly some of the hereditary pre on diseases which have tangles also have Lewy bodies I'll try and get back to that I'll also talk about PICS disease you know I like these old German type names for diseases now we have committees to name diseases front of temple dementia with Parkinsonism link to chromosome 17 now there is a committee decision if you ever heard one I'll also talk about if I'll try and talk about Parkinson's disease and Lewy body dementia I want to make the point I think the Parkinson's disease in my view is not the etiologic entity clearly it's the treatment entity in other words Eldopa treatment but you know there are families and we've studied a family extensively in which some individuals have Parkinson's disease and other individuals have Lewy bodies in other areas particularly the cortex and have a dementing syndrome and I would argue that that's the same disease from an etiologic perspective of course now we treat with Eldopa the treatments are different obviously the dementia doesn't respond to Eldopa but when we have treatments based upon genetic knowledge then we'll treat these two currently current different entities from a treatment perspective in the same way I'll also try and talk about progressive super nuclear palsy and corticobasal degeneration these are sporadic Parkinsonian like diseases in which the pathology tangles now this is where we start I guess with the identification first of all of mutations in the amyloid precursor protein gene we don't know the function of this gene Conrad Bayreuter first suggested when he cloned it that it was probably a self surface receptor and now I think there's data this last year saying he's almost certainly right we've now identified a whole series of mutations in the amyloid precursor protein gene this is the whole protein this is this part of the molecule blown up I'll mention this mutation first this mutation was found by Blasphrangianis group in a disorder different from Alzheimer's disease but in which amyloid deposition occurred in brain blood vessels and really that was a very important finding and led us to start to look for amyloid one of the reasons we started to look for amyloid mutations in Alzheimer's disease and now these there's a quite a number of mutations in Alzheimer's disease being found this is the cluster of mutations at the C terminal end of the amyloid fragment here which all lead to Alzheimer's disease these two lead to Alzheimer's disease and a couple of kindreds one of which is in Belgium and then this double mutation here occurs in a large Swedish kindred with Alzheimer's disease so these mutations all cause Alzheimer's disease typically with an age of onset in the 50s and you can see that there's clear clustering and this clustering happens to be at the points where the amyloid precursor protein is metabolised here's the amyloid precursor protein again and these are the two normal pathways of metabolism the alpha pathway and the beta pathway here these pathways both occur in all of ourselves in all of us all the enzymes responsible for these pathways have been c