Okay, good morning, everyone, and thank you for coming this morning. As you know, we've spent our last 10 weeks together going through a systematic survey of the major areas of genome research, and we're now at the point in the course where it's time to tie all the techniques and the approaches that you've heard about throughout this course together. And by doing this, we hope that you'll get a better appreciation for how these advances in genome research can be used to change how we think about the practice of medicine and to improve public health. It is my great pleasure today to introduce to you Dr. Bruce Korf, who is the Wayne H. and Sarah Cruz Finley Professor of Medical Genetics, the Chair of the Department of Genetics, and the Director of the Heflin Center for Genomic Sciences at the University of Alabama at Birmingham. Bruce is an internationally recognized leader in human genetics, and particularly in the study of neurodevelopmental disorders, such as neurofibromatosis. His work and contributions to the field of medical genetics have been recognized by numerous organizations, including his having received a number of prestigious awards from the National Neurofibromatosis Foundation. He has served on the board of directors of both the American Society of Human Genetics and the American College of Medical Genetics, later going on to be the president of ACMG. Bruce is incredibly committed to mentoring and education, and his influence on graduate education goes well beyond the borders of the UAB campus, having written a textbook entitled Human Genetics, a Problem-Based Approach, which is an introductory graduate textbook that is widely used by medical students and genetic counselors. He's also the co-author of Medical Genetics at a glance, the co-editor of Current Protocols in Human Genetics, and has worked with the American Association of Medical Colleges on efforts that promote the inclusion of genetics into the medical education of all medical students. His efforts in the field of education were recognized by his colleagues in 2009, with Bruce being conferred the award for excellence in human genetics education from the American Society for Human Genetics that year. Finally, Bruce has been a longstanding friend of the Genome Institute, having served on our board of scientific counselors for many years now, and we very much enjoyed interacting with Bruce and have benefited tremendously from his unique perspective on the field of genomic medicine. So I'm very pleased that Bruce can be with us and be part of this series, and please introduce me in welcoming today's speaker, Dr. Bruce Korf. Eddie, thank you very much. Great pleasure to be here. The thing he didn't say reciting those books was through a piece of extremely bad planning, the new editions all converged on the same year. So you can imagine what the evenings and weekends look like as a consequence. But it's obviously a kind of a daunting task trying to do what Andy just said, tie together a series in terms of where this is going in terms of medical practice, and it's even more daunting when you realize what a moving target it is and how you can have a conversation about something that you think is going to happen and don't know when, and then all of a sudden it does happen, and then you look back and say, well, how come we weren't prepared for that? And what do we do now to kind of backfill some of the issues that have come up? And that I think is going to be a theme that you will see as we go along. So these are my disclosures, and let me move straight to the sort of paradigm that I'm going to try to establish in this next hour or so. So I'm going to ask you to suspend disbelief at a couple of levels during this time. We are going to follow Laura, shown in this pedigree, off to the right there. She is an imaginary individual, as you will see, I'm sure. This is not a real patient. We are going to begin with her as an infant and follow her throughout her life. So one suspension of disbelief is going to be the assumption that we are going to be seeing her over maybe 60-year period. But the way in which we're going to approach whatever the issues are is the way we would approach them now. I wouldn't even venture to guess exactly what we'll be doing 60 years from now. But we're trying to use this as a vehicle at least to give you a sense of how for different epics of life genomic medicine may be playing out. The second suspension of disbelief is in a way that you're going to see in a moment that we are going to be dealing with basically a white middle-class kind of scenario. And it is not intended to imply that that is in any sense the kind of main paradigm that genomic medicine will develop along. I didn't think I could ask you to suspend disbelief to the point of having her change her race or ethnicity every slide. So one thing you'll notice, though, there are lots of pictures of people. These were all bought stock photo pictures. It's really a great pleasure not to think about HIPAA for once. So let me give you a sense of where we're going to go. We're going to consider genomic medicine from these different sort of epical issues starting off with newborn screening, diagnostic testing, the issue of prenatal diagnosis, pre-conceptional, then pre-symptomatic, and finally, predispositional testing. And along the way, I try to make some comments as well about therapeutic implications. All right, so our story begins with Laura just after birth, where blood is taken from her heel. It goes to a state newborn screening lab. Her parents aren't really asked for their permission to have this blood drawn. They just notice a band-aid and they're told it's a routine test. And that is the last they ever hear about it. I'm sure you're aware that newborn screening has been ongoing in the US and throughout the developed world for, well, I guess in the 50 or so year range. The picture at the top, I think you can tell, is a fairly dated picture. It reflects the taking of blood from the newborn. In the old days, this bacterial inhibition assay, you can get a sense of the age from the hairdo, I guess. And the concept here was that if you could make a diagnosis of things like phenylketonuria at the time of birth before toxic metabolites have built up, before symptoms of, in this case, PKU occur, and then institute treatment, treatment consisting of primarily a low phenylalanine diet, that you could avoid what otherwise would be a devastating outcome. And in fact, that paradigm has been expanded to many different inborn areas of metabolism. The technology illustrated at the bottom that have tend to mass spectrometry. In a nutshell, you put a sample in one end and you read this spectrum out the other that in principle can diagnose a large number of disorders. And I think by any measure, this has been a major public health contribution in the world of genetics that really has now stood the test of time for half a century or more. Question has been raised whether the paradigm should be extended towards a DNA sequencing based approach. Currently it's done by metabolite testing, fairly close to phenotype. And I refer you to this one paper where a set of disorders, this really was focused more on carrier screening, but the paradigm was much the same. This was a next generation sequencing approach to diagnosis of several hundred recessively transmitted disorders, many of which, not all of which, were inborn areas of metabolism. And I think the point that impressed me from this is this quote, a finding a high proportion of literature annotated mutations that were incorrect, incomplete, or common polymorphisms. This is going to be a recurring theme as we go forward. This notion of the annotation of the genome, I think, is going to be a very long-term kind of enterprise and really does give pause when one is talking about making both diagnostic and ultimately therapeutic decisions on the basis of sequencing if we're not absolutely sure of what the phenotypes actually might be. Well, we'll let Laura now reach age three. She has a brother who's five, but has been experiencing these developmental problems and is diagnosed as having autism spectrum disorder. I think you're aware, and I suspect it was covered somewhere along the way in this course, of one of the first sort of applications of genomic level thinking in diagnostics, what now are referred to as cytogenomic arrays. There really has been a dramatic transition from traditional cytogenetics, which I explained to patients, is like taking a picture of the Earth from a satellite that is orbiting maybe 25,000 miles out, where you can see relatively crude sorts of features. And you can tell that there are cities, but you certainly can't tell even with high resolution cameras, I venture to guess. What's going on inside a particular house? And now with the microarray technology as a mechanism of identification of copy number changes, one almost invisible example of which is shown down here on this slide. The ability to establish diagnoses and individuals with developmental impairment with autism spectrum disorder, a whole host of problems that historically were very difficult to establish genetic diagnoses has really been revolutionized. I can say in our lab, the pickup rate in children with developmental disorders is pushing 15 to 20% in terms of copy number changes that we have good evidence are pathological. So it really is quickly replacing the microscopic analysis of chromosome structure. Not totally because there are things you won't see with the cytogenomic arrays, but for picking up small copy number changes, it has really made a huge difference in day-to-day practice. Well, the question has then come up, what about the use of DNA sequencing technologies in a diagnostic context? And this concept of what some have called the diagnostic odyssey has really been the paradigm that has driven a lot of genetic diagnosis over the course of time. It means you start with a clinical problem, let's say a child with a developmental problem, you establish a differential diagnosis of all the things it could be, which seemed to fit best with the child's history and physical exam and family history and so forth. You then might order genetic testing that is customized to the hypotheses that you've formulated in your differential diagnosis, interpret the results. Very often the results do not turn out to provide an explanation for that individual's problems and so you come back to the starting point. And if the family has the motivation and the patience, you can cycle around this circle many times at considerable expense, considerable frustration. And then in fact oftentimes just simply not come to an answer. And sometimes the family reaches a point of exhaustion where they are no longer motivated to continue to do it. So the question has begun to be raised whether in fact a exome sequencing or genome sequencing approach would be a better way to go that even though the cost of doing the analysis might exceed the cost of most individual genetic tests, perhaps collectively, when you consider the number of turns of the circle that many people experience, perhaps the ultimate cost is lower than testing genes one at a time. And very likely the cost of sequencing and the accompanying analysis will reach a point where it won't make any sense to do tests one at a time because the cost will actually be cheaper to do the whole genome in one shot than to do a piecemeal. And I showed this one screenshot of an example of a diagnosis that was established based on exome sequencing in a child with a disorder that really had otherwise been a mystery in terms of its pathogenesis. Well, that all being said, I think there is a huge way to go in terms of genome annotation point already made in the context of newborn screening. And I show you this slide which actually comes from our lab at UAB and what you're looking at is the NF1 gene, neurofibromatosis type one, which Andy mentioned is an area of special interest of mine. It is a pretty large gene as genes go by no means the largest. The stars below it show different pathological mutations in different individuals and the lines above are copy number changes, mostly deletions that have been found in different individuals. And the main point of this is there really is no hotspot for mutation, almost no two mutations are the same. And, furthermore, many of the rules have proved to be difficult to establish here. What I mean is that some of the mutations are pretty obviously pathological. The lab actually starts with RNA rather than DNA and the reason why is it permits us to determine that there is, in some cases, been abnormal messenger RNA processing. And there are lots of mutations that would be difficult to interpret if all you knew was what they looked like at the genomic level. So, for example, we have found silent mutations that do not change the amino acid sequence at a particular codon, but turn out to alter splicing patterns. So, if you looked at them at the genomic level, you would have decided it was a benign variant. But if you look at the RNA level, you realize it's not so benign. Actually, there have turned out to be stop mutations that aren't behaving as stops so much as splicing mutations. There are deep intron mutations and what otherwise seem to be non-conserved areas. And the only way you know they're mutations is that you can infer that the splicing has been altered and then you can trace it backwards to the genomic level. So, if somebody handed us today, which they practically could, a complete DNA sequence of this particular gene, which actually may be harder than it sounds because there are so many pseudo genes, it's not such a trivial matter to actually even do the sequencing at the genomic level. But if they did, I'm not sure we'd necessarily know what to expect in terms of phenotypes. So the ability to annotate just one gene out of 20,000 is a substantial challenge. Now, multiply that times the number of circumstances and it becomes a fairly serious issue. It also raises the question, exome sequencing does, of all the so-called secondary findings, off-target findings or incidental findings as they've been variously known that are inevitable. We're all, as point I'll make again in a few minutes, carriers for something or other, we all carry things that could be relevant for our medical history. The bar graph you're looking at is from a paper that just came out in genetics in medicine, Robert Green at Harvard as the PI for this project, the senior author. I was one of the participants in this study. What they did was provided us a daunting spreadsheet of 80 some odd conditions that had been pulled out of gene tests, the directory that a lot use in terms of identifying labs that offer genetic testing. And they said, if you were running a exome sequencing lab and you had found a truncating mutation or a missense mutation that was predicted by in silico analysis to be pathological, would you return that result to the clinician that had ordered the test? So the question is, what are the things other than whatever the target of sequencing might have been? In other words, the thing that you think might be explaining the phenotype. What else should you be returning to the ordering clinician? And so basically what it's showing is that for different individuals across this, there were huge differences. Some were very conservative. For example, this individual didn't choose to return very many things. And there were some that were almost completely open to returning virtually everything of the 80 some odd disorders that were on the list. So there was a big discrepancy, not always, certain things I think most people agreed should be returned. I guess an example that gets used all the time is if you incidentally discover a BRCA1 mutation that predicts a high risk of breast and ovarian cancer, there was pretty good consensus that that's something that should be returned to an individual because it is clearly medically actionable, a point we'll come to again in a few minutes. There were other things that were pretty clearly not actionable. I guess the poster case is the ApoE polymorphism, though many people in fact have expressed interest in knowing their ApoE genotype. So there was a lot of debate there. I would caution not to over read this too much, this notion that different experts disagreed is true. Then again, realized they were handed a spreadsheet without a whole lot of guidance and might have produced a different result if all the experts had been in the same room debating one at a time. And in fact, that's sort of happening now. The American College of Medical Genetics has a committee, when in fact Robert and Les Bissecker are co-chairing to ask this question in a more systematic way. There's also a difference between what would the lab return to the ordering of the clinician and what should the clinician actually describe to the family. And so some people interpreted the job of the filtering being at the level of the lab, figuring the clinicians aren't necessarily going to be sophisticated in all of these various disorders and be able to make the judgment. Others had the philosophy that the lab should return all of the results and let the clinician who knows the clinical context for a patient make those decisions. It's a complicated terrain, I can tell you that. And the committee has been meeting for a couple of months now, held an open forum at the ACMG meeting just a week or two ago, got a lot of constructive feedback. So it's a moving target and an ongoing process. But I hope there will be some consensus view as to how to handle these secondary findings that emerges in the coming months. All right, Laura's now married. She and her husband, considering starting a family, they meet with their obstetrician gynecologist. They're of Northern European ancestry and among other things are offered carrier testing for cystic fibrosis. I'm sure, well familiar to many of you here, the idea that there are individuals that are at risk of being carriers of this autosomal recessive condition. But you don't usually, at least historically, know that you're a carrier until or that a couple are both carriers until the birth of a child with cystic fibrosis. So it led to a consensus conference here at the NIH, must have been close to 15 years ago now, where the notion of offering carrier testing in fact was proposed. It generated this educational brochure from the American College of Obstetricians and Gynecologists and the American College of Medical Genetics. And carrier testing with a panel that the American College of Medical Genetics put together has been ongoing now for a long time. In fact, there's a long history of doing carrier testing for a variety of conditions to a fair extent informed by ancestry. So I show here some of the conditions, not necessarily an exhaustive list of things offered to individuals of Ashkenazi Jewish ancestry or African Asian or Mediterranean and then a handful or a couple actually here of pan-ethnic tests, things that might be proposed regardless of ethnicity. In fact, not everybody knows their ancestry. So it might sound straightforward to take a history at the time of a counseling visit and ask about ancestry. And it's not always so clear as time goes on. So the idea of customizing the testing to ancestry may not be so easy to do. Raising again this question, this comes from the same paper from group in Kansas City, looking at the concept of doing carrier testing by next generation sequencing. And I already made the point about some of the questions about annotations. So you find a lot more when you're looking across all possible mutations in the exome, at least for the conditions that might be on such a panel. But the other point made is that pretty much everybody is going to be a carrier for something if you look at a large enough list. So you can just imagine the counseling, I don't know if the word burden is quite the right burden, but the counseling challenge that that entails, which will well be on the point if one looks at it from this perspective of the occasional individual is going to be found to be a carrier. 100% of us are carriers for something if we look long enough and hard enough. But how well annotated the phenotypes are for those carrier states may be quite a different question. Well, in fact, they are found to be cystic fibrosis carriers. They like to have prenatal testing. Fetus is found to be a carrier, but not to be affected. The prenatal diagnostic paradigm has been with us now for a long time. Amniocentesis, chorionic villa sampling, and even the possibility of pre-implantation diagnosis. But there's been a substantial evolution in this area. And one of the drivers has been the idea of prenatal screening, maternal serum screening as well as ultrasound screening. And in just this past several months, the ability now to do a DNA sequence-based approach. This is a screenshot from one of the papers on this topic. Looking at the ability to detect trisomies 13, 18, and 21 based on genome sequencing, essentially counting the number of chromosomes in either of those three groups. Looking to see if there's essentially an excessive amount of chromosome 21 material from a maternal serum sample where one is looking at that small amount of fetal DNA that finds its way into the maternal circulation. Here's again an example of an approach that is moving very quickly from theory into practice. And there are companies now that are beginning to offer this. So this is not a someday we'll be in a situation where we have to think about this. It's taken a long time for this to develop. And yet a relatively short time for it suddenly to surface as a possibility in the clinic. It's even raised the question of whether it's feasible to sequence the entire fetal genome based on this fetal DNA that finds its way into the maternal circulation. You may have seen this paper last year where that was done sort of. They actually used information I think from the eventual child to help understand some of the variants that they were identifying. They knew the father's genome and the mother's genome and the variable in essence to reconstruct the fetal genome. So it's by no means a trivial process. But when you talk about secondary findings in terms of how are you going to handle the long-term implications of making a discovery in an individual who presents for exome sequencing. Well those issues only become magnified when you're talking about doing it either in a newborn or certainly a fetus. You know you could ask the question that I asked earlier should you return a BRCA result. It's not a hard question I don't think if it's an adult. If it's a child are you going to return that result? Well you could make the argument that it may not be immediately relevant to the child but it may be very relevant to the child's parents. And so it becomes a pretty complicated question in terms of how you define who the patient is and for whom you're actually making decisions. Well Laura, now it's 45 and she's just learned that her older sister has been diagnosed with breast cancer. That leads to questions about her risks and in fact there is a family history of others. This is actually a pedigree slightly modified from a family who we saw in our clinic in Birmingham.  So it raised the question in our patient whether she might be at risk by the way there were a couple of cancers of other kinds in the mother's family. We actually organized to do testing on the sister not on our patient because the value of a diagnostic test is much greater when it's done in somebody who actually has the phenotype you're looking at. If we had tested her as the starting point and she had been negative, we wouldn't know if the family risk of cancer was accounted for by a BRCA1 or 2 mutation as opposed to some other cause but since in fact her sister was found to be a BRCA1 carrier that did explain this family risk and when her test turned out to be negative that was much more substantially reassuring. This is actually a good case in point of how quickly things can change. So in the 90s when the BRCA1 and 2 genes were identified and the association with cancer risk was elucidated there was a relatively short transition time from when that had happened in the research lab to when it became available as a clinical test. Although many people at the time would ask the question so what exactly is the clinical utility of being tested for BRCA, are you just learning the name of the thing that you may or may not actually ever get and can you do anything about it? And I think in the years that have passed there has been a very substantial increase in evidence that there in fact are real decisions that can be offered that can be substantially risk reducing. This was one of the major ones, the evidence that Salpingo opherectomy done does protect substantially against both ovarian and also breast cancer. Individuals offered just surveillance had a much more substantial risk of eventually developing cancer. So I think at this point it's pretty widely accepted that there really is a significant risk reduction paradigm. And although I won't go into great detail about it I think it's important to recognize that genomics has made a difference already in therapeutics. The couple of examples would be the use of Herceptin in individuals with her two new amplification in breast cancer or this particular mutation in BRAF that has been found in melanoma and predicts the response of individuals to particular therapeutic choices. So they really are substantial now and likely to be increased examples of genomic testing on tumors and presumably in other disease states that will inform choice of medication. It has raised the issue and there's a pretty well known I think court case percolating through the system right now over exactly who owns the genome. Remember that 20% of your genome, I guess you could say is being leased from various companies. It has raised the question that if we're doing genome level analysis are we going to be in a position to actually reveal all of the things that we have found nevermind whether we should or shouldn't to question I've already been asking but whether we can or can't. It's led to this facetious patentome or redactome all the things that you actually know but can't tell anybody about because somebody else owns the intellectual property on the particular component of the genome that might be relevant to a given clinical situation remains to be seen obviously what happens with this whole concept of patenting and exclusive licensing of genetic tests but I think it's an area that's going to be pushed on very hard as we move into genome level analysis where it's not so easy to stay away from components of the genome that somebody else claims ownership of. All right well Laura now has 60 years of age she has been well. She and her husband have heard about the possibility of having genomic testing and so this leads them to exploring what they can learn from samples that they submit through the internet. A lot of this has been fueled by studies I'm sure you've heard about here perhaps many of you have been involved in organizing such studies. This notion of being able to look at variants that predict risk of common disease won't go into huge detail on both the successes and the challenges the proportion of heritability accounted for by these in spite of large numbers of variants that have been identified in a variety of situations remains relatively challenging so the degree to which this actually truly informs medical care is debatable. The paradigm may be clear enough which is that we are all born with some what might be described as genetic liability which occasionally is overwhelming and that would be the case say for sickle cell anemia where having a particular genetic variant is in and of itself sufficient to cause disease and I think we're very familiar with the sort of rare disease paradigm but in the case of common disorders we're looking more at predisposition than we are at a deterministic model and the idea is that over a course of time as an individual is exposed to various environmental factors they sort of climb this curve and somewhere along the way transition from this pre-symptomatic to disease state not a particularly clear line between the two and then the paradigm is if you knew about what this genetic liability was well first of all maybe you could predict individuals at risk and help them avoid these environmental exposures or if that doesn't work by virtue of knowing this have better understanding of disease mechanisms so that if they do cross this imaginary line you have tools that you can use to help them manage those conditions more effectively. Well whatever you may feel about either the validity of that paradigm or the degree of power of the various genome wide association studies and the degree to which it in fact has informed clinical decision making I'm sure you're well aware that it hasn't stopped a number of companies from beginning to offer direct to consumer genomic testing so far at the level of single nucleotide polymorphisms I think inevitably soon at the level of probably exome sequencing here are three screenshots from companies that have been in this area now for a few years. So yeah I went ahead and did it because I'd been teaching about it for a while and I thought well if I do that I ought to actually have the first hand experience and understand better exactly what it entails. Well so the first thing I learned is that I was at average risk for everything you'd ever heard of which I think is probably okay. This was the way they illustrated my risk of type two diabetes it wasn't particularly different from the population risk. I think I understood pretty reasonably well how firm or not so firm the data set was to make this judgment. I think I knew that having an average risk didn't get me off the hook in terms of the standard advice of diet and exercise but that is the concern. On the one hand you can look at this with a cynical eye. In fact a couple of years ago I was invited to be part of a panel I guess at NIDDK for a project that they were doing for a similar kind of enterprise where they would do testing and on a sheet they would hand out there were recommendations and it began to be obvious when no matter what the condition was for which you were found to be at high risk the recommendations were always lose weight and exercise more. You reached a point where you said well so what exactly is the genomics really contributing to this discussion if it's essentially the same thing as you would otherwise have advised somebody. Is it motivational? I think the data are not necessarily so clear in all individuals that it is. I'll leave it to Colleen. I think she's speaking sometime in the near future and she can talk about some of the work that her group has been doing about this. In my case it was neither motivational nor demotivational I can tell you. I haven't necessarily followed the instructions but I don't think the genomic data made a huge difference. I was also well aware that the sort of degree to which the odds had changed for any of these conditions was really pretty small. By the way one thing you can do with this they do look at your Y chromosome as a male or end your mitochondrial DNA and show you these maps as to where your ancestors came from. I didn't learn anything I didn't know that I had at some point in history an ancestor in Africa and in Europe and other parts of Europe and Asia but they did give you an opportunity if you wanted to opt into a system where other people with the same haplotype could send you an email that says you might be my relative and for about six hours I left that on and when my email box started filling up with this kind of thing from people I had absolutely no idea who they were and I decided that was not such a great idea. The other thing I learned from this though is my pharmacogenetic profile I guess you could say you probably can't read this but at the very top I'm actually at increased sensitivity to warfarin so that means that if the day comes when I might need to be treated with warfarin that the dose that I would need would probably be less than that of somebody else and in fact maybe it'd be at greater risk of hemorrhage as a consequence of a standard dose and you can go down the list here there's a lot of things it means I would respond to copter-grill if I was ever put on that and I think this was actually was potentially useful and in fact I did print this out and handed it to my primary care doctor who looked at it and then put it in a pile somewhere and you know the thing that struck me about this is that there's a lot of debate about whether warfarin testing is cost effective I don't think there's that much debate about whether it can be helpful in predicting the ideal starting dose for a person who needs to be treated so as to avoid either too little treatment which means blood cuts which is the thing you're trying to avoid or too much which could translate to hemorrhage. The debate has more to do with whether it's really cost effective to do that and whether you can do it in a timely enough way to actually make a clinical decision which are both complicated and valid questions but arguably now for me that question is off the table because there's no incremental cost to doing it but what I realized in my own setting is that our healthcare system is completely unprepared for this there is no place to put this I actually don't really know where my primary care doctor put it I have a feeling it's still on his desk in this pile but the truth is of course I'm not the one that would be prescribing warfarin to myself in fact if I ever need it I'm guessing I'm not gonna be in a situation where I can inform anybody about the fact that the testing was done it will be buried under the best of circumstances somewhere in the medical record very unlikely to be visible to somebody in the emergency room or wherever and if I'm traveling I guarantee you that it won't be available so the issue here isn't only whether it's clinically useful and cost effective but whether we have the medical systems in place to actually use any of this information so I've made light of this direct to consumer approach and guess what I would want to suggest is that this may be an example of what some have referred to as a disruptive technology and the examples that you often hear are if you go back in time 30 or so years this is what a computer looked like it filled a room and the companies that made computers that filled this room asked when the first personal computers were on the market they asked their customers should we get into this and it was a bit of a joke because all you could do with this is play space invaders and do other things that kids might enjoy doing but you can't run a business off of these and so they didn't get into that business we all know that's what personal computers might look like now and in fact one of the companies that made this kind of machine eventually was bought by a company that was making personal computers and over time has essentially gone out of business so the idea here is that a disruptive technology begins essentially as a kind of toy and in fact you can think of the kind of consumer direct to consumer genomics because what some have called recreational genomics learning things because they're interesting and it is interesting and you can by the way you can keep people engaged for about five minutes at a cocktail party talking about your personal genomic experience but it has a limited sort of degree of interest at least in my experience but over time this technology gets better and better to the point where it actually sort of crosses the curve because meanwhile this so-called sustaining technology also gets better but only incrementally and after this crosses over this sustaining technology has a real possibility of becoming obsolete so is it the case that our paradigm of a physician or genetic counselor in a room with a patient talking about one gene at a time is probably gonna get better and better over time and right now consumer driven testing may be down here on the curve but as the data set gets better and better is it going to reach a point where it becomes a more mainstream approach? I don't know the answer to that you only know that a technology is disruptive after it's disrupted because if you really knew in advance I guess you would want to invest in these sort of things but the problem is it's really difficult to see when something is on this kind of trajectory but I think there is a real issue here that the data sets probably will get better and better and our ability to communicate results in this one gene at a time mode one doctor or counselor in a room with a patient is going to be very limited in terms of what can be accomplished also I think as we look at risk of common disorders we need to broaden our scope in terms of what we actually count as relevant information a few weeks ago I was asked to give a talk to the American Academy of Pediatrics about epigenomics and epigenetics and my disclosure for that slide by the way for that talk was that I've never worked in the area and so I was pretty far from being conflicted but at the same time I spent a fair amount of time myself just learning about the area it was a fascinating area and it made me realize that maybe one reason we're not being able to completely reach a point of understanding the risks of common disorders is that the epigenome may be as important as the sort of classical genome in terms of conditioning risk of disease and it's raised questions you've seen I'm sure this paper that appeared in Cell just a few weeks ago where you can in principle bring out all the big guns in terms of characterizing your genome and your transcriptome and I don't know your cytokinome or whatever term you would want to use for that there's a lot of data that in principle could be used and I think we're a good ways away from actually demonstrating the clinical utility of all of that. So just the last few minutes I showed this picture which I'm sure most of you have seen in one context or another and I'd like to use this as a way of sort of reflecting on where we are in this concept that a lot of people talk about of personalized medicine and it's a term that gets some pushback in part because nobody wants to admit that they actually practice impersonalized medicine which the existence of personalized medicine sort of implies I think many of you probably would argue that does happen quite a bit but then they argue well it's not a new thing and it's not a new thing in fact I guess you could make the argument that this physician is practicing the ultimate personalized medicine here's his sick patient, a young child and I think by any definition he is giving her his complete wrapped and utter attention and if that's not personalized medicine I don't know what is well there is one thing about it though and you can infer from the distraught look on the child's parents and the puzzled look on his face that personalized though his care may be he does not have a clue what to do to help her and I guess that's where I think is the difference in the modern day concept of personalized medicine from the more classic one namely that as we understand the structure and function of the genome and as that informs us on the mechanisms of physiology we will for the first time have an understanding of the basis of both health and disease and be able to make a real difference and it will require customization of our approach on an individual basis but the real difference is the power of the tools that we can bring that this physician would never have been able to dream of. So I think what we're seeing now is a transformation I think it's fueled by a combination of information technology and genetics and genomics and I would make the argument that the genome will basically is the information technology of the organism and the convergence of these is really kind of moving us down what is almost a sort of rabbit hole and it really raises the issue that it's the handling of the information that is now proving to be rate limiting more than the generation of that information so we need to be raising an entire generation of practitioners who are comfortable in handling the very large data sets that inevitably emerge as we look at a genomic level. Now many have raised the question of whether someday we'll all have our DNA sequences done as a component of routine care essentially as something that just follows you through your life and there's lots of debates I guess some of which I've alluded to as to the utility of that and what exactly are you gonna do with all of the information and who's gonna interpret it for you but there's another complicated question I have already alluded to and that is where are you gonna put this information so it's useful? So maybe the most obvious solution is that it lives within the healthcare system. Now I can tell you that when you discuss that possibility with the people who are in charge of the electronic health record at least at our institution you can sort of see the hair stand up in the back of their neck because the ability of the system to accommodate the volume of information nevermind the decision support tools that that would require is really a very daunting task and if there's one thing for sure it's that they are very zealous guardians of the citadel of exactly what goes into that record and how it's used so that would be a challenge but it's also a challenge how many people will be born, live and die all in the same healthcare system these days probably almost nobody certainly very few so if your genome did live in the medical record of the particular institution let's say where you were born or for that matter where you're living currently what happens when you move is it gonna follow you? Well right now these systems are not particularly interoperable even for the simplest information so if I see a patient at UAB I'm still working with paper records that were sent to me from a nearby hospital where an MRI was done for example so even for the most elemental kinds of tests we're still working in a kind of more paper than electronic mode how are they gonna transmit the genomic information I think we're a long way from that and then even if they did that so what happens if you're traveling some strange place at the time when your care needs to be provided or are you going to still have access to that same information so some people have said well it needs to be in the cloud somewhere wherever that is and it may well solve the problem in terms of the ability to mobilize the information it means you're gonna have to trust that the information is secure and available and maybe that is the direction we're moving but I don't think it's where lots of people are as we speak so whether that's ultimately the right solution I think remains to be seen or some have said well put it in some device that you carry with you that you probably won't lose and so it's just kind of part of it's a possession of your own actually you might not lose it which you might put it in the washing machine but anyway perhaps the systems can be made to accommodate that and people would carry it around actually my favorite solution is so far as I know the most efficient place to store genomic information is the cell nucleus and nobody ever forgets to bring their cell nuclei to the doctor so the question could be asked is the genomic technology moving along a trajectory where the genome sequence will essentially be a giveaway that while you're out in the waiting room and you're filling out that stupid clipboard again somebody comes up and brushes your cheek and it goes into the back room and they sequence your genome and use it and then they throw it away when you leave I don't know if that's the direction things will move in but I find it plausible that the technology to do this is moving to a point where if it's not free it won't be too far from that I think it's more the interpretation and the informatics that are likely to be the much more significant challenge so people have used lots of metaphors for the genome and I think one of the more common ones is this concept of the book of life instructions for the organism and if you think about that you've got a genetic code which is a three letter code and you say so what book is familiar where most of the words are three letters in length and one that you probably know by the way Dartmouth Medical School was just named in honor of Dr. Seuss they don't call it the Dr. Seuss Medical School but it is easy to be lulled into thinking how hard could this be if all this information is there and I guess I would propose to you that a better metaphor if you wanna use a literary metaphor for the genome is this book and I mean by that that the nuances of exactly how all this works requires the ability to read between the lines to a degree that can be deceptive and it can seem a lot more straightforward than it really is and I could well imagine for a long time to come we are going to do what I think people who read Ulysses do which is use concordances and other tools alongside their reading to actually be able to interpret and understand exactly what the text is saying and another literary metaphor that I think applies is this one that does not take long as you begin to look at genomic data to feel like you have gone through the looking glass that the rules that you expect to apply don't necessarily apply quite as you thought they did that's certainly been our experience and I've alluded to it earlier with just one gene, the neurofibromatosis type one gene, the idea that you could make a simple correlation between changes at the genomic level and phenotypic changes sometimes is true and other times turns out to be a lot more complicated and I think almost anybody who has been doing sequencing even one gene at a time has encountered these variants of unknown significance and pathological mechanisms that turn out to be a lot more complicated than they seem to be and so I believe we have a lot left to learn in terms of annotation of genotype and phenotype. So just in closing, what are some of the things that have to happen to get us from where we are to where we all would like to be? Well there is a huge need to educate both physicians or health providers I should say really and the general public about the opportunities in genomic medicine and the complexities I think most people in practice today were educated at a time when none of this was happening on a day to day basis and whatever they might have learned and remember from medical school or residency almost certainly has changed and as the ability to do exome sequencing has moved from a concept to a practice there are precious few people who really are sort of up to speed on exactly how to make this actually happen in a kind of real time way. So there's a pressing need I think to do a massive educational effort both for specialists who will be the front line interpreters as well as for more generalists and for the general public to be discerning consumers about genomic information. As I mentioned earlier genomics really is fundamentally information and access to information at the point of care alluded to just a few minutes ago is increasingly critical. We're gonna be doing screening based testing on a wider scale than we already have been we are going to need tools to provide that in education to individuals who are having screening. So there's almost certainly never going to be enough genetic counselors or geneticists to explain to everybody everything for which they might be a carrier for which they might be at risk. And so we I think need to develop new paradigms for exactly how this education and implementation will take place. Haven't talked at all about the issues of protection of individual rights and privacy as you all know there is both federal and a myriad of state legislation efforts that have occurred over the course of time. But obviously if people don't trust that their information will be used to their ultimate benefit there will be a substantial resistance so we need to continue to address these issues. Think there is going to be a practically a generation of clinical investigators looking at knowledge of outcomes. What does it mean to have a particular genomic variant and what does it predict about your health what are the various interventions that can be offered and how do we know that we're actually improving the quality of care. And finally and I think in my mind what I believe is perhaps the most exciting thing is using the information that we gain from genomics to inform understanding of pathophysiology that in turn leads to the development of new preventative strategies and treatments. So I'm going to end with two quotes. The first has come to be called Damara's Law you've probably heard these things that these are beginning to reach the point almost of being trite but I think can really be informative. And a lot of people have been saying for a long time so when are all these transformations going to take place and Damara's Law stated that we tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run. So watching this unfold in a sort of global ways may be a little bit like watching the hour hand of a clock move not a lot seems to happen from one moment to the next but on the other hand if like today you were to go to sleep and then wake up Rip Van Lincoln style 20 years from now I would bet that the at least practice of medicine would seem practically unrecognizable and the picture that you're looking at to kind of drive the point home is the earth and the moon photographed from a satellite currently orbiting Mars and to me that sort of encapsulates just how dramatically things have changed do the thought experiment of if you could explain go back in time and explain to your fourth grade teacher how a picture like that could be taken and you get a sense of just how dramatically things have changed but over an evolutionary period of time and then finally again I quote you've probably seen before but which I think is particularly apt for this audience that the best way to predict the future is to invent it thanks very much I would like to ask you a couple of questions which are related and you have touched upon that so maybe an elaboration will be in order the questions may very well be one maybe the flip side of the other you started with the idea of diagnostic genomics based on some symptoms maybe symptoms of the individual or family history or information population genetics and then you embarked on the idea of having a genomic diagnosis so the flip side of that will be why not everyone why not everyone should go through all these genomic tests or as you said a genomic sequence as you know in the past there have been a great debate on the issue that if there is no intervention there's no treatment available then why should one go through any diagnostic test so where are we in that dichotomy which we face well first of all making a distinction between diagnostic testing and what you might call screening you know doing just testing to see what you're at risk for is not as clear a distinction as it probably seems on the surface because if you are doing a diagnostic test so somebody comes in with symptoms and you're trying to explain those symptoms this notion of finding what is an incidental finding in that setting is the actual primary finding in a screening setting so in fact there's really not a big difference in essence your diagnostic testing for one thing but you're essentially screening for everything else at the same time so you can't really argue that we're not doing screening this happens not to be the original motivation for doing it so that all being said you know I guess the issues have to do first of all with so what is the clinical utility and that could be either viewed in a simple way or a very complicated way the simple way is can you demonstrate cost effectiveness that for example you found something that permitted you to offer an intervention that modified the outcome and in cost terms maybe save future morbidity and medical expenses so if you think about it that way it's a fairly high bar and there aren't that many examples I don't think right now where you could really make that claim of course you could actually change it to personal utility you know so maybe it isn't clinically useful to know your ApoE genotype but maybe it is useful on an individual basis whether it's for planning or reassurance or whatever so it's not really such a sharp distinction as it might seem but then I guess the issue comes up of what are the costs that are involved and some of those costs might be obvious like you know who's gonna pay for the sequencing so you can take that off the table somebody says well I'll just pay for it of course then you have to ask what are the disparities then in access that are generated when only the wealthy can afford to do this so that becomes an issue but you know you can look at it from a straightforward perspective of yes it costs a certain amount to do the sequencing and to do the interpretation and you know are insurance carriers gonna be willing to cover that or if not who is so that becomes an issue but the other issue then becomes so if you find something and it's of uncertain clinical significance what are the other tests that are going to be done to follow up on that result so now you've been found to be an increased risk of something let's say it's cancer so you're going to suddenly become a frequent visitor to an imaging center or to having standard blood tests done or whatever the particular risk is that you face and is that going to be in the aggregate increasing costs to the system because there'll be lots more of the so-called worried well who are gonna demand screening for things so the cost issue becomes I think a driver. Let aside the economic issues first because those are the most difficult to handle as society but I'm more worried about the fundamental issue if the validity of a test is established by looking at the population large number of people and we say A leads to B so therefore I should also get tested A because I might have A, might need to B but that runs into fundamental question I am different than all other people for which you have established the validity that issue will come up so it'll be hard for me to convince myself just because N number of people had that that I should be also part of that N number. I think it's gonna differ test by test there are gonna be some tests where it's pretty clear if you have this that it means that and you can rely on the data and there are other tests that are going to be almost impossible to interpret in isolation and it will be a constellation of things that distinguish you as an individual and your risks from somebody else and that's actually probably in my mind one of the biggest pitfalls with the direct to consumer testing which is when you look at whatever combination of particular markers they use to assess risk it may not well be the same for the population on which they establish the data compared to the individual being tested and who knows how accurate that is. Thank you. Thank you so much for that was a great talk and I really appreciate your humility as well. So I wanted to actually pick up a little bit on that point and that chart you showed about consumer driven tests, genetic tests, genomic tests and the reality that all of that data that is being generated by these companies is private. So the expectations that we have about making these connections between genotype and phenotype and how good that is. And then as you say, we think we are going to have this association but we don't know so much. How will we be able to gather together? And I don't know how much there is of this. I mean, that's actually a question I was gonna ask you. I mean, we hear a lot about this consumer driven genomic testing, genetic testing.  How much of this is going on relative to the world? Do we tend to sort of be focusing on something that is a very, very small percentage and have that drive us in the wrong directions? And if so, I'm asking sort of three convoluted questions here. How do we gather or get better knowledge of what data they're holding that is not in any public database to be used for our research? So this kind of issue has actually permeated all of genetic testing, if not all of it and very high proportion of it because lots of the genetic tests, nevermind the consumer driven ones, even the physician driven ones are essential private databases, well yeah, for one, and there are many examples like that of companies that offer the testing. Sometimes they own the intellectual property. Sometimes they just are the only ones that have decided to offer a test for some rare condition and they tend to keep the data to themselves. And so it's fine if you use that lab but if somebody else comes along and wants to test somewhere else they may get a very different quality result because that other place doesn't have access to the same database. And there's a lot of discussion about in essence forcing the labs or strongly encouraging them at least to share their data with public databases. I can tell you about two weeks ago the American College of Medical Genetics issued a statement about the clinical use of exome or genome data. Yes, I was there, yes. And one of the points was to strongly encourage the labs that are doing this to share their data in public databases because we will never learn as a community the phenotypic annotation if we have essentially a tower of Babel of different groups keeping the data in their closed system. Now I don't know what the number of individuals who have had the consumer driven testing is if they've made it public I haven't really tried to look for it. I would predict based on the cost that whatever the numbers really are they're a tiny sliver of the entire population. It is really a niche market right now I suspect and it's probably being used by people who can afford to do it and are curious how much it's informed anybody's healthcare. I'm not so sure. And when you have that system that means they are going to be hoarding a tremendous amount of data on probably a limited number of individuals. So yeah I think somewhere along the way we do have to face the fact that you are never going to reach a point where you fully understand the annotation of the genome if you have thousands of private databases that evolve so that was the genesis of the colleges making that point. And related to that I guess is this whole incidental home and what relationship that has to how good the data is as well right? So you're piling one on top of the other. Well you know the other point here is that even if you put all your genomic data out how good is the phenotypic data that it's attached to. So in a lab that's doing testing whatever it might be that they're testing the control that they have to actually know that they're really getting reliable phenotypic data is pretty minimal. So they occasionally can push hard and try to get what they can and probably it depends on the complexity of the phenotype that they're addressing. But right now you can order a test and tell the lab essentially nothing about why you're doing the test. And so they don't know enough about the phenotype even to do the annotation. And of course who is in a position to do that? Well it's the clinicians but the whole healthcare system is driven by priorities that do not include putting phenotypic data into public databases. So I think it's gonna take a more deliberate effort to create this data set and I don't have a lot of confidence that the marketplace is just gonna fall in line and do it kind of automatically. I agree with that. Thank you. Your graph shows that the genome is a dynamic target. So because of the environmental factors with some of the genome you inherit. So how much if I do the test today at a very young age, say 10, how much you could really get from that information versus the environmental factor that will complicate the issues and. Yeah so it's a critical point. I guess I sort of alluded to it that maybe didn't make it explicit when this question of where does your genome live. So there I think are almost certainly gonna be tests that at the moment the test is done the relevance to your care is not obvious at all and may even be non-existent. Until a point comes at a later stage of your life when you maybe are beginning to develop a symptom of some kind or other that then might be informed by the genomic testing. So I mean a kind of simple example would be some risk factor for some kind of arthritis let's just say. And at the moment when it's discovered, let's say it's when you were a child you don't have arthritis. You don't know if you'll ever get it. Your odds ratio may be only very modestly changed. It's not enough to really make any clinical decisions with and so what good is it you could say and the answer is probably not much but dial forward 50 years and now you're presenting to your physician with swollen joints and there could be lots of reasons why that's happening one of which might be the test that was done when you were a child and if that data were still available it might be interpreted very differently in the context of a new symptom than it was at the time when it was first generated. So I mean I think our knowledge base is dynamic but also the clinical circumstances for any particular individual is dynamic and it means that this information may only begin to unfold in terms of its relevance as a person's life goes forward. So I think it's a strong argument why if you're gonna do this at all you wanna do it in a way that it can be sort of continuously revisited and updated and it's also what makes me uncomfortable with the idea that a lab would return only certain kinds of results to the clinician which is a topic of discussion. You know the idea is well the clinician isn't gonna know what to do with this. Don't burden them with thousands of incidental findings that they can't do anything with and I think there is a strong argument there but what's an incidental finding today could become a diagnostic finding at a later point in a person's life. So if there isn't some way of sort of dynamically updating the clinical information and its relevance I think we're missing an opportunity. Thank you. Well thank you all for coming and let's thank today's speaker once again.