 Perfect. Well, thank you all for coming to the genomics health disparities interest group. So this is our summer directors series. So we have speakers throughout the year and we're excited every summer to introduce one of the directors who will give their take on genomics and health disparities. So, to introduce our speaker this time, I'm happy to bring up one of our interest group organizers, Dr. Candice Middlebrooks. Good afternoon. My name is Candice Middlebrooks and I'm a research fellow at the National Human Genome Resource Institute. I'm also on the committee for the genomics and health disparities interest group. It is my pleasure to introduce the director of my institute, Dr. Eric Green. Dr. Eric Green, MD PhD, is the director of the National Human Genome Resource Institutes at the National Institutes of Health, a position he has held since late 2009. He has been at NHGRI for over 24 years. And while directing an independent research program for almost two decades, Dr. Green was at the forefront of efforts to map sequence and understand eukaryotic genomes. His work included significant start to finish involvement in the human genome research project. As director of NHGRI, Dr. Green is responsible for providing overall leadership of the institute's research portfolio, as well as other initiatives. In recent years, this has included designing and launching a number of major programs to accelerate the application of genomics to medical care. Beyond NHGRI-specific programs, Dr. Green has also played an instrumental role in the development of several high-profile efforts relevant to genomics, including the Smithsonian NHGRI exhibition, Genome Unlocking Life Code, the NIH Big Data to Knowledge, or BD2K program, the NIH Genomic Data Sharing Policy, the U.S. Precision Medicine Initiative, and the NIH data comments. So without further ado, I'd like to call up Dr. Eric Green to give his talk entitled, Realities and Opportunities for Genomics in Addressing Health Disparities. Well, thank you very much for that kind introduction. It's a pleasure to be here. For those of you standing, I left a vacant seat for you in front. If anyone wants to migrate to the front, there's actually a couple of empty seats if you're interested, but you're also welcome to hang. When I was asked to do this, I jumped at the opportunity. I have great regard for this and was happy to see this interest group form, and certainly I'm very supportive of it and very enthusiastic about the speakers they have been bringing, and of course I'm delighted to be amongst them and see if I can provide some context for a number of issues that I think are very important at the intersection between health disparities and genomics. So what I'm going to attempt to do today, and then in talking, and then leave time certainly for some discussion, is really to cover three areas. First, a very brief but I think important history of genomics. I suspect there's a lot of heterogeneity amongst you in terms of how much detailed knowledge you have about sort of the historical context that have brought us to where we are today with respect to genomic advances, and I want to at least in an abbreviated form give you a little of that. But the main part of my talk is to really emphasize some new realities that I think we are facing at the intersection between genomics and many issues related to health disparities. And then at the end, I want to just briefly talk about the road ahead and encourage you to help us think more strategically about these important topics. So starting with a very brief history of genomics, I've been involved in the field essentially from the very beginning, but I really want to remind people what a relatively young discipline genomics is. I think somebody believe it's been around a long time, as long as genetics, that's simply not true. In fact, the word genomics was never even put into the scientific or medical press until 1987. It was actually coined at a workshop in Bethesda, Maryland earlier in 1987. And then by the end of the year, they actually started a journal called Genomics and in the inaugural editorial in the first issue of this new journal called Genomics. The editors wrote a piece that really described this new discipline, which they were naming genomics. So why was there a new field created in 1987? There's a lot of reasons for it. It turned out that there had been a series of advances and our technical abilities to analyze DNA, to map it and to cone it and to even read out its letters. And the methods and approaches for doing that had gotten so efficient that it provided the opportunity to think comprehensively about looking at and characterizing and eventually reading out all the DNA of an organism. And it suddenly was recognized that that's its genome. And if you're going to study an entire genome, that's genomics. And imagine if you could do that for the human genome and actually decipher, if you will, the human genetic blueprint. And that, of course, was all part of a discussion about an audacious new project that was being contemplated at the time when the field was named, but then actually became launched by 1990. And of course, that's the human genome project. This is a project that I was very fortunate to get involved in from day one, participated on it until the very end. And it was by any measure a very unusual project. It was a big project. It was international and it was audacious. It was also incredibly successful. It completed in 13 years, its goals, a series of them. The ultimate one would be reading out for the very first time and ordering the G's, A's, T's and C's, all three billion of them that make up the human genome. And that was really quite an accomplishment that really signaled in many ways the reason why a field of genomics had been named. So genomics is really only been around for a little over three decades. And in a very abbreviated form, I thought it'd be useful for you to hear from me, what do I think are the six big highlights of genomics. I was going to give you a highlight reel, not the hour version. I'm going to give you the five minutes version. So that's about, you know, that's not very many minutes per decade, but you're going to hear basically what I think are the biggest highlights in just quick form. The first of which really was what I just talked about, and it really was a remarkable accomplishment. We sequenced, we read out, we ordered the three billion letters of the human genome for the very first time and made that available on the internet to all people freely around the world. And that will always be the number one highlight as far as I'm concerned for the field of genomics. That was 16 years ago, 2003, when the Human Genome Project ended, we had the first reference sequence of the human genome. And lots has happened in genomics in the last 16 years. But as you might imagine here at NIH, in a particular R Institute, the National Human Genome Research Institute, which was originally created by the U.S. Congress to lead the U.S.'s efforts in the Human Genome Project. But of course, when the Genome Project ended, we needed to think more broadly, we didn't want to go away, and we also realized that this was just the start of everything. And so what we recognized our key role was going to be at the National Institutes of Health was to do the obvious, put the word genomic next to a word that's very relevant to health. And of course, that word that was used by the popular press at the time or by the scientific press was met. And that's where you started to see lots and lots of discussion about genomic medicine, genomic medicine, genomic medicine. In reality, 16 years ago when all this was being discussed, and even as the Institute started to think about how are we going to make genomic medicine a reality, the truth of the matter is this is what it felt like. It was sort of a hazy concept. We really weren't quite sure what it was really going to look like and feel like. We knew that's where we wanted to get, but we needed to bring this into focus. And off we went as an institute off we went as a community and off we went even internationally recognizing the series of things that were going to be needed, going from the fruits of the genome project to the realization of genomic medicine, which basically involves the use of genomic information about individual patients to tailor their medical care. Well, what have been the highlights that we've had in this journey, if you will, from the human genome project and which was the starting line of this journey to the realization of genomic medicine, I would say there's five other highlights that are worthy of really high really emphasizing because they really have materialized over the last 16 years. The first of which was very technical. That first human genome sequence, it was really hard to generate and it was not so cheap cost about a billion dollars to generate it, which was fine. It was worth every penny but it's not exactly the kind of thing you're going to use here in the clinical center to help facilitate the medical care of a patient. We needed sequencing genomes to be incredibly cheap. And we've basically done that in 16 years. We've now reduced the cost of sequencing a human genome by essentially a million fold for about a billion dollars to about $1,000. And it's going to even get cheaper in the coming years. That was a technological feat I could spend an hour telling you about that I'm not going to have other things to talk about, but just recognize that without that, nothing else that I'm talking about would be possible. Technical innovation and our ability to inexpensively and increasingly getting more inexpensive read out the letters of a person's genome. With that information, of course, and the technology associated with reading genomes that allowed us to not just settle with just one reference sequence to the human genome. We were interested in sequencing lots of people's genomes, because we want to compare them and we want to catalog how people are different in their basic genetic blueprint, where their letters are different from one another. And now we've got from having one genome sequence to actually having hundreds of thousands I will change this slide I'm sure we'll pass the million mark in the coming few years. We now hundreds of thousands of human genome sequences available to us in public databases. And we've now gone from looking across those three billion letters of the human genome. And when the genome project ended we knew of maybe 10,000 20,000 places that people tended to vary have a different letter at that position. Now it's about 100 million places that we know exactly where how people vary, and we know exactly what letter is in place and different people. And so we have a very, very rich data set of human variation with respect to the genome which is very powerful. We want to layer on top of that information when you see a difference in somebody's genome you want to be able to know is it make a difference in how the genome functions as it actually have a biological influence. Well to do that you need to know how the genome works. And in 16 years we profoundly advanced our understanding about how the human genome functions. Now we have a long way to go but once upon a time we didn't even know how many genes there were. We now know there's about 20,000 genes. Once upon a time we didn't even know if genes were most of the DNA are just a small part. We now know that coding portions of genes are only one and a half percent of all the letters of the genome. And we now know that outside of these coding regions these genes are an incredibly complicated circuitry that dictate where when and how genes are turned on and off by which tissues when and blah blah blah blah. And we're learning more and more how to characterize it. Now we have a long way to go in understanding all the complexities of how the genome works and how a spelling difference in those letters influence how the genome works. But we've really advanced our ability to do that and so we really are now in a very exciting phase of using fundamental tools that are really helping us figure out how the genome works, figure out how variation influences function. And we will be doing this for many more years but we're on a very good trajectory compared to we were 16 years ago. Well once you have the ability to know when a difference in somebody's genome influences how the genome works you now can design studies to say well if it influences how the genome works how does it influence human traits. We're all very or just traits in general we're particularly interested in human traits. Of course what traits are we the most interested in is diseases. We're sitting here in the clinical center at the NIH we passionately care of understanding all the different factors that play into human health and disease. And we have gone from having cursory knowledge about how the genome and differences in the genome influence disease to now really having significant advances and unraveling the genomic basis of human disease. We've made particular strides with rare genetic diseases diseases that are turned out to be simple because it usually is one gene that's broken one gene that has a mutation in it. And in fact we've gone from having knowledge of by the way there's about eight or 9,000 rare diseases that have been characterized. When the genome project began only 61 did we actually know what the mutated gene was, but today it's over 5000 and it grows by dozens dozens every single month. And so we're still trying to close the gap we have still a few thousand more to characterize but we have made massive massive advances in understanding the genomic basis of rare diseases. We've also made major strides in understanding the genomic basis of a disease like cancer, basically the genomic disease. We know that and it will get more and more knowledge in the coming years, understanding how genomic changes lead to different types of cancer and what the implications of those changes are for diagnosing and treating cancer. And then there's the whole world of common diseases and these are the diseases that affect humanity more than any these are the common disease like hypertension diabetes autism Alzheimer's etc etc. Those are really complicated because it's not a single gene. It's usually multiple genes that have a few variants in them. Often what is a greater contribution of the environment and other social factors that play into it. And so this will be the big challenge for the coming 10 and 20 years but I still feel with some successes and a much better knowledge of the right approach to use to characterize common diseases. I'm very optimistic and think we should be very proud of these first 16 years. Common diseases certainly for cancer and unbelievably so for rare diseases. My last highlight I'm particularly proud of because to be honest with you, when I became director of the Institute now almost 10 years ago, I sort of would stop my talks at about this point, because I didn't really have anything to say about medicine. I got as far as diseases, but I never got to actually anything about medicine, but I get to put one more highlight on here because now 10 years later and certainly over the last six and seven years we have seen emerging. Some of the first some of the earliest but clearly vivid examples of how genomic medicine is actually going to become a real and it's been very gratifying even though I know there's so much more to come. I feel like we really have transitioned where we were 16 years ago to be in a position much more like this. It is much more in focus. And while we have a lot more to do. I think we can be really quite impressed with the fact that we have real life examples of genomic medicine being implemented in the real world. I'm often asked what are the hot areas of trauma what are these examples what are these vivid examples, I almost always cite at least as of up to today, sort of these four areas. One is I told you about earlier cancer genomics, I mean the world of cancer research and increasingly cancer care is absolutely changing because of genomics and the tools of genomics. Pharmaco genomics big word but it's just the fact that everybody seems to respond differently to different medications and much of that not all of it but much of that is scripted in differences and our genomes that affect how we metabolize drugs. Knowledge of those genomic differences is beginning to help tailor the selection of the appropriate drug for the appropriate person. And this is becoming more and more real for more and more medications. Having a patient with an unknown disorder or rare disease, and having them sitting in front of you and not knowing what is wrong with them, and then just saying well I'll just sequence their genome and upwards of 50% of time you will figure out what's wrong with them. By the way, that approach has absolutely was was put into sort of motion and reduced to practice right here in this building in the undiagnosed diseases program. But now this has been generalized hundreds of patients with rare diseases get their genome sequence every month, and we are figuring out what is wrong with them in a fraction of cases. This is something I never thought I would necessarily see in my career maybe not even in my lifetime it's already here and now. And the last example because actually the largest example in terms of sheer number is prenatal genetic testing has been around for a long time, but non invasive methods whereby you don't need to do an invasive procedure like an amniocentesis to access the fetal DNA to study the unborn babies chromosomes, rather doing a simple blood draw and detecting the small amount of fetal DNA that naturally is shed from the placenta floats around the maternal bloodstream. This is this is this is absolutely done every day, not just dozens of times hundreds of times worldwide and the companies have set this up so it's a huge industry now. 10 million pregnant women are expected to get non invasive genomic testing done around the world over the next year. It is absolutely the number one genomic medicine test and it's happened very quickly and it's all related to technology development. So, those are the hot areas. So that was about 12 minutes and three decades of genomics of highlights. But what I hope you took away from that is this incredible surge, this incredible arc of scientific to medical story and how the wind is to our back and there's a lot more that's going to happen. So if you haven't noticed, I'm an enthusiastic person. And I'm also quite optimistic about many, many things. But I didn't want to leave you the impression that everything is simple, or that there aren't major problems to solve, or that there aren't imperfections in this storyline of genomics. So that leads me to my second area, which is relates to new realities. This is like cold water in the face kind of realities. We don't have this perfect by any stretch of the imagination. With that said, the optimistic side of me is to say, but that also means there's opportunities. We can do better. And we should think about how to do better. And we should enable people and enable the system to improve. And those are the opportunities that come with these realities. So I'm going to tell you about three major realities that are here and now and need to be dealt with, but there are opportunities for dealing with each of these. So reality number one, in terms of new realities and opportunities, there is a lack of diversity in genomics. Full stop. There's a lack of diversity. We have missed the mark. And this really does represent a problem. This has been studied for a number of years. And in fact, just several years ago, this comment piece by Papjoy and Fullerton sort of updated an analysis that they had done about seven years earlier where they look to see how genomics was doing with respect to population diversity. And while there was some signs of improvement, I don't think you would say overall things got better. And shown here is one of the figure, which I'm going to drill in a minute, but the high level summary is they went from in 2009 as a field. If you looked at the large studies, genomic studies that were analyzing populations for different diseases. In 2009, 96% of all the individuals being studied were of European ancestry, leaving a very small sliver of non-European ancestry. Now, the good news was that in seven years from 2009 to 2016, that situation had improved by some measure in terms of you could see going down to 81% European ancestry and 19%. But before you get too optimistic about that trend, we should drill down a little bit further and show that there are some imperfections. So yes, there was a five-fold increase over seven years with respect to the proportion of non-European samples. The problem is that 78% of the increase came from populations that were limited to basically Asian ancestry. Japan, China, Korea, India and other populations of East Asia, South Asia and Southeast Asia. That worked well for those populations, but what it did though then is that all the other ancestral populations, African and Latin American ancestry, Hispanic ancestry, Native and Indigenous peoples, they represented less than 4% of that increase. And some of those populations are the most vulnerable and traditionally underserved populations in many of the richest nations in the world. So while there was signs of improvement, they weren't sort of evenly distributed by any means and they were still leaving the mark of having a lack of adequate diversity in genomics research. Then earlier this year, another paper was published that did sort of a similar analysis in this 2019 Nature Genetics paper. They basically acknowledged that there was remarkable growth in the number of people who are represented in genomic databases. Again, either through sequencing studies or through other studies that involve this examination of diseases where genomic data was captured on individuals. And the total number of participants and shown at the top are the numbers and on the bottom graph are the percentages. You could see, especially the top panel, the numbers went up and up and up, which is great. More data, more data, more data. The problem is, is look at the individual, the different colors, because as you could see, they're sort of not very proportional. And at the far right shows the global population in numbers at the top and then at percentages at the bottom. And you can see what the problem is, a significant mismatch where individuals of European descent are over, over, over, overwhelmingly represented in these data sets. Many of these other, or essentially all of the other population groups are not represented in the data compared to what they are on earth as a population. And this has consequences, because it actually turns out that there really are the data associated with different ancestral populations really is different. And when you actually go to analyze the data and you want to have controls and you want to have all the right proper scientific means by which you're going to analyze the data. It is inadequate to simply use the European data when you're analyzing data from other ancestral populations. It just doesn't translate. And as you think about some of the clinical analyses that you may want to do to infer whether certain genomic variants put a patient at risk for a disease. It only works for that same population. It doesn't automatically apply when you move to other populations. It is an inadequate control. What that means is the groups that are not well represented are being left behind because there's inadequate data to facilitate the interpretation of the data being generated. Well, this is it's not that this is going unnoticed, but the problem persists. And tell you that NHGRI has recognized that we must start fixing these. We don't think we can fix these problems alone, but as leaders in genomic research, we can at least lead and illustrate the proper path forward. So earlier, I guess it was last year, not earlier this year. Last year we were invited to publish a perspective and a number of us from the Institute put together this perspective in nature genetics that really outlined a number of the things that NHGRI is doing and the importance of doing them and provided at least an illustrative framework for others to follow and at least recognize how we regard this as an important problem. We also voted with our feet. We didn't just write papers. We started changing some of our programs. We started prioritizing some of these things. And to give you a flavor, we have two among our programs, our large programs that are run by our extramural research program, especially in the arena of implementing genomic medicine or in other words, studying the implementation of genomic medicine are these two projects. These are a clinical sequencing evidence generated research and ignite implementing genomics and practice that each have their own characteristics of what they're trying to accomplish. But as we have gone to renew these programs and mature these programs and really have them represent sort of cutting edge programs that are tackling the hardest problems and amongst the hardest problems is helping to fix these problems with diversity. I'm sure that these programs are addressing these things head on. What do I mean by that? Well, we conscientiously have prioritized diversity as these programs have have matured. For example, in the most recent renewals of these programs we've required that 60 to 75% of the participants come from underserved populations. These programs could include racial and ethnic minority populations underserved populations populations who experience poor medical outcomes. We've defined it in broad and in a systematic way to capture many aspects of diversity. As the studies have been designed it's not just about who is getting the care but we really think about how they are getting that care we recognize that health care settings and health care systems vary considerably. There are different parts of the different populations access health care in different ways, and that we don't want to just understand how genomic medicine is going to be implemented at a major academic center we want to understand how it gets implemented across the diversity of sites that health care is delivered. We also want to make sure that we are fundamentally assessing the clinical utility and cost effectiveness of genomic medicine tools and technologies in the real world, which means in diverse settings so once again we want to make sure that we've developed the tools to assess whether or not genomic medicine is improving health care across a diversity of different sites and not just in one site or one type of site like major academic medical center. And finally we want to understand what the barriers are. We don't want to just know the successes that although we want to know those two we want to identify and address the real world barrier to integrating genomics into routine clinical practice in different types of health care system and we want evidence for how to do that and how to sort of guide clinical decision making as part of medical care across a whole host of different places where medical care is delivered and where genomics can be of help. So that's what NHGRI amongst the many things we're doing that's just illustrative of how we are voting with our feet as we say what needs to be fixed. We've been very pleased to recognize that there have been enhanced diversity across different programs at NIH and that this has been embraced in other places at NIH and there's sort of two exemplars I would point out. Some of you might be familiar with the Precision Medicine Initiative or which sort of has as its mainstream the All of Us Research Program this effort to enlist across the United States and enroll a million or more U.S. volunteers who will be followed in a longitudinal fashion who will have measured significant amounts of data collected about them including genomic data. It's a major effort in the All of Us Program to make sure that diversity is captured. I can give you some numbers. There's over 142,000 individuals have now completed the fundamental first research protocol after enrollment in the program. Greater than 80% of the participants are coming from communities who have been traditionally underrepresented in research and greater than 50% are part of a racial ethnic minority group. And keep in mind the amount of data that's going to be collected on these individuals is going to be remarkable in terms of scope and scale which I think has great potential in the coming years to give the kind of data sets to be able to really drill down and not leave diversity behind but actually to actually make it a very much upfront because of the way the enrollment is being conducted. Our colleagues in the National Heart London Blood Institute in a program that we actually interact with extensively called Transomics for Precision Medicine or TopMed is another program where so far they have about 144,000 participants of which about 60% or so are non-European ancestry. So once again, another example where diversity is being embraced in the recruitment upfront and therefore it will ensure that diversity is not left behind. Even beyond the United States, I should point out that population scale genomic studies are sprouting up all over. And in fact all of us program or the programs at NHLBI or programs at NHGRI, I can tell you that around the world major cohort studies are being started or in some cases actually got out of the gates before ours did. And in aggregate and we're actually tracking this actually a consortium of all these cohort groups coming together. And it's really, it's heartening to see the diversity that will be represented at the moment. It's believed there's at least 60 worldwide cohort studies and the countries they're in are sort of shown in the colored countries on the map. And in aggregate, the enrollment figures might indicate there would be upwards of 30 million individuals who will be participating in these and they will bring tremendous diversity because of ancestral and geographic origins as you can see as you look across the world map. So this will be another important contribution. So I hope I left you with this new reality one, we need to do better, but on the other hand there are signs that we are doing better, but we need to continue to pay attention. So new reality to and with it an opportunity. Diverse communities are at risk of facing barriers to accessing genomic medicine. There are barriers now and they are at risk of actually even getting worse. And we need to really be thinking about this and there's really an interesting phenomenon that's going on, because right now, most of the genomic data being generated is being generated as part of research, which means that people like me can help control what happens because I'm in charge or more humorously funding agencies are in charge. They could decide through what the money they're giving out as part of research, they could require certain things just as we are requiring certain and all of us is requiring and these other programs requiring certain levels of diversity. If you're going to get funds from those funders for conducting research, but there's a twist. The new reality is that the world is changing when it comes to how genomic data is going to be generated, because it turns out that it is fully expected based on a study done by this organization called the Global Alliance for Genomics and Health. They believe the trend is that the bulk of genomic data is not going to be generated as part of research, but rather it's going to be generated as part of routine medical care by health care systems. And these are the projections that, you know, maybe right around now it's about 20%. But 2022 is not that far away and the prediction is that the good news is that genomic medicine is being implemented. The good news is it means that lots of health care systems are going to be generating genome sequences on patients upwards of 80% of all genomic data might by 2022 might be generated by these health care systems and this is actually the paper. If you were interested, it's in the bio archive, preprint archive. And basically the bottom line is that there's going to be 40 to 50 million human genome sequences predicted to be generated by 2022, but greater than 80% of them, it's going to be generated as part of health care. Well, one might get slightly concerned about this, because you can't guarantee that access to health care, especially places that are implementing genomic medicine, most aggressively will be places that will provide equal access. To people from all walks of life and all ancestral origins. And so will everyone have equal access and I think that's a fair question. And there's plenty of examples where when it came to new technologies, new developments knew this new that there was not equal access. And so the reason this becomes a reality is it sort of takes away the control of that from funders. Because we will be the minority controller of what data is being generated, and it puts in the hands of the complicated ecosystem of health care to determine who's going to be getting their genome sequence, and therefore what data is going to be available for And so you love those 40 to 50 million human genome sequences to analyze, but you may not be able to control the characteristics of them, it will be controlled by the ecosystem of genomic medicine you think about all of these things, and you can immediately become concerned. If we don't pay significant attention to access to genomic medicine. Everyone won't have equal access. There are new ones associated with access because it's not only just getting your foot in the door and having your blood drawn to be able to get your genome sequence. There's also an issue of if you're even going to want to participate in that you're going to allow your genome to be even part of the conversation about this is that will you understand what this is about, and will the understanding of genomic medicine be equally distributed across the world's population or even in the United States across the US population. And this is another issue that NHGRI among others think a lot about is that we are at a point where our technologies and our advances have accelerated so fast and furious that it's pretty clear that a fundamental understanding of these advances has not kept pace. And it's not necessarily anybody's fault and some of these were victims of our own success. We've been so successful that we haven't been able to bring around because we're just going so fast and furious. So we've become very interested in the challenges of genomic literacy and we recognize it as a very complicated problem and it's not just a single population that we have to think about. We are doing various things across several different domains. We think a lot about K through 16 are recognizing that just fundamental sciences learned and K through 16 stages, and we want to do more to improve the framework for curriculum development and for implementation of tools that will enable K through 16 students to learn more about genomics, since we need to think about the general public from the point of view of just recognizing that people in society need to know more about this. We need to engage individuals so they understand more the fundamentals that we will want to use similar framework we're using for K through 16, but we're going to have to tailor it to a general public community and really think about even at a research level what we should be doing to improve our ability to communicate fundamentals about genomics to patients because general public basically going to be patients. And of course the other community that we need to be thinking about are the people they'll interface with in the healthcare systems. When they access the healthcare system and that's of course these healthcare professionals. We know there's significant gaps between what doctors and nurses and physician and physician assistants and pharmacists know about genomics and what the cutting edge is, and we need to play catch up. And they need to be part of this formula for making sure that fundamental understanding of genomics is provided to patients so they can make informed decisions, and they so that everybody benefits equally from these opportunities. And so this second reality really has to do a lot with thinking about how genomics is going to genomic medicine be implemented, making sure there's fair access make sure there's fair access not only the foot in the door to be part of a genomic medicine implementation, but also making sure everybody understands this. Otherwise people will will will not be as motivated or people will not be properly enabled to participate in decisions about whether to have genomic medicine be part of their health care. But there's opportunities and we need to work on this and we are my last reality and opportunity sort of speaks more to workforce issue. You know, diversity needs to be reflected and who's doing the research. We need to be thinking about the workforce in general, and and the workforce at the research level of the clinical level, so on and so forth. We do look at data. And this is just from the age data book, and just tracking the number of individuals with an age to support her PhD recipients, of course different groups, different groups of from the population, and perhaps not surprisingly we sort of seen the same kind of gap that could have predicted where individuals of European ancestry represent the numbers are going up but they're also going up in a way that that the most significant group remains individuals of European descent. Some community that you can sort of see some of the other communities at the smaller levels, and some communities like American Indian Alaska natives I don't even show up on the graph, because the numbers are so small. So this is not a reflection of society this is a very distorted, but these the individuals for example getting PhDs. And is so they're similar, you know we need a workforce. This is one example there's other examples we give of other parts of the workforce, where similar problems certainly exist. We certainly thought about this a lot at a share I and thinking what we can do. And there's a, and many other groups are thinking about this as well. We think about how to have dialogue with communities to sort of get more people knowledgeable about this field this exciting field and getting them more engaged to improve the genomics workforce overall. I'll just give you two examples, both of which involve sort of an education group we have at the Institute that has been quite strategic and a number of ways. So, for example, for the past couple of years, we have been working with the tribal college faculty to launch a new initiative called the tribal college consortium on genomics training TCC GT. We are just aiming to sort of coordinate better the tribal colleges as well as other federal agencies to expand training and research opportunities in genomics and relate to work with them to figure out what can we do to enable your ability to incorporate genomics more in the context of traditional tribal views. And there's many complexities with that, but it has to start with a dialogue of us understanding what they need. And shown here is just sort of picture from a workshop we held about a year ago, where we are trying to understand what and they're trying to understand what we can provide and help. We're trying to understand how we can tailor some of the genomic literacy framework and elements that we've been developing and tailor it so that would be of maximal utility within the context of their tribal college education system. And then more locally, I can tell you that we've thought even locally about opportunities to start to engage youth and to try to get them more involved in thinking about genomics as a career opportunity. So we have this Prince George's County Economic Development Corporation program called Youth Career Connect, which is designed to support college readiness and workplace skills development for secondary students. And then we have a number of interactions with groups of students where they come to NHRI, they come to NIH sometime and they learn about developments. We have career counseling and points into different opportunities because there's so many different ways to become engaged in the genomics research and genomic medicine implementation workforce to really think about seeing how to match individuals and their interest to the many opportunities that could be provided. So those are two of our more local programs, but even that we've been had staff directly involved in. But we're also creating other kinds of opportunities for all levels of scientists who have been underrepresented and not only from racial and ethnic minorities, but also people with disabilities individuals from disadvantaged backgrounds and so forth. So I'll just give you three other examples of things that in some of our very recent this one is actually just getting out of the gates. We've partnered with the American Society of Human Genetics very recently to create an initiative called Human Genetics Scholars Initiative. It's an outside partnership with sort of a major important society, professional side, American Society of Human Genetics. We only launched it like two months ago. And what we aim to do is to identify, mentor and help prepare a select group of high potential diverse early career individuals for professional success. By doing this, we're going to foster a community of researchers committed to diversity and inclusion. So a number of engagements we're going to have with them over a period of months in the hope of supporting them and getting the society also to help support them in a number of ways, encouraging their continued advancement in the genomics workforce. Right here within our intramural program at NHGRI, we have an intramural postdoctoral fellowship program aimed at health disparities. Particularly we take individuals into this postdoctoral program and who are interested in conducting research at the interface between genomics and health disparities and prepare them. And we broadly define that, but to prepare them and engage them and hopefully help launch careers, whereby they can help be part of the research engine to inform us on some of these challenges. I've been pointing out they represent the opportunity or the potential to have a see some of the opportunities that can come out of understanding these problems a little better. And finally, for a number of years, our extramural program has that sign called a diversity action plan, which basically takes some of our large extramural research programs in some cases genome center like programs or big initiatives, and couples to them, basically an extra element that particularly aimed at some element of improving diversity, either in training, or in workforce development or career development can be at various levels and every program is a little different. But this has been sort of done for a number of years, and we continue to embrace this as actually do our grantees it gives them out about around the country in very different settings in very different ways, basically doing a bunch of experiments to see what can we uniquely be contributing to enhance diversity in a number of ways, and then learning from each other to try to see what might be disseminated to work in other settings as well. So that's what I wanted to tell you. And just in closing, I just want to point out that everything I just talked about with respect to diversity and health disparities really is just a slice of a set of issues related to genomics and society, which are getting more and more complex all the time for a variety of reasons, not the least of which is the second you start dealing with anything that touches health care. There's just so many societal issues because health care is so complicated for so many reasons. And of course, our Institute has has has been embracing the research in this area, actually since the beginning of the Institute essentially, exemplified by something called our ethical legal social applications research program or LC research program ELSI. And that's a extramural research program but even within our intramural program there's a number of investigators that really focus on major research topics related to the interface of genomics and society. And so everything I talked about is really in a broader context. And there's so many other areas that we study in either our extramural programs or intramural programs these range from how to engage different communities including diverse research I touched on. Many issues associated with privacy and data sharing and the complexities of that, especially when you think broadly into different communities, and some of the nuances that you find when it comes to privacy and different communities, dealing with the issue of trust more generally and understanding it at a fundamental level. I touched on the international cohorts but there's an international dimension to almost all of these societal issues. And even if we understand it in the United States, it actually gets even more complicated when you go to different parts of the world in different cultures. There's a whole host of issues related to what's called direct to consumer genomic testing or genomic analysis or DTC, another part of our areas of research involved in genomics and society. Lots of issues about return of genomic information to individuals, what they want to know, what they should know, what they might, how to prepare them for that and so forth. So many issues around that as well. And finally, many issues as I sort of already touched on but just dealing with healthcare professionals, what they understand, how this interfaces with the work that they do, the clinical workflow, interdigital electronic health records and so forth, many complex societal issues at that interface as well. So, that's what I wanted to tell you in terms of the new realities. In terms of the road ahead I just wanted to make a couple comments. I think the first part of my talk, it almost made it seem like all this was simple. It was just, you know, we just went after the genome, we figured it out and the next thing you know, we had six highlights and we were implementing genomic medicine. That journey, I hope you appreciate, wasn't that simple? You know, it really looked more like this. It wasn't a simple spring path. It was very complicated, like all research, it's just really complicated. I really want to emphasize, you know, I was there at the very beginning of the field. I was there on day one of the genome project. You know, don't think for a minute we knew what we were doing. To be honest with you, I still don't really think we know what we're doing. If we knew what we were doing, it would be too simple. I really believe that. If you go to my office and building 31 above my door inside my office, I have a quote from this guy who I assume you recognize. And it really is one of his quotes. He said if we knew what we were doing, it wouldn't be called research. So I readily admit, and it's been the sort of characteristic of genomics. We sometimes make it look so simple and straightforward, but none of this is, because if we knew what we were doing, it wouldn't be all of this is research. And I hope you appreciate that this middle piece that I talked about related to diversity is just a classic example. We don't totally know what we're doing. That's why we have to constantly be asking questions. We need to be constantly talking about this. We need to be constantly researching this, and we'll figure it out. And we always seem to do that in genomics, but we have to recognize that so much of what we are doing we are have to correct our course because we're oftentimes sort of slightly going in the wrong direction and we need to sort of self correct. And every once in a while the Institute does this in a very systematic way, and we're about to do this again and by that I mean we strategically plan. So we strategically plan a lot during the genome project when the genome project ended we put out a strategic plan that we published in nature in 2003, describe what was going to be needed. And then we strategically planned again about 2010 and published in 2011 a strategic plan that's guided us for the last eight years. And the Institute's going to publish a new strategic plan in 2020, and you sort of taking the 2020 vision metaphor as you can see. And, and that's a big part of what we're doing over about a two year period. And where we are, you know, about a little over just about a year before from right now is when we'll be submitting this publication and submitting this paper for publication. And you know, we need a lot of people to help us and we've been engaging lots of people along the way. And we certainly need all you and we would we would really love to hear from you. The Institute is very much one that listens and really tries to synthesize lots of things. I embrace this as something that is critically important as general area, you know, health disparities and its relevance to genomics and vice versa. So then spot him, I think many of you know, sitting right here is my senior advisor. He's just my senior advisor and genomics and health disparities Michael is somewhere he's back there and works with vents. And we regularly strategize about many of these things, including the creation of this of this lecture series. And they're also being very helpful in helping to think about many of the issues around health disparities and genomics as it will play into the formulation of our strategic plan. But we also welcome your comments as well. And we're about to sort of open the floor up for any comments that write anything I said, or, or, or the things you want to say that relevant to our strategic plan. And I should put in two other plugs, and then I really will. I want to hear from you. One plug is if you're interested in a regular update about genomics, my staff and I put together a monthly newsletter. Now, you're welcome not to subscribe to it, but if you wanted one extra email a month, feel free to sign up for that. And the second plug I guess I could put, although I'm not going to remember exactly the date and time is that we are next week are going to be having a town hall related to our strategic planning process on next sometime next week. I'll look it up in a second and it's in it's an ellipse and auditorium, and you'd be welcome to come to it that's where we're actually going to formally start talking about some feedback actually I send email so if all you're on the NIH email we send out emails, at least a couple of them. And I would welcome you to sort of join us at that or you can come in by video cast, and so forth. So I will stop there and please want to hear from you. I have a question. The cohorts. Yeah. Yeah. There's probably multiple glaring areas. There was a continent I don't even know which one I could think of two, but I'll be curious. So it's actually really interesting I can tell you a few things about this. So as I find a. You're more bothered by Africa, you're more bothered by South America, because you could be bothered by both in different ways. But so, so you're absolutely right. And there's a lot of interest and attention being paid to this actually this is a slide I can actually tell you this is a slide that will actually be shown next Tuesday morning at a meeting over the Porter neuroscience building to close meeting so it's not like I can I can't tell you where the heads of international research organizations, which, you know, our director is just one of a whole as a representative there, but they all get together once a year. And there's actually a and this is the, this is the big shots of the big shots. This is a, and they get together and there's a whole topic about all these international cohorts. So I'm sure one of the things and how to coordinate them better, but also the recognition that some countries are not some continents are not represented, and then lots of discussion about how to sort of improve that situation. So, so, so H3 Africa, so that the slight difference or so H3 Africa is a program that I'm sure I as a co lead on coming out of the common finance human heredity and health in Africa. These represent longitudinal population studies where clinical data and genomic data is being captured. And in reality, H3 Africa has some individuals collected, but not so much clinical data and not so much date not so much set up in a way that you could go back and protect the people and it's really not set up as a cohort study. So, yeah, so, so a lot of this, a lot of these have to do with the crime and also, yeah, there's a few other nuances now the desire of course, is absolutely going forward we should think about what could we could do to create a cohort like study on the African continent I would argue similarly in the South America as well. Oh, yeah, I mean, lots of places. Yes. So China, China has some big numbers associated with it. India does not. India does not. Yes. I mean, certainly that's on the list. Absolutely. I mean, you could you could come up with lots of groups. We actually have a sort of a network group that we founded of, of, of health care groups, I mean, professional societies actually don't know if the health services represented on that but that's we are trying to develop these kinds of networks to try to have sort of both dissemination mechanisms but also to try to get them working together and sharing materials and sharing best practices and so forth. But you're absolutely right. Yes, you should add anything that's you should feel free if there's anything you want to add to any of these good questions. As you know, we work with title advisory committee today Wilson's office, which I just. Yes. No. I mean, you're absolutely right. It's a recognized issue. And it, you know, it has if done right, it actually has great promise to actually prove that that some drugs that don't look so good might actually be better if you just stratified them properly. So, by the simple logic, this should be so much better. It's interesting events was just Adam is just organizing a meeting we're having with the FDA around to help to have help them help us with our strategic plan. And I mean, it could be one topic we could certainly explore with them, but but we're getting general input, but that would be a great example of something, you know, this all this plays, you know, pharmacogenomics is basically a genomic test. And just like any of these other genomic tests. They don't hold up well on and on non represented populations. And so it's almost as a pervasive is the same pervasive issue that we've just got to improve every one of these, the way we design these studies, or we're going to really limit the utility of genomic medicine. Other questions comments. Yes. So, do you see another barrier for pharmacogenomics, particularly answer is possible. So, and you see, and you say anything unique about genomics that makes that worse. Or is it just a problem in general, that I think it's the target base. Therapy. Right. And if they don't use them, then we're not going to get data. Right. So, and I, and I when I hear that argument, I guess part of the logic is that if they're, if we limit who gets the drugs, then then that means that they're the prices will be even higher. But the problem is we, but at the same time, nobody wants to give drugs to people that's not going to work. So, so of course, this plays into the economics of drug development and the economics of health care. And I have to just acknowledge that those are those are huge societal problems that that I can hardly put on the back of even the field of genomics and we have to we have absolutely have to deal with those. But, but, but, you know, we would hope that that the long run genomics might help them. But there might be unintended consequences and then we're going to have to grapple with it. I mean, one of the things I've always hoped for, and there have been some signs maybe instrument is it was what we were almost talking about is that there might have been a drugs that were in development. That when they they were found to not be particularly effective or they had really serious adverse because the studies were done blind to genomics. And if genomics had been used to we would have the data we could stratify it, there might be drugs that are put on the shelf that are just never going to come to market. But if they could come to market with a limited or you know somewhat limited genomic use, then all of a sudden you might actually those might be able to be repurposed. Otherwise, they're just being shot. And so that's always been a hope, but you have to do the studies to prove it. Friends, do you want to have any last words or any comments or things were not covered. No, I just want to thank you for coming today and presented interest. Okay, thank you.