 Thanks, Eric. Again, we appreciate the gracious invitation to share and, as you say, extend our very collegial and collaborative partnership between our ICs, which we're looking forward to ongoing synergies and opportunity to get input from this, the expertise gathered in your council that complements and helps us in our directions just to outline a couple of things, how these programs fit into our overall portfolio of both scientific priorities and fiscal management, and then a couple of highlights about some interfaces and we'll throw in a couple other pieces where I'm hopeful that collectively we can think about and brainstorm and strategize about additional synergies and collaborations. I always sort of start with some guiding principles that relate to our NHLBI mission that kind of keeps us grounded in which a big part of our fiscal and strategic approach centers around investigator initiated fundamental discovery science really is the bedrock upon which we think about these particular institute solicited and initiated sort of large programmatic efforts and our ongoing efforts to maintain a balanced portfolio that spans basic translational clinical and population science and how this, again, fits into those enduring principles and a key sort of sacrosanct element that I always use as a touchstone is the integration of training a diverse new generation of leaders of science as part of this and again relevant to our collaborative efforts in this genomics and data science space that we're exploring and then probably actually more relevant to you on this particular point about implementation science in some sense I guess kind of what you do with CSER and insight and thinking about how this technology and our findings and our new knowledge actually penetrates to in a very pragmatic but strategic and evidence-based way into practice that influences how patients are cared for and has public health impact and I think that's that grounding that both our institutes need to continue to put forward such that we're always connecting with the public and the public impact of the discoveries that we fund and then finally a passion of mine to innovate an evidence-based elimination of health inequities which again still stirs stases of backdrop and I think is still very relevant quite frankly to the programs we're pursuing now. Just as a brief overview, certainly this council is familiar with the trials and tribulations that relate to our budget but this just goes to show some of the things that we've been doing in our multi-year perspective modeling to try to again bend the curve in promoting investigative initiated discovery science, particularly R01 funded research at our institute in which we're trying to eek up that pay line despite fiscal constraints and we're making some headway obviously facilitated by the boost up of the two billion dollars from FY16 and I guess we remain hopeful Eric as to what Congress may do in the selection year but given the unpredictability of that I'll stay away that from that in a public session but as we think about those strategies one of the elements has been a strategic planning or what we call strategic visioning process we've been embarked on for last year and a half or so to help provide greater framing and focus and strategic guidance on our institute solicitation and institute major programs that fall into these four major broad goal areas around understanding human biology reducing the impact of disease promoting translation from early to late implementation science and and then our stewardship of the workforce and resources and it was a sort of a typical process for NHLBI that use crowd sourcing and solicited from all 50 states and 42 countries around the world to help us think about what are the most compelling questions and critical challenges we should develop and indeed we're encouraged by the response we got relevant to the presentation today there were a number of things that over the course of time came in that aligned very much with a direction that I know Eric's been pursuing since your strategic plan from several years ago in the genomic medicine space and where we've been talking along since I arrived I see a convergence in this space that was really also bubbled up in the strategic visioning process around the opportunities that exist in precision medicine within our portfolio and a sense from our community that we need to leverage these new technologies for understanding individual factors that account for variances and treatment and response as strategies for both prevention treatment and incorporating that into our research agenda such that we can be more effective at predicting outcomes tailoring treatments refining our approach to clinical trials and really extending the scale scope and depth of our population science. There are some challenges that come from considering how we might implement this related to some elements of how we have typically collected data on a R01 by R01 or grant by grant or even cohort by cohort basis over the decades and where these things often remain behind isolated firewalls and yet the increasing explosion of data that we are seeing some of which are two institutes have catalyzed together particularly with all the sequencing efforts of late that particularly the whole genome sequencing efforts and the fragmentation of that data generation and accessibility and utility in moving those sorts of data sets around and so we certainly look forward to ongoing partnership with genome around some of these areas of open science and how we can get more facile and nimble data integration and movement across data set data sets that we're both are both our institutes are generating similarly again this theme of training and leveraging advances in data science and inviting them into the biomedical arena and vice versa and the opportunities that exist for our collaboration and synergies in that space and as a organ disease based institute a call out for for lack of a better term perhaps a human phenome project in which we say as a clinician scientist hope that our our phenomics catches up with our genomics technology and and and that we seize this opportunity to refine basically the clinical taxonomy that we all kind of grew up with it a much deeper and more fundamental way and I think we've gotten quite a a tailwind provided by the the president and his vision for a precision medicine which I think gave us both a boost certainly Eric and I were shoulder and shoulder in the implementation of trying to go from what a statement in February to a rollout of projects here this fall at the speed of light it seemed like at periods of time for the government to move but indeed removing and making progress and great that Eric Dishman is both here and on board and we'll detail a lot of that for you we we're excited by the opportunity that comes from a space in which folks like a terminole you'll have been around NHL BI has been having these iconic longitudinal community based cohort studies that have collected data and really set a paradigm for so many years on the ability to predict who's at risk of a heart attack and identified things like risk factors and now to overlay the the greater depth of data that we now can put together to maybe hopefully refine that original framing man risk score which helped me Terry probably hasn't changed in about 30 years hopefully we'll we'll get something that can can beat it out and it's in predictive value now we have all this data at least that's the promise let's see if we can actually bring it to fruition and hopefully one of those elements is that the ability to create resources that facilitate the more effective mining of that data the scaling of that data in ways that we can think about it as a broader resource a data commons if you will a shared resource of a virtual public good something that I think the NIH should be involved as a steward in creating that serves for knowledge generation innovation scientific advances as a sort of living ecosystem one in which there's a communal space that engages people from variety of disciplines and perspectives toward asking and answering important questions and that's open and one in which whether you're a participant in a cohort or a member of council that you can gain from those insights and be engaged so this is the vision that I think is starting to emerge I think certainly Eric and I share some of these things and are engaged internally with discussions about you know how NIH probably should be positioned to kind of create this kind of discovery sandbox of these data and data sets in a responsible way that obviously honors privacy and controlled access restrictions but as we look at the future we see the potential particularly in the HLBI space of reimagining clinical research that aligns with our mission as we know it enabling rich data collection it facilitates cohorts of some phenotypes of interest like early onset MI new onset HL for belation hypertension even monogenic disorders like sickle cell disease and potential modifiers asthma COPD etc and apply deep analytics to predict disease risk and identify novel molecular pathobiological mediators and for that to then translate into a space of launching clinical trials with predetermined eligibility predictive risk profiles and embedded long-term follow-up perhaps in existing health systems and again related to emerge and Caesar and ignited can't keep up with all your acronyms but I think there's opportunities as you do these proof of principles that the disease-based ICs can can learn and again will continue to work together toward this convergent vision certainly for us part of advancing into the space is to leverage the class cohorts that we've had and to contemplate a transomic approach for precision medicine our top med program to link the deep phenotyping characterization of heart lung blood sleep phenotypes in our cohorts with the multi-level omics that this Institute has been at the forefront in creating the techniques and technologies and approaches to and I think it's again an opportunity for synergy and partnership where we can continue to hopefully push the envelope and how to to really expand and extend these genomic phenomic analyses at a larger and larger scale and I'm sure Adam will get into the potential collaborative synergies that have come through your complex trait program but there have been some piloting if you will of this approach of linking the multiple layers of things that are happening at the epigenome the transcriptome and and DNA level even in Framingham work that Dan Levy's done even the space of our hypertension phenotype and looking at the multiple layers of omics to start to identify networks and potential mediators that otherwise we may have missed through any one approach alone taking the system strategy and so we're hoping that the top med can continue to extend this beyond a single cohort but leverage the various cohorts of over 100,000 actually a couple hundred thousand individuals that currently have been characterized and for whom we have a number of these biospecimens within the NHLBI portfolio such that we take advantage of these phenotypes and indeed continue to expand them perhaps with personal sensor data information continue to layer the omics and extend beyond just sort of the genic GWAS genotyping that's already been done for over a decade and continue to use the various modalities inclusive of metabolomics microbiome and other elements in ways that builds out our capacity to characterize the determinants of heart, lung, blood, sleep disorders and then to put this data in a space that promotes greater antelope new antelope methods and approaches and it happens in a space that is again communal in bringing together expertise that might reside clearly outside of heart, lung, blood, speed, sleep specialists and in that regard I was aware of this paper that I thought was apropos of this dialogue with this Institute and actually some of the statements made earlier about how we can work together as we develop these data sets of paper that Isaac Cohane's group put out that related to genetic misdiagnosis and a potential for health disparities in which in the case of hypertrophic cardiopathy one of the entities in our portfolio leaders like cricket Sideman at all have provided a great understanding of in terms of sarcomeric defects that now when that rolls out to patient care that unfortunately often reflects of the sort of skewed distribution and frankly your centric nature of a lot of the studies and genomic resources can be problematic when these data and knowledge are brought to bear in African-American patients and the potential to misclassify something as benign or pathogenic without really the evidence base to do so particularly given again that the different allele frequencies in the very cross various ancestral groups and really I think a call out to us to ensure that as the NIH fulfills this mission to turn discovery science and the health of the nation that we create resources they're reflective of the diversity of our great nation and to be explicit about it that's something we've been fairly intentional about in top mid as we've partnered with genome and a number of the sequencing centers to ensure that we really take this opportunity to expand that diversity of populations in which we we start to understand the whole spectrum of genomic variation and not not solely in some narrow sense of political correctness but as a matter of understanding the human family and understanding population histories and and how those have an influence on predispositions to health and disease I think it's a fundamentally a scientific issue not only a matter of doing the right thing so to speak and so far we've been diligent and and quite frankly leverage the legacy of the HLBI has had of having diverse cohorts where there's Jackson heart study strong heart study of Native Americans the multi-ethnic gross study that has captured these groups as well as the various other investigator initiated cohorts so in addition to that diversity seen on the right we also have one across the various phenotypes of heart lung blood and sleep complex traits and again I think this is where we have a lot of synergistic opportunities with what genome's been doing I'm also hopeful that we we start to think about how we can more effectively promote access to these different data types data elements and data sources to ask and answer fundamental questions typically these multi-dimensional data sets and creating that discovery sandbox where all that can come together it's obviously not a trivial matter but we're we're also hopeful that we can work with genome that quite frankly has created a number of these data resources to think about how we promote and enable and facilitate a more seamless integrative analytical strategy that is less encumbered by what is traditionally been kind of an upload download sort of world of data use and and one that can potentially leverage the capabilities of cloud computing where we move and go to the data go to tools that are accessible and as ways to again promote discovery science in this regard I was again intrigued by this a recent paper I came out of star net but again looked at heart lung blood sleep phenotypes in this case the cardiometabolic risk loci and leveraged not only sort of GWAS data but obviously tissue expression data and did that in a way that aligned the GWAS hits eqtl's with CIS trans regulatory pathways and identification of networks to get some further insights into determinants of certain outcomes and so it is always kind of reaffirming that intuitively it kind of makes sense that you might discover not only loss of function gain of function for PCSK 9 but that there might indeed be energetic regulatory regions that were identified that again are important in modulating LDL and risk and indeed are now drug targets for new therapeutic and so to me these are some of the elements of bringing those data sets seamlessly together I think we could probably facilitate in a more user-friendly way than then currently exists and I'm hoping that a data commons kind of concept helps make that more likely to occur similarly this paper that Eric shot was part of and certainly he presented some of this so when he visit us at our last council meeting talking about the work that he had done on this case in childhood diseases and the notion of resilience and a human knockout resource and as we contemplate top med that can leverage existing cohorts where we're hopeful to have whole genome sequencing with a goal at least a hundred thousand individuals and Eric will talk about or D will talk about PMI of a million plus and we already have colleagues at the VA with MVP that soon will have the kind of information in which we should be able to understand that that same example of a misdiagnosis of all those sarcomeric genes to really know that it was that really benign not just on allele frequency but what's the echo MRI and EKG of that variant of at least perhaps hundred people 150 people over the age of 60 so that when we're you are counseling that individual 25 what's the likelihood that they'll have a long QT and sudden death or hypertrophic cardiomyopathy with a little bit more evidence base and creating that capability as I think something that we'd love to see and work with genome to create and so we're starting to see this notion of bring together these multiple layers and levels of data all of which NIH has already invested in but making it not a series of one-off projects and programs but something that indeed can become synthesized integrated in a seamless digital way such that those who are great phenotypers as well as those who are great genomicists can leverage it in a way that have an impact on patients and participants and it's really with that notion that we look forward to synergies and partnership with NHGRI in helping us fulfill those shared visions and purposes and be happy to address any questions or hear any comments and feedback you may have for us thank you for your attention questions yes thank you for that presentation a number of the issues that you touched on have significant ethical social implications to them one of the innovative aspects of NHGRI has been that set aside for LC research and I'm wondering whether NHLBI has ever considered anything that would be analogous or perhaps collaboration with NHLBI on that set of issues where there's some synergy yeah that's a great point again I agree with you I think that's a terrific opportunity for collaborative synergy particularly given genomes long-track record history domain expertise in that space in the sense that a lot of these things are cross-cutting makes more sense to do that as opposed to a disease or organ basis and we look forward to that top med does include on its external panel actually some of the folks around the this table and you know at that they're in that space whether it's a Wiley Burke or Ellen Clayton and others who are thinking about those so definitely an area of interest of ours and quite frankly in one of the areas that we would love even more interchange relates to one of the cohorts that I mentioned the strong heart study and Native American populations and and so the first nation is is a an area of interest and priority I was intrigued Eric that you talked about some of the outreach efforts you've had in that space I think that's a another area where it makes sense for NIH in a collaborative and joint way in a very coherent single voice way to think about how how we address that very thoughtfully so absolutely totally agree with you there so thank you for the presentation I I really like the the vision and the way you presented this idea of this data sandbox or for mining but I noticed that one of the inputs into that sandbox wasn't information we can learn about the connection between genotype and phenotype and model organisms and how that can actually help inform our understanding of biology of variants in humans both in health and disease and so I'm wondering if that's part of your vision and how you if you want to make any comments on that as well yeah so it's a great point I definitely would agree that that sort of comparative genomic element that evolutionary perspective if you will in some ways is consistent with sort of a population history appreciation of things and I'll defer to another day and really to Eric that I think that's one of the areas that we've been in internal dialogue about clearly genome is played a leading role in a lot of sequencing across species and I agree with you there's a wealth of information there that I think would fit very well within the data comments you should be able to to look at a variant and and we're I don't know an enhancer region and be able to understand it not only across human population but across species in a very seamless sort of way with the phenotypes that they've been derived from a zebrafish as well as from a human being and certainly I think all of that's informative and understanding a molecular pathobiology of disease absolutely Gary I'm really glad that you highlighted that paper from the Harvard group on the hypertrophic cardiomyopathy and this really vicious cycle of having SES lower SES and ethnic background mixed together resulting in less genetic testing less research less information which means therefore it's less useful to them and it's just so I think we have to break that cycle quite deliberately and specifically so I mean for example I'm thinking particularly of a resource like ClinVar which is relying very heavily on clinical laboratory testing which is being paid for and is not open because of how poorly served underserved populations are by our insurance system and by a whole variety of other systems to be able to get access to this testing so I think we have to break the cycle quite specifically and deliberately yeah that's all I could say is amen brother um eric borwinkel on the phone has a question you know it's a great comment and erica you're pretty adept at having multiple ICs that support you so if there's anyone who knows the answer to that question it's you but but in all seriousness I think that's one of the opportunities we have with top med is eric used the term sort of prototype some might call us the canaries in the coal mine that I think we can probe and see how this this model is working obviously eric has done this throughout you know his tenure as did francis that I think in this space it it's only makes sense to do this as partnerships it's been clear from a lot of the queries that you've already had that the potentials are for the synergy with all the other resources that this institute has created so to me it's a no-brainer and and and to a certain extent as you know eric it may derive from the fact that the cohorts also have had that sort of approach so as you're aware NIA and aging and and dementia research leverages these same cohorts same true for kidney disease same for at least the pre-diabetic population that has outcomes as we scale these things I think it becomes almost self-evident that the other ICs need to play in the same sandbox and contribute to its ability to go across it'll be a win-win for everybody and that's where I think the data comments can help promote that as opposed to a series of IC specific one-offs and and that's where I'm hoping I think eric shares this we hope that we can create this as an enterprise approach let me answer I'm going to go to Sharon and then Dan but let me I have a direct question that relates to what there's a lot of ericsson the borewinkle just said and it relates to what dishman is going to talk about this afternoon Gary what I was going to ask and just say answer whatever you're comfortable with because recognize an open session and you and I are both individually recognizing that that how the institutes synergize and connect with this evolving precision medicine initiative is a lot of uncertainty but we're all thinking about it but relating to borewinkle's question do you so there's two parts one what is NHLBI thinking about at the moment how they're going to take a program like top med and synergize it with the precision medicine initiative and then second question is will that be an organizational framework to address what borewinkle just asked with I mean will will that become a place that more institutes will gather to figure out how to do the kind of studies that our institutes are comfortable with and I don't know the answer but I'm just curious you know I thought I both of those questions you know I I think we as both ICs and quite frankly with Eric D in play now in place I think we've at least had some preliminary discussions that PMI as you know was initiated as really a disease agnostic platform and so I think it then and and it's making important advances in that space I think the the it's it's fullest potential I would say though relates to not only be being a disease agnostic platform but being able to link to ICs to ask specific questions that are clearly more phenotypes disease specific so I believe and I have to defer to Eric uh that it'll be the synergies of those that that that will be important and so I agree with you that's on a opportune place of convergence I think for ICs around PMI certainly speaking for the NHLBI it's hard to conceive of health systems coming up with even a half million people where heart-long blood sleep phenotypes aren't going to be very common by definition and so I'm hopeful that there are things quite frankly this institute has done probably with Emerge and some of the others where there are EMR phenotypes that we can do a deep dive on in PMI as it matures that we can ask at a scale that I probably can't do through the community-based cohorts and that I think could complement what we're going to have in top mid so that would be my hope speculation and I think it's a win-win with what Eric Dishman wants to do with PMI. From my perspective a lot of this is just going to be dependent on timing you know I mean the sooner it is that there's things there that we can that the precision medicine issue that we can build a project on people will be there I mean I think people be there in a disease specific way people will be in a technology or fundamental questions we have around genomic medicine implementation a lot's going to depend on what the timing looks like okay so Sharon and then Dan. Thank you for the presentation to just follow up I think on one of the early questions one of the things that NHGRI is now doing is really looking at the return of results of genomic results to a number of subjects in a variety of these different consortia and I was wondering given really the scope of sequencing that's going on funded by NHLBI are some of these projects returning specific results and is there a group looking at that which again could perhaps synergize with some of the NHGRI consortia. Yeah so again another great point one where clear synergy has to happen where again this institute has thought about it long and hard and we'd want to lean in to that domain expertise and understanding I would certainly agree how can I put this that there are opportunities to get a strategy on this that top med brings to the surface you can imagine that was a hodgepodge of studies and cohorts we actually lack a coherent way of doing this and so even though we're generating all this data I'm not so sure that there is a coherence across all those studies and I think again there's an opportunity for NHGRI to provide some trans NIH leadership and helping us do this in a thoughtful way and clearly you guys have been thinking about it for a long time so we look forward to that collaboration. So thank you again Gary for that summary. I guess I have three sort of pretty specific questions just sort of to clarify or to help us think about so how do we can all work together better one is do you have a timeline for when when you know an initial set of results might come out of this because I think the the public is getting a little tired of the promise of genomics and and it would be lovely to and I you know I say that because there's a big investment we all know that there is progress but if you have a timeline for this that was question one the question the second question was among the cohorts that that you've accrued some of which are ours thank you do you have a sense of of how broadly phenotype they are so you know in an ideal world they would have phenotypes beyond heart lung blood and sleep but they would also have cancer phenotypes they would have eye phenotypes they would have mental disease phenotypes and some of them will have some of that and and to the extent that they do that that would be really interesting in terms of the kind of network diagram that you actually showed and then I had a third question I can't remember what it is okay but I think those those are the two are plenty yeah yeah given that both of us are over 50 I'm having trouble remembering your first over 50 that's that's trying to be charitable buddy friend but so two good points the second one first that I'd agree that that obviously these studies started off with a very hyper focus and heart lung blood sleep some of them even more hyper focused than that the the the cohorts over the years have been broad but it shouldn't speak out of school but you know even the cardiovascular ones probably could have thought about lung phenotypes better than they did and and and quite frankly given those are comorbidities some of our lung cohorts could have thought about cardiovascular phenotypes a little bit better in many ways this is an opportunity for us to to to get some greater coherence there as we mentioned with the other ICs to the degree to which they put skin in the game in the cohorts to extend that phenotyping again their synergies that I think they're things we could be doing in dimension indeed we're planning to do in dimension dementia whether Alzheimer's disease per se or related disorders they're already plans afoot to include more pet scanning for example in in our cohorts to to to tap into domain expertise in terms of dementia outcome so I agree with you this presses the issue that we need to extend beyond our classical uh phenotypic uh phenotyping regime um and I've already forgotten your first question was it was a timeline question and my third question yeah I want to avoid was the the top the oh and top med stands for omics but this is mostly genomics right now isn't that or am I not so we're so we're encouraging um trends and and obviously we went with the technology that's you know ripe and ready to go but the intent is actually built in that as um you know ability to characterize DNA methylation continues to expand or any other epigenomic analyses that scale um we're we're interested so so it's already built in that we'll be looking at that and certainly RNA seek is uh to the extent we can extrapolate from blood you know but so so we want to pursue those as the scientific question makes sense absolutely uh timeline is tough um you know um so so when are you going to discover all the variations of you know long qt and and you know it it comes back to you uh about how quick you can discover things obviously we're hoping if we get to 60 000 whole genomes we'll have a sense of you know whether this is a strategy that we double down on or not and that's almost a matter of a pipeline issue and an analysis issue is anything and as you know we have built in a lot of traits already that you'd think should yield us some information in a relative short term that's we're hoping and quite frankly in collaboration with genome Eric it's okay it's public as to what phenotypes you're starting with or no yeah so so yeah so so those are you know cardiovascular you know phenotypes and so I think there's a lot of again uh complementarity uh that we we hopefully will we'll learn some things about certainly the early in my one I'm intrigued on because if we get a non-lippid I you know I'd kiss you Dan uh Gail please change the subject no no I I'm expecting the same response although I can't offer that kind of science but I I do have a question and and I first of all thank you for coming um really interesting um I had a question about when you talk about your cohorts whether they're all already collected and whether they are existing in one space whether they're um the data from them have been deposited in dbGaP or or whether there are some things that so you're gonna you're gonna go back to some of the cohorts and ask for additional permission to do uh you know additional um both data and and genome testing so and so that sorry it seems like a really fundamental question you might have already covered it but you know it is uh important one and actually it does have some challenging nuances to it that um so so all dbGaP um to get into top mid um there was screening of the consents to to to make sure that they were uh pretty compliant and and we actually had a screen out a lot of things that uh wouldn't make the grade but that being said um as you this institute has been exploring um you know the the whole genome sequencing data set and whether that aligns with what was contemplated in a consent you know from 10 years ago even as broad as it may have been it one could make the case that that's something we continually need to think about the consent supposed to be a living process and so I appreciated the LC a component I think those are things we have to continually bring to to bear and so uh we're open and again I think it's a point of collaborative synergy to think about if you start to put this stuff in a cloud um what what do we need to do to to make sure we're doing that responsibly uh and consistent with the participant wishes and consent so I still think there's a lot more to be explored and refined okay I think on the issue of time maybe we'll get Adam Felsenfeld to come to the podium um and in a very complimentary talk that we scheduled deliberately after Gary's to describe the opportunities for synergy between our genome sequencing program and the top med program that you just heard about and again I think at the end of Adam's presentation there'll be more time to talk more specifically about those connections