 Thank you. So if you could go to the next slide, I wanted to thank people who contributed to this presentation. My co-chair, Gail Jarvik, great input from the panel members, Larry, Susan and Lisa, I would like to thank them. And I also got some input from the Return of Results Working Group, which the members are listed here. So I'm just going to briefly tell you about the evolution of ROR in Emerge and then talk about some future directions. So next slide, please. And next, I think in the initial Return of Results deliberations in phase one, obviously the unique thing was Return of Results in the context of the EHR, and this group kind of summarized its recommendations in this paper in genetics and medicine, looking at return of results that may vary in the context of each site or other factors such as age, highlighting the importance of the need to generate evidence of clinical validity and actionability before returning results, what are the appropriate methods of return of results, and the need to obtain opinion across diverse sites and also input from lay community and advisory bodies. So this group kind of started the process. Next slide, please. And then in phase two, there was clearly a focus towards implementation, and this is being done in site-specific projects at each site and also at network projects. And this is just not a full but partial listing of the Genomic Medicine Pilot Projects that are being undertaken just to show you the favor of these pilots. Some are including genetic risk scores, for example, for macular degeneration or for myocardial infarction. Others are using just single SNPs, a PoL1, for example, or HFE, or Pact-5-Lyden. Geisinger is doing a study of whole genome sequencing in trios for diagnostic odyssey. And then several of the pediatric sites are looking at returning CIP-2D6 or hypothetical CIP-2D6 results to patients or parents. Next slide, please. So this is an example of an EHR-based Genomic Medicine Pilot study. Myocardial infarction is a leading killer of people in the United States. It often presents a sudden death. We do very poorly with conventional risk factors for predicting myocardial infarction. So the population implications are huge. And if there's any way, any way, however modest, but we can improve the ability to refine risk stratification, that is huge implications. And therefore, we are conducting this pilot study for the myocardial infarction gene study of giving patients a genetic risk score based on 28 steps that are related to susceptibility, versus just giving them conventional risk factor information. And this is communicated by a genetic counselor using the electronic medical record. And they follow up with an MD visit and then we assess them at three and six months for end points such as LDL cholesterol, weight, activity, diet changes, and also some other assessment of how patients understand these results and what they do based on these results. Next slide, please. And these are a few examples of network-wide projects. You heard a lot about eMERGE-PGX. I won't go into that. We are trying to assess the phenotypic correlates of copy number variation and even larger chromosomal abnormalities, what the phenotypic correlates on the medical record. And this was already highlighted, the project to look at hemocomotorcyl variants. It illustrates the power of eMERGE in that we have a total of 1459 individuals across the network that have one or the other of these variants. And so we can look at theotropian phenogens. Next slide, please. Next. And so for return of results, there's a perfect storm in a way because there's been so much investment by institutions and by repositories. And this has coincided with the HITECH Act and the need to implement electronic medical records. And then the remarkable advances in genome sequencing. So all of these factors are really going to throw at us for the next many years the issue of return of results. Next slide, please. And so unique, the eMERGE network is uniquely a place to address some of these issues, not only in the context of genomic discovery, which we already discussed, the many questions we can answer in terms of theotropy or longitudinal phenotypes, but also in implementing genomics in the electronic medical record, whether it's storing the data, visualizing it, linking it to decision support, dealing with incidental findings, reinterpretation, looking at outcomes. And then these kind of somehow merge together in the learning EHR paradigm that was alluded to earlier. And so I think eMERGE is uniquely positioned to do both the discovery implementation and some of the aspects that are in between these two paradigms. Next slide, please. And in the context of discovery, I think this is a huge area. I can't really summarize it in one slide, but in the context of the EHR, the questions were already discussed in the previous presentations. Documentation, the EHR, communication to family members, the unique problems in the pediatric setting for water patient preferences, what about consent, the mechanism and timing of ROR, the incidental findings. So all of these are important questions. And together with CISA consortium, we've had some initial deliberations, and Gail is leading an effort to summarize some of these recommendations in a manuscript that is very complete. Next slide, please. In the context of implementation, obviously there's a question of what could be returned. And you could think of it as listed there, or in the pinning paradigm, so just by Bergen colleagues we could return copy number variation, recessive mutations, single nucleotide variants that are relevant to disease susceptibility, or pharmacogenomics, or genetic risk scores, as you mentioned. And then, of course, the whole issue of sequencing and what comes out of sequencing, actionable variants, as well as incidental findings. Sequencing can be genome-wide or like some are targeted. There's a fair bit of effort then to ascertain the clinical validity of these findings. And so a jury concept where medical experts and others decide on that aspect, the need for this to be clear, certified if it's going to be in the medical record. And sometimes you will also need to resort to statistical modeling to really create the correct statistic for what the genetic variant or the collection of variants implies for risk. And this has to be integrated in the EHR, and then we have to deal with the LC issues. And some of the legal aspects that were highlighted were actually summarized in the paper we wrote in the EHR team issue, and I would refer panelists to that manuscript. The question of storage and reinterpretation, again, very important when we are looking at in the context of implementation and the clinical decision support issues, as well as then trying to assess outcomes of all of this effort, perhaps initially just as implementation outcome, but of course longer term in real clinical outcomes as to that our patients sent checks. Next slide, please. And so these are some ideas that were thrown around for developing a framework where we could assess some of these challenges. For example, let's talk about whole genome or whole exome sequencing, as Debbie mentioned. And the unique aspects would be the multiple phenotypes that we could look at to correlate with this data, the issues of penetrance, pleotropy, pediatric considerations, pathogenicity, all of these emerge, could uniquely address. We could think about targeted sequencing. This could be of the 56 ACMG genes. Again, issues related to pathogenicity, informing kin, et cetera. There's this very widely used genetic testing in the clinics, which is usually doing candidate gene panels. For example, at our institution, we do a whole lot in terms of cardiomyopathy, hypertrophic or dilated. We talk about aneurysms, aortic aneurysm, syndromes, sudden death syndromes, pediatric syndromes. So these are often very expensive data, months to come back, and there's perhaps an error where eMERGE could contribute in focused genomic medicine pilot projects. And of course, we shouldn't forget high-density genotyping, which has been our forte for eMERGE. And many of the sites not only have common variants, but also with more affordable rare variant chips. There's a fair bit of data on rare variants as well. So correlating these to eMERGE to write phenotypes would be quite useful. Next slide, please. And I think I'm going to quickly go with these, because these were very nicely discussed. Within the framework of EHR implementation, we have to address participant privacy and potential vulnerability to adverse social consequences, and therefore appropriate consent to include genomic data in the EHR. It has to be there. We discuss recontact to ascertain preferences over time, and how this could be done electronically, I think is again an area of ripe for investigation. Next slide. And we, of course, need to learn more about how stakeholders perceive all of this activity, whether they are patients, parents, guardians, family members, career providers, laboratorians, investigators, or biorepository scientists. Next slide, please. And I would submit that the eMERGE consortium as a whole, and with it, eMERGE, the ROR Working Group, really is the final transducer of many of these activities for us than to be at the leading edge of implementing genomics, whether we interact with payers or regulatory bodies with ACMG or EGAP, with other energy or activities, such as ClinGen, ROR, or CSER, and with other entities that are looking at making genomic information scalable, machine readable, and thereby can be integrated into the medical record. So I think we have a unique potential strategically positioned in this area. And my last slide is to summarize the unique features of eMERGE to address these knowledge gaps and challenges, the linkage to EHR with deep and diverse genotypes, the diversity of clinical settings and electronic medical records, the diversity of genomic information ranging from sequencing to high density genotypes, the ability to look at best practices for implementation, and finally a cohort at this point of more than 50,000 that includes pediatric patients. So I'm going to stop there. Larry, you can continue even with the same microphone. Thank you.