 So I'm going to make a few comments in the beginning here, and then I'll turn to each of the panelists and see what additional comments and questions they want to have. I think as you'll see that I and a couple of the other panelists, at least, haven't been immersed in the Emerge system. So a lot of what I'm going to present here will be in the form of questions to prop further discussions rather than presenting an alternative view of how things might be done. So next slide, please. So just a couple background comments about what makes children different and why we may want to take particular emphasis on this group of people and obviously health conditions impact on children are different in many respects from adults. Not entirely different. Both suffer from asthma and atopic dermatitis, et cetera, although the diseases may be somewhat different between children and adults. Obviously they need to focus on kids and the health care conditions that affect kids. In addition, obviously, many adult conditions may be secondary, both the genotype and exposure to during childhood years, so there's a need potentially to focus on kids in order to better understand adult onset conditions. A big issue, of course, is that serious health conditions in children are uncommon, and this will get, I hope, to a little bit of discussion about recruitment goals for kids within the system and what would be adequate to study conditions that are less common than things like asthma or ADHD. Kids can be found to be risk for diseases years or decades in the future, presenting, of course, some ethical issues about return results, and obviously children can't consent to participation in research themselves. Older children can ascend an interesting process in and of itself, but obviously they need to engage parents and children in the educational process as well as the return of results process, so giving results to me is different than giving results to me about my child. In certain parents, a parent-child relationship, of course, is considered to be a vulnerable population and a vulnerable relationship to psychosocial impacts. We want to be particularly careful about how we manage this type of information. Next slide, please. So here's a couple of questions. I'm really just keying off Halcyon's presentation under the general category of obstacles to current research. And he has an incongruity between adult and pediatric data sets. Perhaps a need to clarify how pediatric and adult conditions are selected for analysis within the network. But basic question, and I took both comments to suggest that perhaps there's not a need to have overlap here or any increased synthesis of phenotypes that is perfectly appropriate to focus exclusively on kids' conditions and perhaps on adult conditions and overlaps where may be appropriate. This last point really is a broader question. I think the pediatric component is a newer component and this isn't stuff that folks have been enormously productive with this, but perhaps a larger background question is given the rare nature of many pediatric conditions, the need to have a diversity of participants in the network, is the current network large enough with respect to pediatric participants and what are the thoughts about the expansion if it's not over time? Next slide, please. The second downside is the new approaches to existing data, copy number variants, good analytic tools available, and really just reiterating Alkan's presentation here in order to prompt further discussion, doing, in fact, better data on as he stated, frequencies and boundaries of CNVs and database of genomic variation, and can emerge, contribute to data on pathogenicity, is the merged network uniquely placed filling a significant gap about our understanding of CNVs. Next slide. And prospective directions. Again, Alkan's presentation, where he presented the concept of a custom chip with by-spec and clinically relevant and CNVs. I don't know what's the question about is the field ripe for a tool of this sort? How would this impact the nature of the testing and return of results and the other types of issues that the network has been grappling with? Next slide. So a couple of additional questions raised by panelists and some of our interchanges. So this first bullet point really is a reiteration of that question about phenotyping. Now, second bullet, should the merged consortium consider more gene environmental interaction data collection for children? Seems to me to be a particularly important and potentially rich area for this network to explore. What are the opportunities and barriers to collecting those sorts of data for network analysis? Questions about potentially unique issues with pediatric participants? We've got a couple of panels on informed consent and return of results. I think some obviously specific focus at the extent that these issues are somewhat different within families and within pediatric patients, adolescent patients, et cetera. Return of results for the onset conditions. Results on certain clinical. Significance external findings we've got quite a bit about. And this issue of when parents are analyzed or sequenced in order to better clarify child's results. What are the issues that arise when the analysis extends to family members in this way? I think my last slide. So other general questions that came up. And I think there was a reference to this a little bit earlier today. So real opportunity for emergency potentially to work together with the newborn screening sequencing projects and the mutually supported there. And so I'd be interested in a little more information about what's anticipated in that regard. And then are there target conditions for genomic analysis that may have early clinical utility in health care of children? It was a question that came up. And I think part of this, part of the implication is that we're perhaps still looking for an additional proof of principle example. Where's the lower hanging fruit in the domain of health care of children that might be a significant focus here to demonstrate the utility of the approach being used within a network. So I'm going to stop there. And then what I'm going to do is run through our list of panelists and see whether they have additional comments or questions. So I'll start with John Harley. We collect a sense at the age of 13. And at the age of 18, we send a notice to participants in research studies about whether they would, now that they're considered adults, whether they would wish to continue their participation or not. If we don't get an answer from them, we leave it the way it is. If we get an answer from them, we respond to the extent that we can to follow their wishes. And so that seems to be a fairly, the institution as a whole seems to be pretty comfortable with this approach. And I think it's fairly standard across the pediatric research institution to do it this way. How could have presented a lot of interesting discovery, which impresses me that there's a goal to be mined left in all the work that's gone into doing the GWASs and that we should not ignore that. And there's a wonderful opportunity there. And it is an incredible database that will yield for years to come. The pediatric group has one of the best opportunities for finding the outliers that you were talking about before and the outlier in doing outlier analysis, especially for sequencing, the severe phenotypes of children presenting with adult diseases early in life generally has a much higher genetic load and would expect to be a very high yield small group, large odds ratio kind of ascertainment group with which to work. And that seems to be a great opportunity for us. There are lots of issues with integrating the pediatric late comers to the adult world of Emerge. And I personally had resisted the idea of having a pediatric work group that was separate because it would force us to integrate better. And as a consequence, I'm now chair of the pediatric work group. And we have this tendency to reproduce everything that the adult side does. Every little issue that comes up is considered from the perspective of pediatrics. And then we end up duplicating the work without forcing ourselves on the adult side in a way that also encourages the adult side to come our direction. So that's an issue that will probably continue, but we will continue to remind the adults that we're here and that it's an important piece of how we go forward and that the pediatric groups offer some incredible opportunities. I mean, childhood obesity is rampant. It's almost a public health crisis. Asthma is increasing in frequency and involves millions and millions of children and people at this point. Bad allergies are a huge problem in the pediatric population. We have a different concentration of illnesses, but many of them just linger into the adult world pretty easily. And so we'll find phenotypes that cut across and take maximum advantage. And then we'll also do phenotypes that are pediatric oriented. There was talk earlier about the trouble with using opiates. And there's a huge problem with this fetal syndrome from children with mothers who are addicts of opiates. And so those children live in our intensive care units and cost billions. And understanding how they respond and can recover from these things is really important. On the other hand, there's never been a GWAS of any kind done with appendicitis, which has a, what, 50% mortality rate and is only cured by moderate surgery. Well, it's less untreated. It's less untreated. And that's what history is all about. And that's what history is all about. 100 years ago. If you're going to do an appendectomy in 30 seconds, you know, you were pretty much dead. And so there's lots of interesting ways to interact and forward. I appreciate how you learned the trouble of putting all that together from our perspective. John, this is Jeff. Let me clarify with you what you had mentioned about the, when you send a notice out to families now adults of kids who have been enrolled and you don't get a response. How does the, what's the network doing here? We leave it alone. We've tried to reach it. We made a good effort. And they stay in the system. We continue using their information and data into their adulthood. Do you consider them consented or just not opted out? And what are the implications for the use of the data there? So we consider them still usable, whatever you want to call that in terms of the language you'd like to use. They're not thrown out. No, no active, no active step was taken to eliminate them. And so you wouldn't, you might not re-contact them as an act, as a consented participant. Yeah, we can't reach them. So re-contacting them for consent for something else is not, is not an issue. Not an issue. Not an issue. So on the, on the top side we re-contact everyone who turns 18. Maybe a success rate there is about 30%, but the other 30, 35, the other 65, basically their data stay in the database, but nothing new gets added, but it gets just the identified and stays there in the same way as we had it when it turned 18. Okay. Good. We have the same thing at St. Jude. If you, if we can't confirm that the patient wants to stay a subject after the age of majority, then they have to be dropped from the study. So it's quite different. Well, let me delay further conversation on that point, which I think is quite important to finish up with our panelists here and then get back to that discussion. So, Tracy? Yeah, thank you. First of all, I want to thank the Emerge Group for asking me to be part of this. It was a very interesting day. I understood, Sonoma, what you had to say and enjoyed learning about it. Appreciate my fellow panel members' efforts. Bob, I think Jeff emerged my comments into his slides perfectly, so I won't take up any more time at the end of the day here, but I will say I feel like Emerge as an entity is uniquely positioned to lead this translation of genomic information into pediatrics. It will be harder. We've talked about all the barriers that make it a little more difficult, but I think I'm excited about what I hear going on. I look forward to any or all clinical decision support tools showing up on my PC at the office and look forward to ordering that custom emergency chip on the newborns. So, I'm excited about what we're going. I think my comment has already been included and I look forward to other people's thoughts. Great, thanks, Tracy. Cynthia? Yes, hi. Can you hear me okay? Hello? Yep, yep, yep, gotcha. This is Cindy Powell from UNC and I'm a clinical geneticist and a pediatrician and I'm also one of the PIs here on our newborn screening for the whole exome sequencing study. So, I certainly think that to answer one of Jeff's questions that there's a great opportunity for Emerge and our U-19 projects to share information. I think that one of the things that probably applies in some of the areas, the other areas discussed today and the return of results is the FDA oversight and although I think we may be one of the sort of guinea pigs for this, but the FDA is asking us to submit sort of a pre-application to determine whether we need an investigational device exemption for our study in preliminary discussions with the FDA where it seems that it revolves around return of results that are obtained through research, you know, whole genome sequencing and, you know, if they're approved in a CLIA lab that likely will be okay, but I think, you know, that the jury's still out and we're waiting to find out, you know, how this is going to work. I think going forward this certainly can add, you know, cost, time to many of the research projects that are going to use next-gen sequencing. In thinking about some of the areas of study, I've heard a lot about, you know, what we think about the common disorders of childhood with obesity and asthma, autism already mentioned, but also I'd like people to consider birth defects. Certainly as a group, you know, one of the primary conditions of childhood and whether there would be some way to use the eMERGE network to look and gather, you know, more data, whether it's GWAS or sequencing data about birth defects and, you know, thinking about the National Birth Defects Project and the CDC, I think, you know, they're gathering DNA samples on patients that are being ascertained and getting a lot of great clinical information, but, you know, would probably welcome more next-generation sequencing studies of these patients and, you know, utilizing their registry. I think, you know, one thing is that the return of results, I think, is different when one thinks about the age group, and although, you know, there's a lot of overlap with incidental findings that would be, you know, considered for both an adult and a pediatric patient, I think we need to think carefully about the pediatric age group and going forward with this. You know, like Heidi described for the Boston group, you know, we have a group at UNC that's looking at return of results, not only for our adult patient population, research subject population, but also in pediatrics. And there's definitely a lot of differences. And I think, you know, we need to think carefully about how we're going to, you know, use the data, but yet, you know, if there's certain conditions, for example, conditions that we wouldn't want to return to parents of a child, let's say, you know, if we're talking about Alzheimer's, but in the future should a treatment, you know, be found that's beneficial that potentially could start at a young age or at least in early adulthood, we'd want some method to go back and, you know, obtain that information and return that information to families. And the other thing that I just wanted to comment on is, you know, in pediatrics, although we think of the child as a patient, we are evolving to more family-centered care. And I think, you know, going forward, you know, thinking about how this family-centered care in the genomic age can be utilized and considered. And such as, you know, if there's a condition that's identified in a child, such as an autosomal dominant condition, likely one of the parents has it and whether, you know, putting those results into the parent's EHR would be, you know, beneficial and how one would go about doing that. So that's all I have. Thanks. Excellent. Thank you. All right. I wanted to, you know, I guess about seven minutes or so. I wanted to pick up on at least two points and then open it up for whatever else folks have to say. I wanted to get back to this question of re-consenting kids once they reach the age of majority. And I believe what OHRPists have to say about that is that re-consent's appropriate if the sample or data is still subject to ongoing research. But if you can get a waiver of consent if the ongoing research is considered, it meets the criteria for a waiver. Or, of course, you can de-identify the information. But my guess would be in this context, the identification, since you're linking this to an electronic medical record, would not be considered feasible. But maybe that's a question rather than a statement. Other thoughts on that issue? We have an I2V2 system that we have de-identified patient records that are available for non-human subject research in our institution for any faculty member that wants to explore those data. Now, in the narrative portion, cleaning that part is a subject of ongoing concern, but we have enormous amounts of data, a million records. I think Boston has almost two million records. And I don't... CHOP's situation is similar. So we have lots of de-identified data that we can link to genomic data and have it all be de-identified. Well, so, but actually, I mean, it speaks a little bit sort of naïve as if de-identification was a static property and it's lack of light and stuff. Exactly. De-identification. Yeah. And so what we know is that, you know, biologic data, non-genomic data is so inherently rich in attributes that even if it's de-identified, re-identification risk never goes to zero, so the residual risk needs to be controlled with policy. And obviously, there's a whole large working group that pediatrics will grow to know and love as far as eMERGE that's looking at quantitative de-identification science. But I do think the notion of... that in the informatics community, that the idea that de-identification is a safe wall that you can hide behind is gone now and you just have to deal with non-zero re-identification risks in any of these classes of data. So this is Larry. I'll play devil's advocate just a little bit. It seems to me that the entire focus of eMERGE is to use existing electronic medical records to make large-scale genomes possible. And I agree strongly that diseases of children are worth studying and that in fact that diseases of adult diseases which have their onset and childhood are more likely genetic. But one of the attributes of the eMERGE system is that you can identify 18 and 20-year-old one-year-old that have the disease when they were 10 and you can get their DNA now. So why do you need to go and collect DNA on all of these five-year-old continuum? Now newborn screening, I think, is a very different thing than old newborn screening. And probably the pharmacogenomics because little kids are not just small at all. And so if you want to get the biological correlates, you need that. But for many of the disease, severe atopic dermatitis, pediatric onset, psoriasis, why not just go out and find people that had it 10 years ago? And I am playing devil's advocate. I do not fully think that obesity, I mean, come on, you have records. You can go back 20 years and find kids who were obese and three-years-old. But phenotyping them and the child, you don't have to, you know, phenotyping your records back. Yeah. He's part of the medical records. So I think they're part of the medical system. Well, he's an adult. Yeah, so that is the other piece of it, is that we're all in pediatric hospitals. And then they go on and something like that. So coming back to, you know, I have children and there's a breakdown. So somebody has a breakdown. Identify how do I go to children and get the medical records? If people are in the system that's longitude, they'll like, nice and different. That's a good example. But isn't the idea of the consortium to use electronic medical records for your phenotyping and not go out and lay a child? But the thing is, if you get those, if you go to a different institution to get the medical records, that's a big piece of the problem. Imagine you're at the VA. Imagine the VA with 85-year-olds trying to get, in 50 years, electronic medical records from their childhood. Yeah. Well, we're trying from the DOD and I'm going on for it. Or perhaps the more provocative notion in the era of telomere shortening that your, that the common wisdom of ecstatic genomic compliments that you keep from a childhood is, in fact, completely wrong. And it's really quite dynamic. So, samples are required. If you have an institution, you're enriched for a lot of children who have a lot of diseases and picking them out of all of the health, I think it's much harder to do. I think it's a lot of very practical issues for picking the children. So you're imagining that all those children stay fat, you know? And there's a lot of change between the age of three and the amount of obesity and the age of 21. A lot of those kids will get skinny. The point is, you can't study them if you're ascertaining on being fat. But no, you ascertain them on fat at age three. Oh, how do you do that as an adult? What are you going to get that information that people don't remember? You've got to be a walk up every week. You use state stamp sign records at the time of service when they measure them. But I think the point of those records is to go way, way back. And we can identify some individuals who are, for example, in our biobank team, that were obese children, right? Okay. But our average age is something like 52 or something like that now. So even if we go back 30 years, we're not covering that. So you're saying you can't do it a week without the sample bus? No, it's not. It's electronic. If your adult VHRs ask you work, you'll fat three-year-olds. So maybe we need to... Thank you for the provocative question. We've got a few more minutes for this panel. So are there other issues that we want to address? I think if you're going to think about research studies, then that might be the case that you can ascertain adults who are fat when they're younger. But if you're going to talk about clinical utility of any of this, the pediatric age population is the time that you want to intervene. I have an off-the-subject issue that we have the opportunity to bring to the clinic new technologies that haven't really made it to clinical utility in the way that we imagine they will in the future, like methylation. There are three patterns that you talk about that are going to be substantially different in adults, and those methylation patterns are partially inheritable. You can tell if your grandmother spoke from your own methylation pattern from a population basis. And so I think there are genomic technologies that we have not applied yet in a merge that will obviously be so every promise is becoming clinically important and we should prepare ourselves for being able to apply those when the research shows that they are clinically relevant like methylation patterns. Is that where the merge should develop? I think it's one of the places we should prepare ourselves to take advantage of that for specific clinical issues when the research supports the methylation patterns interacting with the genes we have is an obvious way of leveraging the GWAS studies that we've already done. Okay. So we're now at the stage. I just want to be sure, Jeff Baikin, did you have anything else that you wanted to comment on in the pediatric panel? Nope. I'll finish. Thanks very much. Great. Thank you.