 Good afternoon, everyone. My name is Erin Ramos, the Deputy Director of the Division of Genomic Medicine at the National Human Genome Research Institute. We wanted to thank all of you for joining us today. We are excited to provide you some information regarding the multiomics for health and disease program. In a moment, I'll introduce my colleagues. But first, I wanted to walk through the agenda with you. So I'll just quickly review the participation guidelines. And then I will turn it over to my colleague, Dr. Joannella Morales, who's a program director in the Division of Genomic Medicine at NHGRI to provide more specifics on each of the three components of this program. Within that presentation, we'll also hear from our colleagues, doctors, Kim McAllister and Leah McCannick from the National Institute of Environmental Health Sciences and the National Cancer Institute, given they're both co-sponsoring this program. We will ask Joannella to provide a few answers to some of the most common FAQs we've already received, and then we'll open it up for additional dialogue Q&A through the Q&A feature of our Zoom webinar. Next slide, please. So just a reminder, this was on the screen when you joined. We do have a large number of participants with us. Your video and audio are turned off by default. In fact, because of the number of participants, we are going to use the Q&A function primarily. So we'll do our best to collect all your questions, respond to them live. If it's possible, I'm sorry, if we need to provide any follow-up information, we'll make sure to do that. We'll update the FAQ. Those will be posted on the NHGRI website. The webinar itself will actually be recorded as well. And then if you have any specific follow-up questions, you can always reach out to us. The email address for the Multiomics team is listed on this PowerPoint slide. And we would ask if you have nuanced questions about your particular study, perhaps those might be best addressed via an email, but we're looking forward to responding to as many general questions as possible today. Next. So again, this is our NIH Multiomics program team. My colleagues at NHGRI have joined us today, Joti Dayal, Iman Martin, as I mentioned, Joanne Ella Morales, myself, Aaron Ramos, and Riley Wilson. And NCI, we have Leah McCannick and Melissa Rotuno, and NIHS, Kim McAllister. And before we get any further, I really wanted to thank our colleagues with the AVN communications team for setting up the webinar and the website and for doing the post-production processing as well. So a big thank you to Gerald Simani, Makul Underooker, Alvaro Encinas, and William May. So now I'll turn it over to Dr. Morales for her presentation. Thank you. Thank you, Erin, for giving me the opportunity to provide a little bit more detail about the Multiomics program and the funding opportunity announcements that we published earlier this month. As Erin noted, I will start by providing some relevant background and rationale for this program, and then focus on some of the key aspects of the consortium. So a little bit of background, as most of you are no doubt aware, recent advances in high throughput technologies over the years have led to increased access to distinct molecular data types, or omics data, and some of which are noted here, genomics, epigenomics, transcriptomics, proteomics, and metabolomics. And the funding opportunity announcements we are discussing today are focused on multi-omics, which we are defining here as a systems biology approach, where the focus is on the biological system as a whole, where the multiple omic data types are of interest, and the expectation is that the integration of all these data types will provide insights that go beyond what each single omic type alone can produce. Now the systems biology approach also implies a comprehensive assessment of the biological system, whether that's an individual, a tissue or a cell, including the environmental exposures to which it is subject. Now this of course requires a use of high throughput technologies, and that generates a huge amount of data or so-called big data. So multi-omics integration has been shown to be particularly useful in a number of areas, including the ones that I've listed here. For example, to improve the way disease subtypes are defined, or to identify more precise biomarkers than the ones identified by single omics approaches, or to define relationships between data types. And while successes have been recorded in the literature, opportunities do remain to maximize the benefits of multi-omics approaches. For example, computational methods to integrate multiple omic data types with other data types, for example clinical and environmental exposure data are still underdeveloped. So the RFAs that we are discussing today aim to provide opportunities to move the field forward in this scientific area. Now the overarching goal of this program is to validate and enhance generalizable multi-omic approaches to identify meaningful biological changes related to health and disease. And this will be done by establishing a consortium that will bring together experts to apply multi-omics approaches in several disease contexts. And now these experts will first explore the use of multi-omics to detect and assess molecular profiles that are associated with healthy and disease states. They will then leverage these exploratory studies to develop generalizable data harmonization, integration and analysis methods, best practices and standards. And finally, using all the data that is generated in the program, the consortium will create a multi-dimensional data set along with a visualization portal that will be available to the wider research community and will be interoperable with existing resources. As we note in the RFAs, the multi-omics for health and disease consortium is composed of three components. First are the disease study sites, which we have outlined in RFA HG 22008, and we intend to fund up to six disease study sites. The second component is the omics production center or centers, which we have outlined in RFA HG 22009, and we intend to fund no more than two OPCs. And finally, the data analysis and coordination center or DAC, and we outline the DAC in RFA HG 220010, and we intend to fund one DAC. Now the three components will form a steering committee for governance and working groups to carry out the work of the consortium. I will now go in and describe key aspects of each component in a bit more detail. And just as a reminder, I'm providing an overview here, but you can find obviously more details in the RFAs. And as Erin noted at the end of this presentation, there will be an opportunity to ask questions. Okay, so let's talk about the disease study sites or DSSs. And as I just noted, we intend to fund up to six DSSs, and we expect that each DSS would propose a study focus on a disease area where there is evidence that an integrative multi-omics approach would be particularly impactful. For example, that it would help to define molecular profiles associated with healthy and disease states, and that would detect changes to these profiles over time. The proposed study should also be able to detect aspects of disease progression within the five-year timeframe of this program. So, for example, to detect change from one state to the other or transitions across state states. And some examples we highlighted in the RFA include diseases with clear distinct stages. For example, relapsing diseases with exacerbations and remissions, or diseases with distinct stages or transitions, and diseases where a strong environmental component can be measured within the timeframe of the program. Each DSS should demonstrate the ability to enroll a minimum of 300 participants, so 200 participants with disease and 100 generally healthy participants. Each DSS should also ensure that at least 75% of the enrolled participants are from self-identified racial and or ethnic communities that are expected to have genetic ancestry currently understudied in genomics research. We expect the DSS is to follow appropriate recruitment retention and community engagement strategies and processes, and to obtain broad data sharing consent for the collection of multiple measures from multiple omics data types taken at multiple time points. Now, each DSS will be responsible for collecting phenotypic and environmental exposure data, including social determinants of health, and using standard measures when those are available. Each DSS will also be responsible for collecting bio specimens at a minimum of three time points, for example, at baseline levels or at any of the disease states. Samples can be obtained using non-invasive methods, for example, blood, urine, or saliva, though if suitable for the disease that is being proposed, tissue or biopsy samples may be appropriate. Now the disease study sites should budget for the management of the bio samples, including the cost for submitting the samples to the omics production centers, which I will describe in a couple of minutes. Now, while the omics production centers will take place at the, sorry, while the omic, the production of omics data will be, will take place at the omics production centers. Each DSS is expected to propose omics technologies and assays to be applied considering the unique characteristics of the disease that is being proposed. Now, in terms of analysis and methods development, each DSS should propose technological and computational analytical protocols that are appropriate again for the disease that is being proposed, and the omics technologies that also are being proposed as part of the study design. So, each DSS should also propose methodological approaches to address some of the challenges that we aim to address with this consortium related to the application of multi omics technologies. And finally, each DSS will need to demonstrate that the approaches and methods that are proposed to be utilized or will be developed should be generalizable across ancestrally diverse populations. Okay, so now let's move on to the second component of the consortium. These are the omics production centers. And as the name implies, the role of the OPCs is to utilize state of the art high throughput technologies to produce omics data from the samples, including the tissues and cells as needed that are collected by the six DSSes that I described previously. The samples, the FOAs, or so this FOA is targeting the five omics data types that are listed here, genomics, epigenomics, transcriptomics, proteomics and metabolomics. And the second and third columns outline the expected data and the typical assays for each omic data type respectively. Now, while the data types and assays listed here are definitely relevant for for this FOA, there is some flexibility for the OPCs to be innovative and suggest other omes or assays provided that the data production can be made within the allocated budget for the OPCs. Now, also noted in the RFA is our preference to fund one omics production center that would receive the samples from all six DSSes and produce the five omics data types that are that were I listed in the previous slide. Noting of course that there will be recurrent cycles of omic production since the DSSes will be collecting bio samples at more than one time point. So I recognize that it may be challenging to assemble a team with a capability and expertise to produce all data types and so for this reason we are allowing applicants to propose fewer than five omics data types with some caveats a minimum of three. So one of the omic data types must be proposed of those one must be genomics and one must be non nucleic acid, for example, non nucleic acid based, for example proteomics or metabolomics. In such scenarios, we would consider then funding to OPCs and hopefully achieve the goal of producing all the data types that we're hoping for this RFA. And each OPC, of course, would be responsible for proposing a plan for how it will receive the samples and how they will perform the assets. Now, similar to the DSSes each OPC should propose technological and computational protocols appropriate for the omics technologies that are being proposed in the application. Again, each OPC should also propose methodological approaches to address some of the challenges that I've mentioned previously related to the application of multi omics to study health and disease. And again, each OPC will need to demonstrate that these approaches are generalizable across ancestrally diverse populations. So moving on to the third and final component, the data analysis and coordination center. And as the name suggests this center will coordinate consortium activities and logistics including a year long consortium wide protocol development process, collaborative data analysis efforts, the joint development and optimization methods, the use of anvil workspaces, and it will perform outreach for the consortium and finally produce a user friendly website to highlight the products of the consortium. And it will be also responsible for for facilitating the submission of consortium data to the ample platform that means that it will facilitate defining the submission process, also defining the data standards and data model that will be utilized, and finally validating that all consortium data is is is following those data standards and models prior to submission. The DAC is also responsible for creating the multi dimensional data set that will be released by the consortium. And here I have highlighted the characteristics of the data set. And so the DAC is responsible for ensuring that the data set includes all of the components listed here. The DAC will also liaise with the anvil. The DAC will also make sure that novel and previously known variant interpretations are submitted to ClinVar and creating that open access online data resource to share summary level data from the program. Okay, so hopefully that has given you a good overview of each component. And so now I will briefly talk about consortium wide activities. In order for the goals of this program to be achieved, we require a high degree of coordination and collaboration. And so for this reason, the consortium will devote its first year to developing network wide protocols, some of listed here for the key aspects of the work and I've listed some here community engagement approaches recruitment strategies, the plan for the collection of measures of phenotypic and environmental exposure measures, how to process and procure what omics assays will be will be performed the methodology the data models, and finally the plan for utilizing the anvil platform and as I've mentioned before the DAC is responsible for facilitating this process. The analysis of the data and the development of methods is also a cross consortium activity. So the consortium will aim to carry out the analysis that I have listed here so integrating data defining profiles detecting changes, identifying networks, and so forth. And I mentioned earlier but working groups will be established to facilitate all the collaborative work that we envision as part of this consortium. In terms of the timeline. I've mentioned that the first year will be focused on developing the network wide protocols. Year two of the program will be devoted to the enrollment of participants, the collection of measures of baseline measures, and the collection of bio samples that will be then submitted to the OPCs. During years three and four the consortium will collect subsequent measures, the subsequent bio samples, it will focus strongly on the analysis of data and the development of methods and start the process of standardizing and harmonizing the data that has already been produced. And then finally in year five, the consortium will work towards finalizing all the analyses, starting to create that data set that will be released towards the end of the program, and developing that portal and disseminating outputs and findings. In terms of governance, a steering committee will be the main body that will govern the consortium, it will guide the overall direction, scientific direction, and it will be composed of the PIs from the, all the sites and centers as well as NIH program staff. As noted earlier, working groups will be created to facilitate collaborative work. And finally, an external scientific panel will be created to provide input on performance priorities and overall progress. Now, one important area for this consortium is diversity. And as you're aware, there is an overrepresentation of European ancestry, individuals and genomics research. And of course there are scientific, social and ethical challenges that are associated with this. Also importantly, there is a lack of diversity in terms of the genomics workforce. So this set of RF phase, this program aims to address both of these concerns. So to increase the diversity of genetic ancestries, this program expects that 75% of individuals enrolled by each DSS should be from racial and or ethnic communities expected to have genetic ancestries that are understudied in genomics. And to enhance the excellence and inclusivity of the research environment, we expect all sites and centers to assemble study teams that are diverse, and to provide full opportunity and participation to individuals and groups that are underrepresented in genomics workforce, in the genomics workforce. Now let me say a few words about the anvil ecosystem. We expect the data analysis and the methods development to be performed using cloud-based approaches within the anvil. Now anvil stands for analysis, visualization and informatics lab, lab space. It is an NHGRI designated data repository that provides a cloud-based infrastructure and a secure environment for data storage and for analysis. So using the anvil platform will allow the analysis by each site and center, as well as allowing for that collaborative analysis and the development of methods that we are expecting as part of this program. And again, because the DAC will be responsible for managing the collaborative efforts, the anvil allows for the DAC to be able to manage all the data. Now here's a hypothetical diagram of how the consortium could interact with the anvil ecosystem. For example, each site and center could have a private workspace for data analysis and methods development, but shown here in purple there would also be a shared workspace that would be set up for creating that data set that will be released and for any joint efforts that need to be performed as part of the program. Let me say briefly that this program is expected to be in compliance with NIH's genomic data sharing policy. So we expect all applicants to provide a data sharing plan in the resource sharing plan. We expect that applicants will plan for data to be submitted in the appropriate repositories, so anvil for all controlled access data and ClinVar for varying interpretations. We expect that applicants would ensure appropriate consent that appropriate consent is obtained, so general research use for future research use and broad data sharing, and also to share comprehensive metadata and phenotypic clinical and environmental exposure data. So if you want to know a little bit more about this, you can go to the RFA's or you can go to the websites that are listed at the bottom of this slide. And now I would like to invite my colleague Kim McAllister from the National Institutes of Environmental Health Sciences to talk a little bit more about the interest of her institute. Kim. Thanks. Well, good afternoon everyone. I am Kim Calster and I'm from the National Institutes of Environmental Health Sciences. And I think many of you probably already know that this institute is interested in studying many different toxins and chemicals that have an impact on disease. And we do recognize that a lot of environmental exposures not just affect onset of disease, but severity and progression of different disease outcomes as well. So we were really excited to be joining this new consortium effort because we really recognized for a long time that there's a real gap in methods and approaches and guidance for how to integrate a lot of different diverse environmental data with other omics data. And so we're hoping that some exciting innovative methods and approaches related to harmonizing and integrating complex environmental health data with other omics will really come out of this consortium. And you also may know that NIH has has a long strong mystery of community engagement, especially in relation to exploring environmental health disparities and environmental justice issues. And so the strong focus on underrepresented groups in this consortium, therefore really fit with our interest as well. So please just reach out to me if you have questions related to putting in an application for these RFAs that has an environmental exposure component to it. Thank you. Thanks, Kim. And now I would like to invite my colleague Leah mechanic from the NCI to talk a little bit more about NCI's interests. Great. Thank you, John Ella. So hi, I'm Leah mechanic. I'm from the National Cancer Institute. I'm here with my colleague, Melissa rotuno, and we are program directors in the division of cancer control and population sciences. The NCI supports cancer research to advance scientific knowledge to prevent detect, diagnose and treat cancer, and to help cancer survivors live longer, healthier lives. In this RFA NCI is interested in supporting a disease study site that is focused on cancer. And note that studies collecting book tumor normal tissues from cancer cases are strongly encouraged and will be prioritized for funding. We're excited about this RFA and we see several unique opportunities here, including informing how we can scale these multi omics studies to larger population based studies, supporting a collection of longitudinal samples, supporting environmental data with multi omics data, and the emphasis on the study of social determinants of health and ancestral diverse populations. And with that, we're happy as well and NCI, I can email Melissa and I if you have any questions, and I'll turn it over or turn it back to John Ella. Thanks, Liam. And I only have a couple more slides left before we go into the Q&A session. First, I'd like to remind you of the review criteria that will be used to review your applications. You can see here in orange the five general categories that are that will be used for review and I, I would encourage you to go to the RFA's and review the criteria because each RFA has slightly different review criteria. And also to note the key dates to as a reminder the letters of intent are due October 18, the applications are due November 19, and that means that the awards will likely be issued sometime in the summer of 2023. Again, Erin already mentioned this but you can find our email address here below and you can send any additional questions that may come up after this webinar is over. Finally, just to point out that this program does have a page on NHGRI's website. That's where the recording will be posted and we also will post a compilation of all the Q&As that will come up during this discussion for future reference. So thank you all for listening and and thank you all for there are a few of you who contacted us ahead of time with questions. And so we thought that one thing we would do is to go through some of those top questions that were asked. And then Erin will lead us through an open time of Q&As. So I'm just going to go through some of these key questions. Hopefully that will provide some answers that you can then follow up in the Q&A. Okay, so the first question was, well, what diseases are eligible? And you've heard from my colleagues about their IC specific interest. The NHGRI is an institute is disease agnostic. So we did not include a list of specific diseases for applicants to focus on. Rather, our focus is on the kinds of diseases that would accomplish the goals of our program. So the DSS's need to focus on a disease area where they can use multiomics approaches to define associations and to detect changes to association profiles over time. So they need to describe how the proposed study will do this. Also, applicants need to demonstrate that their study will allow for the detection of aspects of disease progression during the five year time frame of the program. The DSS's also need to be able to perform a meaningful study with the 300 participants that I outlined early on. So 200 with disease and 100 without disease. And again, disease areas that have a strong environmental component will be especially relevant for this program. So while we don't provide a list of specific diseases, I've generally outlined the kinds of diseases that we're interested in. And in the RFAs we do highlight as examples, diseases such as relapsing diseases with exacerbations and remissions, or diseases that have a very distinct distinct stages or transitions. So hopefully that's helpful as you think about the diseases that are eligible for these RFAs. Second question briefly, can all participants enrolled by a DSS be from one understudy population? So I already mentioned the emphasis and focus on diversity and that's why we have focused on 75%. We're expecting that at least 75% of the participants come from communities, racial and or ethnic communities that are expected to have genetic ancestries that are currently understudied. Now applicants who want to focus 100% on one particular population should demonstrate that, first of all, they can meet the requirements of the RFA, and that it would be advantageous for the success of the study to have participants that have a fairly homogeneous background. Okay, question number three, can existing cohorts be used? Well, first given that an important goal of this initiative is the development of methods and standards, and the creation of a harmonized and standardized data set. We do prefer new participant enrollment. We do note in the RFA you might have seen that existing cohorts will be considered if the applicant can demonstrate how they meet the requirement for the program, particularly the need to conform to protocols that will be developed during that first year of the consortium, and also the fact that we have a five year program. So applicants would need to make a compelling case that their existing cohort would be suitable for the program. Question number four, how many ohms are expected? So I did mention in one of my slides that the goal for the OPCs is to produce the five molecular categories that I've listed so genomics, epigenomics, transcriptomics, proteomics and metabolomics. I do say that other omics data types will be considered with appropriate justification. And so here you demonstrate that the additional omics data types are relevant for the disease that is being studied and the fit within the allocated budget. Now a DSS can also propose additional omic data types, again provided that the DSS is still able to meet the expectations of the RFA, and that the addition of omic data types is scientifically justifiable and meet data sharing standards. But here I want to emphasize that ultimately decisions will be made during that planning year, and it needs to account the capabilities of the OPCs at the time during that first year. So we also note that applications proposing less than five data types will be considered, provided that at least three of the proposed data types, that at least three data types are proposed, that one of those is genomics, and that one is nucleic acid based, in other words, proteomics or metabolomics. Question number five, and we only have a few more frequently asked questions and then I'll let Erin lead us. Question number five, how will how well established should the environment disease connection be and here we do say very clearly that our program aims to integrate environmental exposure data. The disease areas that have a strong environmental component will be especially relevant. Now if the DSS is planning to incorporate environmental exposure measures, there should be appropriate justification in terms of the preliminary data or extensive background literature to establish that connection between the environmental exposure and onset progression or severity of disease. And finally, I believe what should the year one budget be given the program timeline, especially referring to the fact that that first year will be a planning year. And so here I would say that applicants should propose a budget limit that is the same for all years of the program and so as a reminder for the DSS is each DSS has 500,000 direct cost cap. The OPC is 2.7 million direct costs, if producing all the all omics data types, and for the DAC that's 950,000 direct costs. So hopefully it's been helpful to go through these six frequently asked questions and now I will let Erin help us through the Q&A that you have proposed. I know that was terrific. Thanks so much for the comprehensive overview. We do. We have 16 questions in the chat. We're going to try to answer as many of them as we can live. We did answer two questions already in via the text feature. So we'll start with our first question. And I'll ask you to respond. What will the role of the OPCs for data analysis be? And are they supposed to be blinded for data processing? Thank you, Erin. Just as a quick sound check. Can everyone hear me? You sound clear. Okay, great. Thank you. So applicants should describe their experience. And this is written in the RFA, the computational and statistical data integration and data analysis methods in a cloud based tool development and data wrangling and then work within that annual ecosystem or similar cloud based platform. And this is something that we would decide the methods decision in year one for the protocol development. Okay. Thank you. Thank you, Joti. So just to be clear on that, the OPCs as well, they could sort of include in their justification their preference and thoughts on being blinded. But again, as Joti said, the decision will be made in the first year planning period by the consortium as a whole. Thank you. Okay, next question. Is it anticipated that the program will pull components from proposals for a final consortium? Or will they fund proposals in total? So I'll turn this over to John Allen to respond. Okay, thanks, Erin. Oh, yeah, you can hear me. Thanks, Erin, for that. So, sorry, could you repeat the question, Erin? Yeah, no problem. In the Q&A, it's the question at the top. Is it anticipated that program will pull components from proposals for a final consortium or will they fund proposals in total? So the plan is to fund proposals in total. We will not be pulling taking parts of the different applications. Thank you, Joanella. I will just add one point there that for, if you look at the OPCs FOA, we do write it as funding one to two OPCs, meaning that if there's an OPC, and Joanella covered this, if there's an OPC that is comprehensive, covers all of the ohms, that could be sufficient, but it's possible that we may bring in two components of two separate OPCs. Thanks, Erin, for clarifying them. Okay, next question. What is the amount of direct funding that would be available in year one for an OPC? Joanella did answer that in your FAQs. If you have that, Joanella, just pull it up and restate that. Okay, let me find the slide, but I did say that for direct costs, it would be 2.7 million. I think you're asking for, and this is for the OPCs, and it's the same, and it's the same year one to year five, we're expecting the same budget. Thank you. And thank you Riley for including our responses to these questions as we say them out loud. What is program's view of proposed instrumentation purchases? I'll turn this over to Joati to start. Hi, thank you Erin. Yes, so the applicant should detail the equipment needed or to be purchased within their application, just again ensuring that you don't exceed the direct cost budget limits. Thank you. Okay. Next question. I've seen this question multiple times. So, perhaps there was some confusion. The RFA indicates four disease study sites. Has this changed to six now? Just trying to assess the sample numbers and what to expect. Eman, can you answer that question, please? Sure. The RFA states that we will find up to six. Thus, four would be the minimum. I hope that's helpful. Yes, that's correct. Thank you. Okay. Next question. This is again for the disease study sites. I presume there's a focus on specific diseases given NCI being one of the partner institutes. Should the study diseases exclusively focus on cancer? Are other disease areas accepted or encouraged? Are there disease areas that would be considered non-responsive? Dr. Martin, I'll kick it back to you for that as well. Of course. All diseases would be considered not just cancer. If you're concerned about a particular area of study, feel free to reach out to us. But as of now, the limit is not to cancer, but we are very happy that we are able to partner with NCI for cancer-focused disease study site. And I think, thank you so much. And in Dr. Morales' FAQ, I think the first response that she had on her PowerPoint provided some additional clarification there as well on the expectations of the disease types that we're looking for. Okay. Thank you. Next question. What proposals that use metagenomics, metatranscriptomics, and are microbiome sequencing be considered responsive? And I will turn this over to Joti. Yes. Thank you, Erin. So, again, just reiterating that we're expecting five ohms to be addressed. Any additional omic data types can be proposed as long as it's scientifically justifiable and it meets the data sharing standards. Thank you, Joti. Okay. Our next question. This is referring to the systems biology approach. There seems to only be a linear approach from data generation to data analysis. Is there also feedback envisioned in the full scope of a systems biology approach by experimentally validating the computationally driven predictions by analyzing the multi-omics data? I can take that, Erin. So we've envisioned here because part of the goal is a development of methods, we would expect part of the process is to look at validation of these computationally derived methods. So I would say that there is that expectation that we would be able to do that during the timeframe of this program. Thank you, Jo and Ella. Jo and Ella, while you're on camera, I'll ask you about the next question. It's specific to the omics production centers wondering whether, well, you've addressed the overall budget, I think multiple times. But the question is about how costs are spread over five years, given most of the omics production is in years two through four. Well, I have addressed the fact that we expect the same budget. And I think a lot of how the process will be done at the omics production center will be discussed during that first planning year. So I would say that some of those decisions will need to wait until that is discussed in that year one, but in terms of budgeting, we would expect the same budget to be proposed in all years. Any of my colleagues want to expand on that? I think that was clear, but we can add any additional information to the answered question in the chat. Okay. The next question here. Are the DSS applications expected to be from a single institution or a group of institutions? Sure. So the DSS applications can be either from a single institution or collaborative or cross institutions, please keep direct cost limitations in mind. Thank you. Okay. The next question is about, again, budgeting for omics production. Oh, and this is dependent on the total end. So again, asking for clarification on the number of DSS sites. So I think we've already heard to budget for six DSSs. Joanela, can you remind folks that the number of expected participants enrolled at each? Yeah, sure. And I apologize if there was confusion on the number of DSSs. We are definitely hoping to fund up to six DSSs. And each one should collect or plan to produce data from all the samples that are submitted by the DSS. And so each DSS should have 300 participants. You said 200 with disease and 100 without disease, keeping in mind that there will be collection of biosamples and multiple time points, three time points throughout during the time frame of the program. Hopefully that clarifies. Thank you. Okay, we have a question now about single cell omics. The allowable budget will not support single cell profiling of all omics modalities. We have a question of single cell versus bulk omic profiling. Joanela, you did address this in one of your FAQs, but you sort of state that. Yeah, so so we, the focus here is on on the five molecular data types that we've listed and on the assays that we've, we've also listed in the RFA. And we do say that we want some flexibility for the OPCs and the DSSs to be innovative or to suggest other kinds of assays. What we do say is that you must provide justification for why that kind of other assay would be scientifically beneficial, and also can be accomplished within the budget and the capabilities of the OPCs. I would say, again, some of these decisions on the assays will be finalized during that year one of the of the consortium, but we would be open to suggestions provided, as I said with the caveats that we need justification. Thank you, Joanela. I'm going to calm down just so we have a chance to hear from one of our other panelists. One question is for you. How broad should the environmental exposure data collected be within each study. Yeah, thanks. You know, so we're interested in a wide variety of different exposures I would say probably for what NIHS would be most excited about prioritizing it would probably be in a DSS application that had multiple traditional exposures with social determinants of health. But feel free to reach out, you know, to discuss individual applications with me. Thank you. Thank you, Kim. We have another question about, let's see, should OPCs try to anticipate what kind of samples they will process or what kinds of diseases they might anticipate or use an example. Yeah, I mean, I think, as you might imagine, it's hard for an OPC to predict what kind of applications might come in. But if the goal is to be able to use multiomics to detect profiles, associations with profiles and changes over time. I think the OPC should be focused on on the kinds of assays and the kinds of molecular data that will allow for that. And so I'm, it will be hard for an OPC to try to anticipate that but it should propose the kinds of assays that in general would allow for that kind of activity, and and that would make sense given the ohms that it has the capability to produce. Thank you. Okay. We have a question about the question about remover of exposure data. And can there be a strong international component? So I'll have, Joti, do you want to answer that question please? Sure. So, again, I'm just referring to the RFA. It is anticipated that additional coordination mechanisms may be set up with other US and international groups that may collaborate with the program. Thank you. I think the primary site has to be domestic, but they can, international components can collaborate. That's right. Foreign components are allowed, but the primary site would be a US institution. Thank you. Okay. Okay, this is sort of a question I think that Joe and Ella began to address. And I'll just see if you have any follow up that you want to add and this is regarding the dependency between the OPCs and the DSS and the DAC and the DS and the OPCs. It does not clear how the DSS propose a project without, not clear how the, oh, I think this must be OPCs propose a project without knowing about a DSS project. Yeah, and I mean, I recognize that the way this program works, there's very strong connectivity between all the three components and that's why we have that year one planning, because that that will be essential to make sure it works. But in terms of the application, I mean that the disease study sites understand the disease they're proposing, they understand what makes sense to propose for omics production and for analysis, given the disease that they are studying. And so, so while they don't fully understand the capabilities of the OPCs yet, they can certainly propose an approach, considering that we're hoping for the five data types that are listed here and we're hoping to look at associations and how we're going to push on a change over time. For the OPCs, it's also, I understand, not knowing the exact diseases that will come in. But again, the goal here is to propose the kinds of omic data types or omics assays that make sense given the five particular data types that we are after. So that hopefully that provides a little bit more context but if, again, if any of my colleagues want to chime in, feel free to provide further clarification. Thanks, Joannella. Okay, we have a question about for those of us on study sections, is there still continuous submissions? And Dr. McKinnick, I think turn that over to you. Hi, yes. Thanks, Erin. So this is for RFA is the continuous submission doesn't apply. It applies in general to R01s, R21s and R34 applications. Our applications submitted with standard due dates. Thank you. Okay. I'm trying to look at questions that we haven't addressed yet. There's a question about partnering with commercial CROs to provide one of the omics types. Joti, do you want to answer that one? Yes. So applicants may partner with a commercial CRO provided that the budget is within the budget limits of the direct costs. Thank you. And I'd also add that there's no additional impediments on data sharing with such a partnership. Okay. How, I think we heard this, but it can't hurt to say it again, how many samples total should OPCs budget for Joannella? Yes. So here again, each DSS will have 300 participants and three time points. So that means 900 bio samples per DSS and we're hoping to fund up to six DSSs. Okay. So each DSS be able to analyze their own data to meet their own scientific and disease objectives or is the idea to just generate data that the DAC will analyze? I can answer that as well. Yes, no. So the goal is for each DSS to engage in data analysis. So, so this is not, you know, the idea is not for the DAC to do all the analysis. They will not facilitate collaborative analysis, but each DSS will be engaged in the analysis of their own data. Okay. And here's a follow up question. Are there plans for pooled analysis at the coordination center? What if the six centers funded focus on different diseases? And that again is part of that year one planning in terms of collaborative analysis. It obviously, it's not pooled at the coordination center. Let me just clarify, all the components will work together with the coordination center, facilitating and taking the lead. But the idea is that they will all work together in that ample workspace that I hopefully was able to describe. But yes, I mean, the diseases will probably be different. But there is a hope that there can be some collaborative efforts and hopefully push forward the hope that we have of producing methods as part of this program. Thank you. We've got a number of great questions coming in here. Okay, there's a question on, but we've discussed this already how critical is the environmental exposure component. But I'll turn it over to Kim and Joe and L if you wanted to add anything in addition to what's already been said. You know, certainly for what NIH is going to support, we would need to have a strong environmental component and, you know, I believe NCI is, you know, encouraging that also but obviously an HDI does not need that environmental components or not necessarily anticipating that all of the DSS centers will have that. Do you have anything to add to that? No, I think Kim, unless Simon wants to add I think him covered it pretty well. Okay, nothing to add. Great. We had a couple of questions that I'll group together regarding the OPCs can they similar to the DSS as the questions, can they come in as an application of multiple institutions. There's at least two questions about that. And Joti. Yes, yes, they can come in with multiple institutions, again, within the budget limits that we have. Okay, wonderful. Yes. Okay, there's a question. Well, there only be one site for cancer is it preferred it focuses on one or multiple cancers. Yeah, may I turn this one over to you? Sure. Not sure. I guess, is it asking, I'm not totally sure I understand the question I think it's asking whether or not there will be overlap in the, in the cancer types per disease study site. Would you have two disease study sites with the same cancer. And oh, or is it no, it's asking the opposite is it asking whether or not a DC study site can look at multiple cancers. I think you know, you know this gets back to as long as you're, you know, you're making a good scientific argument for the multiple cancers, or the single cancer. I mean, I think our vision was probably more along lines of single cancers, but multiple cancers could be possible. And as long as you're within the budget for the disease study site. So, and I don't know, Melissa, if you have anything to add you can feel free for that. Yeah, I guess, you know, power calculation. If you are studying more than one cancer and we are looking only at 200 cases here. You know, adding more cancer type might get challenging but if you can make an argument that's feasible, you know, we are open to different scientific questions. Yeah, thanks. Okay. So I'm going to talk a little bit about the disease study sites FO a just lost it here. Okay, can the university lead be in the US, but the population under study be based abroad. Dr Martin. I might require extra steps. So if you have a particular proposal in mind, you may want to reach out to the team. But it is per the RFA that is not impossible. Thank you. Okay. Let's see. There's answered questions about multiple institutions. Which DSS need to conduct multi omics data analysis. Joe and L you answered this but you just want to restate. Yeah, I did. I did answer I did say that, yes, the expectation is that the disease study sites will be engaged in data analysis processes. Okay. And you did cover this but at least I think you did in your presentation so there's a question about the term that a DSS doesn't include the cost of sequencing or other omics costs in the budget for the disease study site FOA dash 008. No, so the data production is an activity of the OPCs. So we expect the budget for that to be in the OPCs. So the RFA 009. Okay. There is a question on prevalence for diseases based on prevalence IE more common diseases versus rare diseases. Joe and Ella then I'm on. Yeah, I mean I would just start by saying we we haven't we haven't outlined preference of disease I mean we again we're focused on conditions where a multi omics approach would be would be advantages and so clearly the applicant needs to come up with strong justification, describing how how the approaches could be used for their disease but we haven't really, you know, provided a list of priority diseases. Prevalence of the disease is not a limitation necessarily, although the statistical acumen to answer the question from a multi omic perspective must stay at the forefront, according to the RFA. So ensuring the proper and peer grounding for the disease chosen, as well as the proper statistical rationale within the limitations of the budget as well as the sample numbers provided in the RFA. Thank you. Okay, thank you. There's a question about how the DAC will be required to develop six different electronic data capture systems for each of the different disease types at a DSS. Is that correct. Joe and Ella, can you try to kick us off on that one. Yeah, so we'll be required to six different electronic data capture systems for each of the depth of the six. I mean, so the DAC is responsible to liaising with the annual ecosystem to set up the workspaces so each, each site and center will have its own workspace, but there will also be shared workspaces where all the components of the consortium can come in and contribute. So I'm not sure if that's what you meant by electronic data capture systems, but the data that will be produced and release as part of the consortium. At the end or towards the end will come out of one of the shared workspaces and that will be the DAC's responsibility. And I would, I would add I suppose that it would be, as you said that the DAC will work with each of the DSS is I think they'll have to be an overarching data model for the program as a whole. And the DAC as you said will work with the DSS is to ensure they can receive the data in an appropriate format. Okay, wonderful. Now there is a question about clarifying the budget for the data analysis and coordination center. So it's, I think first can you confirm the direct cost limit for year one and the out years. I think you already provided this Joan Ella would be helpful to just state that again. Because there was some, some confusion about the language where it says NHGRI intends to commit up to 1.45 and then NIHS and NCI are contributing an additional amount. And so the amount of the overall so when you combine all the different contributions from the different ICs, the direct costs for each DSS is 500,000, the direct costs for the OPC provided that it's one OPC producing all the data types, it's 2.7 million. And for the DAC it's 950,000 the direct costs for the DAC. Okay, thank you. I see there is a question about the anvil and Joan Ella I'll read it and ask you to respond and Dr. Ken Wiley who oversees the anvil just stepped into my office so if we need any clarification he can provide any follow up. For the DAC and sharing of summary level data within a portal. Is this expected to be something integrated with it within anvil or an independent tool. So that that is actually a decision that will be done, probably will be discussed during the year one, but it can be done independently of the anvil. It's not necessarily tied to the anvil. Okay, thank you. Okay, here's a question it was mentioned that approximately 300 individuals will be needed, and that tumor normal adjacent tissue would be potentially a priority for NCI. So the number of samples need to be adjusted for this, ie 150 individuals. Can I turn this over to Leah. Yeah, thanks. Thanks. So, I guess just to clarify to the way the RFA has written it's 200 cases and 100 controls, just for the sample numbers. But I think the thing to keep in mind is that, you know, we, we wouldn't necessarily need to do all the omics assays and all the on all the tumor samples. You may select some of some of the different assays. And I think to think about the, the planning within the first year of the consortium and how and how we're going to select the omics measures by the OPC. Thank you Leah. Okay, will DSS sites be required to collect bio fluids for other DSS targets, ie blood and tissue, even if they are not part of the initial DSS proposal. So that's sort of getting at the flexibility of a DSS to be able to align with other DSS awards. I'll let you go ahead first if you'd like. I'm, I'm, I'm struggling keeping up with a Q&A because it's moving so fast. So I didn't, I didn't, I'm sorry I didn't capture that so if you have an answer that would be great. The question was whether or not bio samples outside like fluids for example blood or urine, in addition to tissue, would it be required of a DSS in addition to the proposed 300. So, would that be an additional requirement on top of. And we've had other questions in the chat as well about whether or not it can be proposed. Those, that was the question. I think it can be proposed but it's not a requirement. Exactly. And hopefully, again, keeping the costs in mind and the scientific question in mind with regard to the own specified. For the owns proposed keeping in mind what source would be ideal to see that own with regards to the disease proposed. I hope that's helpful. Thank you, Amon. Lee, this is a follow up question about cancer studies and forgive me if you already covered this will normal tissue coming from the cancer patient be considered healthy case so we can reduce the number of healthy participants. So, I think, you know, the way that our face that up we want people with disease and people without disease so the normal tissue from a cancer patient wouldn't count the individual as a healthy control. So, I think, but you know, please free to follow up with Melissa and I'm the specific question, if we have it quite addressed it. Okay, thank you. Okay. Here's a question for Joe T. This is referring to a question about the budget so we have the cost of the OPC is averaged out from years one through five. And the question was, I just lost it here. The question was, can the money be carried forward from year one to support omic analysis when the samples become available. Your one is a planning period. When the samples become available. Yeah, so yes year one is a planning period and as far as money being carried over. That is something that program would work with the grantee on that on the, you know, the specifics of the grant. Okay. Another question for NCI is NCI interested in cancer precursors, each example HPV or cervical cancer. Cancer precursors fit within our interest and scope. Okay, thank you. Okay. Some of these I think we've answered so I'm just going to click for example, can the OPCs be comprised of multiple institutions I'll just click that we've answered that, because that that has been addressed. Okay. Would omics data from disease associated microbiomes be responsive to this FOA. I mean, I think that this, we tried to address already that additional omics data types beyond the five molecular omics data types can be proposed and can be justified. So the applicant would need to justify how they would be beneficial for the for the study they're proposing. Thank you. Okay. For the DSS can two sites proposing the same diseases with differences in diversity or aims be funded. Joanne, do you want to describe or Iman the program expectations here. Joanne, please go ahead first. Oh, I was, I was going to say, I think we're aiming for programmatic diversity here so we probably wouldn't fund more than one DSS with the same disease I mean that would be that would be my, my guess like, but I, so I'm not sure. Maybe I misunderstood the question but that that is what I was on what I understood was being was being said multiple DSS is on the same disease. I think additional the question is also asking whether or not, if it was the same disease but a different constellation of populations represented with that suffice to allow for the funding of two and think that would be hard to discern a priority. Yeah, I think we'd actually have to see it. Right and just reiterating programmatic balance to achieve the overall goals of the program. We are looking for the methods and the protocols that come out of this program to be generalizable. So there's an opportunity to deploy those across a number of diseases. I think that would be preferred official. Right. Okay. So there was a question about the NCI CPTAC program, which is ongoing. And there was a question about connecting with them for advice on some of the challenges that they've already identified. Leah. Yeah, I think I think that I think that's a great point and we'll be sure to talk to our CPTAC colleagues about their lessons learned and challenges. We have about 15 minutes left. I'm just looking through the queue to see what questions haven't been answered yet. Aaron, there are a lot of questions on the number of samples and bio sample so I'm just going to, I'm just going to explain that again that we expect to fund six disease sites. The disease site should recruit or enroll 300 participants, but each participant will have three bio samples because they will be collected at three different time points. So that means that that each DSS would have 300 times three. So the OPCs would have to produce data from all the bio samples that will be submitted from all 60 assesses. Hopefully that, that helps. Thank you. Okay. Oh, and sorry, I see that there's a question about three whole genomes for participant and no so you wouldn't have to do whole genome sequencing at three different time points. Thank you. With the disease focus our approaches to integrate diseases encouraged example looking at comorbidities between behavioral and chronicle medical diseases chronic medical diseases and integration with social determinants of health. So I think, you know, are we looking within the goals of the consortium to be able to integrate methods and data across different conditions integrating social determinants of health as well. Joan, how do you want to try to take that. Again, I, I, okay, I'm trouble. Q&A because it just moves. There are so many coming in, I, I'm not tracking with a question I apologize, Aaron. Okay, I think I can answer the question that yes, you know, again, ultimately thinking about the overarching goals of this program we are looking for the outcome to be generalizable methods that aren't disease specific. So of course, part of the proposal would be being able to integrate and analyze the data relevant for your proposed disease, but at the same time it's advantageous to propose and think about methods to be able to integrate and leverage the data from other programs as relevant other disease areas as relevant. Okay. There's a few questions again about I think the international verse domestic component so can clinical sites be based out of the US. Dr Martin, you answered that but why don't you just answer it again since there's a few questions still coming up about that. We have a very specific kind of programmatic structural idea definitely reach out to us. There may be additional steps required if the constellation of the partners is international. I hope that's helpful. Thank you. Okay. Okay, there's a question about sample size here. The sample size of 300. Is that is that sufficiently powered for multi all mix analysis. Don't know if you want to add anything there I think you did cover some of the rationale for that in your presentation. Yeah. I think that you the applicant would have to include power analysis to demonstrate that it can that the study it's it's proposing is suitable for a multiomic approach. I don't know if that helps and leveraging the the pool comparator group as well. Okay. There are other questions here about Do you expect sample collection materials to be included in the DSS budget, or will the OPC purchase in bulk and provide to the DSS. Will a DSS or OPC incorporate the shipping costs. So that's sort of a detailed question but I think it's good to reiterate again the expectations of the DSS versus OPC. Yeah, the DSS should budget for the sample collection, not the OPCs. Okay, thank you. Okay. Okay, here's a question about computing costs. Well strides cover the cloud compute and storage cost overruns. It seems near it seems challenging to budget for data storage and compute with so many unknown variables and I see my colleague Ken Wiley is here and he might be able to add to that. Can you hear, hopefully everybody can hear me. Yeah, so strides can help provide some support for compute storage and egress projects using an envelope. There's also a page that will provide that up you go to the anvil portal.org site. There's a page where it gives you a list of information about the budget how to budget for using an envelope. I can put that also in the chat I think in here so we'll put that in there for people to use. But you should be able to, but I want to make it very clear that strides will require your university to have a existing contract with a third party group, and that could take some time to set up. So make sure that you allow the appropriate time to allow your institute to form those agreements that need to be in place with this third party groups in order to be able to set up strides accounts and receive cloud credits. Janela, rest of the team or something else you want to add. No, I thank you Ken for clarifying that. Thank you. And our team, Joe and Ella Riley will put that link that you referred to Ken in the chat. Thank you so much. Okay, can we can we clarify the whether or not it's one bio sample per visit. Yeah, so the, the goal is to. Yes, the answer. The answer is yes, because we budgeted for 300 participants at three time at three time points. Okay, here's a question about, can different omics be proposed to be conducted by different tissue types for the same participant. Joan, how did you catch that question. Yeah, so this was about. I think I saw the question, more than one type of sample per. One tissue for the same participant. Well, I mean, the, again, I think this is something that that can be proposed by by the DSS but the idea was that it would be three bio samples. 300 participants, three different time points, not necessarily expecting the collection of more than one tissue per per visit, for example. Okay, thank you. And there's another question for our colleagues from NCI for the cancer disease study site, can we propose just plasma collection and no tissue. Well, that's definitely a possibility we do encourage strongly the collection of both tumor and normal so in that case and so I encourage you to reach out to us specifically about what you're proposing and we'll follow up with you. Thank you. So question about time scale for relapsing disease states. Should they occur within five years. Touch on this John L. Do you want to add the expectation is that that we would collect within the timeframe of the program. So hopefully the proposed study you would be able to see that kind of disease progression during during the timeframe. Okay. Okay, there's a number of questions about budget. I'm going to let my team digest some of those questions and see if you want to come back with any specific overarching response to some of those specific budget questions. And then, in the meantime, I'll see if the other questions can be addressed. Okay, here's a question again Leah will the OPC be able to adapt sequencing assays for canceled sample samples for example much deeper whole genome sequencing is required for tumor tissue. Should this be included in the DSS plan. So the DSS should propose what omics characterizations makes the most sense for for their disease study site, and then with it with an assumption that that first year of planning will have some discussions with the consortia and the OPC about what omics that they will ultimately be pursuing. So I think it's really thinking about what really makes the most sense. And with that I might ask Melissa if she has anything to add to that question response. Yeah, I don't have much to add that I would say yes being touched with us and you know it can be also a combination of not having the same assay done on all the samples that you know at each time point but yeah we definitely are encouraging having also the tumor sample and of you know it's also a resource if you collect it and we don't have the means to sequence everything through the specific program is always something that can be added later on to the bulk of knowledge. And again during that first year would be planned what makes more sense to do through this program but the resource might still be valuable so I would encourage to propose what you can do within the strongest scientific question you can propose. Thank you. There was a question about past performance. As far as what are we looking for. I guess for expertise for the data analysis and coordination center. I can answer that I mean we did include some information on the required expertise in throughout the RFA, having a strong record of coordination and and experience with Ambul would be definitely recommended given how a lot of the work will be in the annual ecosystem. Thank you. And as you would in any application just describe describing your overall experience and expertise relevant to the particular FOA that you're applying to. Okay, and we've got five minutes left so just trying to get through here to see if there's any questions from outside of the categories that we already addressed. There's a question about the overall, I think, internal organizational structure for each of the centers. So as a question about is there a particular internal structure required. For example, a number of components with the research focus as well as core activities. I don't I don't think we've specified in the RFA any particular structure I think we would expect to for the applicant to propose that but I think there is flexibility on that. And there's there's some expectations in the FOA is about sort of your role as the individual research team and then your role in coordinating and collaborating with the other disease study sites OPCS and DAC. So, you know, that's that's the area where we'll be looking for some structure within our, you know, the three components of our program but nothing specific is expected within each of your internal applications. Okay. There is a question number of questions, or the gist is that there are investigators that are interested in responding to this program but don't necessarily have a full comprehensive team at their institution. And I think the question is whether or not we can facilitate any of that and I think our one recommendation that we have would be looking at the NIH reporter, which is a public resource so you can do a search on a particular disease or you can do an advanced search with disease and omic analysis and see the the response as far as which investigators may be working in a disease area with genomics or omics area of expertise on top of that that might be a good place to start. So my colleagues want to add anything to that. Okay, there's a question about whether or not these funding opportunities are recommended for established PIs only, or can junior early career PIs also apply. It's not specific to establish PIs junior early career PIs can apply. Wonderful, thank you. Okay. Okay, so with two minutes left I'm going to turn to my colleagues and ask I've been trying to go through the queue there are some questions listed as open I know we did address them. Are there any outstanding questions that you want to address now live otherwise we will make sure to include written answers for all of these questions in FAQ that goes to our website. And as Aaron for moderating that session there were a lot of we thank you for your participation there were a lot of questions really good questions. And as Aaron said we'll make a point to draft answers compile them and post them on our website and I didn't see any, any particular question that we should jump to answer right now. We covered a lot of ground I think. And again, we will be sure to answer all these questions and add them to the FAQ. If you have follow up questions. Please send us an email we can put the email in the chat. If we haven't done that already. Riley do you have the email address that you can pop in the chat please. Riley has done so I see here that she's been put in. She posted the website as well as the email multi omics program at mail.nih.gov. Okay. Wonderful. Well thank you everyone take care again we appreciate your participation from the audience, our panelists of program directors, and our communications team thanks again. Thank you.