Multi-Omics Pre-Application Webinar FAQ

Eligibility/Rules

What diseases are of interest for this funding opportunity announcement (FOA)?

NHGRI is a disease agnostic institute. All diseases areas of public health importance will be considered, provided they can accomplish the goals of the program. DSS applicants should propose a disease area where multi-omics approaches can be used to define associations with healthy and disease states and detect changes to association profiles over time. Applicants will need to describe how their proposed study would advance scientific understanding of the diseases they are proposing, considering the goals of the program. Also, applicants will need to demonstrate that their study will allow for detection of aspects of disease progression during the 5-year timeframe of the program and that they are able to perform a meaningful study with 300 participants (approximately 200 with disease and 100 generally healthy participants), noting that power calculations are expected as described in the RFA. Disease areas that have a strong environmental component will be especially relevant for this program. Studies collecting both tumor and normal tissues from participants with cancer are strongly encouraged and will be prioritized for funding by NCI. While we don’t provide a list of specific diseases in the RFA, we do highlight certain types of conditions that would be suitable, such as relapsing diseases or diseases with distinct stages or transitions.

Will more than one DSS focused on the same disease be funded?

Each DSS applicant should propose its disease of interest. However, to achieve programmatic balance, it is unlikely that more than one DSS focused on the same disease will be funded.

Are pediatric populations eligible for the program?

Yes, pediatric populations are eligible provided applicants can demonstrate their ability to obtain appropriate consent, ensure meaningful community engagement and enroll a minimum of 75% of study participants from self-identified racial and/or ethnic communities expected to have genetic ancestries currently understudied in genomics research. Furthermore, applicants must demonstrate their ability to abide by ethical principles of respect for persons, beneficence, non-maleficence and justice for research in pediatric (and all) populations proposed for this program's RFA.

Budget

Are the DSS applicants expected to propose omic data types to be produced? If so, are the DSS applicants expected to budget for this?

Yes, the DSS applicants are expected to propose omic technologies to be applied, considering the unique characteristics of the phenotype/disease as well as proposed scientific objectives. However, they are not to include costs for the production of omic data given this will take place at the OPC(s). The OPC(s) are expected to produce at a minimum the five standard omic data types (genomics, epigenomics, transcriptomics, proteomics and metabolomics) listed in RFA-HG-22-009. The OPC(s) will therefore budget for the omic data types to be produced.

REVISED Can a DSS applicant propose omic data types, assays, and technologies beyond the standard 5 the OPC(s) are anticipated to perform (genomics, epigenomics, transcriptomics, proteomics, and metabolomics) and if so, how should this be budgeted?  

Yes, a DSS applicant may propose omic assays beyond the five primary assay categories, with sufficient scientific justification and within the direct cost limitations noted in the DSS RFA. Applicants may also propose omics assays beyond the scope of their study design and/or budget if deemed beneficial to achieve the goals of the Consortium as a whole. OPC applicants are encouraged to describe if they have the capability and expertise to perform additional assays beyond the required primary omic assays. During the Year 1 planning period, we will assess the Consortium’s capability, expertise, and overall budget to accomplish additional assays.

Should a DSS applicant budget for the collection, preparation and shipping of samples, or should they assume OPC applicants will budget for this?

As noted in the RFA for the DSS (RFA-HG-22-008), each DSS applicant should budget for the management of biosamples, including ensuring sample stability, quality assessments and quality control. Sample collection materials and shipping costs should also be included in the DSS budget. Each DSS will be responsible for collecting specimens at a minimum of three timepoints and for budgeting for the management of biosamples, including costs associated with submitting the biosamples to the OPC(s) for omic data production. OPC applicants should budget for storage of biosamples for the duration of the program and for the production of omic data for all biosamples submitted by all DSS. If bulk purchases are decided upon, adjustments will be made to the DSS and OPC budgets.

If a DSS applicant believes the budget allowed is not enough for what the RFA asks for, what should they do?

After responding to the RFA-specified design and allowable costs, applicants may propose a strongly justified alternate design that may require small deviations from the sample sizes, numbers of omes supported/under study and/or omic data types. Such alternate designs should be clearly identified and should optimize sound methods and assay production and enable interoperable analytic potential. For budgeting purposes, however, applicants should base their cost estimates on the RFA-specified design.

NEW Can a DSS applicant propose omic data types, assays, and technologies related to environmental exposures beyond the standard 5 and if so, how should this be budgeted?

Yes, a DSS applicant may propose omic assays beyond the five primary assay categories, with sufficient scientific justification and within the direct cost limitations noted in the DSS RFA. Examples include environmental exposure measurements beyond metabolomic, such as microbiomic data and targeted or untargeted methods to analyze various environmental toxicants or chemicals. OPC applicants are encouraged to describe if they have the capability and expertise to perform these additional assays related to environmental exposures as well. Of note, OPC applicants proposing to perform metabolomic assays are expected to have the capability to do high resolution metabolomics that would enable the capture of environmental chemicals. During the Year 1 planning period, we will assess the Consortium’s capability, expertise, and overall budget to accomplish these specialized assays.

Biosamples

How many samples should the DSS collect?

The DSS should enroll at least 300 participants (approximately 200 with disease and 100 generally healthy participants). Given the longitudinal nature of the program, at least one sample type (e.g., blood or saliva or urine etc.) should be collected longitudinally on the same set of study participants over multiple (at least three) time points.

Is a sample size of 300 sufficient for multi-omics analyses?

We recognize that a sample size of 300 may not be adequate to address all scientific questions. However, it may be adequate to address hypotheses about specific disease transitions. Applicants will need to justify the potential knowledge gained for 300 individuals for their proposed disease area and provide power calculations.

Are the DSS allowed to collect multiple types of biospecimens, such as tissue, blood or urine?

More than one sample type (as many as deemed scientifically justifiable) can be collected, within the budget stipulated by the RFA. However, at least one sample type (e.g., blood, saliva or urine) should be collected longitudinally on the same set of study participants over multiple (at least three) time points. Applicants should propose sample collections and assays that can reasonably be expected to be feasible within the OPC budget. If the requested assays exceed the OPC budget allocation, the initial DSS applications will be modified accordingly.

Will a DSS be required to collect biofluids for targets of other DSS awardees (e.g., blood or tissues) even if these samples were not part of their initial DSS application?

Yes, it is possible that during the planning year the steering committee will decide that all DSS should collect a sample type which may have not been included in their initial application.

It seems the OPC is dependent on the DSS and the DACC is dependent on the OPC. Can you clarify what each component is expected to propose when there is uncertainty about what the other components will propose?

Although each component has a unique role, the three are expected to work collaboratively and make joint decisions, especially during the planning year. In general, the DSS will enroll and consent participants, collect phenotypic and environmental exposure measures and collect biosamples at a minimum of three timepoints. DSS applicants should propose a study design focused on a disease area where integrative multi-omics can be used to define associations with healthy and disease states and detect changes to profiles over time. The OPC(s) will produce the omics data types from the biosamples collected by the DSS. OPC applicants should propose standardized, validated methods to provide the most accurate and cost-efficient data for the five standard omic data types and any others, within budgetary limits, they would like to have considered during the planning year. The DACC will produce the harmonized and standardized dataset and coordinate Consortium-wide efforts. DACC applicants should propose sound methods for Consortium coordination and standardized data analysis, regardless of the disease areas ultimately selected among the DSS awardees. All components will work together on the development of methods and analysis of data. Therefore, all should propose analytical tools and methods, including technological and computational, that can be developed and optimized collaboratively.

Recruitment

Are the DSS allowed to use existing cohorts or is new participant recruitment necessary?

Given that an important goal of this initiative is the development of methods and standards, and the creation of a harmonized and standardized dataset, we prefer new participant enrollment. We do note in the RFA, however, that existing cohorts will be considered if the applicant can demonstrate how they meet the requirements for this program, particularly the need to conform to consortium-wide protocols (including for consent, engagement and data collection) that are yet to be developed, detect aspects of disease progression within the timeframe of this program, and meet data sharing requirements. Applicants would need to make a compelling case that an existing cohort would meet all these needs.

Can all participants enrolled by a DSS be from one understudied population?

Yes, as long as the proposed population meets the goal of the RFA for the DSS (RFA-HG-22-008) to advance the application of multi-omics technologies in ancestrally diverse populations. As noted in the RFA (and in Popejoy et al.), racial and ethnic minority populations have been massively understudied in genomic research to date. The Multi-Omics for Health and Disease Consortium expects DSS (RFA HG-22-008) to enroll a minimum of 75% of individuals from self-identified racial and/or ethnic communities expected to have genetic ancestries currently understudied in genomic research. Applicants would need to demonstrate that they can meet this requirement with whatever population(s) they propose and that they can adequately measure, control for (where necessary), and analyze multiple sources of variation in omic, phenotypic, environmental exposure and related data.

Can a DSS applicant propose to study populations based outside the United States?

While applicants can propose to enroll participants based abroad, they must ensure that at least 75% of the enrolled participants are from self-identified racial and/or ethnic communities expected to have genetic ancestries currently understudied in genomics research. Applicants should keep in mind that the consent and data sharing requirements of this program must be met. Applicants would also need to demonstrate their ability to integrate and harmonize multiple data types across DSS including omic, phenotypic and environmental (e.g., SDOH).

NEW What is the role of the healthy comparator group?

Each DSS is expected to enroll at least 100 generally healthy participants free of the disease or condition under study to be contributed to a pooled, Consortium-wide healthy comparator group. Healthy participants should be similar in key demographics and exposures to the participants with disease proposed by each DSS application. In addition to providing a comparison group for the individual DSS proposing it, pooled analyses across all DSS comparator groups will facilitate case-control, case-cohort, and other analytic designs of interest to the Consortium.

NEW If we propose a case-control study design in our DSS application, are we expected to use only the 100 participants free of disease enrolled at our site or the entire pooled comparator group from across the funded DSS?

Use of the Consortium-wide comparator group is encouraged, if it is appropriate given the study design proposed by the DSS applicant. For power calculations, applicants that wish to leverage the pooled comparator group should estimate that up to 600 participants free of diseases under study will be available.

NEW Should we deploy a matched or unmatched approach to enrolling healthy participants given the healthy participants will be available for other DSS awardees to use? 

Either matched or unmatched approaches are allowable, as long as investigators provide justification in their applications and recognize that the approach for enrollment of healthy participants may change during the Year 1 planning period. Healthy participants should be similar in key demographics and exposures to the participants with disease that are enrolled at each DSS. DSS applicants should also consider how the healthy participants from the other DSS sites could be utilized for the collective Consortium goals and incorporate different scenarios into their proposed plan.

Data Analysis

What is the expected relationship between the analyses conducted by the DSS and the collaborative analyses performed by the consortium? Will each DSS be able to analyze data to meet the scientific and disease objectives described in their applications, or is the idea that the DACC will analyze data for all the teams?

We expect all consortium components to contribute to data processing and analysis efforts relevant to the proposed study aims, as well as to questions arising during the course of the program, following the collaborative analysis methods and standards agreed upon by the consortium during the planning year. The DACC has the additional roles of coordinating the collaborative process and liaising with the AnVIL to establish data analysis workspaces.

Are data integration approaches encouraged? For example, integrating comorbidities between behavioral and chronic medical diseases and social determinants of health (SDOH).

Yes, this program encourages and expects integration of ‘omic data types with other data types, such as clinical and environmental data, including SDOH. One of the aims of the program is to develop methods to increase and improve data integration approaches.

Should the focus be on methods development or the application of multi-omics or both?

Both. This program aims for a balance between application of multi-omics technologies and methods development. DSS applicants are expected to propose a study for which an integrative multi-omics approach could be useful in providing insights into the disease, while planning to work with the overall consortium in the development of methods that can be applied to the different diseases under study and are generalizable across populations.

Timeline

What timescale for relapsing disease states is expected given the timeline. Should they occur within five years?

Yes, we expect the DSS applicants to propose a prospective study that allows for the detection of disease progression/regression within the five-year timeframe of this program. Biosamples will therefore be collected at multiple timepoints.

Are there plans for pooled analysis at the coordination center? What if the four to six funded DSS focus on different diseases?

We expect all consortium components to contribute to data processing and analysis efforts relevant to proposed study aims, as well as to questions arising during the course of the study, following the collaborative analysis methods and standards agreed upon by the consortium during the planning year. The DACC has additional roles of coordinating the collaborative process and liaising with the Genomic Analysis, Visualization and Informatics Lab-space (AnVIL) to establish data analysis workspaces. We do expect that the diseases will be different as our goal is to develop methods and perform analyses that are generalizable across diseases and populations.

What sort of past performance are you looking for in potential DACC teams?

DACC applicants are expected to demonstrate experience and expertise in multi-omics high throughput assays, in computational and statistical data integration and data analysis methods, and in cloud-based tool development and data wrangling. Expertise in community engagement, participant recruitment approaches and outreach is also expected.

Is the portal expected to be integrated within AnVIL or an independent tool?

This decision will be made during Year 1 planning. The portal can be made independently from AnVIL.

Will the DACC be required to develop four to six different electronic data capture systems for each of the four to six different disease types at the DSS?

Each site and center will have its own workspace in AnVIL, but there will also be a collaborative workspace. The data being released will come from the shared space, and the DACC will be responsible for that. The DACC will also work on establishing a data model for the program for all sites and centers to conform to, so all data have the same format.

Will the NIH Science and Technology Research Infrastructure for Discovery, Experimentation and Sustainability (STRIDES) Initiative cover cloud compute and storage costs/overruns?

STRIDES may help provide some support for compute storage and egress. STRIDES will require the applicant’s institution to have an existing contract with a third-party group. Applicants should keep in mind that setting this up could take some time.

Are DSS applicants required to incorporate an environmental component?

One of the aims of this program is to encourage integration of multiple types of data, including environmental exposure data and social determinants of health. While an environmental component is not required, DSS applicants that do so will be prioritized.

How well established should the environment-disease connection be?

Diseases for which there is robust empirically grounded literature demonstrating environmental factor associations will be prioritized. DSS applicants planning to incorporate environmental exposure measures are expected to provide appropriate justification in terms of preliminary data or extensive background literature to establish a connection between the environmental exposures and onset, progression or severity of disease outcomes proposed.

How broad should be the environmental exposure data collected within each study?

We are interested in a wide variety of different exposures. NIEHS would be most excited about prioritizing applications that have multiple traditional environmental exposures with social determinants as well. Potential applicants should feel free to contact Dr. Kim McAllister at NIEHS to discuss individual applications.

NEW Is there interest from NIEHS in supporting the generation of environmental data (i.e., exposome measures) within the Omics Production Centers?

Yes, NIEHS is very interested in environmental data of various types. While the collection of environmental exposure measures will mainly be performed by the DSS, OPC applicants are encouraged to describe their capabilities and proposed costs to perform assays and technologies related to the measurement of environmental exposures. 

NEW Can a DSS applicant propose omic data types, assays, and technologies related to environmental exposures beyond the standard 5 and if so, how should this be budgeted?                                                                                                                       

Yes, a DSS applicant may propose omic assays beyond the five primary assay categories, with sufficient scientific justification and within the direct cost limitations noted in the DSS RFA. Examples include environmental exposure measurements beyond metabolomic, such as microbiomic data and targeted or untargeted methods to analyze various environmental toxicants or chemicals. OPC applicants are encouraged to describe if they have the capability and expertise to perform these additional assays related to environmental exposures as well. Of note, OPC applicants proposing to perform metabolomic assays are expected to have the capability to do high resolution metabolomics that would enable the capture of environmental chemicals. During the Year 1 planning period, we will assess the Consortium’s capability, expertise, and overall budget to accomplish these specialized assays.