U24HG011453
Cooperative Agreement
Overview
Grant Description
The Association to Function Knowledge Portal: A Genomic Data Resource for Translating GWAS Associations to Biological Effects - Abstract
Genome-wide association studies (GWAS) have produced associations between many thousands of genetic variants and many hundreds of traits. The "functional effects" of most associations, however, have not yet been elucidated – that is, the causal variants and effector genes responsible for them, and the tissues and pathways through which they act, remain largely unknown.
Over the past few years, three classes of genomic data have arisen for inferring the functional effects of GWAS associations: summary association statistics (effect sizes and p-values for associations between SNPs and traits), genomic annotations (assays of regulatory activity and genomic functional elements), and bioinformatic methods (computationally predicted functional effects).
We argue that two gaps exist in the current resources that aggregate these data: first, no current resource aims to comprehensively curate and catalog all that is known, and all data or methods that could help predict, the functional effects of GWAS associations; second, existing resources are developed with (at best) limited involvement from experts who either originally generated the genomic data and/or understand how to best use them.
We propose to address these gaps by building a new genomic community resource – the Association to Function Knowledge Portal (A2FKP) – using a general software platform we initially developed for type 2 diabetes. Our approach makes use of a key innovation to build a resource that is both high quality and comprehensive: we collaborate with disease expert communities to build dedicated knowledge portals for them, motivating them to contribute their data and expertise, and we then integrate these data alongside those of other communities, providing users with access to a comprehensive resource.
Specific Aim 1 addresses gaps in the comprehensiveness and quality of the data aggregated by current resources regarding the functional effects of GWAS associations. It will establish and manage collaborations with a wide range of disease, data, and method experts, and then work with these communities to identify, aggregate, and curate data for 11 classes of disease.
Specific Aim 2 addresses gaps in current schemas and software platforms for the myriad types of data used for predicting the functional effects of GWAS associations. It will build pipelines for processing genetic and genomic datasets through bioinformatic methods for predicting the functional effects of GWAS associations, apply these pipelines to data aggregated in Aim 1, and transform their outputs to relationships among entities in a knowledge graph.
The goal of Specific Aim 3 is to provide users with direct and visual access to the resources aggregated or computed in Aims 1 and 2. It will develop REST APIs and web portals for querying and visualizing data within the A2FKP.
Significance: The project would produce a high-quality and comprehensive genomic resource of data and methods for predicting the functional effects of GWAS associations. Easy access to such a resource will accelerate the pace by which GWAS associations can be translated into insights into complex disease.
Genome-wide association studies (GWAS) have produced associations between many thousands of genetic variants and many hundreds of traits. The "functional effects" of most associations, however, have not yet been elucidated – that is, the causal variants and effector genes responsible for them, and the tissues and pathways through which they act, remain largely unknown.
Over the past few years, three classes of genomic data have arisen for inferring the functional effects of GWAS associations: summary association statistics (effect sizes and p-values for associations between SNPs and traits), genomic annotations (assays of regulatory activity and genomic functional elements), and bioinformatic methods (computationally predicted functional effects).
We argue that two gaps exist in the current resources that aggregate these data: first, no current resource aims to comprehensively curate and catalog all that is known, and all data or methods that could help predict, the functional effects of GWAS associations; second, existing resources are developed with (at best) limited involvement from experts who either originally generated the genomic data and/or understand how to best use them.
We propose to address these gaps by building a new genomic community resource – the Association to Function Knowledge Portal (A2FKP) – using a general software platform we initially developed for type 2 diabetes. Our approach makes use of a key innovation to build a resource that is both high quality and comprehensive: we collaborate with disease expert communities to build dedicated knowledge portals for them, motivating them to contribute their data and expertise, and we then integrate these data alongside those of other communities, providing users with access to a comprehensive resource.
Specific Aim 1 addresses gaps in the comprehensiveness and quality of the data aggregated by current resources regarding the functional effects of GWAS associations. It will establish and manage collaborations with a wide range of disease, data, and method experts, and then work with these communities to identify, aggregate, and curate data for 11 classes of disease.
Specific Aim 2 addresses gaps in current schemas and software platforms for the myriad types of data used for predicting the functional effects of GWAS associations. It will build pipelines for processing genetic and genomic datasets through bioinformatic methods for predicting the functional effects of GWAS associations, apply these pipelines to data aggregated in Aim 1, and transform their outputs to relationships among entities in a knowledge graph.
The goal of Specific Aim 3 is to provide users with direct and visual access to the resources aggregated or computed in Aims 1 and 2. It will develop REST APIs and web portals for querying and visualizing data within the A2FKP.
Significance: The project would produce a high-quality and comprehensive genomic resource of data and methods for predicting the functional effects of GWAS associations. Easy access to such a resource will accelerate the pace by which GWAS associations can be translated into insights into complex disease.
Awardee
Funding Goals
NHGRI SUPPORTS THE DEVELOPMENT OF RESOURCES AND TECHNOLOGIES THAT WILL ACCELERATE GENOME RESEARCH AND ITS APPLICATION TO HUMAN HEALTH AND GENOMIC MEDICINE. A CRITICAL PART OF THE NHGRI MISSION CONTINUES TO BE THE STUDY OF THE ETHICAL, LEGAL AND SOCIAL IMPLICATIONS (ELSI) OF GENOME RESEARCH. NHGRI ALSO SUPPORTS THE TRAINING AND CAREER DEVELOPMENT OF INVESTIGATORS AND THE DISSEMINATION OF GENOME INFORMATION TO THE PUBLIC AND TO HEALTH PROFESSIONALS. THE SMALL BUSINESS INNOVATION RESEARCH (SBIR) PROGRAM IS USED TO INCREASE PRIVATE SECTOR COMMERCIALIZATION OF INNOVATIONS DERIVED FROM FEDERAL RESEARCH AND DEVELOPMENT, TO INCREASE SMALL BUSINESS PARTICIPATION IN FEDERAL RESEARCH AND DEVELOPMENT, AND TO FOSTER AND ENCOURAGE PARTICIPATION OF SOCIALLY AND ECONOMICALLY DISADVANTAGED SMALL BUSINESS CONCERNS AND WOMEN-OWNED SMALL BUSINESS CONCERNS IN TECHNOLOGICAL INNOVATION. THE SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAM IS USED TO FOSTER SCIENTIFIC AND TECHNOLOGICAL INNOVATION THROUGH COOPERATIVE RESEARCH AND DEVELOPMENT CARRIED OUT BETWEEN SMALL BUSINESS CONCERNS AND RESEARCH INSTITUTIONS, TO FOSTER TECHNOLOGY TRANSFER BETWEEN SMALL BUSINESS CONCERNS AND RESEARCH INSTITUTIONS, TO INCREASE PRIVATE SECTOR COMMERCIALIZATION OF INNOVATIONS DERIVED FROM FEDERAL RESEARCH AND DEVELOPMENT, AND TO FOSTER AND ENCOURAGE PARTICIPATION OF SOCIALLY AND ECONOMICALLY DISADVANTAGED SMALL BUSINESS CONCERNS AND WOMEN-OWNED SMALL BUSINESS CONCERNS IN TECHNOLOGICAL INNOVATION.
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Cambridge,
Massachusetts
021421027
United States
Geographic Scope
Single Zip Code
Related Opportunity
Analysis Notes
Amendment Since initial award the total obligations have increased 382% from $710,735 to $3,423,032.
The Broad Institute was awarded
Genomic Data Resource: Accelerating GWAS Associations Translation
Cooperative Agreement U24HG011453
worth $3,423,032
from National Human Genome Research Institute in September 2021 with work to be completed primarily in Cambridge Massachusetts United States.
The grant
has a duration of 4 years 7 months and
was awarded through assistance program 93.172 Human Genome Research.
The Cooperative Agreement was awarded through grant opportunity Genomic Community Resources (U24).
Status
(Ongoing)
Last Modified 8/20/25
Period of Performance
9/16/21
Start Date
4/30/26
End Date
Funding Split
$3.4M
Federal Obligation
$0.0
Non-Federal Obligation
$3.4M
Total Obligated
Activity Timeline
Transaction History
Modifications to U24HG011453
Additional Detail
Award ID FAIN
U24HG011453
SAI Number
U24HG011453-2997049721
Award ID URI
SAI UNAVAILABLE
Awardee Classifications
Nonprofit With 501(c)(3) IRS Status (Other Than An Institution Of Higher Education)
Awarding Office
75N400 NIH National Human Genome Research Institute
Funding Office
75N400 NIH National Human Genome Research Institute
Awardee UEI
H5G9NWEFHXN4
Awardee CAGE
5BP51
Performance District
MA-07
Senators
Edward Markey
Elizabeth Warren
Elizabeth Warren
Budget Funding
Federal Account | Budget Subfunction | Object Class | Total | Percentage |
---|---|---|---|---|
National Human Genome Research Institute, National Institutes of Health, Health and Human Services (075-0891) | Health research and training | Grants, subsidies, and contributions (41.0) | $1,368,903 | 100% |
Modified: 8/20/25