Cooperative Agreement U01HG013442
- Federal Cooperative Agreement Award Summary Vanderbilt University Medical Center received a $3.07 million Cooperative Agreement awarded on August 15, 2025, under the National Human Genome Research Institute's Human Genome Research program (CFDA 93.172) to develop a machine learning/artificial intelligence (ML/AI) tool that predicts clinical outcomes in individuals carrying pathogenic genetic variants. The project, which runs through July 31, 2027, addresses the clinical challenge of incomplete...
- Federal Project Grant Award Summary Baylor College of Medicine received a $719,909 Project Grant from the National Human Genome Research Institute (NHGRI) under the Human Genome Research program (CFDA 93.172), awarded March 13, 2026, with completion targeted for February 28, 2030. This grant supports the development of a novel, user-friendly local graph genome approach designed to characterize medically relevant complex genomic regions that have historically been challenging to resolve using...
- Federal Project Grant Award Summary The University of Massachusetts Medical School received a $418,750 Project Grant from the National Human Genome Research Institute (NHGRI) under the Human Genome Research program (CFDA 93.172), effective April 1, 2026 through March 31, 2028. This award funds the development of a cis-regulatory element (cCRE)-centric infrastructure within the ANVIL (Analysis Visualization Lab) cloud-based platform to advance understanding of how genetic variation affects gene...
- Federal Project Grant Award Summary The National Human Genome Research Institute (NHGRI) awarded Massachusetts General Hospital a $138,499 Project Grant effective July 1, 2025 through June 30, 2027 under the Human Genome Research program (CFDA 93.172). This award supports research on "Integrating Genetics and Socio-Environmental Factors to Predict Disease Progression," which aims to develop advanced predictive models that combine genetic and socio-environmental data to improve...
- Federal Project Grant Award Summary The National Human Genome Research Institute (NHGRI) awarded the University of Chicago a project grant totaling $196,296 under the Human Genome Research program (CFDA 93.172) to support research on the relationship between genetic relatedness and phenotypic covariance. The project, which commenced May 15, 2025, and will conclude April 30, 2027, focuses on deciphering how genetic relatedness matrices (GRM) and phenotypic covariance measurements function...
- Federal Project Grant Award Summary The National Human Genome Research Institute (NHGRI), through its Human Genome Research program (CFDA 93.172), awarded $877,621 to The Trustees of Columbia University in the City of New York on September 25, 2025, to support the "Disability, Disparities and Data Solidarity in Translational Genomic Research: The 3D-People Project." This project addresses a critical gap in translational genomic research (TGXR) participation by examining how to...
- Federal Project Grant Award Summary The National Human Genome Research Institute (NHGRI) awarded Massachusetts General Hospital a $3.29M Project Grant on September 17, 2025, under the Human Genome Research program (CFDA 93.172) for "Computational and Statistical Methods for Genetic Association Studies of Disease Course Over Time." The grant, with performance concluding August 31, 2029, supports the development of innovative computational tools and statistical methodologies to conduct...
- Federal Project Grant Award Summary The National Human Genome Research Institute (NHGRI) awarded University of California Santa Cruz $633,116 on September 26, 2025, under the Human Genome Research program (CFDA 93.172) to advance comparative genomics through three integrated research objectives. The project, which extends through June 30, 2029, will deliver scalable computational tools and methodologies for analyzing thousands of vertebrate genomes. Primary deliverables include: (1) an automated...
- This $138,428 project grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) will support the development of computationally tractable structured hierarchical models to identify complex genetic associations hidden from current methods. The grantee, J. David Gladstone Institutes, will analyze genomic and clinical trait data using machine learning to build predictive models for individualized disease risk assessment and personalized...
- This Project Grant award of $200,000 from the National Science Foundation's (NSF) Biological Sciences program (CFDA 47.074) supports research at Cornell University to optimize the Genotype Representation Graph (GRG) data structure for efficient analysis of whole genome sequencing (WGS) data on modern parallel computing architectures. The research aims to develop tools and infrastructure to enable faster and more scalable processing of large genomic datasets, such as the UK Biobank, in order to...
GENOME-WIDE CHARACTERIZATION OF COMPLEX VARIANTS AND THEIR PHENOTYPIC EFFECTS IN AFRICAN POPULATIONS - PROJECT SUMMARY ADVANCES IN OMICS TECHNOLOGY HAVE THE POWER TO PROVIDE INTEGRATIVE MODELS OF DISEASE RISK AND INFLUENCE HEALTH OUTCOMES. HOWEVER, THE UTILITY OF THESE MODELS HAS SO FAR BEEN LIMITED TO NON-AFRICAN POPULATIONS, DUE TO BIASES IN AVAILABLE DATASETS. FURTHER, EFFORTS TO IDENTIFY MEDICALLY RELEVANT GENETIC VARIANTS HAVE INCLUDED ONLY A SUBSET OF KNOWN GENETIC VARIANTS AND HAVE HAD LIMITED FOCUS ON PHENOTYPES MOST RELEVANT TO AFRICA. NEWLY AVAILABLE GENOMIC DATASETS FROM THE AFRICAN CONTINENT PROVIDE A RICH OPPORTUNITY TO BEGIN ADDRESSING THIS GAP. MOST LARGE GENOMICS EFFORTS IN BOTH AFRICANS AND NON-AFRICANS HAVE FOCUSED ON SINGLE NUCLEOTIDE POLYMORPHISMS (SNPS), EXCLUDING A LARGE FRACTION OF MORE COMPLEX AND ANCESTRY-SPECIFIC VARIANT TYPES SUCH AS GENOMIC REPEATS. HERE, WE CONSIDER MULTIPLE COMPLEX VARIANT TYPES, FOCUSING ON TANDEM REPEATS (TRS). TRS ARE WELL KNOWN TO CONTRIBUTE TO HUMAN DISEASE. FOR EXAMPLE, LARGE REPEAT EXPANSIONS ARE IMPLICATED IN HUNTINGTON'S DISEASE AND OTHER DISORDERS, AND STEPWISE VARIATION IN REPEAT COPY NUMBER AT TRS HAS BEEN IMPLICATED IN A VARIETY OF COMPLEX TRAITS. ALTHOUGH THEIR ROLE IN HUMAN PHENOTYPES IS WELL ESTABLISHED, DISCOVERY EFFORTS IN REPEAT REGIONS HAVE BEEN LARGELY LIMITED TO DATASETS AND PHENOTYPES DOMINATED BY NON-AFRICANS. WE HYPOTHESIZE THAT DETAILED ANALYSIS OF REPEAT VARIANTS IN AFRICA WILL IDENTIFY NOVEL DISEASE-ASSOCIATED LOCI INCLUDING PATHOGENIC REPEAT EXPANSIONS, AS WELL AS IMPROVE THE UTILITY OF RISK PREDICTION MODELS, ULTIMATELY LEADING TO IMPROVED DIAGNOSIS AND HEALTH OUTCOMES. OUR PROPOSAL LEVERAGES EXISTING AND NOVEL DATA ANALYSIS APPROACHES TO INTERROGATE TECHNICALLY CHALLENGING REPETITIVE REGIONS AND INTEGRATES DIVERSE GENOMICS DATASETS FROM ACROSS THE AFRICAN CONTINENT INCLUDING (1) WHOLE GENOME-SEQUENCING (WGS) FROM MORE THAN 1,000 INDIVIDUALS, (2) SNP ARRAY DATA FROM MORE THAN 10,000 INDIVIDUALS, AND (3) HEALTH OUTCOME INFORMATION RELATED TO TRYPANOSOMIASIS, HIV STATUS, CHRONIC KIDNEY DISEASE, CANCER RISK, AND CARDIOMETABOLIC TRAITS WITH HIGH PREVALENCE IN AFRICAN POPULATIONS. WE WILL FURTHER INCORPORATE EXISTING BIOBANKS CONTAINING TENS OF THOUSANDS OF DIVERSE GENOMES (ADMIXED AFRICANS FROM ALL OF US AND UK BIOBANK) TO VALIDATE FINDINGS AND IMPROVE POWER. THE OVERALL GOAL OF THIS PROPOSAL IS TO IMPROVE HEALTH OUTCOMES IN AFRICA USING INNOVATIVE DATA ANALYSIS AND MACHINE LEARNING TECHNIQUES. SPECIFICALLY, WE WILL CHARACTERIZE GENOME-WIDE TR VARIATION IN AFRICAN INDIVIDUALS (AIM 1), IDENTIFY SIGNALS OF POSITIVE AND NEGATIVE SELECTION AT THESE REGIONS (AIM 2), AND IDENTIFY TRS ASSOCIATED WITH MEDICALLY RELEVANT PHENOTYPES AND GENERATE IMPROVED ANCESTRY SPECIFIC POLYGENIC RISK SCORES (AIM 3). WE BRING TOGETHER A DIVERSE TEAM SPANNING AFRICA (HEADED BY MPIS ADEBIYI AND JJINGO) AND THE US (MPI GYMREK) WHICH HAS ALREADY INITIATED A FRUITFUL COLLABORATION. FURTHER, ANALYSES WILL BE PERFORMED PRIMARILY USING EXISTING AFRICAN SUPERCOMPUTING INFRASTRUCTURE AND LED BY NEW AND EARLY-STAGE AFRICAN INVESTIGATORS AND TRAINEES. OVERALL, THE PROPOSED AIMS WILL LIKELY IDENTIFY NOVEL MEDICALLY RELEVANT GENETIC VARIANTS AND CONTINUE TO FOSTER DATA SCIENCE CAPABILITIES WITHIN AFRICA.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $0 | 12/30/25 | ||
| Not listed | $247.2k | 9/22/25 | ||
| Not listed | $247.2k | 9/22/25 | ||
| Not listed | $250.0k | 8/19/24 | ||
| Not listed | $0 | 12/4/23 |