Advancing the implementation of variant-level functional data into clinical databases and clinical practice

Active Project Grant Awarded Last action

Award ID
R01HG013025
Recipient
Awarding agency
Obligated
$7,133,664

Award facts

Assistance listing
93.172 Human Genome Research
Completion date 71% complete
Place of performance
Seattle, WA 98195, USA

Award details come from USAspending.gov.

Description

Abstract
One of the major challenges limiting the potential of genomic medicine to revolutionize clinical care is the current lack of knowledge about the function of most human genetic variants. Consequently, the majority of clinically encountered genetic variants are classied as variants of uncertain signicance (VUS), which cannot be used for clinical decision making given their unknown relationship to disease. The VUS problem is particularly acute for individuals from populations historically excluded from research, compounding existing healthcare inequities when implementing genomic medicine. Variant-level functional data has the potential to overcome many of these challenges by providing pathogenicity information for variants from diverse populations. For example, we and others have demonstrated that multiplexed assays of variant effect (MAVES) can resolve a large fraction of VUS in clinically important genes (e.g., 49% of BRCA1 VUS, 69% of TP53 VUS, and 93% of DDX3X VUS), and several U.S. And international consortia are currently using MAVES to produce functional data for all possible coding and non-coding variants associated with all genes that have been linked to human disease. Given the potential of functional information to augment the implementation of genomic medicine, clinical guidelines have recently been updated to recommend the use of variant-level functional data when interpreting variant pathogenicity. However, despite the potential clinical utility of large-scale functional datasets, how best to implement them such that clinicians can appropriately incorporate variant functional data into clinical practice remains unknown. In this proposal we aim to address this unmet need in genomic medicine using the following approach: first, we will generate a framework for standardizing and disseminating curated large-scale functional data into clinician-facing resources, and implement this framework into clinvar (aim 1) second, we will perform a proof-of-concept integration of variant level functional data in clinvar into two large clinical practices to evaluate the clinical uptake and impact of variant-level functional data (aim 2). Finally, we will build and disseminate resources for training clinicians on best practices for integrating functional data into clinical practice (aim 3). Overall, this proposal has the potential to significantly advance the implementation of genomic data into clinical practice by enabling clinicians to appropriately leverage emerging variant-level functional data to resolve VUS, thereby making genomic medicine more equitable and impactful.

Transactions

Action Obligated Date
Amendment $796,220
Amendment $715,577
Amendment $64,814
Amendment $64,814
Amendment $729,157
Amendment $729,157
Amendment $729,157
Amendment $0
Amendment $0
Amendment $0
Amendment $826,192
Amendment $826,192
Amendment $826,192
Original award $826,192
Show all 14

Subawards

Subrecipient Amount Awarded
The Walter And Eliza Hall Institute Of Medical Research Advancing the implementation of variant-level functional data into clinical databases and clinical practice. $58,558
The Walter And Eliza Hall Institute Of Medical Research $57,297
The Walter And Eliza Hall Institute Of Medical Research $56,064

Quick answers

Who received award R01HG013025?

R01HG013025 was awarded to University Of Washington by National Human Genome Research Institute (National Institutes of Health) on June 1, 2023.

How much is award R01HG013025 worth?

$7,133,664 has been obligated on R01HG013025.

On GovTribe

See this award's full record

  • Every transaction and subaward
  • The recipient's other awards and teaming partners
  • Similar grant awards
  • Ask GovTribe AI about this award