Poster ID
P-02
Poster Title
Making Genetic Tests Computable: Integrating NIH GTR with GA4GH Standards
Authors
Adriana Malheiro, National Center for Biotechnology Information (NCBI), NLM, NIH
Thilakam Venkatapathi, National Center for Biotechnology Information (NCBI), NLM, NIH
Douglas J Hoffman, National Center for Biotechnology Information (NCBI), NLM, NIH
Sahithi Punyasamudram, National Center for Biotechnology Information (NCBI), NLM, NIH
Marilu Hoeppner, National Center for Biotechnology Information (NCBI), NLM, NIH
Brandi Kattman, National Center for Biotechnology Information (NCBI), NLM, NIH
Thilakam Venkatapathi, National Center for Biotechnology Information (NCBI), NLM, NIH
Douglas J Hoffman, National Center for Biotechnology Information (NCBI), NLM, NIH
Sahithi Punyasamudram, National Center for Biotechnology Information (NCBI), NLM, NIH
Marilu Hoeppner, National Center for Biotechnology Information (NCBI), NLM, NIH
Brandi Kattman, National Center for Biotechnology Information (NCBI), NLM, NIH
Abstract
GA4GH standards increasingly connect genomic data, clinical context, and responsible data use. Yet the test itself is often weakly represented: why it was ordered, what it was intended to detect, how it was performed, and which laboratory-defined assay generated the result. The NIH Genetic Testing Registry (GTR®, https://www.ncbi.nlm.nih.gov/gtr) can help close this gap by providing public, structured descriptions of orderable clinical and research genetic and genomic tests offered by labs worldwide. Each test is assigned a versioned unique identifier (ID) and includes testing indication, targets, methods, performance characteristics, and lab information. By organizing tests around standardized conditions, targets, intended uses and methodologies, GTR can help model how test descriptions and test indications may be represented consistently across clinical genomics systems. GTR IDs and test descriptions could serve as a computable test-metadata layer across standards.
For Clinical & Phenotype Data Capture, GTR IDs can represent the performed or considered test in Phenopackets and clinical reports, linking phenotype, test target, specimen, methods, and result context. For Discovery workstream, GTR fields can become Beacon/Data Connect facets for searches related to test, gene, condition, method, and lab. For Genomic Knowledge Standards, GTR can link variant and gene to test availability. For AI workstream, GTR test descriptions, update date, and lab information can support transparency, responsible clinical decision support, and evaluation of AI-generated test recommendations. GTR can support the Technical Alignment Sub-Committee by providing consistent representation of genetic tests across GA4GH products. GA4GH Implementation Forum may map GTR test records into GA4GH-compatible schemas like Phenopackets for clinical context or Data Connect for searchable test data fields. GTR can support the National Initiatives Forum by serving as a reference test-catalog of national genomic laboratories and enabling the comparison of catalogs.
This work was supported by the National Center for Biotechnology Information of the National Library of Medicine (NLM), National Institutes of Health (NIH). The contributions of the NIH author(s) are considered Works of the United States Government. The findings and conclusions presented in this paper are those of the author(s) and do not necessarily reflect the views of the NIH or the U.S. Department of Health and Human Services.
For Clinical & Phenotype Data Capture, GTR IDs can represent the performed or considered test in Phenopackets and clinical reports, linking phenotype, test target, specimen, methods, and result context. For Discovery workstream, GTR fields can become Beacon/Data Connect facets for searches related to test, gene, condition, method, and lab. For Genomic Knowledge Standards, GTR can link variant and gene to test availability. For AI workstream, GTR test descriptions, update date, and lab information can support transparency, responsible clinical decision support, and evaluation of AI-generated test recommendations. GTR can support the Technical Alignment Sub-Committee by providing consistent representation of genetic tests across GA4GH products. GA4GH Implementation Forum may map GTR test records into GA4GH-compatible schemas like Phenopackets for clinical context or Data Connect for searchable test data fields. GTR can support the National Initiatives Forum by serving as a reference test-catalog of national genomic laboratories and enabling the comparison of catalogs.
This work was supported by the National Center for Biotechnology Information of the National Library of Medicine (NLM), National Institutes of Health (NIH). The contributions of the NIH author(s) are considered Works of the United States Government. The findings and conclusions presented in this paper are those of the author(s) and do not necessarily reflect the views of the NIH or the U.S. Department of Health and Human Services.