The NIH genetic testing registry: a new, centralized database of genetic tests to enable access to comprehensive information and improve transparency

Rubinstein, Wendy S.; Maglott, Donna; Lee, Jennifer M.; Kattman, B; Malheiro, Adriana; Ovetsky, Michael; Hem, Vichet; Gorelenkov, Viatcheslav; Song, Guangfeng; Wallin, Craig; Husain, Nora; Chitipiralla, Shanmuga; Katz, Kenneth S.; Hoffman, Douglas; Jang, Wonhee; Johnson, Mark W.; Karmanov, Fedor; Ukrainchik, Alexander; Денисенко, М.Б.; Fomous, Cathy; Hudson, Kathy; Ostell, James

doi:10.1093/nar/gks1173

Cited by 148 publications

(118 citation statements)

References 12 publications

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“…The Genetic Testing Registry provides a clearinghouse for information regarding laboratories offering clinical genetic tests (http://www.ncbi.nlm.nih.gov/gtr/) (59). Laboratories voluntarily submit information about the tests they offer.…”

Section: Resourcesmentioning

confidence: 99%

Preemptive Clinical Pharmacogenetics Implementation: Current Programs in Five US Medical Centers

Dunnenberger¹,

Crews²,

Hoffman³

et al. 2015

Annu. Rev. Pharmacol. Toxicol.

443

381

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Although the field of pharmacogenetics has existed for decades, the implementation of, pharmacogenetic testing in clinical care has been slow. There are numerous publications, describing the barriers to clinical implementation of pharmacogenetics. Recently, several freely, available resources have been developed to help address these barriers. In this review we, discuss current programs that use preemptive genotyping to optimize the pharmacotherapy of, patients. Array-based preemptive testing includes a large number of relevant pharmacogenes, that impact multiple high-risk drugs. Using a preemptive approach allows genotyping results to, be available prior to any prescribing decision so that genomic variation may be considered as, an inherent patient characteristic in the planning of therapy. This review describes the common, elements among programs that have implemented preemptive genotyping and highlights key, processes for implementation, including clinical decision support.

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Section: Resourcesmentioning

confidence: 99%

Preemptive Clinical Pharmacogenetics Implementation: Current Programs in Five US Medical Centers

Dunnenberger¹,

Crews²,

Hoffman³

et al. 2015

Annu. Rev. Pharmacol. Toxicol.

443

381

View full text Add to dashboard Cite

show abstract

“…Finally, the number of NIH-registered genetic tests for a given gene is a useful proxy for its current clinical testing volume and for the likelihood of identifying additional VUSs ( Figure 1B). 28 Genes with large numbers of registered tests and existing VUSs are clearly in need of additional variant-interpretation support.…”

Section: Prioritization Of Functional Elementsmentioning

confidence: 99%

Variant Interpretation: Functional Assays to the Rescue

Starita

Ahituv

Dunham

et al. 2017

The American Journal of Human Genetics

322

294

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Classical genetic approaches for interpreting variants, such as case-control or co-segregation studies, require finding many individuals with each variant. Because the overwhelming majority of variants are present in only a few living humans, this strategy has clear limits. Fully realizing the clinical potential of genetics requires that we accurately infer pathogenicity even for rare or private variation. Many computational approaches to predicting variant effects have been developed, but they can identify only a small fraction of pathogenic variants with the high confidence that is required in the clinic. Experimentally measuring a variant's functional consequences can provide clearer guidance, but individual assays performed only after the discovery of the variant are both time and resource intensive. Here, we discuss how multiplex assays of variant effect (MAVEs) can be used to measure the functional consequences of all possible variants in disease-relevant loci for a variety of molecular and cellular phenotypes. The resulting large-scale functional data can be combined with machine learning and clinical knowledge for the development of ''lookup tables'' of accurate pathogenicity predictions. A coordinated effort to produce, analyze, and disseminate large-scale functional data generated by multiplex assays could be essential to addressing the variant-interpretation crisis.

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“…This information is mined from two resources, GeneTests (23) and the recently added Genetic Testing Registry (24). These display a link to a disease page in the external source, where related laboratories and tests are listed.…”

Section: Gene-disease Connectionsmentioning

confidence: 99%

MalaCards: an amalgamated human disease compendium with diverse clinical and genetic annotation and structured search

et al. 2016

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The MalaCards human disease database (http://www.malacards.org/) is an integrated compendium of annotated diseases mined from 68 data sources. MalaCards has a web card for each of ∼20 000 disease entries, in six global categories. It portrays a broad array of annotation topics in 15 sections, including Summaries, Symptoms, Anatomical Context, Drugs, Genetic Tests, Variations and Publications. The Aliases and Classifications section reflects an algorithm for disease name integration across often-conflicting sources, providing effective annotation consolidation. A central feature is a balanced Genes section, with scores reflecting the strength of disease-gene associations. This is accompanied by other gene-related disease information such as pathways, mouse phenotypes and GO-terms, stemming from MalaCards’ affiliation with the GeneCards Suite of databases. MalaCards’ capacity to inter-link information from complementary sources, along with its elaborate search function, relational database infrastructure and convenient data dumps, allows it to tackle its rich disease annotation landscape, and facilitates systems analyses and genome sequence interpretation. MalaCards adopts a ‘flat’ disease-card approach, but each card is mapped to popular hierarchical ontologies (e.g. International Classification of Diseases, Human Phenotype Ontology and Unified Medical Language System) and also contains information about multi-level relations among diseases, thereby providing an optimal tool for disease representation and scrutiny.

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The NIH genetic testing registry: a new, centralized database of genetic tests to enable access to comprehensive information and improve transparency

Cited by 148 publications

References 12 publications

Preemptive Clinical Pharmacogenetics Implementation: Current Programs in Five US Medical Centers

Preemptive Clinical Pharmacogenetics Implementation: Current Programs in Five US Medical Centers

Variant Interpretation: Functional Assays to the Rescue

MalaCards: an amalgamated human disease compendium with diverse clinical and genetic annotation and structured search

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