ArticleAmerican journal of human genetics2025
Consultation informs strategies for improving the use of functional evidence in variant classification.
Article in American journal of human genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed.
- 'Truthsets' for clinical validation of large-scale functional assays: Practice recommendations from Cancer Variant Interpretation Group UK (CanVIG-UK).medRxiv : the preprint server for health sciences · 2026Article
- Functional assays for BRCA1 and BRCA2 variant analysis: new tools and their applications.NPJ breast cancer · 2026Review
- A scalable approach to resolving variants of uncertain significance.bioRxiv : the preprint server for biology · 2026Article
- Multiplexed assays of variant effect for clinical variant interpretation.Nature reviews. Genetics · 2026Review
- ClinMAVE: a curated database for clinical application of data from multiplexed assays of variant effect.Nucleic acids research · 2026Article
- Functional assessment of protein variants in structured domains by fluorescence cross-correlation spectroscopy.Scientific reports · 2026Article
- MaveMD: A functional data resource for genomic medicine.medRxiv : the preprint server for health sciences · 2025Article
- Validating data from multiplex assays of variant effect: A CanVIG-UK national survey of NHS clinical scientists.American journal of human genetics · 2025Article
- Insights on improving accessibility and usability of functional data to unlock their potential for variant interpretation.American journal of human genetics · 2025Article
Corrections and comments
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Authors and funding
17 authors.
Funding
Abstract
When investigating whether a variant identified by diagnostic genetic testing is causal for disease, applied genetics professionals evaluate all available evidence to assign a clinical classification. Functional assays of higher and higher throughput are increasingly being generated and, when appropriate, can provide strong functional evidence for or against pathogenicity in variant classification. Despite functional assay data representing unprecedented value for genomic diagnostics, challenges remain around the application of functional evidence in variant curation. To investigate a growing gap articulated in recent international studies, we surveyed genetic diagnostic professionals in Australasia to assess their application of functional evidence in clinical practice. The survey results echo the universal difficulty in evaluating functional evidence but expand on this by indicating that even self-proclaimed expert respondents are not confident to apply functional evidence, mainly due to uncertainty around practice recommendations. Respondents also identified the need for support resources and educational opportunities, and in particular requested expert recommendations and updated practice guidelines to improve translation of experimental data to curation evidence. We then collated a list of 226 functional assays and the evidence strength recommended by 19 ClinGen Variant Curation Expert Panels. Specific assays for more than 45,000 variants were evaluated, but evidence recommendations were generally limited to lower throughput and strength. As an initial step, we provide our collated list of assay evidence as a source of international expert opinion on the evaluation of functional- evidence and conclude that these results highlight an opportunity to develop additional support resources to fully utilize functional evidence in clinical practice.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.