ArticleAmerican journal of human genetics2017
Variant Interpretation: Functional Assays to the Rescue.
Article in American journal of human genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 235 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
235 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Clinical management among individuals with variant of uncertain significance in hereditary cancer: A systematic review and meta-analysis.Clinical genetics · 2021Pooled it
- Genetic kidney diseases: Decoding molecular taxonomies to drive precision nephrology and therapeutic innovation.Genes & diseases · 2027Review
- Functional analysis of germline RUNX1 variants identified in individuals with suspected familial platelet disorder.Blood advances · 2026Article
- Advancing genetic pathogenicity prediction with three-dimensional proteoform-phenotype analysis.medRxiv : the preprint server for health sciences · 2026Article
- Applying the FDA's plausible mechanism guidance across the rare disease landscape.Nature genetics · 2026Article
- Systematic and proactive evaluation of AIRE missense variant effects.American journal of human genetics · 2026Article
- Article
- Evolution-guided yeast complementation reveals functional differences in human PSPH variants.FEBS open bio · 2026Article
- Kozak sequence libraries for systematically characterizing transgenes across expression levels.Nucleic acids research · 2026Article
- Advancing precision hepatology for rare paediatric liver diseases.European journal of pediatrics · 2026Review
- Deep mutational scanning reveals pharmacologically relevant insights into TYK2 signaling and disease.eLife · 2026Article
- Lynch Syndrome: An Update of Underlying Molecular Mechanisms, Phenotypes and Methods to Classify Variants of Uncertain Significance.Biomedicines · 2026Review
- Phenotype-Specific Recalibration of MAVE Data Enables Repurposing ofmedRxiv : the preprint server for health sciences · 2026Article
- Article
- Massively parallel functional genomic assays in endocrinology: from promise to delivery.Journal of molecular endocrinology · 2026Review
- PoolParty: streamlined design of DNA sequence libraries in Python.bioRxiv : the preprint server for biology · 2026Article
- Phenotypic prediction of missense variants via deep contrastive learning.Nature biomedical engineering · 2026Article
- Massively parallel quantification of mutational impact on IAPP amyloid formation.Nature communications · 2026Article
- Creating an atlas of variant effects to resolve variants of uncertain significance and guide cardiovascular medicine.Nature reviews. Cardiology · 2026Review
- A scalable approach to resolving variants of uncertain significance.bioRxiv : the preprint server for biology · 2026Article
175 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
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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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.