Considerations for clinical curation, classification and reporting of low-penetrance and low effect size variants associated with disease risk
Ozlem Senol-Cosar, Ryan J. SchmidtiD, Emily QianiD, Derick C. Hoskinson, Heather Mason‐SuaresiD, Birgit FunkeiD, Matthew S. LeboiD
Abstract
PurposeClinically relevant variants exhibit a wide range of penetrance. Medical practice has traditionally focused on highly penetrant variants with large effect sizes and, consequently, classification and clinical reporting frameworks are tailored to that variant type. At the other end of the penetrance spectrum, where variants are often referred to as "risk alleles", traditional frameworks are no longer appropriate. This has led to inconsistency in how such variants are interpreted and classified. Here, we describe a conceptual framework to begin addressing this gap. MethodsWe used a set of risk alleles to define data elements that can characterize the validity of reported disease associations. We assigned weight to these data elements and established classification categories expressing confidence levels. This framework was then expanded to develop criteria for inclusion of risk alleles on clinical reports. ResultsFoundational data elements include cohort size, quality of phenotyping, statistical significance, and replication of results. Criteria for determining inclusion of risk alleles on clinical reports include presence of clinical management guidelines, effect size, severity of the associated phenotype, and effectiveness of intervention. ConclusionsThis framework represents an approach for classifying risk alleles and can serve as a foundation to catalyze community efforts for refinement.
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 31
- FWCI
- 1.95
- Field percentile
- top 14%
- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Classification of Variants of Reduced Penetrance in High Penetrance Cancer Susceptibility Genes: Framework for Genetics Clinicians and Clinical Scientists by CanVIG-UK (Cancer Variant Interpretation Group-UK)
Alice Garrett, Sophie Allen, … J. Williams·Genetics in MedicinePeer-reviewed·Oct 24, 2024
- Ancestrally and Temporally Diverse Analysis of Penetrance of Clinical Variants in 72,434 Individuals
Iain S. Forrest, Kumardeep Chaudhary, … Ron Do·medRxiv·Mar 11, 2021
- Assessing the pathogenicity, penetrance and expressivity of putative disease-causing variants in a population setting
Caroline Fiona Wright, Ben West, … Michael N. Weedon·The American Journal of Human GeneticsPeer-reviewed·Jan 18, 2019
- VarSight: Prioritizing Clinically Reported Variants with Binary Classification Algorithms
Undiagnosed Diseases Network, James Holt, … Elizabeth A. Worthey·BMC BioinformaticsPeer-reviewed·Oct 15, 2019
- Clinical validation of large-scale functional assays: insights from 2,120 gene-truthset-assay evaluations
Sophie Allen, Charlie F Rowlands, … Cancer Variant Interpretation Group UK (CanVIG-UK)·medRxiv·Jul 14, 2026
- Endophenotype Effect Sizes Provide Evidence Supporting Variant Pathogenicity in Monogenic Disease Susceptibility Genes
Jennifer L. Halford, Valerie N. Morrill, … Steven A. Lubitz·Nature CommunicationsPeer-reviewed·Aug 30, 2022