How to Interpret Variants of Uncertain Significance (VUS): A Practical Guide to Reclassification and Clinical Communication

By Dr. Zubair Khalid, DVM, MS, PhD · 2026-08-21

Key Takeaways

• Variants of Uncertain Significance (VUS) are common, affecting approximately 41% of individuals undergoing diagnostic genetic testing, necessitating systematic management rather than ad-hoc review.
• VUS classification relies on integrating multiple evidence domains, including population frequency data from large databases (e.g., gnomAD), in silico computational predictions (e.g., CADD-Phred, SIFT), functional assays (e.g., ATM functional assay), and family segregation studies.
• A structured workflow for VUS management involves initial classification, continuous evidence monitoring (quarterly to annually), periodic reclassification reviews triggered by new data or scheduled intervals, and prompt communication of outcomes to patients and referring providers.
• Subclassifying VUS can stratify risk, with variants in lower subclasses demonstrating a significantly lower likelihood of reclassification to pathogenic or likely pathogenic status compared to those in higher subclasses.
• Reclassification of VUS is an ongoing process, with evidence-based reviews crucial for updating classifications as population databases expand and new functional or clinical data emerge, preventing static interpretations from becoming outdated.
• Effective communication of VUS results and subsequent reclassifications is paramount, requiring clear explanations of uncertainty, potential for change, and implications for medical management to avoid patient misinterpretation.

A variant of uncertain significance (VUS) is a genetic variant for which current evidence is insufficient to determine whether it causes disease. This article provides a systematic workflow for laboratory professionals, researchers, and clinicians to manage VUS results, including periodic re-evaluation using new data sources, structured reclassification procedures, and clear communication strategies for patients and referring providers. The practical outcome is a reproducible process that reduces the duration of uncertainty and supports informed clinical decisions without overstating what current evidence allows.

Scope and Reader Context

This guidance applies to germline variant interpretation in diagnostic and research settings. The primary audience includes molecular laboratory professionals who issue variant reports, genetic counselors who communicate results, and researchers who generate functional or population data that may inform classification. The workflow described here assumes access to standard bioinformatics infrastructure and follows the evidence framework established by professional guidelines, with emphasis on the practical steps that laboratories can implement with existing resources.

The scale of the VUS problem is substantial. In a large cohort study of nearly 1.7 million individuals who underwent diagnostic genetic testing for hereditary disorders between 2014 and 2022, approximately 41 percent had at least one VUS and about 32 percent had only VUS results 8. These findings demonstrate that VUS results are not rare events but rather a routine outcome of clinical genetic testing. Laboratories and clinicians therefore need a defined process for managing these results instead of treating each VUS as an isolated case.

The VUS Classification Framework

Definition and Categories

A VUS occupies the middle ground between benign and pathogenic classifications. The classification system used by clinical laboratories assigns variants to five categories: pathogenic, likely pathogenic, uncertain significance, likely benign, and benign. The VUS category includes variants where evidence is contradictory, insufficient, or of limited strength. This category is not homogeneous. Some VUS have substantial evidence leaning toward pathogenicity, while others have evidence suggesting a benign role 11.

Evidence Types Used in Classification

Classification relies on multiple evidence domains. Population frequency data from large databases helps establish whether a variant is too common in healthy individuals to be a rare disease cause. Computational prediction tools provide in silico assessments of potential functional impact. Functional assays test variant effects in experimental systems. Segregation analysis examines whether the variant tracks with disease in families. Case-control studies compare variant frequencies between affected and unaffected individuals. Each evidence type carries different weight, and the integration of multiple lines of evidence strengthens classification decisions.

The Role of VUS Subclassification

Some clinical laboratories have begun subclassifying VUS to reflect the direction and strength of available evidence. A study examining four clinical laboratories that use VUS subclasses found that variants in the lowest subclass were never reclassified as likely pathogenic or pathogenic, while variants in the highest subclass were much more likely to be reclassified as pathogenic or likely pathogenic 11. This finding has practical implications. Subclassification helps laboratories prioritize which VUS warrant intensive follow-up investigation and helps clinicians understand which results are more likely to change with additional data.

At a Glance: VUS Management Workflow

Core Principles of VUS Interpretation

Evidence Must Be Current

Variant classification is not a one-time event. The evidence base for any given variant changes as population databases grow, functional assays improve, and clinical data accumulate. Laboratories that maintain periodic review processes can reclassify variants when sufficient new evidence emerges. The large cohort study referenced earlier demonstrated that reclassification occurs across many disease genes and that different evidence types contribute to these changes 8. A static classification that is never revisited will become outdated.

Evidence Quality Determines Confidence

Not all evidence carries equal weight. Population frequency data from well-curated databases provides strong support for benign classification when a variant is common. Functional assays that have been calibrated with known benign and pathogenic controls provide strong support when results align with those controls. Computational predictions alone rarely suffice for reclassification. The ATM functional assay study illustrates this principle. The assay was calibrated using 48 benign and pathogenic control variants and achieved 100 percent specificity and 97 percent sensitivity in distinguishing neutral from deleterious variants 7. This calibration step is essential because unvalidated assays cannot support clinical classification decisions.

Uncertainty Is Not Absence of Information

A VUS result does not mean the variant has no effect. It means the current evidence does not meet the threshold for a definitive classification. Some VUS will eventually be reclassified as pathogenic, and others will be reclassified as benign. The subclassification approaches described earlier help distinguish these possibilities 11. Clinicians should communicate this distinction to patients so that a VUS result is understood as an evidence gap instead of a negative finding.

Practical Workflow for VUS Re-Evaluation

Step 1: Establish a Variant Tracking System

Laboratories need a systematic method for tracking VUS across patients and time. A spreadsheet or database should record the variant identifier, gene, genomic coordinates, initial classification date, evidence reviewed, and the next review date. This tracking system serves as the foundation for periodic re-evaluation. Without such a system, VUS results may remain unchanged indefinitely even when new evidence would support reclassification.

Step 2: Monitor New Evidence Sources

Regular monitoring of evidence sources is the core activity of VUS re-evaluation. Population frequency databases should be checked for updated allele counts. Published literature should be searched for functional studies, case reports, and segregation data involving the specific variant. The NCBI provides access to multiple databases that aggregate genetic variation data, literature, and clinical assertions 1. Researchers and laboratory professionals can use these resources to stay current on variant-specific evidence.

Step 3: Apply Updated Evidence to Classification

When new evidence is identified, the laboratory should reassess the variant using the standard classification framework. The reclassification decision should be documented with the specific evidence that changed the classification. If the evidence remains insufficient, the variant stays in the VUS category and the review date is updated. If the evidence now supports a different classification, the laboratory should issue an updated report.

Step 4: Communicate Reclassification Results

Reclassification outcomes must be communicated to the ordering clinician and, through that clinician, to the patient. The communication should explain what changed, why it changed, and what the new classification means for medical management. A reclassification from VUS to pathogenic may warrant changes in screening or preventive measures. A reclassification from VUS to benign may relieve unnecessary anxiety and reduce inappropriate interventions.

Step 5: Document and Archive the Process

Every reclassification decision should be documented with the evidence reviewed, the classification rationale, and the date of the decision. This documentation supports quality assurance, enables future audits, and provides a record that can be shared with other laboratories or databases. The Galaxy Training Network offers accessible training on reproducible analysis workflows that can help laboratories standardize their variant interpretation processes 4.

Data Inputs for VUS Interpretation

Population Frequency Data

Large-scale population sequencing projects have transformed variant interpretation by providing allele frequencies for millions of variants. A variant that appears frequently in healthy populations is unlikely to be a rare highly penetrant disease cause. Conversely, a variant that is absent from population databases may be either a rare pathogenic variant or a rare benign variant. Population frequency data must be interpreted in the context of the disease prevalence and inheritance pattern. The NCBI provides access to population variation databases that aggregate data from multiple studies 1.

Functional Assay Data

Functional assays provide direct experimental evidence about variant effects. These assays measure a biological consequence of the variant, such as protein function, cellular localization, or pathway activation. The ATM study described earlier developed a functional assay that distinguished neutral from deleterious variants with high accuracy and enabled reclassification of 79 of 88 VUS (90 percent) when integrated with other evidence 7. Similarly, the SpeckSeq method for MEFV variants identified gain-of-function mutations that were poorly predicted by computational tools and supported reclassification that led to new diagnoses 9. These examples demonstrate that functional data can be decisive when computational predictions are ambiguous.

Computational Prediction Scores

In silico prediction tools estimate the likelihood that a variant affects protein function. These tools use sequence conservation, protein structure, and biochemical properties of amino acid substitutions to generate scores. A study of children with global developmental delay and intellectual disability used CADD-Phred and SIFT prediction scores to annotate VUS and estimated that 221 VUS were potentially damaging 10. However, the same study found that 18 of these predicted damaging variants were present in the healthy population, illustrating the limitation of computational predictions alone 10. Computational scores can prioritize variants for further investigation but cannot replace functional or clinical evidence.

Segregation and Clinical Data

Family segregation data and clinical observations contribute evidence about variant pathogenicity. If a variant segregates with disease in multiple affected family members, this supports pathogenicity. If affected individuals do not carry the variant, this argues against pathogenicity. Clinical data from large patient cohorts can also reveal phenotypic patterns associated with specific variants. The ATM study found that clinical characteristics from a database of 1,134 breast cancer patients were distinct for carriers of neutral versus deleterious ATM variants 7. This type of clinical correlation strengthens classification decisions.

Options and Tradeoffs in VUS Management

Option 1: Passive Monitoring

A laboratory may choose to reclassify VUS only when prompted by external events, such as a clinician inquiry or a new publication. This approach requires minimal resources but leaves many VUS unclassified for extended periods. Patients who received VUS results may never learn of reclassifications that occur years later.

Option 2: Scheduled Periodic Review

A laboratory may establish a fixed review interval, such as annual or biennial re-evaluation of all VUS. This approach ensures that every VUS is revisited on a regular schedule. The tradeoff is the staff time required to review potentially hundreds or thousands of variants. The subclassification approaches described earlier can help prioritize which variants warrant the most intensive review 11.

Option 3: Evidence-Triggered Review

A laboratory may reclassify a VUS when specific evidence triggers are met, such as a new population frequency that exceeds a benign threshold or a published functional study involving the variant. This approach is efficient because it focuses resources on variants with new evidence. The challenge is establishing reliable monitoring systems to detect evidence triggers.

Option 4: Hybrid Approach

Most laboratories will benefit from combining scheduled reviews with evidence-triggered reviews. A scheduled annual review catches variants that accumulate evidence gradually, while evidence-triggered reviews respond quickly to significant new data. The hybrid approach balances thoroughness with efficiency.

Records and Measurements for VUS Management

Essential Records

Laboratories should maintain the following records for each VUS:

• Variant identifier and genomic coordinates
• Gene and transcript information
• Initial classification and date
• Evidence reviewed at initial classification
• VUS subclass if applicable
• Review dates and outcomes
• Reclassification decisions with rationale
• Communication dates and methods

Quality Metrics

Laboratories can track several metrics to assess their VUS management program:

• Percentage of VUS reclassified within 1, 2, and 5 years
• Proportion of reclassifications toward pathogenic versus benign
• Time from initial classification to reclassification
• Number of VUS with no evidence review in the past 2 years
• Clinician and patient satisfaction with reclassification communication

Benchmarking

The large cohort study provides context for expected reclassification rates. Among the 1,689,845 individuals tested, 692,227 had at least one VUS and 535,385 had only VUS results 8. Laboratories can compare their reclassification rates with published benchmarks to assess whether their review processes are effective.

Common Failure Patterns in VUS Management

Failure to Revisit Initial Classifications

The most common failure is treating VUS classification as permanent. Variants that were classified as VUS when population databases were small may now have sufficient frequency data for benign classification. Laboratories that do not schedule periodic reviews will miss these reclassification opportunities.

Overreliance on Computational Predictions

Computational tools are useful for prioritization but cannot replace experimental or clinical evidence. The developmental delay study found that some variants predicted to be damaging were present in the healthy population 10. Laboratories that reclassify based on computational scores alone risk both false positive and false negative classifications.

Inadequate Functional Assay Validation

Functional assays must be validated with known controls before their results can support clinical classification. The ATM assay achieved high accuracy because it was calibrated with 48 benign and pathogenic controls 7. Assays without such calibration may produce results that are difficult to interpret or that do not reflect true variant effects.

Poor Communication of Uncertainty

Clinicians and laboratories sometimes communicate VUS results in ways that cause patients to misinterpret the finding. A VUS may be understood as a definitive disease-causing mutation or as a completely normal result. Neither interpretation is correct. The communication strategy described in the next section addresses this failure pattern.

Delayed Reclassification Communication

When a VUS is reclassified, the updated result must reach the patient and clinician promptly. Delays in communication can lead to continued inappropriate medical management or continued anxiety. Laboratories should have a defined process for issuing updated reports and notifying ordering clinicians.

Communication Strategies for VUS Results

Initial Result Communication

When a VUS is first reported, the clinician should explain that the result means the laboratory cannot currently determine whether the variant affects health. The clinician should emphasize that this is a common outcome and does not necessarily indicate a disease risk. The patient should be told that the classification may change as more evidence becomes available and that the laboratory will monitor the variant.

Reclassification Communication

When a VUS is reclassified, the communication should explain the change clearly. For a reclassification to pathogenic or likely pathogenic, the clinician should discuss the medical management implications and any recommended screening or preventive measures. For a reclassification to benign or likely benign, the clinician should explain that the variant is now considered not to cause disease and that no further action is needed based on this result.

Template for Patient Letter

A patient letter for VUS reclassification should include the following elements:

• The variant and gene involved
• The previous classification and the new classification
• The evidence that led to the reclassification
• What the new classification means for the patient and family
• Whether any medical management changes are recommended
• Contact information for questions and follow-up

Genetic Counseling Discussion Points

Genetic counselors should address the following topics when discussing VUS results:

• The meaning of uncertainty in genetic testing
• The likelihood that the classification will change
• The evidence types that might lead to reclassification
• The implications for family members
• The distinction between a VUS and a pathogenic variant
• The option for periodic follow-up and re-contact

Professional Escalation Criteria

When to Escalate to a Variant Curation Committee

A laboratory should escalate a VUS to a formal variant curation committee when:

• Multiple evidence types are available but contradictory
• The variant is in a gene with established clinical actionability
• The variant has been observed in multiple unrelated affected individuals
• A reclassification decision would change medical management
• The variant is the subject of conflicting interpretations between laboratories

When to Refer for Research Investigation

A VUS may warrant referral for research investigation when:

• The variant is in a gene with limited functional assay options
• The variant is recurrent in the patient population
• The variant affects a protein domain with known functional importance
• Family segregation studies are feasible but have not been performed
• The variant is in a gene where VUS are particularly common

When to Recommend Clinical Follow-Up

Clinicians should consider clinical follow-up for patients with VUS when:

• The VUS is in a gene associated with the patient's phenotype
• The VUS subclassification suggests possible pathogenicity
• Additional family members could provide segregation data
• The patient has clinical features that overlap with the gene-associated condition
• The result would change management if reclassified as pathogenic

Limitations and Evidence Gaps

Incomplete Functional Coverage

Functional assays are not available for most genes. The ATM study developed a new assay because existing options were lacking for that gene 7. For many genes, no validated functional assay exists, and VUS in those genes must rely on other evidence types.

Population Database Limitations

Population databases are not representative of all ancestral groups. Variants that are rare in one population may be common in another. The large cohort study found that VUS rates varied across clinician-reported race, ethnicity, and ancestry groups 8. Laboratories must interpret population frequency data in the context of the patient's ancestry.

Computational Prediction Uncertainty

Computational prediction tools have limited accuracy for certain variant types. Gain-of-function variants are particularly difficult to predict because most tools are trained to identify loss-of-function effects. The SpeckSeq study noted that gain-of-function mutations are poorly predicted in silico 9. This limitation means that computational scores should be interpreted with caution for genes where gain-of-function is the disease mechanism.

Reclassification Rate Variability

Reclassification rates vary by gene, variant type, and evidence availability. Some VUS will be reclassified quickly as new data emerge, while others may remain uncertain for years. The subclassification study found that variants in the lowest subclass were never reclassified as pathogenic, suggesting that some VUS are likely benign despite insufficient evidence for formal reclassification 11.

Safety and Regulatory Context

Laboratory Accreditation Requirements

Clinical laboratories that report variant classifications are subject to accreditation requirements that include quality management systems, proficiency testing, and documentation standards. The variant interpretation process should be documented in standard operating procedures that are reviewed and updated regularly.

Data Sharing and Transparency

Laboratories are encouraged to share variant classifications with public databases to support collective knowledge. The NCBI provides infrastructure for submitting and accessing variant data 1. Sharing classifications enables other laboratories to benefit from reclassification decisions and reduces the likelihood of conflicting interpretations.

Professional Guidelines Compliance

Variant classification should follow the professional guidelines established by the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. These guidelines define the evidence framework and classification categories. Laboratories should ensure that their classification processes align with current guidelines and that staff are trained in guideline application.

Training and Skill Development

Bioinformatics Training Pathways

Laboratory professionals who interpret variants need training in bioinformatics methods, database usage, and evidence evaluation. The EMBL-EBI Training program offers learning pathways for bioinformatics data resources and practical analysis education 2. These resources can help laboratory professionals develop the skills needed for variant interpretation.

Reproducible Analysis Skills

Variant interpretation should be reproducible. The nf-core documentation describes community standards for pipeline usage and configuration that support reproducible analysis workflows 5. The Carpentries lessons provide foundational training in computing, data management, shell, Git, and programming that underpin reproducible analysis practices 6.

Workflow Training

The Galaxy Training Network provides accessible workflow training and analysis tutorials that can help laboratories implement standardized variant interpretation processes 4. Bioconductor offers official package and workflow documentation for genomic analysis in the R environment 3. These resources support the technical skills needed for evidence evaluation and reclassification.

Practical Implementation Steps

Step 1: Inventory Existing VUS

Create a complete inventory of all VUS reported by your laboratory. Include the variant identifier, gene, date of initial classification, and any subclassification. This inventory serves as the starting point for the review process.

Step 2: Prioritize VUS for Review

Prioritize VUS based on clinical actionability, evidence availability, and time since last review. VUS in genes with established medical management guidelines should be reviewed first. VUS with new population data or published functional studies should also be prioritized.

Step 3: Conduct Evidence Review

For each prioritized VUS, search population databases, literature, and functional assay repositories for new evidence. Document the evidence found and assess whether it changes the classification. The NCBI provides access to multiple databases that can be searched for variant-specific information 1.

Step 4: Apply Classification Framework

Apply the standard classification framework to the updated evidence. If the evidence supports reclassification, document the rationale and issue an updated report. If the evidence is insufficient, update the review date and continue monitoring.

Step 5: Communicate Results

Notify the ordering clinician of any reclassification. Provide a clear explanation of the change and its implications. For reclassifications that affect medical management, recommend appropriate follow-up.

Step 6: Update Records and Databases

Update internal records with the reclassification decision and date. Submit the updated classification to public databases to support collective knowledge. Document the evidence that supported the reclassification for future reference.

Common Questions in VUS Management

How Often Should VUS Be Reviewed?

The review interval depends on the evidence landscape for the specific variant and gene. Variants in well-studied genes with rapidly growing evidence may warrant annual review. Variants in poorly characterized genes may require less frequent review. The subclassification approach can help prioritize which variants need more frequent review 11.

What Evidence Is Strongest for Reclassification?

Functional assay data from validated assays and population frequency data from large databases are among the strongest evidence types. The ATM study demonstrated that functional results integrated into a points-based framework enabled reclassification of 90 percent of VUS 7. Clinical segregation data and case-control studies also provide strong evidence when available.

Can a VUS Be Reclassified as Benign?

Yes. Many VUS are eventually reclassified as benign or likely benign as population data accumulate. The large cohort study found that VUS were reclassified in both directions, toward benign and toward pathogenic 8. The subclassification study found that variants in the lowest subclass were never reclassified as pathogenic, suggesting that many low-evidence VUS are likely benign 11.

What Should Patients Do While Waiting for Reclassification?

Patients should follow clinical recommendations based on their personal and family history instead of the VUS result alone. The VUS should not be treated as a disease-causing variant unless clinical features suggest otherwise. Patients should be encouraged to stay in contact with their genetics provider and to report any new family history information.

How Can Laboratories Share Reclassification Data?

Laboratories can submit variant classifications to public databases such as ClinVar, which is accessible through the NCBI 1. Sharing classifications helps other laboratories and reduces the likelihood of conflicting interpretations. Laboratories should ensure that submissions include the evidence supporting the classification.

What Are the Limitations of Computational Prediction?

Computational prediction tools cannot definitively establish pathogenicity or benignity. The developmental delay study found that some variants predicted to be damaging were present in the healthy population 10. Computational scores should be used to prioritize variants for further investigation, not to make final classification decisions.

How Should Conflicting Classifications Be Resolved?

Conflicting classifications between laboratories should be resolved through evidence review and data sharing. Laboratories should compare the evidence used for their classifications and identify the source of the discrepancy. Public databases that aggregate classifications can help identify conflicts and support resolution.

When Should a VUS Be Reported as a Secondary Finding?

VUS in genes associated with medically actionable conditions may be reported as secondary findings when identified incidentally. The decision to report should follow professional guidelines and institutional policies. The communication strategy should address the uncertainty inherent in a VUS result.

A Practical Decision Framework for VUS Reclassification Prioritization

Laboratories managing large volumes of VUS face a common operational problem: which variants deserve immediate re-evaluation, which can wait for scheduled review, and which should be deprioritized until new evidence emerges. The evidence-triggered and scheduled review approaches described earlier establish the general workflow, but they do not provide a concrete method for ranking variants when resources are limited. This section presents a scoring framework that laboratories can adapt to their specific gene panels, patient populations, and staffing levels.

The Need for a Structured Prioritization System

The scale of VUS management is substantial. In a cohort of nearly 1.7 million individuals who underwent diagnostic genetic testing, 692,227 had at least one VUS and 535,385 had only VUS results 8. A laboratory that tests thousands of patients per year will accumulate thousands of VUS entries in its tracking system. Reviewing every variant with equal intensity is neither feasible nor clinically justified. Some VUS have evidence that leans strongly toward a particular classification, while others have almost no evidence at all. The subclassification study found that variants in the lowest evidence subclass were never reclassified as pathogenic, whereas variants in the highest subclass were much more likely to be reclassified as pathogenic or likely pathogenic 11. This finding confirms that evidence level predicts reclassification likelihood and supports the use of a prioritization system that directs resources toward variants most likely to yield a classification change.

Components of the Prioritization Score

A practical prioritization framework assigns points across several domains that reflect both the likelihood of reclassification and the clinical impact of that reclassification. The framework described here uses five components, each scored from 0 to 4, producing a total score from 0 to 20. Laboratories can adjust the weighting to reflect their specific clinical context, but the components provide a starting point that can be implemented with existing records.

Component 1: Evidence Volume and Direction

This component assesses how much evidence currently exists and whether it points toward a particular classification. A VUS with no evidence beyond the initial observation receives 0 points. A VUS with limited population frequency data and no functional studies receives 1 point. A VUS with population data that approaches but does not cross a benign frequency threshold receives 2 points. A VUS with conflicting evidence, such as one functional study suggesting pathogenicity and another suggesting neutrality, receives 3 points. A VUS with multiple evidence types that consistently point in the same direction but do not quite meet the threshold for reclassification receives 4 points. The rationale for this scoring is that variants with substantial directional evidence are more likely to be reclassified when a small amount of additional data emerges.

Component 2: Time Since Last Review

This component reflects the principle that evidence accumulates over time. A VUS reviewed within the past 6 months receives 0 points. A VUS reviewed 6 to 12 months ago receives 1 point. A VUS reviewed 1 to 2 years ago receives 2 points. A VUS reviewed 2 to 3 years ago receives 3 points. A VUS that has never been reviewed since initial classification or was reviewed more than 3 years ago receives 4 points. The large cohort study demonstrated that reclassification occurs over time as evidence accumulates 8. Variants that have not been revisited for several years are more likely to have new evidence available.

Component 3: Clinical Actionability of the Gene

This component assesses whether a reclassification would change medical management. A VUS in a gene with no established medical management guidelines receives 0 points. A VUS in a gene with management guidelines that are primarily surveillance-based receives 2 points. A VUS in a gene with management guidelines that include prophylactic surgery, targeted therapy, or other high-impact interventions receives 4 points. The ATM gene exemplifies a moderate-risk cancer susceptibility gene where VUS limit the power of clinical genetic testing for cancer risk management and personalized medicine 7. Reclassifying a VUS in such a gene has direct implications for screening and prevention decisions.

Component 4: Variant Characteristics

This component considers features of the variant itself that correlate with reclassification likelihood. A variant in an intronic region with no predicted splicing effect receives 0 points. A synonymous variant with no predicted effect receives 1 point. A missense variant in a poorly conserved region receives 2 points. A missense variant in a highly conserved functional domain receives 3 points. A variant that creates a premature stop codon, alters a canonical splice site, or affects a known functional domain with established disease relevance receives 4 points. The ATM functional study identified hotspots for deleterious VUS at specific amino acid regions, demonstrating that variant location within a protein can predict functional impact 7. Variants in such regions warrant higher priority.

Component 5: Evidence Availability in the Literature

This component assesses whether new evidence is likely to have been published since the last review. A VUS in a gene with no recent publications and no active research community receives 0 points. A VUS in a gene with occasional case reports receives 1 point. A VUS in a gene with active functional study development receives 2 points. A VUS in a gene with recently published functional assay data receives 3 points. A VUS in a gene where a new functional assay has been described that could directly test the variant receives 4 points. The development of the ATM functional assay enabled reclassification of 79 of 88 VUS (90 percent) when integrated with other evidence 7. Similarly, the SpeckSeq method for MEFV variants supported reclassification that led to novel diagnoses 9. When such methods become available for a gene, VUS in that gene should be prioritized for review.

Applying the Scoring Framework

The prioritization score is calculated by summing the five component scores. The resulting total guides the review schedule and resource allocation.

Score 16 to 20: Immediate Review

Variants in this range should be reviewed within 30 days. These are variants with substantial directional evidence, long time since last review, high clinical actionability, concerning variant characteristics, and likely new evidence availability. A variant in this category might be a missense VUS in a highly conserved domain of a cancer susceptibility gene that was last reviewed 3 years ago and for which a new functional assay has been published. The ATM study demonstrated that functional results incorporated into a points-based framework enabled reclassification of 90 percent of VUS 7. Variants meeting this threshold warrant immediate attention because the likelihood of reclassification is high and the clinical impact is significant.

Score 11 to 15: Priority Review

Variants in this range should be reviewed within 90 days. These are variants with moderate directional evidence or high clinical actionability but less evidence volume. A variant in this category might be a VUS in a clinically actionable gene that was last reviewed 2 years ago but has limited functional evidence available. The subclassification study found that variants with more evidence were more likely to be reclassified 11. These variants warrant priority review because additional evidence may push them over the reclassification threshold.

Score 6 to 10: Scheduled Review

Variants in this range should be reviewed at the next scheduled annual review. These are variants with limited evidence, recent prior review, or lower clinical actionability. A variant in this category might be a missense VUS in a gene with no established management guidelines that was reviewed 1 year ago with no new evidence identified. These variants should be monitored but do not require immediate attention.

Score 0 to 5: Deferred Review

Variants in this range should be reviewed at the next scheduled biennial review or when an evidence trigger occurs. These are variants with minimal evidence, recent review, and low clinical actionability. The subclassification study found that variants in the lowest subclass were never reclassified as pathogenic 11. These variants are unlikely to be reclassified without substantial new evidence and do not warrant intensive resource allocation.

Implementing the Framework in Practice

Step 1: Assign Initial Scores

For each VUS in the tracking system, assign scores for each of the five components. This initial scoring can be completed by a laboratory professional or variant curator using existing records. The scoring should be documented in the variant tracking system so that it can be reviewed and updated.

Step 2: Calculate Total Scores and Assign Review Categories

Sum the five component scores and assign each variant to one of the four review categories. This step creates a prioritized worklist that guides resource allocation. The worklist should be reviewed by the laboratory director or variant curation committee to ensure that the prioritization is appropriate for the laboratory's clinical context.

Step 3: Conduct Reviews According to Priority

Conduct evidence reviews for variants in the immediate and priority categories first. For each variant, search population databases, literature, and functional assay repositories for new evidence. The NCBI provides access to multiple databases that aggregate genetic variation data, literature, and clinical assertions 1. Document the evidence found and assess whether it changes the classification.

Step 4: Update Scores After Each Review

After each review, update the component scores based on the evidence reviewed and the date of the review. The time since last review component resets to 0. The evidence volume and direction component may increase if new evidence was found. The evidence availability component may decrease if the literature search revealed no new relevant publications.

Step 5: Track Reclassification Outcomes

Track the reclassification outcomes for variants reviewed under each priority category. This tracking provides data to validate the prioritization framework. If variants in the deferred category are being reclassified at high rates, the scoring weights may need adjustment. If variants in the immediate category are rarely reclassified, the scoring may be overestimating the likelihood of reclassification.

Common Failure Patterns in Prioritization

Failure to Update Scores After Evidence Emerges

The most common failure is assigning initial scores and never updating them. New population data, functional studies, and clinical reports can change the evidence landscape for a variant. The large cohort study found that reclassification occurs as evidence accumulates 8. Laboratories should update scores whenever new evidence is identified, also at scheduled review intervals.

Overweighting Clinical Actionability

Clinical actionability is important, but it should not dominate the prioritization decision. A VUS in a highly actionable gene with no evidence and no likelihood of new evidence will not be reclassified regardless of how many points it receives for actionability. The prioritization score should reflect the likelihood of reclassification as well as the impact of reclassification.

Underweighting Evidence Direction

Some laboratories focus on evidence volume without considering whether the evidence points toward a particular classification. A VUS with conflicting evidence may require more intensive review than a VUS with no evidence, because the conflicting evidence may be resolvable with additional data. The scoring framework should reward directional evidence that approaches but does not cross the reclassification threshold.

Ignoring Ancestry-Specific Considerations

Population frequency data must be interpreted in the context of the patient's ancestry. The large cohort study found that VUS rates varied across clinician-reported race, ethnicity, and ancestry groups 8. A variant that is rare in one population may be common in another. Laboratories should consider whether new population data are relevant to the specific populations they serve.

Records and Measurements for Prioritization

Laboratories should maintain the following records for the prioritization framework:

• Component scores for each VUS with the date of scoring
• Total prioritization score and assigned review category
• Date of last review and date of next scheduled review
• Evidence identified during each review
• Reclassification outcomes with dates
• Updates to component scores with rationale

Quality metrics for the prioritization framework include:

• Percentage of VUS reviewed within the assigned review category timeline
• Reclassification rate by priority category
• Time from prioritization score assignment to reclassification
• Number of VUS with outdated scores (more than 1 year since last update)
• Correlation between prioritization score and reclassification likelihood

Professional Escalation Criteria for Prioritization Decisions

A laboratory should escalate a prioritization decision to the variant curation committee when:

• A variant receives a score of 16 or higher but the laboratory lacks resources for immediate review
• A variant in the deferred category is reclassified as pathogenic by another laboratory
• A new functional assay becomes available for a gene with many VUS in the deferred category
• Conflicting evidence emerges that changes the evidence direction component for a high-priority variant
• The prioritization framework produces consistently poor correlation with reclassification outcomes

The prioritization framework described here provides a concrete method for managing the operational challenge of VUS re-evaluation. By scoring variants across evidence volume, time since review, clinical actionability, variant characteristics, and evidence availability, laboratories can direct resources toward the variants most likely to yield reclassification and most likely to impact clinical care. The framework should be validated against local reclassification data and adjusted as evidence accumulates.

Frequently Asked Questions

What is the difference between a VUS and a likely pathogenic variant?

A likely pathogenic variant has evidence that strongly supports a disease-causing role but does not meet the threshold for definitive pathogenicity. A VUS has evidence that is insufficient or contradictory. The distinction matters for clinical management. Likely pathogenic variants are often treated as pathogenic for clinical purposes, while VUS are not used for medical decision making unless other clinical evidence supports action.

How long does it take for a VUS to be reclassified?

The time to reclassification varies widely depending on the variant, gene, and evidence availability. Some VUS are reclassified within months when new population data or functional studies emerge. Others remain uncertain for years. The subclassification study found that variants with more evidence were more likely to be reclassified, suggesting that evidence accumulation is the key driver of reclassification timing 11.

Can a VUS be reclassified more than once?

Yes. A variant may move from VUS to likely pathogenic and then to pathogenic as additional evidence accumulates. Alternatively, a variant may move from VUS to likely benign and then to benign. Each reclassification should be based on the totality of evidence available at that time.

What should a clinician do when a patient receives a VUS result?

The clinician should explain the meaning of the VUS result, emphasize that it is not a definitive disease-causing finding, and recommend management based on personal and family history. The clinician should also discuss the possibility of reclassification and the plan for monitoring the variant. Referral to genetic counseling can help patients understand the implications.

How can patients contribute to VUS reclassification?

Patients can contribute by providing updated family history information, participating in family segregation studies, and enrolling in research studies that investigate VUS. Patients can also consent to data sharing that enables laboratories to aggregate evidence across individuals. The ATM study used clinical data from a large patient database to validate functional assay results 7.

What is the role of functional assays in VUS reclassification?

Functional assays provide direct experimental evidence about variant effects. Validated assays can distinguish neutral from deleterious variants with high accuracy, as demonstrated by the ATM study 7. Functional data are particularly valuable when computational predictions are ambiguous or when population data are insufficient. The SpeckSeq study demonstrated that functional methods can identify gain-of-function variants that computational tools miss 9.

Are VUS more common in certain genes or populations?

VUS rates vary by gene, with some genes harboring thousands of VUS. The ATM gene was noted to harbor thousands of missense VUS that limit the power of clinical genetic testing 7. VUS rates also vary across ancestral groups, as demonstrated by the large cohort study that found differences across clinician-reported race, ethnicity, and ancestry groups 8.

What happens if a VUS is reclassified after a patient has already received results?

The laboratory should issue an updated report and notify the ordering clinician. The clinician should then communicate the reclassification to the patient. The communication should explain what changed, why it changed, and what the new classification means for medical management. This process should occur promptly to avoid continued uncertainty or inappropriate management.

Related Bioinformatics Guides

• How to Interpret Gene Set Enrichment Analysis Results
• Detecting Structural Variants with Long-Read Sequencing: Methods and Considerations
• Metabolomics Data Analysis in R: A Practical Workflow
• Metagenomics Tools: A Practical Guide to Software and Pipelines
• Microbiome Data Analysis in R: A Practical Guide for Compositional Data

Related Clinical & Scientific Guides

• A Practical Guide to Detecting Antimicrobial Resistance Genes in Shotgun Metagenomic Data
• Computational Immunology: Modeling the Immune System
• How to Set Hard Filters for Germline Variant Calling: A Practical Guide to GATK Best Practices

References and Further Reading

• NCBI Data Resources. National Center for Biotechnology Information.
• EMBL-EBI Training. European Bioinformatics Institute.
• Bioconductor. Bioconductor Project.
• Galaxy Training Network. Galaxy Project.
• nf-core Documentation. nf-core.
• The Carpentries Lessons. The Carpentries.
• Reclassification of ATM Missense Variants of Uncertain Significance by Integrating Results from Systematic Functional Assays into an ACMG Points-Based Framework.. Clinical cancer research : an official journal of the American Association for Cancer Research, 2025.
• Rates and Classification of Variants of Uncertain Significance in Hereditary Disease Genetic Testing.. JAMA network open, 2023.
• SpeckSeq enables high-throughput functional stratification of MEFV variants in autoinflammatory diseases.. The Journal of experimental medicine, 2026.
• Genetic determinants of global developmental delay and intellectual disability in Ukrainian children.. Journal of neurodevelopmental disorders, 2024.
• Distinct rates of VUS reclassification are observed when subclassifying VUS by evidence level.. Genetics in medicine : official journal of the American College of Medical Genetics, 2025.

This article is educational and does not replace validated analysis plans, institutional policy, clinical interpretation, or specialist review.