The ACMG/AMP guidelines have long served as the gold standard for variant classification, shaping how genetic evidence is assessed and communicated in clinical settings. As the field evolves, so too must our tools and frameworks - and the upcoming Version 4 (V4) update reflects that ongoing progress.
These forthcoming updates aim to bring greater consistency, precision, and clinical utility to variant interpretation through a more quantitative, transparent structure. At Genomenon, we’ve been closely tracking these changes and have proactively updated our workflows to ensure we're not just ready for V4 - we're already operating in alignment with its direction.
Key Updates in ACMG V4: A Shift Toward Quantitative Precision
The forthcoming V4 revision introduces foundational changes to how genetic variants are interpreted, moving beyond static rules to a more structured and quantitative approach. Some of the key updates include:
- A points-based system that allows for more nuanced interpretation
- Integration of Gene-Disease Validity to better tailor criteria to specific gene contexts
- Refined evidence types - with some added, others removed, and many reweighted
- Introduction of decision trees to help guide the application of criteria
- More granular distinctions within criteria to improve calibration and consistency
- The ability to balance pathogenic and benign evidence, supporting more transparent decision-making
Why is V4 being developed?
ACMG V4 is being developed to resolve several key limitations in the previous version. It aims to eliminate inconsistencies and ambiguities in how criteria are applied, offering clearer definitions and structured guidance. The update also addresses the problem of double-counting overlapping evidence, which previously led to inflated classifications. V4 introduces more precise guidance for weighing conflicting pathogenic and benign evidence side by side. A major improvement is the shift toward a more quantitative approach, using a points-based system to support consistent scoring. Finally, V4 incorporates the latest recommendations from ClinGen working groups and sets the stage for ongoing updates as the field evolves.
Ultimately, the goal is to bring more reproducibility, transparency, and standardization to variant interpretation - making it easier for labs and clinicians to align with evolving best practices and emerging ClinGen specifications.
Five Steps We’ve Already Taken Toward V4 Readiness
1. Integration of Internal Gene-Disease Validity Frameworks
We’ve implemented comprehensive internal Gene-Disease Validity Reports that mirror ClinGen’s structured validity model.
This allows us to:
- Systematically evaluate the strength of gene-disease relationships
- Align our assessments with V4’s requirement for disease-specific evidence calibration
- Strengthen the application of criteria that depend on the underlying gene-disease association
2. Proband Counting Infrastructure
We’ve developed a standardized system to track and quantify affected probands across case studies.
This infrastructure ensures:
- Consistent capture of proband-level data
- Support for the new points-based system introduced in V4
- Accurate scoring for evidence criteria related to case-level data (e.g., PS4, PP1)
3. Systematic Meiosis Counting for Segregation Analysis
Our workflows now include structured tracking of meiotic events across pedigrees to evaluate co-segregation evidence.
This enables:
- Precision in assigning points for segregation (PP1), in line with V4’s quantitative expectations
- Elimination of ambiguity in interpreting pedigree structures
- Increased confidence in segregation-based pathogenicity scoring
4. Workflow Updates for In-Trans Observations
We’ve revised our processes to clearly distinguish between confirmed and assumed in trans variant observations.
These updates reflect:
- V4’s refined scoring under PM3, where the strength of evidence depends on confirmation status
- Improved tracking and documentation for phasing data
- Enhanced transparency in how compound heterozygous observations are classified
5. Standardization of In Silico Predictions Using REVEL
We’ve adopted REVEL as our default tool for in silico prediction of variant impact.
This decision was made to:
- Align with ACMG V4’s recommendation of REVEL as a preferred tool
- Provide more consistent and validated computational evidence
- Reduce reliance on outdated or unsupported in silico scores
Why It Matters
By proactively aligning our workflows with the direction of ACMG V4, we’re doing more than future-proofing our own processes - we’re giving our partners a head start. These five steps weren’t just about internal readiness; they were about making sure our partners don’t have to pause, pivot, or patch their systems when the new guidelines are finalized.With standardized gene-disease frameworks, robust proband and segregation tracking, improved in trans observation handling, and trusted in silico tools already in place, our partners gain immediate access to a system that’s designed for where the field is going - not just where it’s been.
The result? Faster onboarding, smoother transitions, and variant classifications that will remain consistent and reliable even as the standards shift. We’re not just ready - we’re helping our partners stay ahead of the curve.
Conclusion: Moving Forward with Confidence
As the field of genomic medicine continues to evolve, Genomenon remains committed to delivering variant interpretations that are not only accurate - but future-proof.
We’re actively monitoring updates from ClinGen and ACMG, and we’re engaging with the broader community to ensure alignment, transparency, and shared progress.
We’ve also signed up to trial the guidelines when the broader trials become available - so we’ll be putting V4 into practice even before the final version is officially released.
Stay ahead with us - explore how our variant curation services can support your evolving needs.
