The Evidence Tab provides tools to review, document, and classify variants efficiently. It combines manual and automated features to ensure accurate pathogenicity assessment, interpretation notes, and evidence visualization.

Users can import past interpretations, apply ACMG classification wizards, and generate evidence graphs—all within one workspace. Access is available only for tagged variants, ensuring that evidence review is focused and traceable.

1. Pathogenicity selection

A dropdown menu lets you assign the variant’s pathogenicity manually:

• Pathogenic (P)

• Likely Pathogenic (LP)

• Variant of Uncertain Significance (VUS)

If the variant already exists in , its previously assigned classification will display alongside a Curate logo, ensuring consistency across analyses.

Any updates you make here are reflected in both the case summary and reports.

2. Variant Interpretation notes

The Interpretation Notes field contains a draft explanation of the variant, pre-populated with details from the AI Shortlist algorithm.

Editing is supported via the Edit Text link. In edit mode, the Paste icon becomes available, letting you quickly add standardized content.

You can expand notes using the dropdown options:

1. Import data from Curate:

   1. Gene - Import interpretation and gene notes linked to the gene from Curate Genes.

   2. Variant - Import interpretation and variant notes linked to the specific variant from Curate Variants.

3. A See evidence button

A See Evidence button appears beneath the Evidence box.

• This links directly to the Evidence Page, where you can view a graphical breakdown of supporting and conflicting evidence.

• You can also regenerate the Evidence Graph if new information (e.g., phenotype match, curated disease selection) is added.

4)

The ACMG SNV Classification wizard:

• Automates classification for sequence variants.

• 26 of 28 ACMG criteria are pre-calculated using Emedgene’s algorithms.

• 2 criteria require manual confirmation (BS2 and PS4).

The ACMG CNV Classification wizard:

• Automates classification of copy number variants (CNVs).

• Integrates CNV-specific parameters such as Copy Number, CNV Quality Score, and Size.

• CNV tags are largely automated, but users can review and override assignments as needed.

5) Sanger Confirmation toggle button

• A simple toggle button lets you mark whether the variant:

  • Should be submitted for Sanger validation, or

  • Has already been confirmed by Sanger sequencing.

Note: Keep in mind that the Evidence tab is active only for variants that have been automatically or manually tagged. To enable the Evidence tab, you need to assign any tag to the variant under consideration.

Review and edit the ACMG Classification of a CNV

The ACMG CNV Classification wizard is located in the Evidence tab of the Variant page. Itis available for tagged genomic variants.

The ACMG CNV Classification wizard is located in the Evidence section of the Variant page. It is available for tagged genomic variants.

The tool automatically scores sections 1, 2, 3, and partially scores sections 4 and 5 of the ACMG/Clingen guidelines, including the full PVS1 calculation required for intragenic variants. All the relevant data is summarized in an accessible table.

This tool is designed to save significant review time, reducing manual effort by up to 75–90% (ASHG 2020 abstract).

Factors considered in CNV scoring

When determining the automated classification, the system considers:

• Inheritance patterns – whether the CNV is de novo or segregates in a family

• Gene content – the number and type of genes affected, including ClinGen dosage sensitivity and predicted haploinsufficient genes

• Overlap with known pathogenic regions – alignment with established genomic regions linked to disease

By combining these elements, the scoring logic provides a clearer and more consistent starting point for CNV interpretation.

How do I review and edit the ACMG Classification of a CNV?

The ACMG SNV classification wizard features:

1. Automatically calculated ACMG class and score

1. ACMG score slider that shows the ranges of ACMG values for each classification and highlights where the current CNV falls:

   • Benign: ≤ –0.99

   • Likely Benign: –0.98…–0.90

1. Reclassify button that enables Edit mode

1. Gene Number:

   • Gene Number shows the total protein-coding RefSeq genes overlapped by the CNV. Of these:

     • Established ClinGen genes (dosage sensitivity or insensitivity defined by ClinGen scores)

1. Gene table that provides a summary of the affected protein-coding genes:

   • Gene description:

     • Name - HGNC gene symbol,

*Criteria with variable score:

• 2F, 2I

• 4A, 4B, 4C, 4D, 4E, 4I, 4J, 4K, 4L, 4M, 4N, 4O

• 5A, 5B, 5C, 5E, 5G, 5H

Where can I review and edit the ACMG Classification of a SNV?

The ACMG SNV Classification wizard is located in the Evidence tab of the Variant page. It facilitates classification of variant pathogenicity through the automation of 26 out of 28 ACMG criteria and enabling manual review and editing of the tags presented as interactive buttons.

The ACMG SNV Classification Wizard is located in the Evidence section of the Variant Page and is designed to guide users through the interpretation of single nucleotide variants (SNVs) using the ACMG/AMP framework. It automates 26 out of 28 ACMG criteria, with PS4 requiring full manual entry and BS2 partially automated (50% manual).

The ACMG SNV Classification wizard includes a pathogenicity bar that visually represents the .

The wizard is available for tagged SNVs in disease-associated genes and displays a visual pathogenicity bar summarizing the cumulative pathogenicity score.

The wizard is available for tagged sequence variants in disease-associated genes. The results of the classification are also highlighted in the of the . Unlike the wizard, automatically assigned criteria and resulting variant class are shown in the for all variants in disease-associated genes, regardless of their status.

How do I review and edit the ACMG Classification of a SNV?

Each ACMG tag is represented by an interactive button including a checkbox for selection (1), the criterion name (2) and evidence strength indicator (3).

Pathogenic criteria are represented by red boxes, while benign criteria boxes are colored green. Each ACMG criterion has three possible states:

• Neutral (1) - represented by an empty checkbox. Criterion requires further investigation.

• Negative (2) - represented by a cross. Criterion is not applicable.

• Positive (3) - represented by a tick and dark color. Criterion is applicable.

Each ACMG tag can be manually checked, unchecked, or set to an undefined state by clicking the interactive button's checkbox element.

To examine in detail or modify the underlying evidence for the particular ACMG tag, select it by clicking on the tag name. The button becomes flood-filled (b), as opposed to it's original, non-selected, state (a).

Upon selection, a description of the criterion and its underlying evidence emerges below. Yes and No radio buttons accompany each piece of evidence. The tag can be assigned if Yes has been selected for all the underlying conditions.

You may modify evidence strength in the Strength dropdown (Stand Alone, Very Strong, Strong, Moderate, Supporting), which will impact both the pathogenicity class and score calculations.

Notes can be added to any tag, and changes are saved using the Save button.

After you've modified ACMG classification, you can either save manual changes by pressing the Save button or reset via Revert manual changes. Keep in mind that after saving your edits, Revert manual changes will become unavailable.

Warnings for ACMG tag schema versions

ACMG classifications rely on a defined ACMG tag schema, which is periodically updated to reflect new ClinGen/ACMG recommendations or platform logic improvements. To ensure classification accuracy, schema versioning is now tracked independently from the overall variant analysis engine.

When opening a case in Analyze, the system compares:

• The ACMG schema version currently applied in the case analysis

• The ACMG schema version used when the variant was curated in Curate

If the curated schema is older than the current schema:

• Curated ACMG tags will not be applied in Analyze

• The system reapplies the current schema’s criteria

• A warning appears:

You can synchronize schemas by clicking Update Curate on the variant. This updates the variant’s ACMG schema version in Curate to match Analyze, and the updated classification is saved like any other variant update.

Disease source used in ACMG evaluation

When a gene–disease association is available from multiple databases (for example: OMIM, CGD, Orphanet etc.), the variant page and gene related diseases card display all available disease sources. However, ACMG inheritance-based rules use only the OMIM disease to determine the inheritance mode.

• Multiple disease entries may appear in the UI.

• ACMG logic selects only OMIM entry when determining the inheritance mode.

• If OMIM does not include a pre-populated inheritance mode, ACMG rules that rely on inheritance mode will not be triggered—even if another source (such as CGD) contains this information.

ACMG classification of mtDNA variants

The ACMG SNV Classification wizard is available for ACMG classification of tagged mtDNA variants. To classify an mtDNA variant, please manually assign the relevant criteria; the resulting ACMG classification will be calculated automatically.

Seven criteria have been removed in compliance with : PM1, PM3, PP2, PP5, BP1, BP3, BP6.

The SNVs classification engine applies the joint American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines for interpreting sequence variants using 28 evidence criteria (PMID: 25741868).

Emedgene independently determines the overall ACMG variant pathogenicity score and class.

ACMG variant classification

Emedgene applies the ACMG classification guidelines for variant interpretation using the standardized framework established by the American College of Medical Genetics and Genomics (ACMG). This approach is further refined with recommendations from the ClinGen Sequence Variant Interpretation (SVI) Working Group and other expert-reviewed publications to ensure consistent, evidence-based classification of genomic variants.

When assigning a final classification, Emedgene applies the ACMG thresholds with the above combination rules:

Pathogenic

• 1 Very Strong (PVS1) and ≥1 Strong (PS1–PS4), or

• 1 Very Strong and ≥2 Moderate (PM1–PM6), or

• 1 Very Strong + 1 Moderate + 1 Supporting, or

Likely Pathogenic

• 1 Very Strong + 1 Moderate, or

• 1 Very Strong + 1 Supporting, or

• 1 Strong + 1–2 Moderate, or

• 1 Strong + ≥2 Supporting, or

Benign

• 1 Stand-alone benign (BA1) — overrides all other tags, or

• ≥2 Strong benign (BS1–BS4).

Likely Benign

• 1 Strong benign + 1 Supporting benign, or

• ≥2 Supporting benign (BP1–BP7).

ACMG variant score

Emedgene calculates the ACMG score for Single Nucleotide Variants (SNVs) using the framework recommended by the American College of Medical Genetics and Genomics (ACMG), along with refinements from ClinGen Sequence Variant Interpretation (SVI) Working Group and other published guidelines (PMID: 32720330).

The software assigns points to each active criterion based on its strength of evidence:

• Supporting evidence = 1 point

• Moderate evidence = 2 points

• Strong evidence = 4 points

The total ACMG score is calculated by adding the points from all pathogenic criteria and subtracting the points from all benign criteria. The result is then interpreted according to these thresholds:

Tag strength adjustments and combination rules

Some ACMG criteria have special handling to ensure consistent scoring in line with expert recommendations:

• PM2 always counts as Supporting strength, regardless of any manual user change (PM2 SVI Recommendation Ver 1.0, 2020). If you set PM2 to a higher level, the system will warn:

• If Very Strong (PVS1) is combined with any Supporting (PP1–PP5), the maximum final classification is Likely Pathogenic, not Pathogenic (PM2 SVI Recommendation Ver 1.0, 2020).

• If PM1 and PP3 are both positive, the combination is capped at Strong strength, regardless of individual strengths (Pejaver et al., 2022). This prevents inflated scoring when computational evidence overlaps with known mutational hotspot data.

Tracking and traceability of manual changes

The interface tracks and displays all manual modifications to ACMG tags, including changes to tag status, strength, or question responses:

• User icon → appears on tags, questions, or strength indicators when manually changed. Hover to see the username.

• Emedgene icon (EMG) → indicates the system’s original automated classification. Hover to see the original status or strength.

• Dependency-driven changes (e.g., a strength auto-adjusted because a related question was changed) still show the user icon for traceability.

In the Summary tab, tags are color-coded, and manual changes show user icons directly on the tag for quick review.

Real-time warnings during classification

When certain tag combinations are applied, the system displays immediate, context-specific warnings in the header area:

• PM2 changed → “PM2 is recommended to be set to supporting level (PM2 SVI Recommendation Ver 1.0, 2020).”

• PM1 + PP3 both positive → “When PM1 is applied with PP3, the outcome will be limited to Strong (Pejaver et al., 2022).”

• PP5 positive → “PP5 excluded (Biesecker et al., 2018).”

ClinGen gene specifications (v100.39.0+)

When a variant is located on a gene with a existing submission within the ClinGen Criteria Specification (CSpec) Registry, an indication is presented in the ACMG section with a link to the CSpec registry. The indication is only applicable for specifications that are in status 'Released'.

The CSpec Registry is intended to provide access to the Criteria Specifications used and applied by and biocurators in the classification of variants.

ACMG automation module

Emedgene have implemented a technical automated solution for most criteria based on our scientific advisors’ recommendations and feedback from top clinical customers. For each criterion, we elaborate on the logic employed and the associated underlying thresholds. In addition, we give the user the flexibility to change the weight of specific criteria based on his professional judgment as recommended by ACMG/AMP guidelines.

ACMG criteria are mainly evaluated automatically using rule-based logic, allowing users to review and adjust evidence as needed. However, BS2 (partly) and PS4 need manual evaluation.

To learn how each criterion is assessed, select the corresponding evidence code in the table below.

^{_{Richards, S., Aziz, N., Bale, S., Bick, D., Das, S., Gastier-Foster, J., ... & ACMG Laboratory Quality Assurance Committee. (2015). Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genetics in Medicine, 17(5), 405-424. doi:10.1038/gim.2015.30}}

Population Data

This section explains how population frequency data from large databases like gnomAD and ExAC is used to assess whether a variant is too common to be disease-causing. These criteria are part of the ACMG guidelines and help determine if a variant is more likely to be benign or pathogenic.

PS4 - Increased prevalence in affected individuals (Pathogenic, Strong-Supporting)

PS4 is applied when a variant is significantly more common in affected individuals than in unaffected controls, based on statistical comparison. This suggests the variant may play a role in causing the condition.

To apply PS4:

• There must be case-control data showing that the variant occurs more frequently in individuals with the disease.

• The strength of PS4 (Supporting, Moderate, or Strong) depends on the size of the study, quality of the evidence, and statistical significance (e.g., odds ratio, p-value).

This criterion is especially useful when working with common variants in complex disorders or when evaluating variants studied in large population cohorts.

PM2 - Rare or absent in population (Pathogenic, Supporting)

PM2 is applied when a variant is either very rare or completely absent in large population databases. This supports the idea that the variant might be disease-causing, because harmful variants are usually not common in healthy people.

In Emedgene, PM2 is automatically applied based on the gene and inheritance mode:

• For dominant conditions: the variant must occur in less than 0.01% of the population.

• For recessive conditions: the threshold is less than 1%.

• If there's known data in ClinVar for that gene, the system uses the highest known frequency of a confirmed disease-causing variant—up to a 1% cap—to fine-tune the cutoff.

This means:

• If a variant’s frequency is below the expected level for the disease—and particularly for that gene—PM2 will be applied.

• If a known pathogenic variant in the same gene has a high frequency, PM2 won’t be triggered unless the current variant is rarer than that.

This ensures that PM2 is more accurate and avoids flagging common variants as pathogenic.

BA1 - Very common variants (Benign, Strong)

BA1 is used when a variant is very common—specifically, if it appears in more than 5% of the population in large public datasets like gnomAD or in an internal database of at least 1,000 individuals. This level of frequency is too high for a variant to be responsible for rare genetic diseases, so BA1 provides strong evidence that the variant is benign.

BS1 - More common than expected (Benign, Strong)

BS1 is used when a variant is more common than you'd expect for a specific disease, even if it doesn’t reach the 5% threshold needed for BA1. It’s a strong indicator that the variant is likely benign.

In Emedgene, this is automatically calculated if the variant’s allele frequency is above a certain threshold that's specific to the gene and condition. These thresholds are calculated based on data from ClinVar, particularly variants that are pathogenic or likely pathogenic (P/LP) and have at least one-star review (meaning they’re well-reviewed and reliable).

The threshold also considers the mode of inheritance:

• For autosomal dominant (AD) diseases, the expected frequency is lower.

• For autosomal recessive (AR) diseases, a higher frequency might be acceptable.

This gene-specific logic improves how BS1 is applied and helps prevent mistakes in variant interpretation, especially for genes that naturally have more variation in the general population.

BS2 - Found in healthy people (Benign, Strong) (v100.39.0+)

BS2 is used when the variant is found in people who are healthy, even though the disease it’s associated with would normally appear in early childhood and be fully penetrant (i.e., definitely cause symptoms). If someone has the variant but is clearly unaffected, that’s a strong sign that the variant is not disease-causing.

BS2 is partially automated. BS2 is positively activated when the following all two conditions are met:

• Variant’s segregation pattern matches a known inheritance mode (AD, AR, or XLR).

• The variant is observed in public databases according to the expected zygosity

• Additionally, two conditions are manually set according to the observed state of the disease:

Computational and Predictive Data

Computational evidence plays a key role in classifying variants, especially when experimental data is unavailable. This section summarizes how Emedgene uses in silico (computer-based) predictions to support or refute a variant’s potential pathogenicity, in line with ACMG guidelines.

PVS1 - Predicted loss of function (Pathogenic, Very Strong)

PVS1 is applied when a variant is predicted to result in a loss of function (LoF) in a gene where such a mechanism is known to cause disease. This includes variants such as nonsense (stop-gain), frameshift, canonical splice site changes, or large deletions that disrupt essential exons. Emedgene uses a structured, evidence-based decision tree aligned with the ClinGen framework (Abou Tayoun et al., 2018) and transcript-based considerations outlined by Walker et al. (2023).

To determine the appropriate evidence strength (Very Strong, Strong, Moderate, Supporting), the platform evaluates multiple factors:

• Whether the affected exon is biologically important (e.g., present in canonical or disease-relevant transcripts).

• Whether the variant is likely to trigger nonsense-mediated decay (NMD).

• Whether the disrupted region is known to be critical for protein function.

A graphical interface visually traces this decision logic in the Emedgene platform, enabling users to see exactly how the PVS1 tag was determined and what supporting evidence was used.

References:

• Abou Tayoun et al., 2018 – ClinGen LoF Framework

• Walker et al., 2023 – Transcript and functional considerations for LoF variants

PS1 - Same amino acid change as known pathogenic variant (Pathogenic, Strong) (v100.39.0+)

PS1 is used when a variant results in the same amino acid change as a previously confirmed pathogenic variant, but via a different nucleotide change.

This implies that the functional consequence is identical, even if the underlying DNA sequence is different. For example, two different codons could both result in the same substitution at the protein level.

The defined logic supports both missense and splice variants. For missense, PS1 is applied when the variant leads to the same amino acid substitution as a ClinVar pathogenic variant on the same codon. For splice variants, PS1 is applied when the variant affects the same splice site or region as a ClicVar pathogenic variant, with similar predicted impact based on SpliceAI and SpliceAI-10K.

Strength is assigned based on variant type, location, and ClinVar classification. Supporting evidence includes links to the ClinVar variant, SpliceAI score, and predicted effect.

References:

• Walker et al., 2023 – Computational and RNA-splicing evidence / bioinformatic codes

PM5 - Novel missense at known pathogenic residue (Pathogenic, Moderate)

PM5 applies when a new missense variant occurs at a protein position where other different missense changes have already been classified as pathogenic.

This suggests that the position is critical for protein function and intolerant to change. Emedgene cross-references the variant against known pathogenic variants at the same amino acid site to apply this criterion.

PM4 - In-frame indels or stop-loss outside repeats (Pathogenic, Moderate)

PM4 is used when a variant leads to an in-frame deletion or insertion, or a stop-loss, outside of a repetitive region of the gene.

In-frame variants do not shift the reading frame, but they can still alter protein function if they affect a structurally or functionally important region. Emedgene checks whether the variant is located within low-complexity or repetitive regions before applying PM4, increasing the specificity of this evidence.

PP3 - Damaging computational predictions (Pathogenic, Supporting-Strong)

PP3 supports pathogenicity when multiple in silico prediction tools suggest that a variant is deleterious. This is typically applied to missense or splicing variants and can vary in strength based on the confidence of the tools. Emedgene uses thresholds aligned with Pejaver et al. (2022) and Walker et al. (2023).

In Emedgene, this includes:

• Missense impact (REVEL score)

• Splicing impact (SpliceAI)

• Conservation scores (evolutionary constraint)

The strength of PP3—Supporting, Moderate, or Strong—is determined by how confident the predictions are:

• REVEL score (Pejaver et al., 2022):

  • 0.644–0.773: Supporting

  • 0.773–0.932: Moderate

A variant must meet at least two supportive predictions across conservation, protein impact, or splicing tools to qualify. Tools may include REVEL, SpliceAI, dbscSNV, and conservation metrics like GERP or SiPhy.

This scoring ensures a standardized, evidence-based use of computational tools in variant interpretation.

References:

• Pejaver et al., 2022 – Benchmarking REVEL for clinical variant prediction

• Walker et al., 2023 – Standardizing splicing predictions using SpliceAI

BP1 - Missense variant in a truncation-driven gene (Benign, Supporting)

BP1 applies to missense variants found in genes typically associated with disease through loss-of-function mechanisms (e.g., nonsense or frameshift), not missense.

Emedgene evaluates ClinVar data to calculate a benign-to-pathogenic ratio, and applies BP1 when there is at least a 5:1 ratio in favor of benign variants at the same gene locus. This is supporting evidence for benignity, particularly when missense variants are less likely to be disease-causing in that gene.

BP4 - Benign computational predictions (Benign, Supporting-Very Strong)

BP4 supports a benign interpretation when multiple computational predictors suggest the variant is not likely to be damaging. As with PP3, the strength of BP4 can vary depending on the tool confidence.

For missense variants, REVEL thresholds are:

• Very Strong Benign: < 0.003

• Strong: 0.003–0.016

• Moderate: 0.016–0.183

For splicing, BP4 applies when SpliceAI score ≤ 0.1, suggesting minimal or no disruption to splicing.

As with PP3, a minimum of two independent predictors must agree for BP4 to be applied. This ensures evidence consistency across protein function and splicing tools. Emedgene uses these thresholds to adjust the strength of BP4 accordingly, making the evaluation more consistent and aligned with recent research.

References:

• Pejaver et al., 2022 – REVEL thresholds

• Walker et al., 2023 – SpliceAI benign cutoffs

BP7 - Synonymous variant with low impact (Benign, Supporting)

BP7 is applied to synonymous (silent) or non-coding intronic variants that are not predicted to affect splicing and fall in non-conserved regions. Emedgene applies BP7 only when the following are true:

• The variant is synonymous or deep intronic

• SpliceAI score is ≤ 0.1, confirming no splicing disruption

This criterion supports benign interpretation and helps users confidently classify silent variants that otherwise appear suspicious due to location in exons or introns.

Reference:

• Walker et al., 2023 – Updated guidance for BP7 using splicing prediction

Functional Data

Functional data criteria assess the results of experimental studies—both in vitro (in the lab) and in vivo (in living systems)—to determine whether a variant disrupts gene or protein function. This type of evidence is powerful because it reflects direct biological testing rather than predictions alone.

PS3 - Functional studies show damaging effect (Pathogenic, Variable Strength)

PS3 is applied when reliable experimental studies demonstrate that a variant has a deleterious effect on the gene or its protein product. These effects might include:

• Loss of enzymatic activity

• Disruption of protein structure or folding

• Impaired molecular interactions

The studies used must be well-validated, reproducible, and performed in a relevant biological context. Emedgene surfaces supporting publications automatically by scanning literature databases for functional assays relevant to the variant under review, as outlined in Walker et al., 2023 and Brnich et al., 2020.

The strength of PS3 (Supporting, Moderate, or Strong) depends on:

• The type and quality of the assay

• The number of independent studies showing consistent results

• How closely the assay reflects the true disease mechanism

For example, a high-quality cell-based assay showing complete loss of protein function in a well-characterized disease gene could support PS3_Strong, while a partial defect in a less direct assay might be PS3_Moderate. All evidence is traceable in Emedgene, and users can adjust final strength based on their own review.

References:

• Walker, C.E. et al., 2023 – Updated guidance for integrating functional and computational evidence into variant classification.

• Brnich, S.E. et al., 2020 – Recommendations for the application of functional evidence in clinical variant interpretation (American Journal of Human Genetics).

PM1 - Missense variant in mutational hotspot or critical functional domain (Pathogenic, Moderate)

PM1 is assigned when a missense variant falls within a mutational hotspot or critical protein domain that:

• Has > 70% pathogenic missense variants reported

• Has at least 10 ClinVar entries

• Shows no benign variation in population databases

These regions often correspond to active sites, binding domains, or structural motifs critical for protein function. Variants in these areas are more likely to have clinical impact. PM1 is not applied to mtDNA variants.

PP2 - Missense variant in gene where missense is a commom mechanism (Pathogenic, Supporting)

PP2 applies to missense variants in genes where:

• Disease is frequently caused by missense changes (often affecting critical functional regions)

• Benign missense variation is rare

Emedgene calculates a pathogenic-to-benign ratio using ClinVar data, applying PP2 when this ratio is ≥ 2:1 with at least 10 total entries for the gene. This ensures statistical reliability. PP2 is not applied to mitochondrial DNA (mtDNA)variants.

In practice, this means if a gene is known to cause disease through subtle amino acid changes rather than truncating mutations, and nearly all missense changes are pathogenic, a new missense variant is more likely to be disease-causing.

BS3 - Functional studies show no damaging effect (Benign, Variable Strength)

BS3 is the benign counterpart to PS3. It is applied when robust functional evidence demonstrates that a variant does not impair the gene’s or protein’s function. This can include:

• Normal activity levels in enzyme assays

• Proper localization in cell-based imaging

• Correct protein folding and stability

As with PS3, Emedgene’s automated literature classifier identifies relevant publications and integrates them directly into the variant’s evidence record, helping users avoid manual searches.

The strength of BS3 depends on:

• The assay’s relevance to the known disease mechanism

• The number of independent lines of evidence showing normal function

• Agreement with other evidence (e.g., population frequency)

A high-quality study showing full wild-type function in multiple models may support BS3_Strong, whereas evidence from a single model may support BS3_Supporting.

References:

• Walker, C.E. et al., 2023 – Updated guidance for integrating functional and computational evidence into variant classification.

• Brnich, S.E. et al., 2020 – Recommendations for the application of functional evidence in clinical variant interpretation (American Journal of Human Genetics).

Segregation Data

PP1 - Cosegregation with disease in multiple affected family members (Pathogenic, Variable Strength) (v100.39.0+)

PP1 is applied when there is clear evidence that a variant segregates with the disease in a family. For this criterion to be met in Emedgene, all three of the following must be true:

1. At least two affected family members are included in the case data.

2. The variant co-occurs with the disease phenotype in the pedigree — meaning every affected person carries the variant.

3. The variant is in a gene that is definitively known to cause a disease that matches the observed phenotype in the family.

PP1 strength is determined according to the combination of affected and unaffected family members within the pedigree.

In practice, PP1 provides stronger evidence as the number of segregating family members increases. For example, if five affected relatives across multiple generations all carry the same variant in a gene known to cause the disease, this can significantly raise confidence in a pathogenic classification.

Reference:

• Richards et al., 2015 – ACMG Guidelines for the Interpretation of Sequence Variants; Emedgene Help Guide – Segregation Evidence Logic

• Biesecker et al., 2024 – ClinGen guidance for use of the PP1/BS4 co-segregation and PP4 phenotype specificity criteria for sequence variant pathogenicity classification

BS4 - Lack of segregation in affected members of a family (Benign, Strong) (v100.39.0+)

BS4 is applied when there is clear evidence against segregation, meaning that the variant does not track with the disease within a family. For BS4 to be assigned in Emedgene, all of the following conditions must be met:

1. The case is not a singleton and there must be more than one affected family member included.

2. The lack of segregation is consistent across available pedigree data and not explainable by incomplete penetrance or phenotypic misclassification.

When these conditions are met, BS4 can strongly support a benign classification, especially for conditions with high penetrance, where all affected individuals would be expected to have the causal variant.

Reference:

• Richards et al., 2015 – ACMG Guidelines for the Interpretation of Sequence Variants; Emedgene Help Guide – Segregation Evidence Logic

• Biesecker et al., 2024 – ClinGen guidance for use of the PP1/BS4 co-segregation and PP4 phenotype specificity criteria for sequence variant pathogenicity classification

De novo data

De novo evidence is applied when a genetic variant appears for the first time in an affected individual (proband) and is absent in both biological parents. This type of evidence can strongly support pathogenicity, especially for disorders known to occur from new mutations rather than inherited variants. Emedgene evaluates this automatically based on case data, genomic analysis, and phenotype matching.

PS2 - Confirmed de novo variant (Pathogenic, Strong to Moderate)

PS2 is assigned when a variant is confirmed to be de novo in a patient who has the associated disease, with both paternity and maternity genetically validated. To meet the PS2 criteria in Emedgene:

1. The proband must carry the variant in a heterozygous state (or hemizygous if male for X-linked variants).

2. Both parents must be wild-type (reference) for that position in their genotypes and clinically unaffected.

3. Parentage confirmation — both maternity and paternity — must be established through genetic testing in the lab module, ensuring the variant is truly new and not inherited.

Emedgene also integrates phenotype specificity scoring using the Phenomeld engine. This ensures that the de novo event is evaluated in the context of how well the patient’s clinical features match the disease linked to the gene. Based on ClinGen SVI Working Group (2021) recommendations:

• If the phenotype matches at the PP4 threshold, PS2 is applied at Strong strength.

• If the phenotype match score is ≥0.8, PS2 is applied at Moderate strength.

• If the phenotype match score is ≥0.4, PS2 is applied at Supporting strength.

This structured approach makes PS2 more consistent and reliable, reducing false positives from unrelated phenotypes.

References:

• Richards, S. et al., 2015 - Standards and Guidelines for the Interpretation of Sequence Variants: A Joint Consensus Recommendation of the ACMG and the AMP. Genetics in Medicine.

• ClinGen Sequence Variant Interpretation (SVI) Working Group, 2021 - Recommendations for De Novo Criteria (PS2 & PM6), Version 1.1.

• Phenomeld – Emedgene’s phenotype-matching system for clinical correlation in variant curation platform Emedgene Analyze.

PM6 - Assumed de novo variant without parentage confirmation (Pathogenic, Moderate to Supporting)

PM6 is used for cases where the variant appears to be de novo, but parentage is not genetically confirmed. The application conditions are the same as for PS2, with the following differences:

1. The proband is heterozygous (or hemizygous) for the variant.

2. Both parents appear wild-type for the variant and are clinically unaffected.

3. Parentage confirmation data is unavailable — either because it was not tested or not recorded.

Phenotype matching again plays a key role in determining PM6 strength:

• PP4 threshold phenotype match → PM6 at Moderate strength.

• Phenotype score ≥0.8 → PM6 at Supporting strength.

• Phenotype score ≥0.4 → PM6 at Supporting strength (lower confidence).

PM6 provides valuable evidence when parentage testing cannot be performed but should be interpreted cautiously, especially for disorders that might have late-onset or incomplete penetrance.

References:

• ClinGen Sequence Variant Interpretation (SVI) Working Group, 2021 - Recommendations for De Novo Criteria (PS2 & PM6), Version 1.1.

• Phenomeld – Emedgene’s phenotype-matching system for clinical correlation in variant curation platform Emedgene Analyze.

The 2021 recommendations from the ClinGen Sequence Variant Interpretation (SVI) Working Group introduced a point-based system to guide the strength of PS2 and PM6 based on phenotypic specificity:

This integration makes de novo evidence more nuanced, standardised, and phenotype-informed, improving classification consistency.

Allelic Data

Allelic data refers to how a variant behaves when it occurs alongside another variant in the same gene or genomic region. It can provide strong evidence either for pathogenicity (when the combination is disease-causing) or for benignity (when the combination does not cause disease). Emedgene applies these ACMG criteria based on variant phasing, inheritance patterns, and supporting parental data.

PM3 - Varinat in trans with a pathogenic variant in a recessive condition (Pathogenic, Moderate to Very Strong)

PM3 is used to support pathogenicity for autosomal recessive conditions when the variant under review is found in trans (on the opposite chromosome) with another pathogenic (P) or likely pathogenic (LP) variant in the same gene.

• In trans means that each variant is inherited from a different parent, so both copies of the gene are altered in the affected individual.

• This combination can cause disease when loss of function from both alleles is the known mechanism.

Conditions for applying PM3 in Emedgene:

1. The condition must be recessive. PM3 is not applied for dominant disorders or mitochondrial DNA (mtDNA) variants.

2. Parental data is required to confirm that the two variants are in trans (each from a different parent).

3. The second variant must have a ClinVar classification of P or LP and a review status of 2–4 stars, indicating moderate to high confidence.

Strength Adjustment: Following ClinGen SVI PM3 v1.0 (2019) recommendations, Emedgene uses a point-based system to determine whether PM3 is applied as Supporting, Moderate, Strong, or Very Strong. Points are assigned based on:

• Phasing – Confirmed in trans vs. unknown

• Classification of the second variant – P, LP, or VUS

• Zygosity – Whether the proband is heterozygous or homozygous

This structured scoring ensures PM3 is only applied when evidence is robust, improving accuracy in recessive disease interpretation.

Reference:

• ClinGen SVI Working Group (2019) - Sequence Variant Interpretation Recommendation for In Trans Criterion (PM3) – Version 1.0

BP2 - Variant in trans in a dominant condition or in cis in any condition (Benign, Supporting)

BP2 supports a benign interpretation when the variant is observed:

1. In trans with a known pathogenic variant in a dominant condition (where having one pathogenic variant is enough to cause disease).

   • If the individual carries both the pathogenic variant and the variant under review but remains unaffected, this suggests the reviewed variant is not contributing to disease.

2. In cis (on the same chromosome) with a known pathogenic variant, in any inheritance pattern.

Requirements in Emedgene:

• Parental testing must confirm whether the variants are in cis or in trans.

• The pathogenic variant must have strong supporting evidence (P or LP classification with reliable ClinVar review).

BP2 is especially useful when evaluating variants in well-studied genes where phasing data is available and disease mechanisms are well understood.

BP3 - In-frame indels in repetitive regions without known function (Benign, Supporting)

BP3 applies to in-frame insertions or deletions (indels) that occur within repetitive genomic regions that have no known functional importance.

• These regions are typically identified using UCSC RepeatMasker annotations.

• Because these repetitive regions can tolerate small sequence changes without affecting gene function, such indels are less likely to be disease-causing.

Conditions for BP3 in Emedgene:

• The variant must be an in-frame change (does not disrupt the reading frame of the gene).

• The repetitive region must be non-functional, based on current genomic annotations.

• BP3 is not applied to mtDNA variants due to different repeat region structures in mitochondrial genomes.

Reference:

• UCSC Genome Browser – RepeatMasker annotations.

Other Database

In ACMG/AMP variant interpretation, “Other Database” criteria refer to classifications taken from trusted external sources—such as ClinVar—that have a strong reputation for accuracy but do not provide publicly accessible or complete functional evidence for the specific variant. Because they rely on classification credibility rather than direct evidence, these tags are applied at a supporting evidence level under ACMG guidelines. They are never used for mitochondrial DNA (mtDNA) variants.

PP5 - Pathogenic classification from a reputable source without accessible evidence (Pathogenic, Supporting)

PP5 is applied when a variant has been reported as pathogenic or likely pathogenic by a reputable source, such as ClinVar, but the laboratory does not have access to the detailed functional evidence necessary to perform an independent evaluation.

Application conditions in Emedgene:

1. The variant must be present in ClinVar with a classification of Pathogenic or Likely Pathogenic.

2. The ClinVar entry must have a review status of 2–4 stars, meaning the classification is based on multiple submitters or expert panel review, giving it moderate to high reliability.

3. The publications linked to the ClinVar submission are automatically checked.

PP5 can provide supporting evidence for pathogenicity when a highly credible classification exists but the lab cannot fully verify the evidence internally. This is especially helpful when dealing with rare variants reported by expert panels or well-established databases. However, because independent verification is not possible, PP5 is only used as supporting-level evidence under ACMG guidelines (Richards et al., 2015).

References:

• Richards, S. et al. (2015) - Standards and Guidelines for the Interpretation of Sequence Variants, Genetics in Medicine, 17(5):405–424.

• ClinVar – National Center for Biotechnology Information (NCBI).

BP6 - Benign classification from a reputable source without accessible evidence (Benign, Supporting)

BP6 is applied when a variant has been reported as benign or likely benign by a reputable source, such as ClinVar, but the laboratory does not have access to the detailed functional evidence needed for independent evaluation.

Application conditions in Emedgene:

1. The variant must be present in ClinVar with a classification of Benign or Likely Benign.

2. The ClinVar entry must have a review status of 2–4 stars for credibility.

3. The system automatically checks the publications linked to the ClinVar submission.

BP6 supports a benign interpretation when a trusted classification exists but the underlying data is not accessible to the lab. It allows curators to benefit from reputable community classifications while acknowledging that these cannot be independently confirmed. Like PP5, BP6 is applied at the supporting evidence level in ACMG scoring, as recommended in Richards et al. (2015).

References:

• Richards, S. et al. (2015) - Standards and Guidelines for the Interpretation of Sequence Variants, Genetics in Medicine, 17(5):405–424.

• ClinVar – National Center for Biotechnology Information (NCBI).

Other Data

In the ACMG/AMP variant interpretation framework, the term “Other Data” refers to evidence types that don’t fall neatly into categories like population frequency, computational predictions, or functional assays. Instead, these criteria rely on clinical context, external expert consensus, or case-level observations. They often require manual review and judgment, and are especially useful when interpreting variants in rare or complex disease settings.

PP4 - Phenotypic Specificity (Pathogenic, Supporting)

PP4 applies when a patient’s phenotype or family history is highly specific for a disease caused by a single gene. Traditionally, this tag was limited to monogenic conditions. However, recent updates based on Biesecker et al., 2024, expand its scope to genetically heterogeneous disorders, provided the phenotype remains uniquely informative.

In Emedgene, PP4 is supported by a smart algorithm that evaluates phenotypic specificity using Phenomeld, a genome-wide phenotype-matching engine. It identifies all genes associated with the patient’s clinical features and calculates specificity based on how few genes match. The fewer the matches, the stronger the PP4 evidence. For example:

• If >200 genes match the phenotype → PP4 is not applied.

• If <50 genes match → PP4 may be applied at Supporting or Moderate strength.

• Rare phenotype combinations across genes may also trigger PP4.

PP4 is only assigned if all relevant genes have been sequenced (e.g., via WES or WGS). Co-segregation evidence (PP1) can complement PP4 in complex cases.

Reference:

• Biesecker et al., 2024 - Refining Phenotype-Based Variant Interpretation: Updated Guidance on PP4, Genetics in Medicine.

BP5 - Alternate molecular basis (Benign, Supporting) (v100.39.0+)

BP5 is applied when a variant is found in a case with an alternate molecular explanation for the disease. This tag supports benign classification by indicating that the observed phenotype is likely caused by another variant or condition.

BP5 is positively activated when all three conditions are met:

• The gene related disease is inheritance mode autosomal dominant.

• The existence of an alternate variant with strong pathogenic evidence and phenotypic match.

• The alternate variant's phenotypic match is strong enough to indicate that this single variant is the disease causing variant.

Reference:

• Richards et al., 2015 - Standards and guidelines for the interpretation of sequence variants, Genetics in Medicine.

• Biesecker et al., 2018 - The ACMG/AMP Reputable Source Criteria

BP6 - Reputable source, no independent evidence (Benign, Supporting)

BP6 is assigned when a reputable source (e.g., ClinVar) reports a variant as benign or likely benign, but the lab cannot independently verify the evidence. In Emedgene, BP6 is applied only if:

• The variant is listed in ClinVar with 2–4 stars.

• No functional studies are cited in the associated publications.

• The variant is not mitochondrial (mtDNA), as BP6 is excluded from mtDNA workflows.

This tag helps streamline classification when external consensus exists but internal validation is limited.

Reference:

• ClinGen SVI Working Group, 2023 - Recommendation for reputable source PP5 and BP6 ACMG/AMP criteria.