2015 American College of Medical Genetics (ACMG) variant interpretation framework

A variety of evidence types can contribute to assertions of pathogenicity or benignity, for example, the number of independent cases with a characteristic phenotype, familial segregation data, frequency in population controls and functional analyses. Historically, appropriation of disparate evidence elements could differ widely between diagnostic laboratories and produce discrepant classifications. To advance consistency in diagnostic variant interpretation, in 2015, the ACMG published a framework for variant classification.³ In 2016, it was agreed by the UK Association for Clinical Genomic Science (UK-ACGS) to adopt formally across NHS molecular diagnostics the ACMG framework for variant interpretation. Each year, a detailed UK ACMG-based specification is published, ‘The UK-ACGS Best Practice Guidelines for Variant Classification in Rare Disease’.⁴

Cancer Variant Interpretation Group UK (CanVIG-UK)

CanVIG-UK was established in 2017 as part of the UK-ACGS activity supporting adoption and dissemination of the ACMG framework for variant interpretation.⁵ CanVIG-UK currently comprises >100 clinical scientists, clinical geneticists and genetic counsellors, with representation from each of the 25 Molecular Diagnostic Laboratories and Clinical Genetics Services of the UK (NHS) and Republic of Ireland. The group meets monthly to undertake multidisciplinary review and interpretation of problematic clinically detected variants. CanVIG-UK maintains an annually updated consensus specification for CSGs of the UK-ACGS Best Practice Guidelines for Variant Classification in Rare Disease (hereafter termed the CanVIG-UK specification).⁵

Outcome

Derived from the Tavtigian Bayesian metastructure and consistent with the UK-ACGS Best Practice Guidelines for Variant Classification in Rare Disease 2020, we defined an ‘exponent scoring system’, similar to the approach taken by Tavtigian et al in a recent adaptation of their original metastructure.^{4 10 11} Evidence elements were allocated points according to evidence strength level: (towards pathogenicity) VS (eight points), S (four points), M (two points), and P (one point) and (towards benignity) S (−4 points) and P (−1 points) (table 1A). Arithmetic summing of the exponent scores for the contributing evidence elements generates an ‘exponent sum’. Assignment of a particular classification is predicated on attainment of an exponent sum threshold value of 6–9 (likely pathogenic), ≥10 (pathogenic), (−1)−(−5) (likely benign) and ≤−6 (benign) (table 1B).

Discussion

Conversion of the tally-based 2015 ACMG framework into a numerical exponent scoring system (derived from the Tavtigian Bayesian metastructure) is a useful evolution of the ACMG framework allowing rapid calculation of variant classification category. It is designed to augment, not replace the five-level classification system. In addition, the exponent scoring system:

• Enables delineation of previously undescribed legitimate combinations of evidence elements of equivalent numerical posterior probability.

• Highlights the incongruity in the numerical posterior probability for some combinations of evidence elements in the original 2015 ACMG framework, as previously described by Tavtigian et al. ¹⁰

• Allows objective stratification of the evidence strength for likely pathogenic variants (exponent score sum range 6–9). The exponent system provides a clearer and more consistent numerical language with which to continue dialogue regarding management quandaries about likely pathogenic variants being of ‘lower confidence’ and ‘higher confidence’. This typically comprises contexts in which a higher bar of evidence is argued to be desirable (eg, prenatal testing).

• Likewise allows objective stratification of evidence strength for ‘uncertain’ variants (exponent score sum range 0–5) (table 2, as described in the UK-ACGS Best Practice Guidelines for Variant Classification in Rare Disease 2020).⁴ Again, the exponent system provides a clearer and more consistent numerical language with which to debate longstanding clinical quandaries/scenarios, such as:

  Table 2

  Five strengths of variant of uncertain significance, annotated by potential evidence combinations, posterior probability of pathogenicity, ‘exponent sum’ and UK-ACGS Best Practice Guidelines for Variant Classification in Rare Disease descriptor⁴

  Exponent score for evidence elements	Exponent sum	Overall (posterior) probability of pathogenicity (%)	UK-ACGS descriptor
  Towards pathogenicity: 8 (very strong), 4 (strong), 2 (moderate), 1 (supporting) towards benignity: −4 (strong), −1 (supporting)
  4+1	5	0.812 (81.2)	Hot VUS
  2+2+1
  2+1+1+1
  1+1+1+1+1
  4	4	0.675 (67.5)	Warm VUS
  2+2
  2+1+1
  1+1+1+1
  2+1	3	0.500 (50.0)	Tepid VUS
  1+1+1
  2	2	0.325 (32.5)	Cool VUS
  1+1
  1	1	0.188 (18.8)	Ice-cold VUS

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  UK-ACGS, UK Association for Clinical Genomic Science; VUS, variant of uncertain significance.

  1. Quantifying the magnitude of additional evidence required for a VUS to achieve a classification of likely pathogenic (eg, ‘a four-point-VUS, for which two more exponent points are required for upclassification to likely pathogenic’).

  2. Defining the swathe of VUSs for which ‘active’ variant monitoring is indicated (eg, perhaps all five-point VUSs).

  3. Differential evidence requirements in oncology between the therapeutic context and the context of familial risk prediction. It has been argued in oncology that evidence of therapeutic actionability for some somatic biomarkers in use may be significantly weaker than for others, for example, atypical BRAF variants as indication for vemurafenib administration or an Allred score of 4 as indication for tamoxifen administration.^12–14 Whilst it has been argued that germline variants of posterior probability of pathogenicity of 0.8-0.9 (80%–90%)could be equivalently eligible as therapeutic biomarkers (while not used for genetic risk prediction), any changes to current practice would require very careful consideration of potential clinical pitfalls and detailed economic evaluation.

Key to implementation of the Bayesian metastructure (and indeed the 2015 ACMG framework) is recognition that the overall (posterior) probability of pathogenicity is dependent not just on the aggregate likelihood ratio of the contributory evidence elements but also on the prior probability of pathogenicity. The exponent sums presented correspond to the respective posterior probability thresholds only in the context of a specified prior probability of 0.1 (10%). This approximates to clinical analysis of a limited gene set in a proband with a suspected Mendelian disorder.^{10 15} In the context of a substantially lower prior probability (absence of phenotype and/or examination of a much larger gene set), additional evidence elements will be required to attain a specified posterior probability.^{16 17} Potential methods for estimating the prior probability of pathogenicity in different contexts are under development by several groups; integration into clinical variant interpretation frameworks is a priority for future work.

Outcome

Outcome

As previously described by Tavtigian et al and the UK-ACGS Best Practice Guidelines for Variant Classification in Rare Disease 2020, we confirmed that two combinations in the 2015 ACMG framework were incongruous with the exponent scoring system, (1) one ascribed as pathogenic for which the exponent score is only eight and (2) one ascribed as likely pathogenic for which the exponent score is 10.^{4 10} Consistent with restrictions in combination due to non-permissibility (table 4) and/or incompatible variant types (table 5), we confirmed validity of nine new combinations for pathogenic and three for likely pathogenic.

Discussion

It was the overall consensus of the CanVIG-UK group to retain the requirement for at least two items of evidence to provide buffer against false-positive classification of a variant as likely benign/likely pathogenic via a spurious evidence item. Thus, although a sufficient exponent sum is attained with a single evidence item, classification out of VUS is not permitted in these instances: (1) likely pathogenic with a single very strong evidence element, (2) likely benign with a single supporting/strong evidence element.

Outcome

These three approaches were reviewed within CanVIG-UK through application to a number of exemplar variants. Consensus opinion was for option 3 as laid out in the following consensus recommendations and in table 7.

Discussion

In variant classification, we seek to balance the clinical benefit of classification of a variant out of the ‘VUS’ category against the harms of erroneous misclassification. Variants classified as likely pathogenic have a 90%–99%likelihood of pathogenicity: this group should thus contain a ~5% (1%–10%) frequency of variants that are truly benign and have been misclassified as likely pathogenic. Variants classified as likely benign have a 0.1%–10%likelihood of truly being pathogenic. Thus, while downclassification of variants in CSGs will and should occur periodically in practice, it is important to recognise the consequent clinical disruption, particularly if multiple unaffected family members have undertaken risk-reducing surgery.

There would be a clear rationale for agnostic use of the net exponent score if all evidence was of unquestionable provenance and guaranteed to be wholly correct. In practice, in clinical observations, laboratory assays and/or published reports, there is always potential for error in evidence generation or communication. The presence of discordant evidence elements will occur by chance through statistical distribution of true results; it may also be an indicator towards error within one of the evidence items. Discordant results between clinical findings and laboratory results may also be an indicator of intermediate penetrance. Overall in CanVIG-UK, we adopted a strategy whereby classification from VUS to another class was permitted, providing the conflicting evidence did not exceed a single supporting evidence element.

PM2 (absence in controls) provides evidence of rarity, rather than evidence against benignity and can thus be ignored when calculating the net exponent sum for benignity. Pathogenic variants will necessarily be rare (except occasional founders); the frequency of benign variants will vary from very common to very rare.