Skip main navigation

ACMG & ACGS guidelines Part 6: De novo, allelic and segregation data

ACMG & ACGS guidelines part 6_
© St George’s, University of London

In this step, we will consider how data from family studies are used in the ACMG guidelines1 and ACGS update.2

This encompasses three evidence categories:

  • De novo data
  • Allelic data
  • Segregation data.

Since we have not discussed these types of data before, we will cover them here in some detail.

De novo data

Look at the figure below, which shows the part of the ACMG evidence framework that relates to de novo data.

De novo data can be used as evidence to support a pathogenic classification. There are two criteria that might be used to support pathogenicity (PS2 and PM6).

Table showing the De novo data row in the ACMG guideline table. Info is as follows: Pathogenic: Moderate: De novo (without paternity & maternity confirmed) PM6, Strong: De novo (paternity & maternity confirmed) PS2 Click to expand

A variant is described as ‘de novo’ if it occurred for the first time in an affected individual and was not inherited from their parents. This type of inheritance is not uncommon for rare diseases.

De novo status can be used as evidence in support of pathogenicity if the phenotype and family history of the disease are consistent (e.g. the clinical presentation is concordant with the gene and, for dominant variants, the parents are unaffected parents but the child is affected).

This consistency is important, because de novo occurrence alone is not enough to determine that a variant is pathogenic. In fact, whole genome sequencing studies have shown that healthy individuals carry around 40-80 de novo SNVs in their genome, with an average of 1-2 affecting the coding sequence.3

When assessing apparently de novo variants it is important to confirm paternity and maternity wherever possble. Without doing this there remains the possibility that a variant could be clinically insignificant if inherited from a healthy but unknown and untested biological parent. The ACMG guidance1 uses different codes depending upon whether paternity and maternity have been confirmed:

  • PS2 – if maternity and paternity have been confirmed, for example if the variant was identified through trio exome or genome sequencing. (These tests would reveal, as an incidental finding, if there was non-paternity or non-maternity, so confirm biological parentage.)
  • PM6 – if maternity and paternity have not been confirmed, for example if the variant was identified through targeted Sanger sequencing of the affected individual and their parents. (This test would confirm the variant as de novo, but would not reveal non-paternity or non-maternity, so here biological parentage is not confirmed.)

It also stipulates that these codes can only be used if the phenotype is consistent with that expected for the gene in question and suggests using a sliding scale, from supporting to strong, to reflect how well the phenotype matches the genotype, how specific the phenotype is and if there is a high degree of genetic heterogeneity.

For instance, if a de novo variant has been identified through trio exome sequencing (therefore confirming maternity and paternity) but the phenotype is consistent with the genotype but non-specific, PS2 can be used but only at supporting strength: PS2_Supporting.

Detailed guidance4 on how to determine the strength level at which PS2/PM6 can be applied has been developed by the ClinGen Sequence Variant Interpretation working group:

  • This points-based system considers whether the parental relationships are confirmed or assumed, the phenotypic specificity, and the genotype-phenotype consistency, for each de novo occurrence of a given variant.
  • The combined point value for all de novo occurrences is then calculated to determine the level at which PS2/PM6 can be applied.

Allelic data

Look at the figure below, which shows the part of the ACMG evidence framework that relates to allelic data.

Allelic data can be used as evidence to support either a benign or a pathogenic classification. There is one criterion that might be used to support pathogenicity (PM3) and one criterion that might be used to support a benign classification (BP2).

Table showing the allelic data row in the ACMG guideline table. Info is as follows: Benign: Supporting: Observed in trans with a dominant variant BP2, Pathogenic: Moderate: For recessive disorders, detected in trans with a pathogenic variant PM3. Click to expand

This category is applicable to recessive conditions and considers the phase of a variant, i.e. whether a variant is in cis (on the same chromosome) or in trans (on the opposite chromosome) with an established pathogenic variant. This requires testing of parents to confirm phase.

Diagram showing in variants in trans, two chromosomes with a cross marking the variant on each as well as variants in cis which is two chromosomes with both variants marked by a cross on the left chromosome

In recessive disease, the evidence category PM3 can be used if the variant is in trans with a (likely) pathogenic variant in an affected individual.

PM3 can be up- or downgraded, according to whether the variant phasing has been confirmed or not, and the classification of the variant observed on the other allele.

Detailed guidance5 on how to apply PM3 has recently been published by the ClinGen Sequence Variant Interpretation (SVI) working group:

  • This points-based system is based upon the phasing of the two variants (i.e. whether confirmed in trans or unknown), whether the variants are compound heterozygous or homozygous, and the classification of the variant observed on the other allele (i.e. pathogenic/likely pathogenic/VUS) for each proband.
  • Application of PM3 is contingent on the allele frequency of both variants being sufficiently rare (meets PM2 threshold). This is to avoid incorrect application of PM3 to high frequency variants that are likely to occur in ​trans​ with pathogenic/likely pathogenic variants based on frequency.
  • The combined points value for all probands can be used to determine the appropriate evidence strength level at which PM3 can be applied.

Allelic data can also be used in support of a benign variant classification:

  • In the context of a fully penetrant dominant disorder, if a variant is observed to be in trans with a pathogenic (or likely pathogenic) variant in an affected individual, this can be considered supporting evidence for a benign variant classification, BP2.
  • In the context of an individual affected by a recessive condition, finding that the variant under investigation is in cis with a known pathogenic (or likely pathogenic) variant, rather than in trans, can be considered evidence in support of a benign variant classification, BP2.

Segregation data

Look at the figure below, which shows the part of the ACMG evidence framework that relates to segregation data.

Segregation data can be used as evidence to support either a benign or a pathogenic classification. There is one criterion that might be used to support pathogenicity (PP1) and one criterion that might be used to support a benign classification (BS4).

Table showing the segregation data row in the ACMG guidelines table. Info is as follows: Benign: Strong: Non-segregation with disease BS4, Pathogenic: Supporting: Co-segregation with disease in multiple affected family members PP1, Supporting to Moderate to Strong: Increased segregation data. Click to expand

Segregation data can be collected from families where multiple relatives are affected, and from individuals across multiple affected families.

Segregation of a specific variant with a phenotype or disease in multiple affected family members, or across multiple families can be used as evidence in support of pathogenicity (PP1). Conversely, non-segregation of a variant with disease can be used as evidence in support of a benign classification (BS4).

Segregation data must be considered carefully as there are several caveats:

  • Segregation of a variant with a phenotype may be evidence of linkage of that locus to the disorder, but it does not confirm pathogenicity of the variant itself, which may instead be in linkage disequilibrium with a pathogenic variant.
  • Penetrance (which may be age-related) should be carefully considered before assigning ‘unaffected’ status to family members.
  • In more common phenotypes (e.g. breast cancer), phenocopies may occur. These are individuals affected with the condition due to a non-genetic or different genetic cause.
  • When using non-segregation with disease of a variant in support of a benign classification, biological family relationships must be confirmed.

Segregation data can be used on a sliding scale: it can be used as stronger evidence with increasing segregation data (PP1_Moderate or PP1_Strong). Detailed guidelines have been produced to support segregation data analysis and determine the strength at which PP1 should be applied,6 and these will be fully discussed in the next step.

We have created a PDF table summarising these three different categories of evidence, and how they relate to the various ACMG criteria. We suggest that you take some time now to study this table in detail, make sure you understand the circumstances in which each evidence criterion is used, and download it for future reference.

Again, whilst this provides a brief summary, those wishing for full details should refer to the relevant sections of the ACMG guidelines1 and ACGS update.2

Talking point

Family studies may seem a relatively easy way to investigate a variant’s pathogenicity. However, you will now have learnt that many affected family members are needed to provide significant evidence.

Can you think of any other complexities in testing multiple relatives, and why this may not always be the best option for patients?

References
1 Richards S, Aziz N, Bale S, et al, ‘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’. Genet Med. 2015;17(5):405-424. doi:10.1038/gim.2015.30
2 Ellard S, Baple E, Callaway A, et al, ‘ACGS Best Practice Guidelines for Variant Classification in Rare Disease 2020’, AGCS. 2020.
3 Acuna-Hidalgo R, Veltman JA, Hoischen A. New insights into the generation and role of de novo mutations in health and disease. Genome Biol. 2016;17(1):241. Published 2016 Nov 28. doi:10.1186/s13059-016-1110-1.
4 ClinGen Sequence Variant Interpretation Recommendation for de novo Criteria (PS2/PM6) – Version 1.1 Working Group Page ClinGen Sequence Variant Interpretation Recommendation for de novo Criteria (PS2/PM6)
5 ClinGen Sequence Variant Interpretation Recommendation for in trans Criterion (PM3) – Version 1.0 Working Group Page ClinGen Sequence Variant Interpretation Recommendation for in ​trans​ Criterion (PM3)
6 Jarvik GP, Browning BL. Consideration of Cosegregation in the Pathogenicity Classification of Genomic Variants. Am J Hum Genet. 2016;98(6):1077-1081. doi:10.1016/j.ajhg.2016.04.003

For those taking part in the external course evaluation please follow this link to provide feedback for the step.

© St George’s, University of London
This article is from the free online

Interpreting Genomic Variation: Fundamental Principles

Created by
FutureLearn - Learning For Life

Our purpose is to transform access to education.

We offer a diverse selection of courses from leading universities and cultural institutions from around the world. These are delivered one step at a time, and are accessible on mobile, tablet and desktop, so you can fit learning around your life.

We believe learning should be an enjoyable, social experience, so our courses offer the opportunity to discuss what you’re learning with others as you go, helping you make fresh discoveries and form new ideas.
You can unlock new opportunities with unlimited access to hundreds of online short courses for a year by subscribing to our Unlimited package. Build your knowledge with top universities and organisations.

Learn more about how FutureLearn is transforming access to education