Interpretation of variants by ACMG standards and guidelines

Extensive annotation is applied during our genomics analysis. Interpretation of genetic determinants of disease is based on many evidence sources. One important source of interpretation comes from the 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, Richards et al. ¹. See also Li et al., 2017 ² and Riggs et al., 2020 ³. The following tables are provided as they appear in the initial steps of our filtering protocol for the addition of ACMG-standardised labels to candidate causal variants.

For reference, alternative public implementations of ACMG guidelines can be found in Li et al., 2017 ⁴ and Xavier et al., 2019 ⁵; please note these tools have not implemented here nor is any assertion of their quality offered. Examples of effective variant filtering and expected candidate variant yield in studies of rare human disease are provided by Pedersen et al., 2021 ⁶.

Criteria for classifications

Evidence_type	label	Evidence	Manual_adjustment	ACGM_label	Caveat_checks	Criteria
pathogenicity	VS1	very_strong		PVS1	4	null variant (nonsense, frameshift, canonical +- 2 splice sites, initiation codon, single or multiexon deletion) in a gene where LOF is a known mechanism of disease
pathogenicity	S1	strong		PS1	1	Same amino acid change as a previously established pathogenic variant regardless of nucleotide change
pathogenicity	S2	strong	manual	PS2	1	De novo (both maternity and paternity confirmed) in a patient with the disease and no family history
pathogenicity	S3	strong	manual	PS3	1	Well-established in vitro or in vivo functional studies supportive of a damaging effect on the gene or gene product
pathogenicity	S4	strong		PS4	2	The prevalence of the variant in affected individuals is significantly increased compared with the prevalence in controls
pathogenicity	S5	other		PS5		The user has additional (value) strong pathogenic evidence
pathogenicity	M1	moderate		PM1		Located in a mutational hot spot and/or critical and well-established functional domain (e.g., active site of an enzyme) without benign variation
pathogenicity	M2	moderate		PM2	1	Absent from controls (or at extremely low frequency if recessive) in Exome Sequencing Project, 1000 Genomes Project, or Exome Aggregation Consortium
pathogenicity	M3	moderate	manual	PM3	1	For recessive disorders, detected in trans with a pathogenic variant
pathogenicity	M4	moderate		PM4		Protein length changes as a result of in-frame deletions/insertions in a nonrepeat region or stop-loss variants
pathogenicity	M5	moderate		PM5	1	Novel missense change at an amino acid residue where a different missense change determined to be pathogenic has been seen before
pathogenicity	M6	moderate		PM6		Assumed de novo, but without confirmation of paternity and maternity
pathogenicity	M7	moderate	other	PM7		The user has additional (value) moderate pathogenic evidence
pathogenicity	P1	supporting	manual	PP1		Cosegregation with disease in multiple affected family members in a gene definitively known to cause the disease
pathogenicity	P2	supporting		PP2		Missense variant in a gene that has a low rate of benign missense variation and in which missense variants are a common mechanism of disease
pathogenicity	P3	supporting		PP3	1	Multiple lines of computational evidence support a deleterious effect on the gene or gene product (conservation, evolutionary, splicing impact, etc.)
pathogenicity	P4	supporting	manual	PP4		Patient’s phenotype or family history is highly specific for a disease with a single genetic etiology
pathogenicity	P5	supporting		PP5		Reputable source recently reports variant as pathogenic, but the evidence is not available to the laboratory to perform an independent evaluation
pathogenicity	P6	supporting	other	PP6		The user has additional (value) supporting pathogenic evidence
benign	A1	stand_alone		BA1		Allele frequency is >5% in Exome Sequencing Project, 1000 Genomes Project, or Exome Aggregation Consortium
benign	S1	strong		BS1		Allele frequency is greater than expected for disorder
benign	S2	strong		BS2		Observed in a healthy adult individual for a recessive (homozygous), dominant (heterozygous), or X-linked (hemizygous) disorder, with full penetrance expected at an early age
benign	S3	strong	manual	BS3		Well-established in vitro or in vivo functional studies show no damaging effect on protein function or splicing
benign	S4	strong	manual	BS4	1	Lack of segregation in affected members of a family
benign	S5	strong	other	BS5		The user has additional (value) strong benign evidence
benign	P1	supporting		BP1		Missense variant in a gene for which primarily truncating variants are known to cause disease
benign	P2	supporting	manual	BP2		Observed in trans with a pathogenic variant for a fully penetrant dominant gene/disorder or observed in cis with a pathogenic variant in any inheritance pattern
benign	P3	supporting		BP3		In-frame deletions/insertions in a repetitive region without a known function
benign	P4	supporting		BP4	1	Multiple lines of computational evidence suggest no impact on gene or gene product (conservation, evolutionary, splicing impact, etc.)
benign	P5	supporting	manual	BP5		Variant found in a case with an alternate molecular basis for disease
benign	P6	supporting		BP6		Reputable source recently reports variant as benign, but the evidence is not available to the laboratory to perform an independent evaluation
benign	P7	supporting		BP7		A synonymous (silent) variant for which splicing prediction algorithms predict no impact to the splice consensus sequence nor the creation of a new splice site AND the nucleotide is not highly conserved
benign	P8	supporting	other	BP8		The user has additional (value) supporting benign evidence

Caveats implementing filters

Implementing the guidelines for interpretation of annotation requires multiple programmatic steps. The number of individual caveat checks indicate the number of bioinformatic filter functions used. Unnumbered caveat checks indicate that only a single filter function is required during reference to annotation databases. However, each function depends on reference to either one or several evidence source databases (approximately 150 sources) which are not shown here.

Evidence_type	label	Evidence	Manual_adjustment	ACGM_label	Caveat_number	Caveat
pathogenicity	VS1	very_strong		PVS1	1	LoF not disease causing for gene
pathogenicity	VS1	very_strong		PVS1	2	LoF at 3prime end (loftee)
pathogenicity	VS1	very_strong		PVS1	3	exon skipping splce that leave functional protein
pathogenicity	VS1	very_strong		PVS1	4	multiple transcript check
pathogenicity	S1	strong		PS1	1	Assess for splicing vs amino acid change
pathogenicity	S2	strong	manual	PS2	1	“Do not assume maternity or paternity i.e. egg donor, surrogate”
pathogenicity	S3	strong	manual	PS3	1	Quality of functional evidence
pathogenicity	S4	strong		PS4	1	“Assess RR, OR, CI for case/control evidence”
pathogenicity	S4	strong		PS4	2	Rare variant in multiple indipendent cases can guide
pathogenicity	S5	other		PS5
pathogenicity	M1	moderate		PM1
pathogenicity	M2	moderate		PM2	1	Indels in population reference may not match your protocol
pathogenicity	M3	moderate	manual	PM3	1	Pedigree sequencing is ideal. Phasing (GATK) may guide. Ldlink may guide
pathogenicity	M4	moderate		PM4
pathogenicity	M5	moderate		PM5	1	Assess for splicing vs amino acid change
pathogenicity	M6	moderate		PM6
pathogenicity	M7	moderate	other	PM7
pathogenicity	P1	supporting	manual	PP1
pathogenicity	P2	supporting		PP2
pathogenicity	P3	supporting		PP3	1	“Prediction methods may have used the same data sources, do not assume each as independent evidence”
pathogenicity	P4	supporting	manual	PP4
pathogenicity	P5	supporting		PP5
pathogenicity	P6	supporting	other	PP6
benign	A1	stand_alone		BA1
benign	S1	strong		BS1
benign	S2	strong		BS2
benign	S3	strong	manual	BS3
benign	S4	strong	manual	BS4	1	Question the accuracy of segregation. Presence of phenocopies can mimic lack of segregation. Additional pathogenic variants may produce autosomal dominant pattern.
benign	S5	strong	other	BS5
benign	P1	supporting		BP1
benign	P2	supporting	manual	BP2
benign	P3	supporting		BP3
benign	P4	supporting		BP4	1	“Prediction methods may have used the same data sources, do not assume each as independent evidence”
benign	P5	supporting	manual	BP5
benign	P6	supporting		BP6
benign	P7	supporting		BP7
benign	P8	supporting	other	BP8

References

Richards, S. et al., 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), pp.405–423. DOI: 10.1038/gim2015.30. ↩
Li, M.M. et al., 2017. Standards and guidelines for the interpretation and reporting of sequence variants in cancer: a joint consensus recommendation of the Association for Molecular Pathology, American Society of Clinical Oncology, and College of American Pathologists. The Journal of Molecular Diagnostics, 19(1), pp.4–23. DOI: 10.1016/j.jmoldx.2016.10.002. ↩
Riggs, E.R. et al., 2020. Technical standards for the interpretation and reporting of constitutional copy-number variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics (ACMGe and the Clinical Genome Resource (ClinGen). Genetics in Medicine, 22(2), pp.245–257. DOI: 10.1038/s41436-019-0686-8. ↩
Li, Q. and Wang, K., 2017. InterVar: clinical interpretation of genetic variants by the 2015 ACMG-AMP guidelines. The American Journal of Human Genetics, 100(2), pp.267–280. DOI: 10.1016/j.ajhg.2017.01.004. ↩
Xavier, A. et al., 2019. TAPES: A tool for assessment and prioritisation in exome studies. PLoS Computational Biology, 15(10), e1007453. DOI: 10.1371/journal.pcbi.1007453. ↩
Pedersen, B.S. et al., 2021. Effective variant filtering and expected candidate variant yield in studies of rare human disease. NPJ Genomic Medicine, 6(1), pp.1–8. DOI: 10.1038/s41525-021-00227-3. ↩