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. 2024 Nov;26(11):101213.
doi: 10.1016/j.gim.2024.101213. Epub 2024 Jul 25.

Assessment of the evidence yield for the calibrated PP3/BP4 computational recommendations

Sarah L Stenton  1 , Vikas Pejaver  2 , Timothy Bergquist  3 , Leslie G Biesecker  4 , Alicia B Byrne  5 , Emily A W Nadeau  6 , Marc S Greenblatt  6 , Steven M Harrison  7 , Sean V Tavtigian  8 , Predrag Radivojac  9 , Steven E Brenner  10 , Anne O'Donnell-Luria  11 ; ClinGen Sequence Variant Interpretation Working Group
Collaborators, Affiliations

Assessment of the evidence yield for the calibrated PP3/BP4 computational recommendations

Sarah L Stenton et al. Genet Med. 2024 Nov.

Abstract

Purpose: To investigate the number of rare missense variants observed in human genome sequences by ACMG/AMP PP3/BP4 evidence strength, following the ClinGen-calibrated PP3/BP4 computational recommendations.

Methods: Missense variants from the genome sequences of 300 probands from the Rare Genomes Project with suspected rare disease were analyzed using computational prediction tools that were able to reach PP3_Strong and BP4_Moderate evidence strengths (BayesDel, MutPred2, REVEL, and VEST4). The numbers of variants at each evidence strength were analyzed across disease-associated genes and genome-wide.

Results: From a median of 75.5 rare (≤1% allele frequency) missense variants in disease-associated genes per proband, a median of one reached PP3_Strong, 3-5 PP3_Moderate, and 3-5 PP3_Supporting. Most were allocated BP4 evidence (median 41-49 per proband) or were indeterminate (median 17.5-19 per proband). Extending the analysis to all protein-coding genes genome-wide, the number of variants reaching PP3_Strong score thresholds increased approximately 2.6-fold compared with disease-associated genes, with a median per proband of 1-3 PP3_Strong, 8-16 PP3_Moderate, and 10-17 PP3_Supporting.

Conclusion: A small number of variants per proband reached PP3_Strong and PP3_Moderate in 3424 disease-associated genes. Although not the intended use of the recommendations, this was also observed genome-wide. Use of PP3/BP4 evidence as recommended from calibrated computational prediction tools in the clinical diagnostic laboratory is unlikely to inappropriately contribute to the classification of an excessive number of variants as pathogenic or likely pathogenic by ACMG/AMP rules.

Keywords: ACMG/AMP recommendations; Clinical classification; Computational predictors; PP3/BP4 criteria; Variant interpretation.

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Conflict of interest statement

Conflict of Interest Leslie G. Biesecker receives royalties from Wolters-Kluwer for authorship of UpToDate, is a member of the Illumina Medical Ethics Committee, and receives research support from Merck, Inc. Anne O’Donnell-Luria oversees the Rare Genomes Project, which received research funding from Illumina Inc. Steven M. Harrison is an employee of Ambry Genetics. Vikas Pejaver and Predrag Radivojac participated in the development of some of the tools assessed in this study. Steven E. Brenner receives research support at UC Berkeley from Tata Consultancy Services. All other authors declare no conflicts of interest.

Update of

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