TY - JOUR
T1 - Assessment of the evidence yield for the calibrated PP3/BP4 computational recommendations
AU - ClinGen Sequence Variant Interpretation Working Group
AU - Stenton, Sarah L.
AU - Pejaver, Vikas
AU - Bergquist, Timothy
AU - Biesecker, Leslie G.
AU - Byrne, Alicia B.
AU - Nadeau, Emily A.W.
AU - Greenblatt, Marc S.
AU - Harrison, Steven M.
AU - Tavtigian, Sean V.
AU - Radivojac, Predrag
AU - Brenner, Steven E.
AU - O'Donnell-Luria, Anne
AU - Tayoun, Ahmad A.
AU - Berg, Jonathan S.
AU - Cutting, Garry R.
AU - Ellard, Sian
AU - Kang, Peter
AU - Karbassi, Izabela
AU - Karchin, Rachel
AU - Mester, Jessica
AU - Pesaran, Tina
AU - Plon, Sharon E.
AU - Rehm, Heidi L.
AU - Strande, Natasha T.
AU - Topper, Scott
N1 - Publisher Copyright:
© 2024 American College of Medical Genetics and Genomics
PY - 2024/11
Y1 - 2024/11
N2 - 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.
AB - 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.
KW - ACMG/AMP recommendations
KW - Clinical classification
KW - Computational predictors
KW - PP3/BP4 criteria
KW - Variant interpretation
UR - http://www.scopus.com/inward/record.url?scp=85204127825&partnerID=8YFLogxK
U2 - 10.1016/j.gim.2024.101213
DO - 10.1016/j.gim.2024.101213
M3 - Article
C2 - 39030733
AN - SCOPUS:85204127825
SN - 1098-3600
VL - 26
JO - Genetics in Medicine
JF - Genetics in Medicine
IS - 11
M1 - 101213
ER -