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Assessment of the evidence yield for the calibrated PP3/BP4 computational recommendations.
Stenton, Sarah L; Pejaver, Vikas; Bergquist, Timothy; Biesecker, Leslie G; Byrne, Alicia B; Nadeau, Emily A W; Greenblatt, Marc S; Harrison, Steven M; Tavtigian, Sean V; Radivojac, Predrag; Brenner, Steven E; O'Donnell-Luria, Anne.
Afiliação
  • Stenton SL; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA; Division of Genetics and Genomics, Boston Children's Hospital, Harvard Medical School, Boston, MA.
  • Pejaver V; Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY.
  • Bergquist T; Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY.
  • Biesecker LG; Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD.
  • Byrne AB; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA.
  • Nadeau EAW; Department of Medicine and University of Vermont Cancer Center, University of Vermont, Larner College of Medicine, Burlington, VT.
  • Greenblatt MS; Department of Medicine and University of Vermont Cancer Center, University of Vermont, Larner College of Medicine, Burlington, VT.
  • Harrison SM; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA; Ambry Genetics, Aliso Viejo, CA.
  • Tavtigian SV; Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah School of Medicine, Salt Lake City, UT.
  • Radivojac P; Khoury College of Computer Sciences, Northeastern University, Boston, MA.
  • Brenner SE; Department of Plant and Microbial Biology and Center for Computational Biology, University of California, (redundant), Berkeley, CA.
  • O'Donnell-Luria A; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA; Division of Genetics and Genomics, Boston Children's Hospital, Harvard Medical School, Boston, MA. Electronic address: odonnell@broadinstitute.org.
Genet Med ; 26(11): 101213, 2024 Jul 25.
Article em En | MEDLINE | ID: mdl-39030733
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.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Genet Med Assunto da revista: GENETICA MEDICA Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Genet Med Assunto da revista: GENETICA MEDICA Ano de publicação: 2024 Tipo de documento: Article