Evidence map›Paper›PMID 39030733›Full record

ArticleGenetics in medicine : official journal of the American College of Medical Genetics2024

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

Sarah L Stenton, Vikas Pejaver, Timothy Bergquist, Leslie G Biesecker, Alicia B Byrne, Emily A W Nadeau, Marc S Greenblatt, Steven M Harrison, Sean V Tavtigian, Predrag Radivojac and 3 more

Abstract read
In one paragraph

Article in Genetics in medicine : official journal of the American College of Medical Genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed.

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  13. Calibration of additional computational tools expands ClinGen recommendation options for variant classification with PP3/BP4 criteria.Genetics in medicine : official journal of the American College of Medical Genetics · 2025
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Sarah L StentonProgram 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.
Vikas PejaverInstitute 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.
Timothy BergquistInstitute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY.
Leslie G BieseckerCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD.
Alicia B ByrneProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA.
Emily A W NadeauDepartment of Medicine and University of Vermont Cancer Center, University of Vermont, Larner College of Medicine, Burlington, VT.
Marc S GreenblattDepartment of Medicine and University of Vermont Cancer Center, University of Vermont, Larner College of Medicine, Burlington, VT.
Steven M HarrisonProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA; Ambry Genetics, Aliso Viejo, CA.
Sean V TavtigianDepartment of Oncological Sciences, Huntsman Cancer Institute, University of Utah School of Medicine, Salt Lake City, UT.
Predrag RadivojacKhoury College of Computer Sciences, Northeastern University, Boston, MA.
Steven E BrennerDepartment of Plant and Microbial Biology and Center for Computational Biology, University of California, (redundant), Berkeley, CA.
Anne O'Donnell-LuriaProgram 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.
ClinGen Sequence Variant Interpretation Working Group

Funding

Baylor College of Medicine/Stanford University Clinical Genome Resource (CLINGEN)U24HG009649 · NHGRI · BAYLOR COLLEGE OF MEDICINE · PI TERI Ellen KLEIN, Aleksandar Milosavljevic · 2021 to 2026
$31.5M
The Clinical Genome Resource – Advancing genomic medicine through biocuration and expert assessment of genes and variants at scaleU24HG009650 · NHGRI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI JONATHAN S BERG, Jessica Ezzell Hunter · 2021 to 2026
$30.0M
ClinGen AI Data Delivery SupplementU24HG006834 · NHGRI · BROAD INSTITUTE, INC. · PI Marina DiStefano, CHRISTA LESE MARTIN · 2021 to 2026
$26.7M
The Genome Aggregation Database (gnomAD)U24HG011450 · NHGRI · BROAD INSTITUTE, INC. · PI Mark Joseph Daly, Konrad Karczewski · 2021 to 2026
$22.3M
Joint Center for Mendelian GenomicsUM1HG008900 · NHGRI · BROAD INSTITUTE, INC. · PI O'DONNELL-LURIA, ANNE, REHM, HEIDI L · 2016 to 2020
$16.5M
Genomic Ascertainment - Clinical and Behavioral AspectsZIAHG200387 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI BIESECKER, LESLIE · 2013 to 2025
$15.5M
Broad Institute Mendelian Genomic Research CenterU01HG011755 · NHGRI · BROAD INSTITUTE, INC. · PI Anne O'Donnell-Luria, MICHAEL E TALKOWSKI · 2021 to 2026
$14.6M
Clinical and Molecular Studies of MalformationsZ01HG200328 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI BIESECKER, LESLIE G · 2005 to 2008
$5.5M
Supporting IGVF by modeling genetics, function, and phenotype with machine learningU01HG012022 · NHGRI · NORTHEASTERN UNIVERSITY · PI Predrag Radivojac · 2021 to 2026
$3.4M
Upgrading rigor and efficiency of germline cancer gene variant classification for the 2020sR01CA264971 · NCI · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI Sean Vahram Tavtigian · 2022 to 2026
$2.9M
Integrative data science approaches for rare disease discovery in health recordsR00LM012992 · NLM · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI PEJAVER, VIKAS RAO · 2022 to 2024
$709k
Intramural NIH HHS Z01 HG200328NCI NIH HHS R01 CA264971NHGRI NIH HHS U01 HG011755NHGRI NIH HHS U01 HG012022NHGRI NIH HHS U24 HG006834NHGRI NIH HHS U24 HG009649NHGRI NIH HHS U24 HG009650NHGRI NIH HHS U24 HG011450NHGRI NIH HHS UM1 HG008900NLM NIH HHS R00 LM012992
6 · The paper itself

Abstract

purposeTo 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.

methodsMissense 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.

resultsFrom 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.

conclusionA 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.

Indexed as

Computational BiologyGenome, HumanMutation, MissenseGene FrequencyGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansSoftwareACMG/AMP recommendationsClinical classificationComputational predictorsPP3/BP4 criteriaVariant interpretation

Identifiers

PMID39030733
PMCPMC11560577

What Socratic holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.