Evidence map›Paper›PMID 40084623›Full record

ArticleGenetics in medicine : official journal of the American College of Medical Genetics2025

Calibration of additional computational tools expands ClinGen recommendation options for variant classification with PP3/BP4 criteria.

Timothy Bergquist, Sarah L Stenton, Emily A W Nadeau, Alicia B Byrne, Marc S Greenblatt, Steven M Harrison, Sean V Tavtigian, Anne O'Donnell-Luria, Leslie G Biesecker, Predrag Radivojac and 3 more

Abstract read
In one paragraph

Article in Genetics in medicine : official journal of the American College of Medical Genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed, 1 pooled it
–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

47 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. AlphaGenome Atlas:medRxiv : the preprint server for health sciences · 2026
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  8. Elevated Hemoglobin AJournal of clinical laboratory analysis · 2026
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  10. Review
  11. Article
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  15. Review
  16. Article
  17. Article
  18. medRxiv : the preprint server for health sciences · 2026
    Article
  19. Cancer genomic profiling predicts pathogenicity ofmedRxiv : the preprint server for health sciences · 2026
    Article
  20. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Timothy BergquistInstitute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY.
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.
Emily A W NadeauDepartment of Medicine and University of Vermont Cancer Center, University of Vermont, Larner College of Medicine, Burlington, VT.
Alicia B ByrneProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA.
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.
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.
Leslie G BieseckerCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD.
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, Berkeley, CA.
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. Electronic address: vikas.pejaver@mssm.edu.
ClinGen Sequence Variant Interpretation Working Group

Funding

Conduits: Mount Sinai Health System Translational Science HubUL1TR004419 · NCATS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Rosalind J Wright · 2022 to 2026
$46.4M
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
Rare & Mosaic Disorders - Clinical ResearchZIAHG200388 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI BIESECKER, LESLIE · 2013 to 2025
$17.3M
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
Center for Critical Assessment of Genome InterpretationU24HG007346 · NHGRI · UNIVERSITY OF CALIFORNIA BERKELEY · PI BRENNER, STEVEN E, IOANNIDIS, NILAH MONNIER · 2020 to 2025
$3.8M
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
COVID and Translational Science supercomputer (CATS)S10OD030463 · OD · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI KOVATCH, PATRICIA · 2021 to 2021
$2.0M
Big Omics Data Engine 2 SupercomputerS10OD026880 · OD · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI KOVATCH, PATRICIA · 2019 to 2019
$2.0M
Intramural NIH HHS ZIA HG200387Intramural NIH HHS ZIA HG200388NCATS NIH HHS UL1 TR004419NCI NIH HHS R01 CA264971NHGRI NIH HHS R01 HG013350NHGRI NIH HHS U01 HG011755NHGRI NIH HHS U01 HG012022NHGRI NIH HHS U24 HG006834NHGRI NIH HHS U24 HG007346NHGRI NIH HHS U24 HG009649NHGRI NIH HHS U24 HG009650NIH HHS S10 OD026880NIH HHS S10 OD030463NLM NIH HHS R00 LM012992
6 · The paper itself

Abstract

purposeWe previously developed an approach to calibrate computational tools for clinical variant classification, updating recommendations for the reliable use of variant impact predictors to provide evidence strength up to Strong. A new generation of tools using distinctive approaches has since been released, and these methods must be independently calibrated for clinical application.

methodsUsing our local posterior probability-based calibration and our established data set of ClinVar pathogenic and benign variants, we determined the strength of evidence provided by 3 new tools (AlphaMissense, ESM1b, and VARITY) and calibrated scores meeting each evidence strength.

resultsAll 3 tools reached the Strong level of evidence for variant pathogenicity and Moderate for benignity, although sometimes for few variants. Compared with previously recommended tools, these yielded at best only modest improvements in the trade-offs between evidence strength and false-positive predictions.

conclusionAt calibrated thresholds, 3 new computational predictors provided evidence for variant pathogenicity at similar strength to the 4 previously recommended predictors (and comparable with functional assays for some variants). This calibration broadens the scope of computational tools for application in clinical variant classification. Their new approaches offer promise for future advancement of the field.

Indexed as

Computational BiologyGenetic VariationCalibrationHumansSoftwareACMG/AMP classificationAlphaMissenseCalibrationESM1bVARITY

Identifiers

PMID40084623
PMCPMC12208618

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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 OpenQuestion graph.