Evidence map›Paper›PMID 41727046›Full record

ArticlebioRxiv : the preprint server for biology2026

A scalable approach to resolving variants of uncertain significance.

Malvika Tejura, Yile Chen, Abbye E McEwen, Ross Stewart, Yuriy Sverchkov, Florent Laval, Ivan Woo, Daniel Zeiberg, Runxi Shen, Shawn Fayer and 64 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

74 authors.

Malvika TejuraDepartment of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0001-5356-1977
Yile ChenDepartment of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0003-4406-1166
Abbye E McEwenDepartment of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0001-7187-7975
Ross StewartKhoury College of Computer Sciences, Northeastern University, Boston, MA, USA.ORCID 0009-0006-4240-9308
Yuriy SverchkovDepartment of Biostatistics and Medical Informatics, University of Wisconsin, Madison, WI, USA.ORCID 0000-0002-9851-8582
Florent LavalCenter for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA.ORCID 0000-0001-7744-6199
Ivan WooBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.ORCID 0009-0003-0945-8851
Daniel ZeibergThe Institute for Experiential AI, Northeastern University, Boston, MA, USA.ORCID 0000-0002-6919-7572
Runxi ShenImaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID 0000-0002-8883-5496
Shawn FayerDepartment of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0003-1883-9069
Jeremy StoneBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0002-7565-2463
Nahum SmithBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.ORCID 0009-0007-5494-7477
Silvia CasadeiBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0003-2619-5662
Ziyu R WangDepartment of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.ORCID 0009-0000-4924-2463
Matthew W SnyderBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0001-7433-4343
Benjamin J CapodannoBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.ORCID 0009-0007-1273-879X
Pankhuri GuptaDepartment of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.ORCID 0009-0002-5802-1296
Mariam BenazouzMolecular Engineering and Sciences Institute, University of Washington, Seattle, WA, USA.ORCID 0000-0001-8561-296X
Shantanu JainThe Institute for Experiential AI, Northeastern University, Boston, MA, USA.ORCID 0000-0002-7169-9483
Sarah HeidlBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.ORCID 0009-0000-7692-9391
Lara MuffleyDepartment of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0002-3035-3339
Shengcheng DongDepartment of Genetics, Stanford University, Stanford, CA, USA.ORCID 0000-0001-5728-8090
Benjamin C HitzDepartment of Genetics, Stanford University, Stanford, CA, USA.ORCID 0000-0003-3361-3594
Idan GabdankDepartment of Genetics, Stanford University, Stanford, CA, USA.ORCID 0000-0001-5025-5886
Khine LinDepartment of Genetics, Stanford University, Stanford, CA, USA.ORCID 0000-0002-5222-2428
Estelle Y DaDepartment of Bioinformatics, Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia.ORCID 0000-0002-9313-7860
Sabrina BestBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.ORCID 0009-0008-6352-0106
Sally GrindstaffBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0003-0930-0520
David ReinhartBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.ORCID 0009-0009-1975-4180
Leslie Rodriguez-SalasBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.ORCID 0009-0008-0602-8035
Obsa SeidBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.ORCID 0009-0008-4348-1082
Allyssa J VandiDepartment of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.ORCID 0009-0001-6781-416X
Cameron WenmanBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.ORCID 0009-0001-0819-0326
Melinda K WheelockDepartment of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.ORCID 0009-0002-9825-6276
Sriram PendyalaDepartment of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0003-3395-3417
Dan HolmesDepartment of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0002-0489-4043
Alicia XuBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.ORCID 0009-0001-9766-3622
Airi HosokaiBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.ORCID 0009-0008-5802-7130
Maxime TixhonCenter for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA.ORCID 0009-0004-4289-6842
Chloe RenoDonnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.ORCID 0009-0009-9332-0831
Jessica D EwaldImaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID 0000-0002-7555-736X
Kerstin Spirohn-FitzgeraldCenter for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA.ORCID 0000-0002-2071-1606
Tanisha TeelucksinghDonnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.ORCID 0000-0002-1151-8433
Tong HaoCenter for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA.ORCID 0000-0001-7908-3256
Zitong S ChenImaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID 0009-0009-4335-9922
Marzieh HaghighiImaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID 0000-0002-2291-2356
Ahmad Kamal HamidImaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID 0000-0003-4835-5807
Esteban A MigliettaImaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID 0000-0002-4898-7794
Erin WeisbartImaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID 0000-0002-6437-2458
Georges CoppinCenter for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA.ORCID 0000-0001-7647-3240
Luke LambourneCenter for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA.ORCID 0000-0002-7001-7575
Marinella GebbiaDonnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.ORCID 0000-0002-2550-2141
Atina G CotéDonnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.ORCID 0000-0002-0340-9325
Warren van LoggerenbergDepartment of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.ORCID 0000-0002-4912-1044
Kirby M FawcettDepartment of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.ORCID 0009-0004-0729-5283
Robert D SteinerDepartment of Pediatrics, University of Wisconsin-Madison, Madison, WA, USA.ORCID 0000-0003-4177-4590
Jill M JohnsenDivision of Hematology and Oncology, Department of Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0002-2279-2550
Andrew B StergachisDepartment of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0002-1299-3674
Lilia M IakouchevaDepartment of Psychiatry, University of California San Diego, La Jolla, CA, USA.ORCID 0000-0002-4542-5219
Shantanu SinghImaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID 0000-0003-3150-3025
Beth A CiminiImaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID 0000-0001-9640-9318
Frederick P RothDonnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.ORCID 0000-0002-6628-649X
Richard G JamesCenter for Immunity and Immunotherapies, Seattle Children's Research Institute, Seattle, WA, USA.ORCID 0000-0002-2302-7367
IGVF Coding Variants Focus Group
Marc VidalCenter for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA.ORCID 0000-0003-3391-5410
Mikko TaipaleDonnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.ORCID 0000-0003-3811-1761
Anne E CarpenterImaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID 0000-0003-1555-8261
Michael A CalderwoodCenter for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA.ORCID 0000-0001-6475-1418
Mark CravenDepartment of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA.ORCID 0000-0002-8917-7464
Vikas PejaverInstitute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID 0000-0002-1943-0284
Alan F RubinCollaborative Centre for Genomic Cancer Medicine, University of Melbourne, Melbourne, VIC, Australia.ORCID 0000-0003-1474-605X
Predrag RadivojacKhoury College of Computer Sciences, Northeastern University, Boston, MA, USA.ORCID 0000-0002-6769-0793
Douglas M FowlerDepartment of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0001-7614-1713
Lea M StaritaDepartment of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0003-2870-5099

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
Genomic Analysis of Network Perturbations in Human DiseaseP50HG004233 · NHGRI · DANA-FARBER CANCER INST · PI VIDAL, MARC · 2007 to 2017
$31.6M
Support for the use and evaluation of large cloud-based genomic datasets.U24HG012012 · NHGRI · STANFORD UNIVERSITY · PI Mark Bender Gerstein, Benjamin Hitz · 2021 to 2026
$23.0M
University of Washington Mendelian Genomics Research Center (UW-MGRC)U01HG011744 · NHGRI · UNIVERSITY OF WASHINGTON · PI MICHAEL Joseph BAMSHAD, Evan Eichler · 2021 to 2026
$15.8M
The Center for Actionable Variant Analysis; measuring variant function at scaleUM1HG011969 · NHGRI · UNIVERSITY OF WASHINGTON · PI Douglas M Fowler, Lea Starita · 2021 to 2026
$9.9M
Molecular phenotyping of ~100,000 coding variants across Mendelian disease genesUM1HG011989 · NHGRI · DANA-FARBER CANCER INST · PI Marc Vidal · 2021 to 2026
$9.9M
Medical Genetics Training GrantT32GM007454 · NIGMS · UNIVERSITY OF WASHINGTON · PI Gail Pairitz Jarvik, Andrew Ben Stergachis · 1985 to 2026
$6.9M
Linking Variants to Multi-scale Phenotypes via a Synthesis of Subnetwork Inference and Deep LearningU01HG012039 · NHGRI · UNIVERSITY OF WISCONSIN-MADISON · PI Mark W. Craven · 2021 to 2026
$3.5M
Supporting IGVF by modeling genetics, function, and phenotype with machine learningU01HG012022 · NHGRI · NORTHEASTERN UNIVERSITY · PI Predrag Radivojac · 2021 to 2026
$3.4M
Advancing the implementation of variant-level functional data into clinical databases and clinical practiceR01HG013025 · NHGRI · UNIVERSITY OF WASHINGTON · PI Lea Starita, Andrew Ben Stergachis · 2023 to 2026
$3.1M
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
NCATS NIH HHS UL1 TR004419NHGRI NIH HHS P50 HG004233NHGRI NIH HHS R01 HG013025NHGRI NIH HHS R01 HG013350NHGRI NIH HHS U01 HG011744NHGRI NIH HHS U01 HG012022NHGRI NIH HHS U01 HG012039NHGRI NIH HHS U24 HG012012NHGRI NIH HHS UM1 HG011969NHGRI NIH HHS UM1 HG011989NHLBI NIH HHS R01 HL152066NIGMS NIH HHS T32 GM007454NIH HHS S10 OD026880NIH HHS S10 OD030463NIMH NIH HHS R21 MH128827NIMH NIH HHS R56 MH128365
6 · The paper itself

Abstract

Over 90% of missense variants across ~4,000 disease-associated genes are variants of uncertain significance (VUS). Experimental variant effect measurements provide critical evidence about pathogenicity and inform disease biology, but most variants lack data and clinical translation has been limited. The Impact of Genomic Variation on Function Consortium generated experimental data for 62,215 variants across ten genes using multiplexed assays and 1,407 variants across 163 genes using arrayed assays, curated 193,139 additional community-generated variant effect measurements across 30 additional genes, and developed automated calibration methods for translating experimental data and variant effect predictions into clinical evidence. To reduce current VUS, we developed a scalable workflow using only experimental and predictive evidence, enabling reclassification of 75% of the 16,115 VUS in these genes as pathogenic or benign with <1% error. To minimize future VUS, we analyzed >90,000 unobserved variants; 62% had enough evidence to be "preclassified" as pathogenic or benign. We validated our data, evidence and classifications using All of Us and created interactive resources to enable clinical use of the calibrated data. Thus, for 40 genes, representing 1% of the clinical genome, we resolve most existing VUS and future variants, illustrating how systematic use of scalable evidence can empower genomic medicine.

Identifiers

PMID41727046
PMCPMC12918978

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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.