A scalable approach to resolving variants of uncertain significance

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.

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-02-15
DOI
https://doi.org/10.64898/2026.02.14.705848
Primary Topic
Genomics and Rare Diseases
Type
article
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article

A scalable approach to resolving variants of uncertain significance

Sally B. Grindstaff, Matthew W. Snyder, S Best, A Stergachis et al.
bioRxiv (Cold Spring Harbor Laboratory)
Genomics and Rare Diseases
article

A scalable approach to resolving variants of uncertain significance

Sally B. Grindstaff, Matthew W. Snyder, S Best, A Stergachis, Sarah Heidl, Lara A. Muffley, Pankhuri Gupta, Esteban Miglietta, Michael A. Calderwood, Jessica Ewald, Leslie Rodriguez-Salas, Tong Hao, Shengcheng DONG, Mikko Taipale, Predrag Radivojac, Anne E. Carpenter, Daniel Zeiberg, Ivan M. H. Woo, D. Mark Holmes, Khine Lin, David Reinhart, Estelle Y. Da, Mark Craven, B. C. Hitz, M. Vidal, Y P Chen, Frederick P. Roth, BA Cimini, Maxime Tixhon, Mariam Benazouz, Allyssa Vandi, Douglas M. Fowler, Benjamin J. Capodanno, Airi Hosokai, Ross Stewart, Lea M. Starita, Alan F. Rubin, Malvika Tejura, Luke Lambourne, Shawn Fayer, Silvia Casadei, Florent Laval, Alicia Xu, Runxi Shen, Marzieh Haghighi, Lilia M Iakoucheva, Georges Coppin, Ahmad Kamal Hamid, Yuriy Sverchkov, IGVF Coding Variants Focus Group, Melinda K Wheelock, Atina G. Atina, Obsa Seid, Warren van van Loggerenberg, Idan Gabdank, Shantanu Jain, Zitong S. Chen, Kirby M Fawcett, Tanisha Teelucksingh, Richard G. James, Cameron Wenman, Kerstin Spirohn-Fitzgerald, Vikas Pejaver
article en

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.

bioRxiv (Cold Spring Harbor Laboratory)
Wisconsin Department of Health Services (US), Broad Institute (US), Northeastern University (US), European Bioinformatics Institute (GB), University of Wisconsin–Madison (US), Harvard University (US), University of Pittsburgh (US), University of Toronto (CA), Walter and Eliza Hall Institute of Medical Research (AU), University of Washington (US), Lunenfeld-Tanenbaum Research Institute (CA), University of Washington Medical Center (US), University of California San Diego (US), Boston VA Research Institute (US), Dana-Farber Cancer Institute (US), Sinai Health System (CA), Brotman Baty Institute (US), AGRF Ltd (AU), Genomic Health (United States) (US), Stanford University (US), Icahn School of Medicine at Mount Sinai (US)
Openalex Percentile: Top 52%
Genomics and Rare Diseases
DOIOpen Access PDFOpenAlex
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