Evidence map›Paper›PMID 42238420›Full record

ArticlemedRxiv : the preprint server for health sciences2026

Phenotype-Specific Recalibration of MAVE Data Enables Repurposing of

Pankhuri Gupta, Elsa V Balton, Mavika Tejura, Runjun D Kumar, Matthew W Snyder, Jeremy Stone, Rehan M Villani, Peter H Byers, Sirisak Chanprasert, Ian A Glass and 17 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 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

27 authors.

Pankhuri GuptaDivision of Medical Genetics, University of Washington, Seattle, WA, USA.
Elsa V BaltonDivision of Medical Genetics, University of Washington, Seattle, WA, USA.
Mavika TejuraDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.
Runjun D KumarDepartment of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA.
Matthew W SnyderBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.
Jeremy StoneBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.
Rehan M VillaniQIMR Berghofer, Brisbane, QLD, Australia.
Peter H ByersDivision of Medical Genetics, University of Washington, Seattle, WA, USA.
Sirisak ChanprasertDivision of Medical Genetics, University of Washington, Seattle, WA, USA.
Ian A GlassDivision of Medical Genetics, University of Washington, Seattle, WA, USA.
Martha Horike-PyneDivision of Medical Genetics, University of Washington, Seattle, WA, USA.
Danny E MillerDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.ORCID 0000-0001-6096-8601
Jane RanchalisDivision of Medical Genetics, University of Washington, Seattle, WA, USA.
Elisabeth A RosenthalDivision of Medical Genetics, University of Washington, Seattle, WA, USA.ORCID 0000-0001-6042-4487
Andrew K SolomonDivision of Rheumatology, University of Washington, Seattle, WA, USA.
Mark WenerDivision of Rheumatology, University of Washington, Seattle, WA, USA.ORCID 0000-0002-8304-6957
Undiagnosed Diseases Network (UDN)
Kathleen A LeppigDivision of Medical Genetics, University of Washington, Seattle, WA, USA.
Matthew D BensonDepartment of Ophthalmology and Visual Sciences, University of Alberta, Edmonton, Alberta, Canada.
Melissa J MacPhersonDepartment of Medical Genetics, University of Alberta,l, Edmonton, Alberta, Canada.
Gail P JarvikDivision of Medical Genetics, University of Washington, Seattle, WA, USA.
Katrina M DippleDivision of Medical Genetics, University of Washington, Seattle, WA, USA.
Elizabeth E BlueDivision of Medical Genetics, University of Washington, Seattle, WA, USA.ORCID 0000-0002-0633-0305
Douglas M FowlerDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.
Lea M StaritaDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.ORCID 0000-0003-2870-5099
Abbye E McEwenDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.
Andrew B StergachisDivision of Medical Genetics, University of Washington, Seattle, WA, USA.ORCID 0000-0002-1299-3674

Funding

Diagnosing the Unknown for Care and Advancing Science (DUCAS)U2CNS132415 · NINDS · HARVARD MEDICAL SCHOOL · PI Francis Sessions Cole · 2023 to 2026
$32.1M
Clinical Sequencing Core Facility for the Undiagnosed Diseases Network (UDN)U01HG007942 · NHGRI · BAYLOR COLLEGE OF MEDICINE · PI ENG, CHRISTINE · 2014 to 2021
$10.2M
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
Pacific Northwest Undiagnosed Diseases Network Clinical SiteU01NS134355 · NINDS · UNIVERSITY OF WASHINGTON · PI ELIZABETH ELOYCE BLUE, Katrina M Dipple · 2023 to 2026
$3.0M
Long-read DNA and RNA sequencing to identify disease-causing genetic variation and streamline testingDP5OD033357 · OD · UNIVERSITY OF WASHINGTON · PI MILLER, DANNY ERWIN · 2022 to 2025
$1.9M
C BRIGGSAE AND C ELEGANS GENOMIC SEQUENCE COMPARISONF32HG000130 · NHGRI · WASHINGTON UNIVERSITY · PI COUCH, JENNIFER A · 1994 to 1995
–
NHGRI NIH HHS F32 HG000130NHGRI NIH HHS R01 HG013025NHGRI NIH HHS U01 HG007942NIH HHS DP5 OD033357NINDS NIH HHS U01 NS134355NINDS NIH HHS U2C NS132415
6 · The paper itself

Abstract

Purpose: Multiplexed assays of variant effect (MAVEs) are transforming clinical variant interpretation. However, many genes are associated with more than one disease, making it unclear whether functional data generated in one disease context may be directly applicable to another. For example, germline Methods: Saturation genome editing (SGE) data for Results: Phenotype-specific recalibration using Conclusion: Phenotype-specific recalibration enables appropriately calibrated reuse of MAVE datasets across distinct disease contexts, increasing the clinical utility of MAVE datasets and the interpretability of variants in pleiotropic genes. This framework expands the diagnostic utility of existing functional datasets without requiring new experimental assays.

Identifiers

PMID42238420
PMCPMC13228737

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Registered trials

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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.