Evidence map›Paper›PMID 40480200›Full record

ArticleAmerican journal of human genetics2025

Validating data from multiplex assays of variant effect: A CanVIG-UK national survey of NHS clinical scientists.

Sophie Allen, Alice Garrett, Charlie F Rowlands, Miranda Durkie, George J Burghel, Rachel Robinson, Alison Callaway, Joanne Field, Bethan Frugtniet, Sheila Palmer-Smith and 12 more

Abstract read
In one paragraph

Article in American journal of human genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. High-throughput mapping of 6,888bioRxiv : the preprint server for biology · 2026
    Article
  6. MaveMD: A functional data resource for genomic medicine.medRxiv : the preprint server for health sciences · 2025
    Article
  7. Article
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

22 authors.

Sophie AllenDivision of Genetics and Epidemiology, the Institute of Cancer Research, London, UK.
Alice GarrettDivision of Genetics and Epidemiology, the Institute of Cancer Research, London, UK; St George's University Hospitals NHS Foundation Trust, Tooting, London, UK.
Charlie F RowlandsDivision of Genetics and Epidemiology, the Institute of Cancer Research, London, UK.
Miranda DurkieNorth East and Yorkshire Genomic Laboratory Hub, Sheffield Children's Hospital NHS Foundation Trust, Sheffield, UK.
George J BurghelManchester Centre for Genomic Medicine and NW Laboratory Genetics Hub, Manchester University Hospitals NHS Foundation Trust, Manchester, UK; Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, the University of Manchester, Manchester, UK.
Rachel RobinsonYorkshire Regional Genetics Service, Leeds Teaching Hospitals NHS Trust, Leeds, UK.
Alison CallawayCentral and South Genomics Laboratory Hub, Wessex Genomics Laboratory Service, University Hospital Southampton NHS Foundation Trust, Salisbury, UK.
Joanne FieldGenomics and Molecular Medicine Service, Nottingham University Hospitals NHS Trust, Nottingham, UK.
Bethan FrugtnietSt George's University Hospitals NHS Foundation Trust, Tooting, London, UK.
Sheila Palmer-SmithWales Genomic Health Centre, Cardiff and Vale University Health Board, Cardiff, UK.
Jonathan GrantLaboratory Genetics, Queen Elizabeth University Hospital, NHS Greater Glasgow and Clyde, Glasgow, UK.
Judith PaganSouth East Scotland Clinical Genetics, Western General Hospital, Edinburgh, UK.
Trudi McDevittDepartment of Clinical Genetics, Children's Health Ireland at Crumlin, Dublin, Ireland.
Katie SnapeSt George's University Hospitals NHS Foundation Trust, Tooting, London, UK.
Helen HansonPeninsula Regional Genetics Service, Royal Devon University Healthcare National Health Service Foundation Trust, Exeter, UK; Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Exeter, UK.
Terri McVeighThe Royal Marsden National Health Service Foundation Trust, Fulham Road, London, UK.
David J AdamsWellcome Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.
Gregory M FindlayThe Genome Function Laboratory, the Francis Crick Institute, London, UK.
Rehan M VillaniQIMR Berghofer, Brisbane, QLD, Australia.
Amanda B SpurdleQIMR Berghofer, Brisbane, QLD, Australia; University of Queensland, Brisbane, QLD, Australia.
Clare TurnbullDivision of Genetics and Epidemiology, the Institute of Cancer Research, London, UK; The Royal Marsden National Health Service Foundation Trust, Fulham Road, London, UK. Electronic address: turnbull.lab@icr.ac.uk.
CanVIG-UK Consortium

Funding

Cancer Research UK A27223Medical Research Council CC2190
6 · The paper itself

Abstract

Advances in technology have made it possible for multiplex assays of variant effect (MAVEs) to systematically generate functional data for thousands of genetic variants. Robust clinical validation and accessible online resources for MAVE data have previously been identified as barriers to the clinical adoption of new MAVEs. We delivered a survey during the November 2024 Cancer Variant Interpretation Group UK (CanVIG-UK) meeting comprising National Health Service (NHS) clinical scientists and clinical geneticists and received 46 responses from individuals regularly performing variant classification for diagnostic reporting. Only 35% reported they would accept clinical validation of the MAVE provided by the authors who conducted the assay; 20% reported they would attempt clinical validation themselves, and 61% would await clinical validation by a trusted central body. 72% reported they would use MAVE data ahead of a formal peer-reviewed publication if reviewed and clinically validated by a trusted central body. When scoring central bodies on a scale of 1-5 for confidence in their review and validation of MAVEs, CanVIG-UK (median = 5), variant curation expert panels (VCEPs; median = 5), and ClinGen SVI Functional Working Group (median = 4) all scored highly. Participants supported making variant-level data accessible via a relevant web resource (although the majority of participants expressed that additional assay-level or variant-level information would have a low likelihood of altering validation scores provided by a trusted central body). These findings, from a comparatively homogeneous clinical diagnostic group operating in a resource-constrained healthcare setting, indicate that clinical application of new MAVEs for variant classification will be delayed unless robust clinical validations are performed by a trusted central body and made readily accessible.

Indexed as

Genetic TestingGenetic VariationNeoplasmsHumansReproducibility of ResultsState MedicineSurveys and QuestionnairesUnited KingdomACMG/AMP variant classification frameworkBrnich-style validationCanVIG-UKclinical variant classificationMAVE dataPS3/BS3 scoresvariant truth sets

Identifiers

PMID40480200
PMCPMC12256791

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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 OpenQuestion graph.