Evidence map›Paper›PMID 34906510›Full record

ArticleGenetics in medicine : official journal of the American College of Medical Genetics2022

Reanalysis of eMERGE phase III sequence variants in 10,500 participants and infrastructure to support the automated return of knowledge updates.

Hana Zouk, Wanfeng Yu, Andrea Oza, Megan Hawley, Prathik K Vijay Kumar, Christopher Koch, Lisa M Mahanta, John B Harley, Gail P Jarvik, Elizabeth W Karlson and 7 more

Abstract read
In one paragraph

Article in Genetics in medicine : official journal of the American College of Medical Genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
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  3. Review
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  5. Review
  6. Article
  7. The landscape of reported VUS in multi-gene panel and genomic testing: Time for a change.Genetics in medicine : official journal of the American College of Medical Genetics · 2023
    Article
  8. Article
  9. 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

17 authors.

Hana ZoukLaboratory for Molecular Medicine, Mass General Brigham Personalized Medicine, Cambridge, MA; Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA.
Wanfeng YuLaboratory for Molecular Medicine, Mass General Brigham Personalized Medicine, Cambridge, MA.
Andrea OzaLaboratory for Molecular Medicine, Mass General Brigham Personalized Medicine, Cambridge, MA.
Megan HawleyLaboratory for Molecular Medicine, Mass General Brigham Personalized Medicine, Cambridge, MA.
Prathik K Vijay KumarLaboratory for Molecular Medicine, Mass General Brigham Personalized Medicine, Cambridge, MA.
Christopher KochLaboratory for Molecular Medicine, Mass General Brigham Personalized Medicine, Cambridge, MA.
Lisa M MahantaLaboratory for Molecular Medicine, Mass General Brigham Personalized Medicine, Cambridge, MA.
John B HarleyDivision of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH; University of Cincinnati College of Medicine, Cincinnati, OH; US Department of Veteran Affairs Medical Center, Cincinnati, OH.
Gail P JarvikDepartments of Medicine (Medical Genetics) and Genome Sciences, University of Washington School of Medicine, Seattle, WA.
Elizabeth W KarlsonBrigham and Women's Hospital, Harvard Medical School, Boston, MA.
Kathleen A LeppigGenetic Services, Kaiser Permanente of Washington, Seattle, WA.
Melanie F MyersDivision of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH; University of Cincinnati College of Medicine, Cincinnati, OH.
Cynthia A ProwsDivision of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH.
Marc S WilliamsGenomic Medicine Institute, Geisinger, Danville, PA.
Scott T WeissBrigham and Women's Hospital, Harvard Medical School, Boston, MA.
Matthew S LeboLaboratory for Molecular Medicine, Mass General Brigham Personalized Medicine, Cambridge, MA; Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA.
Heidi L RehmLaboratory for Molecular Medicine, Mass General Brigham Personalized Medicine, Cambridge, MA; Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA; Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA. Electronic address: hrehm@mgh.harvard.edu.

Funding

Finding Genomic Profiles of COVID-19 Phenotypes from the EHRU01HG008685 · NHGRI · BRIGHAM AND WOMEN'S HOSPITAL · PI ELIZABETH W KARLSON, Matthew S Lebo · 2015 to 2026
$13.6M
Variation, Function, and Disease Supplement ProgramU01HG008657 · NHGRI · UNIVERSITY OF WASHINGTON · PI David Russell Crosslin, Gail Pairitz Jarvik · 2015 to 2026
$13.4M
Global Alliance for Genomic Health (GA4GH)U01HG008676 · NHGRI · BRIGHAM AND WOMEN'S HOSPITAL · PI LENNON, NIALL JOHN, REHM, HEIDI L · 2015 to 2019
$8.6M
The Electronic Medical Records and Genomics (eMERGE) Network Phase III Coordinating Center (U01)U01HG008701 · NHGRI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI PETERSON, JOSEPH F. · 2015 to 2019
$7.1M
OMOP information model for eMERGE phenotypingU01HG008679 · NHGRI · GEISINGER CLINIC · PI WILLIAMS, MARC S. · 2015 to 2019
$4.4M
Better Outcomes for Children: Promoting Excellence in Healthcare Genomics to Inform PolicyU01HG008666 · NHGRI · CINCINNATI CHILDRENS HOSP MED CTR · PI HARLEY, JOHN BARKER · 2015 to 2019
$4.2M
NHGRI NIH HHS U01 HG008657NHGRI NIH HHS U01 HG008666NHGRI NIH HHS U01 HG008676NHGRI NIH HHS U01 HG008679NHGRI NIH HHS U01 HG008685NHGRI NIH HHS U01 HG008701
6 · The paper itself

Abstract

purposeThe clinical genomics knowledgebase is dynamic with variant classifications changing as newly identified cases, additional population data, and other evidence become available. This is a challenge for the clinical laboratory because of limited resource availability for variant reassessment.

methodsThroughout the Electronic Medical Records and Genomics phase III program, clinical sites associated with the Mass General Brigham/Broad sequencing center received automated, real-time notifications when reported variants were reclassified. In this study, we summarized the nature of these reclassifications and described the proactive reassessment framework we used for the Electronic Medical Records and Genomics program data set to identify variants most likely to undergo reclassification.

resultsReanalysis of 1855 variants led to the reclassification of 2% (n = 45) of variants, affecting 0.6% (n = 67) of participants. Of these reclassifications, 78% (n = 35) were high-impact changes affecting reportability, with 8 variants downgraded from likely pathogenic/pathogenic to variants of uncertain significance (VUS) and 27 variants upgraded from VUS to likely pathogenic/pathogenic. Most upgraded variants (67%) were initially classified as VUS-Favor Pathogenic, highlighting the benefit of VUS subcategorization. The most common reason for reclassification was new published case data and/or functional evidence.

conclusionOur results highlight the importance of periodic sequence variant reevaluation and the need for automated approaches to advance routine implementation of variant reevaluations in clinical practice.

Indexed as

Genetic TestingGenetic VariationGenetic Predisposition to DiseaseGenomicsHumansAutomated variant reclassification alertseMERGEVariant reassessment frameworkVariant reclassification

Identifiers

PMID34906510
PMCPMC10128874

What OpenQuestion holds

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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.