Evidence map›Paper›PMID 36305854›Full record

ArticleGenetics in medicine : official journal of the American College of Medical Genetics2023

Informing variant assessment using structured evidence from prior classifications (PS1, PM5, and PVS1 sequence variant interpretation criteria).

Vineel Bhat, Ivan A Adzhubei, James D Fife, Matthew Lebo, Christopher A Cassa

Open access · greenAbstract read
In one paragraph

Article in Genetics in medicine : official journal of the American College of Medical Genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.3field-weighted citation impact, top 18% of its field
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

6 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Language models reveal evidence gaps in variants of uncertain significance.medRxiv : the preprint server for health sciences · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. 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

5 authors at 2 institutions in 1 country.

Vineel BhatDivision of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
Ivan A AdzhubeiDepartment of Biomedical Informatics, Blavatnik Institute, Harvard Medical School, Boston, MA.
James D FifeDivision of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
Matthew LeboLaboratory for Molecular Medicine, Mass General Brigham Personalized Medicine, Boston, MA; Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
Christopher A CassaDivision of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA. Electronic address: cassa@alum.mit.edu.
Brigham and Women's Hospital · USHarvard University · US

Funding

Integrated pathogenicity assessment of clinically actionable genetic variantsR01HG010372 · NHGRI · BRIGHAM AND WOMEN'S HOSPITAL · PI CASSA, CHRISTOPHER · 2018 to 2022
$3.5M
NHGRI NIH HHS R01 HG010372
6 · The paper itself

Abstract

purposeThis study aimed to explore whether evidence of pathogenicity from prior variant classifications in ClinVar could be used to inform variant interpretation using the American College of Medical Genetics and Genomics/Association for Molecular Pathology clinical guidelines.

methodsWe identified distinct single-nucleotide variants (SNVs) that are either similar in location or in functional consequence to pathogenic variants in ClinVar and analyzed evidence in support of pathogenicity using 3 interpretation criteria.

resultsThousands of variants, including many in clinically actionable disease genes (American College of Medical Genetics and Genomics secondary findings v3.0), have evidence of pathogenicity from existing variant classifications, accounting for 2.5% of nonsynonymous SNVs within ClinVar. Notably, there are many variants with uncertain or conflicting classifications that cause the same amino acid substitution as other pathogenic variants (PS1, N = 323), variants that are predicted to cause different amino acid substitutions in the same codon as pathogenic variants (PM5, N = 7692), and loss-of-function variants that are present in genes in which many loss-of-function variants are classified as pathogenic (PVS1, N = 3635). Most of these variants have similar computational predictions of pathogenicity and splicing effect as their associated pathogenic variants.

conclusionBroadly, for >1.4 million SNVs exome wide, information from previously classified variants could be used to provide evidence of pathogenicity. We have developed a pipeline to identify variants meeting these criteria that may inform interpretation efforts.

Indexed as

Genetic TestingGenomicsExomeGenetic VariationHumansPathology, MolecularRNA SplicingACMG/AMPClinVarPS1/PM5/PVS1 evidenceSequence variant interpretation guidelinesVariants of uncertain significance

Identifiers

PMID36305854
PMCPMC10223563
OpenAlexW4307499336

What OpenQuestion holds

Textmetadata
LicenceTDM
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.