Evidence map›Paper›PMID 41330372›Full record

ReviewAmerican journal of human genetics2026

Interpreting the functional impact of genetic variants: The need for context qualifiers.

Simone Martinelli, Hélène Cavé, Alessandro De Luca, Marina DiStefano, Rachel Karchin, Ana Clara Lugones, Anne O'Donnell-Luria, Deborah I Ritter, David Tamborero, Michael Y Tolstorukov and 3 more

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in American journal of human genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. A matter of switch: how RAC1 variants drive distinct disorders.European journal of human genetics : EJHG · 2026
    Article
  3. Review
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

13 authors.

Simone MartinelliDepartment of Oncology and Molecular Medicine, Istituto Superiore di Sanità, Rome 00161, Italy.
Hélène CavéDépartement de Génétique, Unité de Génétique Moléculaire, Hôpital Robert Debré, Assistance Publique des Hôpitaux de Paris (AP-HP), 75019 Paris, France.
Alessandro De LucaMedical Genetics Laboratory, Fondazione IRCCS Casa Sollievo della Sofferenza, Viale dei Cappuccini, 71013 San Giovanni Rotondo, Italy.
Marina DiStefanoProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Rachel KarchinThe Institute for Computational Medicine, The Johns Hopkins University, Baltimore, MD 21218, USA; Departments of Biomedical Engineering, Oncology, and Computer Science, The Johns Hopkins University, Baltimore, MD 21218, USA.
Ana Clara LugonesDepartamento de Biología, Bioquímica y Farmacia, Universidad Nacional del Sur, 8000 Bahía Blanca, Argentina; Bitgenia, C1420 Buenos Aires, Argentina.
Anne O'Donnell-LuriaProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA 02115, USA.
Deborah I RitterDepartment of Pediatrics, Baylor College of Medicine, Texas Children's Hospital, Houston, TX 77030, USA.
David TamboreroDepartment of Oncology and Pathology, Karolinska Institutet, 17177 Stockholm, Sweden.
Michael Y TolstorukovDepartment of Informatics and Analytics, Dana-Farber Cancer Institute, Boston, MA 02215, USA.
Paulo Vidal CampregherHospital Israelita Albert Einstein, 05652-900 São Paulo, Brazil; Genesis Genomics, 04703-901 São Paulo, Brazil.
Marco TartagliaMolecular Genetics and Functional Genomics, Bambino Gesù Children's Hospital IRCCS, 00146 Rome, Italy. Electronic address: marco.tartaglia@opbg.net.
Dmitriy SonkinNational Cancer Institute, Division of Cancer Treatment and Diagnosis, Rockville, MD 20850, USA. Electronic address: dmitriy.sonkin@nih.gov.

Funding

OpenCRAVAT: Informatics Tools for High-Throughput Analysis of Cancer MutationsU24CA258393 · NCI · JOHNS HOPKINS UNIVERSITY · PI Rachel Karchin · 2022 to 2026
$3.3M
NCI NIH HHS U24 CA258393
6 · The paper itself

Abstract

Genetic alterations influence biological function through a variety of molecular mechanisms. While common functional descriptions (such as loss of function and gain of function) are useful, they may fail to capture mechanistic complexity, particularly in cases of pleiotropy and context-dependent variant effects. To improve variant interpretation and classification, we propose a framework incorporating "context qualifiers" to address mechanistic specificity. This perspective explores the limitations of common functional descriptors and discusses the criteria needed to implement context qualifiers in variant interpretation frameworks to enhance precision medicine applications.

Indexed as

Genetic VariationHumansPrecision Medicinedominant-negative functionfunctional annotationgain of functiongene variantsloss of functionMuller’s morphsprecision medicine

Identifiers

PMID41330372
PMCPMC12824612

What OpenQuestion holds

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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.