Evidence map›Paper›PMID 41877242›Full record

ArticleGenome medicine2026

COBT: a gene-based rare variant burden test for case-only study designs using aggregated genotypes from public reference cohorts.

Antoine Favier, Stefania Chounta, Alejandro Garcia, Fabienne Jabot-Hanin, Xiaoyi Chen, Nicolas Garcelon, Anita Burgun, Manuel Higueras, Agathe Guilloux, Alexandre Benmerah and 10 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genome medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

20 authors.

Antoine FavierClinical Bioinformatics Laboratory, Université Paris Cité, INSERM UMR1163, Imagine Institute, Paris, F-75006, France.
Stefania ChountaClinical Bioinformatics Laboratory, Université Paris Cité, INSERM UMR1163, Imagine Institute, Paris, F-75006, France.
Alejandro GarciaClinical Bioinformatics Laboratory, Université Paris Cité, INSERM UMR1163, Imagine Institute, Paris, F-75006, France.
Fabienne Jabot-HaninImagine Institute, Bioinformatics Platform, Structure Fédérative de Recherche Necker, INSERM US24/CNRS UMS 3633, Université Paris Cité, INSERM UMR 1163, Paris, F-75015, France.
Xiaoyi ChenImagine Institute, Data Science Platform, Université Paris Cité, INSERM UMR 1163, Paris, F-75015, France.
Nicolas GarcelonClinical Bioinformatics Laboratory, Université Paris Cité, INSERM UMR1163, Imagine Institute, Paris, F-75006, France.
Anita BurgunClinical Bioinformatics Laboratory, Université Paris Cité, INSERM UMR1163, Imagine Institute, Paris, F-75006, France.
Manuel HiguerasUniversidad de La Rioja, Scientific Computation Research Institute (SCRIUR), Logroño, La Rioja, 26006, Spain.
Agathe GuillouxUniversité Paris Cité, Sorbonne Université, INSERM, Centre de recherche des Cordeliers, Paris, F- 75006, France.
Alexandre BenmerahImagine Institute, Laboratory of Hereditary Kidney Diseases, Université Paris Cité, INSERM UMR 1163, Paris, F-75015, France.
Yoann MartinImagine Institute, Laboratory of Hereditary Kidney Diseases, Université Paris Cité, INSERM UMR 1163, Paris, F-75015, France.
Katy BillotImagine Institute, Laboratory of Hereditary Kidney Diseases, Université Paris Cité, INSERM UMR 1163, Paris, F-75015, France.
Jean-Michel RozetImagine Institute, Laboratory of Genetics in Ophthalmology (LGO), Université Paris Cité, INSERM UMR 1163, Paris, F-75015, France.
Isabelle PerraultImagine Institute, Laboratory of Genetics in Ophthalmology (LGO), Université Paris Cité, INSERM UMR 1163, Paris, F-75015, France.
Valérie Cormier-DaireImagine Institute, Laboratory of pathophysiological basis of skeletal dysplasia, Université Paris Cité, INSERM UMR 1163, Paris, F-75015, France.
Céline HuberImagine Institute, Laboratory of pathophysiological basis of skeletal dysplasia, Université Paris Cité, INSERM UMR 1163, Paris, F-75015, France.
Mohamad ZaidanService de Néphrologie, Dialyse et Transplantation, Assistance Publique-Hôpitaux de Paris (AP-HP), Hôpital Universitaire Bicêtre, 78, avenue du Général Leclerc, Le Kremlin-Bicêtre, F-94270, France.
Tania Attie-BitachAssistance Publique-Hôpitaux de Paris (AP-HP), Necker Hospital for Sick Children, Fédération de Génétique et Médecine Génomique, Service de Médecine Génomique des Maladies Rares, Paris, F‑75015, France.
Sophie SaunierImagine Institute, Laboratory of Hereditary Kidney Diseases, Université Paris Cité, INSERM UMR 1163, Paris, F-75015, France.
Antonio RausellClinical Bioinformatics Laboratory, Université Paris Cité, INSERM UMR1163, Imagine Institute, Paris, F-75006, France. antonio.rausell@institutimagine.org.

Funding

Agence Nationale de la Recherche C'IL-LICO project (ANR-17-RHUS-0002)
6 · The paper itself

Abstract

Rare disease gene discovery is limited by small cohorts and the frequent absence of matched controls. We present the Case-Only Burden Test (COBT), a gene-based burden test for case-only designs accounting for multiple variants per individual and additive effects. COBT uses a Poisson model to test for excess variants in a gene relative to expectations from population mutation rates. Simulations show high power and competitive performance versus case-control burden tests. Validation on 1000 Genomes data demonstrated good model fit and low false-positive rates. Applied to 478 ciliopathy patients, COBT re-identified known causal genes and highlighted candidate variants in unsolved cases.

Indexed as

Genetic VariationGenotypeRare DiseasesCase-Control StudiesComputer SimulationGenetic Association StudiesGenetic Predisposition to DiseaseHumansBurden testingCase-only association analysisCiliopathiesRare diseasesStatistical genetics

Identifiers

PMID41877242
PMCPMC13134200

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.