Article in Science (New York, N.Y.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
0numbers the graph read from it
0cells of the map it votes in
14citing 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.
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
32 authors.
Natalie J Wallis *Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK.ORCID 0000-0001-9543-3711
Alyce McClellan *Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK.ORCID 0000-0003-0658-4812
Alexander MörseburgMetabolic Research Laboratories, Institute of Metabolic Science, University of Cambridge, Cambridge, UK.ORCID 0000-0003-4832-4007
Katherine A KentistouMRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK.ORCID 0000-0002-5816-664X
Aqfan JamaluddinInstitute of Metabolism and Systems Research, University of Birmingham, Birmingham, UK.ORCID 0000-0003-4934-3277
Georgina K C DowsettMetabolic Research Laboratories, Institute of Metabolic Science, University of Cambridge, Cambridge, UK.ORCID 0000-0002-2134-8554
Ellen SchofieldDepartment of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK.ORCID 0000-0003-0648-1418
Anna Morros-NuevoDepartment of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK.ORCID 0009-0007-0309-3811
Sadia SaeedINSERM UMR 1283, CNRS UMR 8199, European Genomic Institute for Diabetes, Institut Pasteur de Lille, Lille, France.ORCID 0000-0003-3144-7772
Brian Y H LamMetabolic Research Laboratories, Institute of Metabolic Science, University of Cambridge, Cambridge, UK.ORCID 0000-0002-3638-9025
Natasha T SumanasekeraDepartment of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK.ORCID 0009-0001-9953-5376
Justine ChanDepartment of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK.ORCID 0000-0002-2151-8031
Sambhavi S KumarDepartment of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK.ORCID 0009-0002-4948-9225
Rey M ZhangDepartment of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK.ORCID 0000-0003-1755-0407
Jodie F WainwrightDepartment of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK.ORCID 0009-0004-1726-2442
Marie DittmannDepartment of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK.ORCID 0000-0002-0470-5580
Gabriella LakatosMetabolic Research Laboratories, Institute of Metabolic Science, University of Cambridge, Cambridge, UK.
Kara RainbowMetabolic Research Laboratories, Institute of Metabolic Science, University of Cambridge, Cambridge, UK.ORCID 0000-0002-8089-0693
David WithersMetabolic Research Laboratories, Institute of Metabolic Science, University of Cambridge, Cambridge, UK.
Rebecca BoundsMetabolic Research Laboratories, Institute of Metabolic Science, University of Cambridge, Cambridge, UK.ORCID 0000-0001-8830-9456
Marcella MaMetabolic Research Laboratories, Institute of Metabolic Science, University of Cambridge, Cambridge, UK.ORCID 0000-0002-2228-7466
Alexander J GermanInstitute of Life Course and Medical Sciences and School of Veterinary Science, University of Liverpool, Neston, UK.ORCID 0000-0002-3017-7988
Jane LadlowDepartment of Veterinary Medicine, University of Cambridge, Cambridge, UK.ORCID 0000-0002-8076-4021
David SarganDepartment of Veterinary Medicine, University of Cambridge, Cambridge, UK.ORCID 0000-0001-9897-2489
Philippe FroguelINSERM UMR 1283, CNRS UMR 8199, European Genomic Institute for Diabetes, Institut Pasteur de Lille, Lille, France.ORCID 0000-0003-2972-0784
I Sadaf FarooqiMetabolic Research Laboratories, Institute of Metabolic Science, University of Cambridge, Cambridge, UK.ORCID 0000-0001-7609-3504
Ken K OngMRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK.ORCID 0000-0003-4689-7530
Giles S H YeoMetabolic Research Laboratories, Institute of Metabolic Science, University of Cambridge, Cambridge, UK.ORCID 0000-0001-8823-3615
John A TadrossMetabolic Research Laboratories, Institute of Metabolic Science, University of Cambridge, Cambridge, UK.ORCID 0000-0002-8424-1252
John R B PerryMetabolic Research Laboratories, Institute of Metabolic Science, University of Cambridge, Cambridge, UK.ORCID 0000-0001-6483-3771
Caroline M GorvinInstitute of Metabolism and Systems Research, University of Birmingham, Birmingham, UK.ORCID 0000-0002-1361-9174
Eleanor RaffanDepartment of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK.ORCID 0000-0002-1403-3538
Funding
Medical Research Council MC_UU_00006/2Medical Research Council MC_UU_00014/1Wellcome Trust 207462Wellcome Trust 224155
6 · The paper itself
Abstract
Obesity is a heritable disease, but its genetic basis is incompletely understood. Canine population history facilitates trait mapping. We performed a canine genome-wide association study for body condition score-a measure of obesity-in 241 Labrador retrievers. Using a cross-species approach, we showed that canine obesity genes are also associated with rare and common forms of obesity in humans. The lead canine association was within the gene DENN domain containing 1B (
Indexed as
Death Domain Receptor Signaling Adaptor ProteinsDog DiseasesDogsGuanine Nucleotide Exchange FactorsObesityAdipose TissueAllelesAnimalsFemaleGenomeGenome-Wide Association StudyHumansMalePolymorphism, Single NucleotideReceptor, Melanocortin, Type 4Signal TransductionDeath Domain Receptor Signaling Adaptor ProteinsDENND1A protein, humanGuanine Nucleotide Exchange FactorsMC4R protein, humanReceptor, Melanocortin, Type 4
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.
Canine genome-wide association study identifies · full record | OpenQuestion