Evidence map›Paper›PMID 36693108›Full record

ArticlePLoS genetics2023

Bayesian mixed model analysis uncovered 21 risk loci for chronic kidney disease in boxer dogs.

Frode Lingaas, Katarina Tengvall, Johan Høgset Jansen, Lena Pelander, Maria H Hurst, Theo Meuwissen, Åsa Karlsson, Jennifer R S Meadows, Elisabeth Sundström, Stein Istre Thoresen and 8 more

Open access · goldAbstract read
In one paragraph

Article in PLoS 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
2.1field-weighted citation impact, top 12% 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, 10 citations in OpenAlex.

  1. Genomic analyses identify 15 risk loci and revealProceedings of the National Academy of Sciences of the United States of America · 2025
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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

18 authors at 5 institutions in 4 countries.

Frode LingaasFaculty of Veterinary Medicine, Department of Preclinical Sciences and Pathology, Norwegian University of Life Sciences, Ås, Norway.
Katarina TengvallScience for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.
Johan Høgset JansenFaculty of Veterinary Medicine, Department of Preclinical Sciences and Pathology, Norwegian University of Life Sciences, Ås, Norway.
Lena PelanderDepartment of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden.ORCID 0000-0001-9865-312X
Maria H HurstBioVet Veterinary Laboratory AB, Sollentuna, Sweden.
Theo MeuwissenFaculty of Biosciences, Norwegian University of Life Sciences, Ås, Norway.
Åsa KarlssonScience for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.
Jennifer R S MeadowsScience for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.
Elisabeth SundströmScience for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.
Stein Istre ThoresenFaculty of Veterinary Medicine, Department of Preclinical Sciences and Pathology, Norwegian University of Life Sciences, Ås, Norway.
Ellen Frøysadal ArnetFaculty of Veterinary Medicine, Department of Preclinical Sciences and Pathology, Norwegian University of Life Sciences, Ås, Norway.
Ole Albert GuttersrudFaculty of Veterinary Medicine, Department of Preclinical Sciences and Pathology, Norwegian University of Life Sciences, Ås, Norway.
Marcin KierczakDepartment of Cell and Molecular Biology, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
Marjo K HytönenDepartment of Medical and Clinical Genetics, University of Helsinki, Helsinki, Finland.ORCID 0000-0003-1976-5874
Hannes LohiDepartment of Medical and Clinical Genetics, University of Helsinki, Helsinki, Finland.
Åke HedhammarDepartment of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden.
Kerstin Lindblad-TohScience for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.
Chao WangScience for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.ORCID 0000-0003-3936-4023
Norwegian University of Life Sciences · NOUppsala University · SESwedish University of Agricultural Sciences · SEUniversity of Helsinki · FIBroad Institute · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chronic kidney disease (CKD) affects 10% of the human population, with only a small fraction genetically defined. CKD is also common in dogs and has been diagnosed in nearly all breeds, but its genetic basis remains unclear. Here, we performed a Bayesian mixed model genome-wide association analysis for canine CKD in a boxer population of 117 canine cases and 137 controls, and identified 21 genetic regions associated with the disease. At the top markers from each CKD region, the cases carried an average of 20.2 risk alleles, significantly higher than controls (15.6 risk alleles). An ANOVA test showed that the 21 CKD regions together explained 57% of CKD phenotypic variation in the population. Based on whole genome sequencing data of 20 boxers, we identified 5,206 variants in LD with the top 50 BayesR markers. Following comparative analysis with human regulatory data, 17 putative regulatory variants were identified and tested with electrophoretic mobility shift assays. In total four variants, three intronic variants from the MAGI2 and GALNT18 genes, and one variant in an intergenic region on chr28, showed alternative binding ability for the risk and protective alleles in kidney cell lines. Many genes from the 21 CKD regions, RELN, MAGI2, FGFR2 and others, have been implicated in human kidney development or disease. The results from this study provide new information that may enlighten the etiology of CKD in both dogs and humans.

Indexed as

Genome-Wide Association StudyRenal Insufficiency, ChronicAllelesAnimalsBayes TheoremDogsHumansKidneyPolymorphism, Single Nucleotide

Identifiers

PMID36693108
PMCPMC9897549
OpenAlexW4317867593

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.