Evidence map›Paper›PMID 39190485›Full record

ArticleThe Journal of clinical investigation2024

Quantifying variant contributions in cystic kidney disease using national-scale whole-genome sequencing.

Omid Sadeghi-Alavijeh, Melanie My Chan, Gabriel T Doctor, Catalin D Voinescu, Alexander Stuckey, Athanasios Kousathanas, Alexander T Ho, Horia C Stanescu, Detlef Bockenhauer, Richard N Sandford and 2 more

Abstract read
In one paragraph

Article in The Journal of clinical investigation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
  2. The Genomic Infinity Loop.Journal of the American Society of Nephrology : JASN · 2026
    Article
  3. Fifty Shades of Risk: Population Studies and the Genetic Architecture of Kidney Diseases.Journal of the American Society of Nephrology : JASN · 2026
    Review
  4. Observational
  5. Review
  6. Observational
  7. 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

12 authors.

Omid Sadeghi-AlavijehCentre for Kidney and Bladder Health, University College London, London, United Kingdom.
Melanie My ChanCentre for Kidney and Bladder Health, University College London, London, United Kingdom.
Gabriel T DoctorCentre for Kidney and Bladder Health, University College London, London, United Kingdom.
Catalin D VoinescuCentre for Kidney and Bladder Health, University College London, London, United Kingdom.
Alexander StuckeyGenomics England, Queen Mary University of London, London, United Kingdom.
Athanasios KousathanasGenomics England, Queen Mary University of London, London, United Kingdom.
Alexander T HoGenomics England, Queen Mary University of London, London, United Kingdom.
Horia C StanescuCentre for Kidney and Bladder Health, University College London, London, United Kingdom.
Detlef BockenhauerCentre for Kidney and Bladder Health, University College London, London, United Kingdom.
Richard N SandfordAcademic Department of Medical Genetics, Cambridge University, Cambridge, United Kingdom.
Adam P LevineCentre for Kidney and Bladder Health, University College London, London, United Kingdom.
Daniel P GaleCentre for Kidney and Bladder Health, University College London, London, United Kingdom.

Funding

Wellcome Trust
6 · The paper itself

Abstract

BACKGROUNDCystic kidney disease (CyKD) is a predominantly familial disease in which gene discovery has been led by family-based and candidate gene studies, an approach that is susceptible to ascertainment and other biases.METHODSUsing whole-genome sequencing data from 1,209 cases and 26,096 ancestry-matched controls participating in the 100,000 Genomes Project, we adopted hypothesis-free approaches to generate quantitative estimates of disease risk for each genetic contributor to CyKD, across genes, variant types and allelic frequencies.RESULTSIn 82.3% of cases, a qualifying potentially disease-causing rare variant in an established gene was found. There was an enrichment of rare coding, splicing, and structural variants in known CyKD genes, with statistically significant gene-based signals in COL4A3 and (monoallelic) PKHD1. Quantification of disease risk for each gene (with replication in the separate UK Biobank study) revealed substantially lower risk associated with genes more recently associated with autosomal dominant polycystic kidney disease, with odds ratios for some below what might usually be regarded as necessary for classical Mendelian inheritance. Meta-analysis of common variants did not reveal significant associations, but suggested this category of variation contributes 3%-9% to the heritability of CyKD across European ancestries.CONCLUSIONBy providing unbiased quantification of risk effects per gene, this research suggests that not all rare variant genetic contributors to CyKD are equally likely to manifest as a Mendelian trait in families. This information may inform genetic testing and counseling in the clinic.

Indexed as

Kidney Diseases, CysticWhole Genome SequencingAutoantigensCase-Control StudiesCollagen Type IVFemaleGene FrequencyGenetic Predisposition to DiseaseGenetic VariationHumansMaleReceptors, Cell SurfaceAutoantigensCollagen Type IVPKHD1 protein, humanReceptors, Cell Surfacetype IV collagen alpha3 chainBioinformaticsGenetic diseasesGeneticsMolecular geneticsNephrology

Identifiers

PMID39190485
PMCPMC11444187

What OpenQuestion holds

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LicenceCC BY
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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.