Evidence map›Paper›PMID 33102956›Full record

ArticleKidney international reports2020

IgA Nephropathy Genetic Risk Score to Estimate the Prevalence of IgA Nephropathy in UK Biobank.

Kittiya Sukcharoen, Seth A Sharp, Nicholas J Thomas, Robert A Kimmitt, Jamie Harrison, Coralie Bingham, Monika Mozere, Michael N Weedon, Jessica Tyrrell, Jonathan Barratt and 2 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Kidney international reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
1.8field-weighted citation impact, top 14% 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

17 citing papers in PubMed, 27 citations in OpenAlex.

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  15. IgAN Genetic Risk Score in the Clinical Setting.Kidney international reports · 2020
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors at 4 institutions in 1 country.

Kittiya SukcharoenThe Academic Renal Unit, Royal Devon and Exeter Foundation Trust, Exeter, UK.
Seth A SharpInstitute of Biomedical and Clinical Sciences, University of Exeter Medical School, Exeter, UK.
Nicholas J ThomasThe Academic Renal Unit, Royal Devon and Exeter Foundation Trust, Exeter, UK.
Robert A KimmittThe Academic Renal Unit, Royal Devon and Exeter Foundation Trust, Exeter, UK.
Jamie HarrisonInstitute of Biomedical and Clinical Sciences, University of Exeter Medical School, Exeter, UK.
Coralie BinghamThe Academic Renal Unit, Royal Devon and Exeter Foundation Trust, Exeter, UK.
Monika MozereDepartment of Renal Medicine, University College London, London, UK.
Michael N WeedonInstitute of Biomedical and Clinical Sciences, University of Exeter Medical School, Exeter, UK.
Jessica TyrrellInstitute of Biomedical and Clinical Sciences, University of Exeter Medical School, Exeter, UK.
Jonathan BarrattDepartment of Cardiovascular Sciences, University of Leicester, Leicester, UK.
Daniel P GaleDepartment of Renal Medicine, University College London, London, UK.
Richard A OramInstitute of Biomedical and Clinical Sciences, University of Exeter Medical School, Exeter, UK.
University of Exeter · GBRoyal Devon & Exeter NHS Foundation Trust · GBUniversity College London · GBUniversity of Leicester · GB

Funding

Medical Research Council MC_PC_17228Medical Research Council MC_QA137853Wellcome Trust
6 · The paper itself

Abstract

backgroundIgA nephropathy (IgAN) is the commonest glomerulonephritis worldwide. Its prevalence is difficult to estimate, as people with mild disease do not commonly receive a biopsy diagnosis. We aimed to generate an IgA nephropathy genetic risk score (IgAN-GRS) and estimate the proportion of people with hematuria who had IgAN in the UK Biobank (UKBB).

methodsWe calculated an IgAN-GRS using 14 single-nucleotide polymorphisms (SNPs) drawn from the largest European Genome-Wide Association Study (GWAS) and validated the IgAN-GRS in 464 biopsy-proven IgAN European cases from the UK Glomerulonephritis DNA Bank (UKGDB) and in 379,767 Europeans in the UKBB. We used the mean of IgAN-GRS to calculate the proportion of potential IgAN in 14,181 with hematuria and other nonspecific renal phenotypes from 379,767 Europeans in the UKBB.

resultsThe IgAN-GRS was higher in the IgAN cohort (4.30; 95% confidence interval [95% CI: 4.23-4.38) than in controls (3.98; 3.97-3.98;

conclusionsWe used an IgAN-GRS to estimate the prevalence of IgAN contributing to common phenotypes that are not always biopsied. The noninvasive use of polygenic risk in this setting may have further utility to identify likely etiology of nonspecific renal phenotypes in large population cohorts.

Indexed as

chronic kidney diseaseepidemiologyGenetic Risk ScoreshematuriaIgA nephropathy

Identifiers

PMID33102956
PMCPMC7572308
OpenAlexW3042502129

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.