Evidence map›Paper›PMID 23704318›Full record

Trial reportGut2014

Improving coeliac disease risk prediction by testing non-HLA variants additional to HLA variants.

Jihane Romanos, Anna Rosén, Vinod Kumar, Gosia Trynka, Lude Franke, Agata Szperl, Javier Gutierrez-Achury, Cleo C van Diemen, Roan Kanninga, Soesma A Jankipersadsing and 17 more

Abstract readClinical Trial
In one paragraph

Trial report in Gut, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
61citing papers in PubMed, 2 pooled it
–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

61 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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1 more citing papers are in PubMed but not listed here.

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

27 authors.

Jihane RomanosDepartment of Genetics, University of Groningen, University Medical Centre Groningen, , Groningen, The Netherlands.
Anna Rosén
Vinod Kumar
Gosia Trynka
Lude Franke
Agata Szperl
Javier Gutierrez-Achury
Cleo C van Diemen
Roan Kanninga
Soesma A Jankipersadsing
Andrea Steck
Georges Eisenbarth
David A van Heel
Bozena Cukrowska
Valentina Bruno
Maria Cristina Mazzilli
Concepcion Núñez
Jose Ramon Bilbao
M Luisa Mearin
Donatella Barisani
Marian Rewers
Jill M Norris
Anneli Ivarsson
H Marieke Boezen
Edwin Liu
Cisca Wijmenga
PreventCD Group

Funding

GENETIC AND ENVIRONMENTAL CAUSES OF CELIAC DISEASER01DK050979 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI REWERS, MARIAN J · 1995 to 2014
$4.0M
Characterizing the genetic architecture of childhood onset celiac disease using nR21DK084568 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI LIU, EDWIN · 2009 to 2010
$766k
Medical Research Council G1001158NIDDK NIH HHS 5R1DK084568-02NIDDK NIH HHS R01 DK050979NIDDK NIH HHS R21 DK084568
6 · The paper itself

Abstract

backgroundThe majority of coeliac disease (CD) patients are not being properly diagnosed and therefore remain untreated, leading to a greater risk of developing CD-associated complications. The major genetic risk heterodimer, HLA-DQ2 and DQ8, is already used clinically to help exclude disease. However, approximately 40% of the population carry these alleles and the majority never develop CD.

objectiveWe explored whether CD risk prediction can be improved by adding non-HLA-susceptible variants to common HLA testing.

designWe developed an average weighted genetic risk score with 10, 26 and 57 single nucleotide polymorphisms (SNP) in 2675 cases and 2815 controls and assessed the improvement in risk prediction provided by the non-HLA SNP. Moreover, we assessed the transferability of the genetic risk model with 26 non-HLA variants to a nested case-control population (n=1709) and a prospective cohort (n=1245) and then tested how well this model predicted CD outcome for 985 independent individuals.

resultsAdding 57 non-HLA variants to HLA testing showed a statistically significant improvement compared to scores from models based on HLA only, HLA plus 10 SNP and HLA plus 26 SNP. With 57 non-HLA variants, the area under the receiver operator characteristic curve reached 0.854 compared to 0.823 for HLA only, and 11.1% of individuals were reclassified to a more accurate risk group. We show that the risk model with HLA plus 26 SNP is useful in independent populations.

conclusionsPredicting risk with 57 additional non-HLA variants improved the identification of potential CD patients. This demonstrates a possible role for combined HLA and non-HLA genetic testing in diagnostic work for CD.

Indexed as

Decision Support TechniquesGenetic Predisposition to DiseaseGenetic TestingPolymorphism, Single NucleotideCase-Control StudiesCeliac DiseaseFemaleGenetic MarkersHLA-DQ AntigensHumansLogistic ModelsMaleModels, GeneticProportional Hazards ModelsProspective StudiesRisk AssessmentGenetic MarkersHLA-DQ2 antigenHLA-DQ8 antigenHLA-DQ AntigensCeliac DiseaseCoeliac DiseaseGenetic TestingHlaMolecular Genetics

Identifiers

PMID23704318
PMCPMC3933173

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.