Evidence map›Paper›PMID 27912794›Full record

ArticleArthritis research & therapy2016

A genetic risk score composed of rheumatoid arthritis risk alleles, HLA-DRB1 haplotypes, and response to TNFi therapy - results from a Swedish cohort study.

Xia Jiang, Johan Askling, Saedis Saevarsdottir, Leonid Padyukov, Lars Alfredsson, Sebastien Viatte, Thomas Frisell

Open access · goldAbstract read
In one paragraph

Article in Arthritis research & therapy, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.5field-weighted citation impact, top 16% 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

9 citing papers in PubMed, 14 citations in OpenAlex.

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  5. [Innovative treatments in rheumatology].Zeitschrift fur Rheumatologie · 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

7 authors at 3 institutions in 2 countries.

Xia JiangUnit of Clinical Epidemiology (KEP), Department of Medicine, Karolinska University Hospital, SE-171 76, Stockholm, Sweden. xia.jiang@ki.se.
Johan AsklingUnit of Clinical Epidemiology (KEP), Department of Medicine, Karolinska University Hospital, SE-171 76, Stockholm, Sweden.
Saedis SaevarsdottirRheumatology Unit, Department of Medicine Solna, Karolinska Institutet, and Karolinska University Hospital, Stockholm, Sweden.
Leonid PadyukovRheumatology Unit, Department of Medicine Solna, Karolinska Institutet, and Karolinska University Hospital, Stockholm, Sweden.
Lars AlfredssonCardiovascular Unit, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
Sebastien ViatteArthritis Research UK Centre for Genetics and Genomics, Centre for Musculoskeletal Research, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Oxford Road, Manchester, M13 9PT, UK.
Thomas FrisellUnit of Clinical Epidemiology (KEP), Department of Medicine, Karolinska University Hospital, SE-171 76, Stockholm, Sweden.
Karolinska University Hospital · SEKarolinska Institutet · SEManchester Academic Health Science Centre · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo prevent debilitating and irreversible joint damage, rheumatoid arthritis (RA) is often treated with tumor necrosis factor inhibitor (TNFi), but many patients do not respond to this costly therapy. Few predictors for response are known, and it has been proposed that genetic factors which influence the development of RA may also influence disease severity and response to therapy. Several previous studies have attempted to confirm this but results remain inconclusive. We expand on previous studies by including more RA risk alleles, and maximize power by combining them into a genetic risk score.

methodWe linked genotyped RA patients from the Epidemiological Investigation of Rheumatoid Arthritis study to the Swedish Rheumatology Quality Register, identifying patients who started a TNFi as their first biological disease-modifying anti-rheumatic drug, with a return visit within 2-8 months after treatment start (N = 867). We calculated risk scores from 76 established RA risk SNPs, and four HLA-DRB1 amino acid positions, and tested whether risk scores or individual genetic risk factors could predict the European League Against Rheumatism (EULAR) response.

resultsWe found no association between any of the risk scores or HLA-DRB1 haplotypes and EULAR response, neither overall nor stratified by anti-citrullinated protein/peptide antibody (ACPA) status. When evaluating each of the 76 SNPs, we found that the number of SNPs presenting significant associations was not higher than expected by chance (5/76 SNPs had p < 0.05 in ACPA-positive RA, 4/76 in ACPA-negative RA).

conclusionOverall, known RA risk SNPs do not predict response to TNFi, either individually or when combined into a risk score. This does not support the hypothesis that genes influencing RA onset would also influence its prognosis and treatment response.

Indexed as

AdultAgedAllelesAntirheumatic AgentsArthritis, RheumatoidCohort StudiesDrug ResistanceFemaleGenetic Predisposition to DiseaseHaplotypesHLA-DRB1 ChainsHumansMaleMiddle AgedRisk FactorsSwedenAntirheumatic AgentsHLA-DRB1 ChainsTumor Necrosis Factor-alphaGeneticHLA-DRB1 haplotypesRheumatoid arthritis risk SNPsTumor necrosis factor inhibitor prediction

Identifiers

PMID27912794
PMCPMC5135751
OpenAlexW2559058470

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LicenceCC BY
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Registered trials

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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.