Evidence map›Paper›PMID 28566086›Full record

ReviewBMC medicine2017

The genetics of gout: towards personalised medicine?

Nicola Dalbeth, Lisa K Stamp, Tony R Merriman

Open access · goldAbstract readReview
In one paragraph

Review in BMC medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
4.4field-weighted citation impact, top 5% 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

28 citing papers in PubMed, 71 citations in OpenAlex.

  1. Trial
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  9. Review
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  14. Epigenetic and Metabolic Regulation of Macrophages during Gout.Gout, urate, and crystal deposition disease · 2023
    Article
  15. Article
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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

3 authors at 2 institutions in 1 country.

Nicola DalbethDepartment of Medicine, Faculty of Medical and Health Sciences, University of Auckland, 85 Park Rd, Grafton, Auckland, 1023, New Zealand. n.dalbeth@auckland.ac.nz.
Lisa K StampDepartment of Medicine, University of Otago, Christchurch, New Zealand.
Tony R MerrimanDepartment of Biochemistry, University of Otago, Dunedin, New Zealand.
University of Otago · NZUniversity of Auckland · NZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the last decade, there have been major advances in the understanding of the genetic basis of hyperuricaemia and gout as well as of the pharmacogenetics of urate-lowering therapy. Key findings include the reporting of 28 urate-associated loci, the discovery that ABCG2 plays a central role on extra-renal uric acid excretion, the identification of genes associated with development of gout in the context of hyperuricaemia, recognition that ABCG2 variants influence allopurinol response, and the impact of HLA-B*5801 testing in reducing the prevalence of allopurinol hypersensitivity in high-risk populations. These advances, together with the reducing cost of whole genome sequencing, mean that integrated personalised medicine approaches may soon be possible in clinical practice. Genetic data may inform assessment of disease prognosis in individuals with hyperuricaemia or established gout, personalised lifestyle advice, selection and dosing of urate-lowering therapy, and prevention of serious medication adverse effects. In this article, we summarise the discoveries from genome-wide association studies and discuss the potential for translation of these findings into clinical practice.

Indexed as

Precision MedicineAllopurinolGenome-Wide Association StudyGoutGout SuppressantsHumansHyperuricemiaLife StylePrognosisUric AcidAllopurinolGout SuppressantsUric AcidGeneticsGenome-wide association studyGoutPersonalised medicineUrate

Identifiers

PMID28566086
PMCPMC5452604
OpenAlexW2619919203

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.