Evidence map›Paper›PMID 31276222›Full record

ArticleDiabetic medicine : a journal of the British Diabetic Association2019

Type 1 diabetes genetic risk score discriminates between monogenic and Type 1 diabetes in children diagnosed at the age of <5 years in the Iranian population.

H Yaghootkar, F Abbasi, N Ghaemi, A Rabbani, M N Wakeling, P Eshraghi, S Enayati, S Vakili, S Heidari, K Patel and 8 more

Open access · hybridAbstract read
In one paragraph

Article in Diabetic medicine : a journal of the British Diabetic Association, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
2.0field-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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.

  1. Systematic Review of Polygenic Risk Scores for Type 1 and Type 2 Diabetes.International journal of molecular sciences · 2020
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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

18 authors at 4 institutions in 2 countries.

H YaghootkarGenetics of Complex Traits, University of Exeter Medical School, Royal Devon & Exeter Hospital, Exeter, UK.ORCID 0000-0001-9672-9477
F AbbasiGrowth and Development Research Centre, Tehran University of Medical Sciences, Tehran, Iran.
N GhaemiDepartment of Paediatric Disease, Faulty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
A RabbaniGrowth and Development Research Centre, Tehran University of Medical Sciences, Tehran, Iran.
M N WakelingInstitute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, UK.
P EshraghiDepartment of Paediatric Disease, Faulty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
S EnayatiMetabolic Disorders Research Centre, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
S VakiliMedical Genetics Research Centre, Mashhad University of Medical Sciences, Mashhad, Iran.
S HeidariGrowth and Development Research Centre, Tehran University of Medical Sciences, Tehran, Iran.
K PatelInstitute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, UK.
F SayarifardGrowth and Development Research Centre, Tehran University of Medical Sciences, Tehran, Iran.
S Borhan-DayaniMetabolic Disorders Research Centre, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
T J McDonaldInstitute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, UK.
S EllardInstitute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, UK.
A T HattersleyInstitute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, UK.
M M AmoliMetabolic Disorders Research Centre, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
R VakiliDepartment of Paediatric Disease, Faulty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
K ColcloughDepartments of Molecular Genetics, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK.
Tehran University of Medical Sciences · IRUniversity of Exeter · GBMashhad University of Medical Sciences · IRRoyal Devon & Exeter NHS Foundation Trust · GB

Funding

Department of Health ICA-SCL-2016-02-003Department of Health NIHR-HCS-P12-03-03Wellcome TrustWellcome Trust 108101/Z/15/Z
6 · The paper itself

Abstract

aimTo examine the extent to which discriminatory testing using antibodies and Type 1 diabetes genetic risk score, validated in European populations, is applicable in a non-European population.

methodsWe recruited 127 unrelated children with diabetes diagnosed between 9 months and 5 years from two centres in Iran. All children underwent targeted next-generation sequencing of 35 monogenic diabetes genes. We measured three islet autoantibodies (islet antigen 2, glutamic acid decarboxylase and zinc transporter 8) and generated a Type 1 diabetes genetic risk score in all children.

resultsWe identified six children with monogenic diabetes, including four novel mutations: homozygous mutations in WFS1 (n=3), SLC19A2 and SLC29A3, and a heterozygous mutation in GCK. All clinical features were similar in children with monogenic diabetes (n=6) and in the rest of the cohort (n=121). The Type 1 diabetes genetic risk score discriminated children with monogenic from Type 1 diabetes [area under the receiver-operating characteristic curve 0.90 (95% CI 0.83-0.97)]. All children with monogenic diabetes were autoantibody-negative. In children with no mutation, 59 were positive to glutamic acid decarboxylase, 39 to islet antigen 2 and 31 to zinc transporter 8. Measuring zinc transporter 8 increased the number of autoantibody-positive individuals by eight.

conclusionsThe present study provides the first evidence that Type 1 diabetes genetic risk score can be used to distinguish monogenic from Type 1 diabetes in an Iranian population with a large number of consanguineous unions. This test can be used to identify children with a higher probability of having monogenic diabetes who could then undergo genetic testing. Identification of these individuals would reduce the cost of treatment and improve the management of their clinical course.

Indexed as

Genetic Predisposition to DiseaseAutoantibodiesChild, PreschoolConsanguinityDiabetes Mellitus, Type 1FemaleGlucokinaseGlutamate DecarboxylaseHigh-Throughput Nucleotide SequencingHomozygoteHumansInfantIranIslets of LangerhansMaleMembrane ProteinsAutoantibodiesGlucokinaseGlutamate DecarboxylaseMembrane ProteinsMembrane Transport ProteinsNucleoside Transport ProteinsPTPRN protein, humanReceptor-Like Protein Tyrosine Phosphatases, Class 8SLC19A2 protein, humanSLC29A3 protein, humanwolframin proteinZinc Transporter 8

Identifiers

PMID31276222
PMCPMC7027759
OpenAlexW2954141288

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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.