Evidence map›Paper›PMID 28510587›Full record

ArticlePloS one2017

Sibling method increases risk assessment estimates for type 1 diabetes.

Hoang V Lam, Dat T Nguyen, Cao D Nguyen

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 28% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Review
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 3 institutions in 2 countries.

Hoang V LamDepartment of Endocrinology, Cho Ray Hospital, Ho Chi Minh City, Vietnam.
Dat T NguyenDepartment of Science and Technology, Hoa Sen University, Ho Chi Minh City, Vietnam.
Cao D NguyenDepartment of Business and Information System, Economics University, Ho Chi Minh City, Vietnam.
Cho Ray Hospital · VNHoa Sen University · VNUniversity of Economics Ho Chi Minh City · VN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We presented a risk assessment model to distinguish between type 1 diabetes (T1D) affected and unaffected siblings using only three single nucleotide polymorphism (SNP) genotypes. In addition we calculated the heritability from genome-wide identity-by-descent (IBD) sharing between full siblings. We analyzed 1,253 pairs of affected individuals and their unaffected siblings (750 pairs from a discovery set and 503 pairs from a validation set) from the T1D Genetics Consortium (T1DGC), applying a logistic regression to analyze the area under the receiver operator characteristic (ROC) curve (AUC). To calculate the heritability of T1D we used the Haseman-Elston regression analysis of the squared difference between the phenotypes of the pairs of siblings on the estimate of their genome-wide IBD proportion. The model with only 3 SNPs achieving an AUC of 0.75 in both datasets outperformed the model using the presence of the high-risk DR3/4 HLA genotype, namely AUC of 0.60. The heritability on the liability scale of T1D was approximately from 0.53 to 0.92, close to the results obtained from twin studies, ranging from 0.4 to 0.88.

Indexed as

SiblingsAdultAge of OnsetAllelesArea Under CurveDiabetes Mellitus, Type 1Genetic MarkersGenetic Predisposition to DiseaseHumansInheritance PatternsLogistic ModelsModels, GeneticMorbidityPolymorphism, Single NucleotideRisk AssessmentRisk FactorsGenetic Markers

Identifiers

PMID28510587
PMCPMC5433695
OpenAlexW2614807120

What OpenQuestion holds

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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.