Evidence map›Paper›PMID 14639528›Full record

ArticleAmerican journal of human genetics2003

Search for haplotype interactions that influence susceptibility to type 1 diabetes, through use of unphased genotype data.

Jian Zhang, Faming Liang, Willem R M Dassen, Bart A J Veldman, Pieter A Doevendans, Mathisca De Gunst

Erratum issuedOpen access · greenAbstract readComparative Study
In one paragraph

Article in American journal of human genetics, 2003. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.4field-weighted citation impact, top 34% 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

5 citing papers in PubMed, 12 citations in OpenAlex.

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4 · The record

Corrections and comments

  • Erratum issued
    Veldman, Bart A J [added]
5 · Who and what money

Authors and funding

6 authors at 5 institutions in 4 countries.

Jian ZhangInstitute of Mathematics and Statistics, University of Kent at Canterbury, Kent, United Kingdom. j.zhang@kent.ac.uk
Faming Liang
Willem R M Dassen
Bart A J Veldman
Pieter A Doevendans
Mathisca De Gunst
Chinese Academy of Sciences · CNMaastricht University · NLNetherlands Heart Institute · NLTexas A&M University · USUniversity of Amsterdam · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Type 1 diabetes is a T-cell-mediated chronic disease characterized by the autoimmune destruction of pancreatic insulin-producing beta cells and complete insulin deficiency. It is the result of a complex interrelation of genetic and environmental factors, most of which have yet to be identified. Simultaneous identification of these genetic factors, through use of unphased genotype data, has received increasing attention in the past few years. Several approaches have been described, such as the modified transmission/disequilibrium test procedure, the conditional extended transmission/disequilibrium test, and the stepwise logistic-regression procedure. These approaches are limited either by being restricted to family data or by ignoring so-called "haplotype interactions" between alleles. To overcome this limit, the present study provides a general method to identify, on the basis of unphased genotype data, the haplotype blocks that interact to define the risk for a complex disease. The principle underpinning the proposal is minimal entropy. The performance of our procedure is illustrated for both simulated and real data. In particular, for a set of Dutch type 1 diabetes data, our procedure suggests some novel evidence of the interactions between and within haplotype blocks that are across chromosomes 1, 2, 3, 4, 5, 6, 7, 8, 11, 12, 15, 16, 17, 19, and 21. The results demonstrate that, by considering interactions between potential disease haplotype blocks, we may succeed in identifying disease-predisposing genetic variants that might otherwise have remained undetected.

Indexed as

Genetic Predisposition to DiseaseModels, GeneticAlgorithmsDiabetes Mellitus, Type 1Genetic TestingGenotypeHaplotypesHumansPolymorphism, Single Nucleotide

Identifiers

PMID14639528
PMCPMC1180402
OpenAlexW2129907261

What OpenQuestion holds

Textmetadata
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.