Evidence map›Paper›PMID 12952878›Full record

ArticleGenome research2003

Global haplotype diversity in the human insulin gene region.

John D H Stead, Matthew E Hurles, Alec J Jeffreys

Open access · bronzeAbstract readComparative Study
In one paragraph

Article in Genome research, 2003. 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
–field-weighted citation impact
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, 41 citations in OpenAlex.

  1. Article
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  6. Has human evolution stopped?Rambam Maimonides medical journal · 2010
    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.

John D H SteadDepartment of Genetics, University of Leicester, Leicester LE1 7RH, UK. jdstead@umich.edu
Matthew E Hurles
Alec J Jeffreys
University of Leicester · GBUniversity of Cambridge · GB

Funding

Wellcome Trust
6 · The paper itself

Abstract

The insulin minisatellite (INS VNTR) has been intensively analyzed due to its associations with diseases including diabetes. We have previously used patterns of variant repeat distribution in the minisatellite to demonstrate that genetic diversity is unusually great in Africans compared to non-Africans. Here we analyzed variation at 56 single nucleotide polymorphisms (SNPs) flanking the minisatellite in individuals from six populations, and we show that over 40% of the total genetic variance near the minisatellite is due to differences between Africans and non-Africans, far higher than seen in most genomic regions and consistent with differential selection acting on the insulin gene region, most likely in the non-African ancestral population. Linkage disequilibrium was lower in African populations, with evidence of clustering of historical recombination events. Analysis of haplotypes from the relatively nonrecombining region around the minisatellite revealed a star-shaped phylogeny with lineages radiating from an ancestral African-specific haplotype. These haplotypes confirmed that minisatellite lineages defined by variant repeat distributions are monophyletic in origin. These analyses provide a framework for a cladistic approach to future disease association studies of the insulin region within both African and non-African populations, and they identify SNPs which can be rapidly analyzed as surrogate markers for minisatellite lineage.

Indexed as

AfricaAllelesDiabetes MellitusEvolution, MolecularGenetics, PopulationGenetic VariationGenotypeHaplotypesHumansInsulinLinkage DisequilibriumMinisatellite RepeatsMolecular Sequence DataPhylogenyPolymorphism, Single NucleotideUnited KingdomInsulin

Identifiers

PMID12952878
PMCPMC403702
OpenAlexW2047306415

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.