Evidence map›Paper›PMID 18093291›Full record

ArticleBMC genetics2007

A genome-wide scan for type 1 diabetes susceptibility genes in nuclear families with multiple affected siblings in Finland.

Qing Qiao, Anne-May Osterholm, Bing He, Janne Pitkäniemi, Heather J Cordell, Cinzia Sarti, Leena Kinnunen, Eva Tuomilehto-Wolf, Karl Tryggvason, Jaakko Tuomilehto

Open access · diamondAbstract read
In one paragraph

Article in BMC genetics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 25% 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, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Gene therapy in diabetes.Self/nonself · 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

10 authors at 4 institutions in 3 countries.

Qing QiaoDepartment of Public Health, University of Helsinki, Finland. qing.qiao@ktl.fi
Anne-May Osterholm
Bing He
Janne Pitkäniemi
Heather J Cordell
Cinzia Sarti
Leena Kinnunen
Eva Tuomilehto-Wolf
Karl Tryggvason
Jaakko Tuomilehto
University of Helsinki · FIKarolinska Institutet · SEInstitute for Molecular Medicine Finland · FINewcastle University · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA genome-wide search for genes that predispose to type 1 diabetes using linkage analysis was performed using 900 microsatellite markers in 70 nuclear families with affected siblings from Finland, a population expected to be more genetically homogeneous than others, and having the highest incidence of type 1 diabetes in the world and, yet, the highest proportion in Europe of cases (10%) carrying neither of the highest risk HLA haplotypes that include DR3 or DR4 alleles.

resultsIn addition to the evidence of linkage to the HLA region on 6p21 (nominal p = 4.0 x 10-6), significant evidence of linkage in other chromosome regions was not detected with a single-locus analysis. The two-locus analysis conditional on the HLA gave a maximum lod score (MLS) of 3.1 (nominal p = 2 x 10-4) on chromosome 9p13 under an additive model; MLS of 2.1 (nominal p = 6.1 x 10-3) on chromosome 17p12 and MLS of 2.5 (nominal p = 2.9 x 10-3) on chromosome 18p11 under a general model.

conclusionOur genome scan data confirmed the primary contribution of the HLA genes also in the high-risk Finnish population, and suggest that non-HLA genes also contribute to the familial clustering of type 1 diabetes in Finland.

Indexed as

Chromosome MappingGenetic Predisposition to DiseaseNuclear FamilyAdolescentAdultChildChild, PreschoolChromosomes, HumanDiabetes Mellitus, Type 1FinlandGenetic LinkageHumansInfantMiddle AgedSiblings

Identifiers

PMID18093291
PMCPMC2225422
OpenAlexW2033101511

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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.