Evidence map›Paper›PMID 29893858›Full record

ArticleHuman molecular genetics2018

A collective diabetes cross in combination with a computational framework to dissect the genetics of human obesity and Type 2 diabetes.

Heike Vogel, Anne Kamitz, Nicole Hallahan, Sandra Lebek, Tanja Schallschmidt, Wenke Jonas, Markus Jähnert, Pascal Gottmann, Lisa Zellner, Timo Kanzleiter and 12 more

Open access · hybridAbstract read
In one paragraph

Article in Human molecular genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
2.2field-weighted citation impact, top 12% 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

15 citing papers in PubMed, 21 citations in OpenAlex.

  1. Article
  2. Identification of a critical interval for type 2 diabetes QTL on chromosome 4 in DDD-AMammalian genome : official journal of the International Mammalian Genome Society · 2025
    Article
  3. Article
  4. E96V Mutation in theInternational journal of molecular sciences · 2023
    Article
  5. Article
  6. Alterations of Lipid Profile in Livers with Impaired Lipophagy.International journal of molecular sciences · 2022
    Article
  7. Article
  8. Identification of Novel Genes Involved in Hyperglycemia in Mice.International journal of molecular sciences · 2022
    Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
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

22 authors at 9 institutions in 2 countries.

Heike VogelDepartment of Experimental Diabetology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal D-14558, Germany.
Anne KamitzDepartment of Experimental Diabetology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal D-14558, Germany.
Nicole HallahanDepartment of Experimental Diabetology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal D-14558, Germany.
Sandra LebekGerman Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany.
Tanja SchallschmidtGerman Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany.
Wenke JonasDepartment of Experimental Diabetology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal D-14558, Germany.
Markus JähnertDepartment of Experimental Diabetology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal D-14558, Germany.
Pascal GottmannDepartment of Experimental Diabetology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal D-14558, Germany.
Lisa ZellnerDepartment of Experimental Diabetology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal D-14558, Germany.
Timo KanzleiterDepartment of Experimental Diabetology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal D-14558, Germany.
Mareike DamenGerman Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany.
Delsi AltenhofenGerman Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany.
Ralph BurkhardtInstitute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University Hospital Leipzig, Leipzig D-04303, Germany.
Simone RennerGerman Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany.
Maik DahlhoffGerman Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany.
Eckhard WolfGerman Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany.
Timo D MüllerGerman Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany.
Matthias BlüherDepartment of Medicine, University of Leipzig, Leipzig D-04103, Germany.
Hans-Georg JoostDepartment of Experimental Diabetology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal D-14558, Germany.
Alexandra ChadtGerman Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany.
Hadi Al-HasaniGerman Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany.
Annette SchürmannDepartment of Experimental Diabetology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal D-14558, Germany.
Heinrich Heine University Düsseldorf · DEGerman Center for Diabetes Research · DEDeutsches Diabetes-Zentrum e.V. · DEGerman Institute of Human Nutrition · DELeipzig University · DELudwig-Maximilians-Universität München · DETechnical University of Munich · DEUniversity Hospital Leipzig · DEUniversity of Potsdam · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To explore the genetic determinants of obesity and Type 2 diabetes (T2D), the German Center for Diabetes Research (DZD) conducted crossbreedings of the obese and diabetes-prone New Zealand Obese mouse strain with four different lean strains (B6, DBA, C3H, 129P2) that vary in their susceptibility to develop T2D. Genome-wide linkage analyses localized more than 290 quantitative trait loci (QTL) for obesity, 190 QTL for diabetes-related traits and 100 QTL for plasma metabolites in the outcross populations. A computational framework was developed that allowed to refine critical regions and to nominate a small number of candidate genes by integrating reciprocal haplotype mapping and transcriptome data. The efficiency of the complex procedure was demonstrated for one obesity QTL. The genomic interval of 35 Mb with 502 annotated candidate genes was narrowed down to six candidates. Accordingly, congenic mice retained the obesity phenotype owing to an interval that contains three of the six candidate genes. Among these the phospholipase PLA2G4A exhibited an elevated expression in adipose tissue of obese human subjects and is therefore a critical regulator of the obesity locus. Together, our broad and complex approach demonstrates that combined- and comparative-cross analysis exhibits improved mapping resolution and represents a valid tool for the identification of disease genes.

Indexed as

Polymorphism, Single NucleotideQuantitative Trait LociAdipose TissueAdolescentAdultAgedAged, 80 and overAnimalsBiomarkersChromosome MappingComputational BiologyCrosses, GeneticDiabetes Mellitus, Type 2FemaleGenetic LinkageGroup IV Phospholipases A2BiomarkersGroup IV Phospholipases A2PLA2G4A protein, human

Identifiers

PMID29893858
PMCPMC6097155
OpenAlexW2806864318

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.