Evidence map›Paper›PMID 35796564›Full record

ArticleHuman molecular genetics2022

Comparative genomic analyses of multiple backcross mouse populations suggest SGCG as a novel potential obesity-modifier gene.

Tanja Kuhn, Katharina Kaiser, Sandra Lebek, Delsi Altenhofen, Birgit Knebel, Ralf Herwig, Axel Rasche, Angela Pelligra, Sarah Görigk, Jenny Minh-An Khuong and 5 more

Open access · hybridAbstract read
In one paragraph

Article in Human molecular genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 23% 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, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Pooled it
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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

15 authors at 4 institutions in 1 country.

Tanja KuhnMedical Faculty, Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Duesseldorf D-40225, Germany.
Katharina KaiserMedical Faculty, Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Duesseldorf D-40225, Germany.
Sandra LebekMedical Faculty, Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Duesseldorf D-40225, Germany.
Delsi AltenhofenMedical Faculty, Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Duesseldorf D-40225, Germany.
Birgit KnebelMedical Faculty, Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Duesseldorf D-40225, Germany.
Ralf HerwigDepartment of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin D-14195, Germany.
Axel RascheDepartment of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin D-14195, Germany.
Angela PelligraMedical Faculty, Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Duesseldorf D-40225, Germany.
Sarah GörigkMedical Faculty, Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Duesseldorf D-40225, Germany.
Jenny Minh-An KhuongMedical Faculty, Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Duesseldorf D-40225, Germany.
Heike VogelGerman Center for Diabetes Research (DZD), Partner Düsseldorf / Partner Potsdam, Munich-Neuherberg, Germany.
Annette SchürmannGerman Center for Diabetes Research (DZD), Partner Düsseldorf / Partner Potsdam, Munich-Neuherberg, Germany.
Matthias BlüherHelmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Zentrum München at the University of Leipzig and University Hospital Leipzig, Leipzig D-04103, Germany.
Alexandra ChadtMedical Faculty, Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Duesseldorf D-40225, Germany.
Hadi Al-HasaniMedical Faculty, Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Duesseldorf D-40225, Germany.ORCID 0000-0003-2543-0130
Deutsches Diabetes-Zentrum e.V. · DEGerman Center for Diabetes Research · DEMax Planck Institute for Molecular Genetics · DEHelmholtz Zentrum München · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To nominate novel disease genes for obesity and type 2 diabetes (T2D), we recently generated two mouse backcross populations of the T2D-susceptible New Zealand Obese (NZO/HI) mouse strain and two genetically different, lean and T2D-resistant strains, 129P2/OlaHsd and C3HeB/FeJ. Comparative linkage analysis of our two female backcross populations identified seven novel body fat-associated quantitative trait loci (QTL). Only the locus Nbw14 (NZO body weight on chromosome 14) showed linkage to obesity-related traits in both backcross populations, indicating that the causal gene variant is likely specific for the NZO strain as NZO allele carriers in both crosses displayed elevated body weight and fat mass. To identify candidate genes for Nbw14, we used a combined approach of gene expression and haplotype analysis to filter for NZO-specific gene variants in gonadal white adipose tissue, defined as the main QTL-target tissue. Only two genes, Arl11 and Sgcg, fulfilled our candidate criteria. In addition, expression QTL analysis revealed cis-signals for both genes within the Nbw14 locus. Moreover, retroviral overexpression of Sgcg in 3T3-L1 adipocytes resulted in increased insulin-stimulated glucose uptake. In humans, mRNA levels of SGCG correlated with body mass index and body fat mass exclusively in diabetic subjects, suggesting that SGCG may present a novel marker for metabolically unhealthy obesity. In conclusion, our comparative-cross analysis could substantially improve the mapping resolution of the obesity locus Nbw14. Future studies will throw light on the mechanism by which Sgcg may protect from the development of obesity.

Indexed as

Diabetes Mellitus, Type 2ADP-Ribosylation FactorsAnimalsBody WeightChromosome MappingFemaleGenes, ModifierGenomicsHumansMiceMice, Inbred StrainsObesitySarcoglycansADP-Ribosylation FactorsARL11 protein, humanSarcoglycansSGCG protein, human

Identifiers

PMID35796564
PMCPMC9703946
OpenAlexW4284879953

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.