Evidence map›Paper›PMID 28199320›Full record

ArticlePloS one2017

The use of urinary proteomics in the assessment of suitability of mouse models for ageing.

Esther Nkuipou-Kenfack, Joost P Schanstra, Seerat Bajwa, Martin Pejchinovski, Claire Vinel, Cédric Dray, Philippe Valet, Jean-Loup Bascands, Antonia Vlahou, Thomas Koeck and 8 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.2field-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

4 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. 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

18 authors at 10 institutions in 5 countries.

Esther Nkuipou-KenfackMosaiques Diagnostics GmbH, Hannover, Germany.
Joost P SchanstraInstitut National de la Santé et de la Recherche Médicale (INSERM), U1048, Institut of Cardiovascular and Metabolic Disease, Toulouse, France.
Seerat BajwaLeibniz Institute of Age Research, Fritz Lipmann Institute, Jena, Germany.
Martin PejchinovskiMosaiques Diagnostics GmbH, Hannover, Germany.
Claire VinelInstitut National de la Santé et de la Recherche Médicale (INSERM), U1048, Institut of Cardiovascular and Metabolic Disease, Toulouse, France.
Cédric DrayInstitut National de la Santé et de la Recherche Médicale (INSERM), U1048, Institut of Cardiovascular and Metabolic Disease, Toulouse, France.
Philippe ValetInstitut National de la Santé et de la Recherche Médicale (INSERM), U1048, Institut of Cardiovascular and Metabolic Disease, Toulouse, France.
Jean-Loup BascandsInserm-UMR Diabète athérothrombose Thérapies Réunion Océan Indien (DéTROI), plateforme CYROI, Sainte-Clotilde, France.
Antonia VlahouBiotechnology Division, Biomedical Research Foundation Academy of Athens, Athens, Greece.
Thomas KoeckMosaiques Diagnostics GmbH, Hannover, Germany.
Melanie BorriesSystems Biology of the Cellular Microenvironment Group, Institute of Molecular Medicine and Cell Research, Albert-Ludwigs-University, Freiburg im Breisgau, Germany.
Hauke BuschSystems Biology of the Cellular Microenvironment Group, Institute of Molecular Medicine and Cell Research, Albert-Ludwigs-University, Freiburg im Breisgau, Germany.
Wibke Bechtel-WalzUniversity Hospital Freiburg, Freiburg, Germany.
Tobias B HuberDepartment of Medicine IV, Faculty of Medicine, Medical Center, University of Freiburg, Freiburg, Germany.
Karl L RudolphLeibniz Institute of Age Research, Fritz Lipmann Institute, Jena, Germany.
Andreas PichHannover Medical School, Core Facility Proteomics, Hannover, Germany.
Harald MischakMosaiques Diagnostics GmbH, Hannover, Germany.
Petra ZürbigMosaiques Diagnostics GmbH, Hannover, Germany.
Mosaiques Diagnostics and Therapeutics (Germany) · DEInserm · FRLeibniz Institute on Aging - Fritz Lipmann Institute (FLI) · DEAcademy of Athens · GRGerman Cancer Research Center · DEHeidelberg University · DEInstitut des Maladies Métaboliques et Cardiovasculaires · FRMedizinische Hochschule Hannover · DEUniversity Medical Center Freiburg · DEUniversity of Freiburg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ageing is a complex process characterised by a systemic and progressive deterioration of biological functions. As ageing is associated with an increased prevalence of age-related chronic disorders, understanding its underlying molecular mechanisms can pave the way for therapeutic interventions and managing complications. Animal models such as mice are commonly used in ageing research as they have a shorter lifespan in comparison to humans and are also genetically close to humans. To assess the translatability of mouse ageing to human ageing, the urinary proteome in 89 wild-type (C57BL/6) mice aged between 8-96 weeks was investigated using capillary electrophoresis coupled to mass spectrometry (CE-MS). Using age as a continuous variable, 295 peptides significantly correlated with age in mice were identified. To investigate the relevance of using mouse models in human ageing studies, a comparison was performed with a previous correlation analysis using 1227 healthy subjects. In mice and humans, a decrease in urinary excretion of fibrillar collagens and an increase of uromodulin fragments was observed with advanced age. Of the 295 peptides correlating with age, 49 had a strong homology to the respective human age-related peptides. These ortholog peptides including several collagen (N = 44) and uromodulin (N = 5) fragments were used to generate an ageing classifier that was able to discriminate the age among both wild-type mice and healthy subjects. Additionally, the ageing classifier depicted that telomerase knock-out mice were older than their chronological age. Hence, with a focus on ortholog urinary peptides mouse ageing can be translated to human ageing.

Indexed as

Models, BiologicalProteomicsAgingAnimalsCapillary ElectrochromatographyFemaleHumansMaleMass SpectrometryMiceMice, KnockoutPeptidesProteomePeptidesProteome

Identifiers

PMID28199320
PMCPMC5310860
OpenAlexW2587965175

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.