Evidence map›Paper›PMID 28556428›Full record

ArticleAging cell2017

Identification of tissue-specific transcriptional markers of caloric restriction in the mouse and their use to evaluate caloric restriction mimetics.

Jamie L Barger, James M Vann, Nicole L Cray, Thomas D Pugh, Angela Mastaloudis, Shelly N Hester, Steven M Wood, Michael A Newton, Richard Weindruch, Tomas A Prolla

Open access · goldAbstract read
In one paragraph

Article in Aging cell, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
4.8field-weighted citation impact, top 4% 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

26 citing papers in PubMed, 1 synthesis or guideline pooled it, 49 citations in OpenAlex.

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  19. Reversing age-associated arterial dysfunction: insight from preclinical models.Journal of applied physiology (Bethesda, Md. : 1985) · 2018
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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 2 countries.

Jamie L BargerLifeGen Technologies LLC, Madison, WI, USA.ORCID 0000-0001-8694-0068
James M VannLifeGen Technologies LLC, Madison, WI, USA.
Nicole L CrayLifeGen Technologies LLC, Madison, WI, USA.
Thomas D PughLifeGen Technologies LLC, Madison, WI, USA.
Angela MastaloudisCenter for Anti-Aging Research, NSE Products, Inc., Provo, UT, USA.
Shelly N HesterCenter for Anti-Aging Research, NSE Products, Inc., Provo, UT, USA.
Steven M WoodCenter for Anti-Aging Research, NSE Products, Inc., Provo, UT, USA.
Michael A NewtonDepartments of Statistics and of Biostatistics and Medical Informatics, University of Wisconsin, Madison, WI, USA.
Richard WeindruchLifeGen Technologies LLC, Madison, WI, USA.
Tomas A ProllaLifeGen Technologies LLC, Madison, WI, USA.
Thermo Fisher Scientific (Norway) · NONu Skin (United States) · USUniversity of Wisconsin–Madison · USUniversity of Wisconsin System · US

Funding

TrainingU54AI117924 · NIAID · UNIVERSITY OF WISCONSIN-MADISON · PI CRAVEN, MARK W. · 2014 to 2018
$11.3M
Role of Sirt3 in Aging and Caloric RestrictionR01AG038679 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI DENU, JOHN M, PROLLA, TOMAS ALBERTO · 2011 to 2016
$1.6M
Identification of Transcriptional Biomarkers of Calorie Restriction in Adipose TiR43AG034833 · NIA · LIFEGEN TECHNOLOGIES, LLC · PI BARGER, JAMIE LOUIS · 2010 to 2010
$124k
NIAID NIH HHS U54 AI117924NIA NIH HHS R01 AG038679NIA NIH HHS R43 AG034833
6 · The paper itself

Abstract

Caloric restriction (CR) without malnutrition has been shown to retard several aspects of the aging process and to extend lifespan in different species. There is strong interest in the identification of CR mimetics (CRMs), compounds that mimic the beneficial effects of CR on lifespan and healthspan without restriction of energy intake. Identification of CRMs in mammals is currently inefficient due to the lack of screening tools. We have performed whole-genome transcriptional profiling of CR in seven mouse strains (C3H/HeJ, CBA/J, DBA/2J, B6C3F1/J, 129S1/SvImJ, C57BL/6J, and BALB/cJ) in white adipose tissue (WAT), gastrocnemius muscle, heart, and brain neocortex. This analysis has identified tissue-specific panels of genes that change in expression in multiple mouse strains with CR. We validated a subset of genes with qPCR and used these to evaluate the potential CRMs bezafibrate, pioglitazone, metformin, resveratrol, quercetin, 2,4-dinitrophenol, and L-carnitine when fed to C57BL/6J 2-month-old mice for 3 months. Compounds were also evaluated for their ability to modulate previously characterized biomarkers of CR, including mitochondrial enzymes citrate synthase and SIRT3, plasma inflammatory cytokines TNF-α and IFN-γ, glycated hemoglobin (HbA1c) levels and adipocyte size. Pioglitazone, a PPAR-γ agonist, and L-carnitine, an amino acid involved in lipid metabolism, displayed the strongest effects on both the novel transcriptional markers of CR and the additional CR biomarkers tested. Our findings provide panels of tissue-specific transcriptional markers of CR that can be used to identify novel CRMs, and also represent the first comparative molecular analysis of several potential CRMs in multiple tissues in mammals.

Indexed as

Caloric Restriction2,4-DinitrophenolAdipose Tissue, WhiteAgingAnimalsBezafibrateCarnitineCitrate (si)-SynthaseGene Expression ProfilingGene Expression RegulationGlycated HemoglobinInterferon-gammaMaleMetforminMiceMice, Inbred BALB C2,4-DinitrophenolBezafibrateCarnitineCitrate (si)-SynthaseGlycated HemoglobinInterferon-gammaMetforminPioglitazoneQuercetinResveratrolSirt3 protein, mouseSirtuin 3StilbenesThiazolidinedionesTumor Necrosis Factor-alphaagingbiomarkerscaloric restrictiongene expressionmouse

Identifiers

PMID28556428
PMCPMC5506434
OpenAlexW2618334954

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.