Evidence map›Paper›PMID 32777345›Full record

ArticleMolecular and cellular neurosciences2020

Aging lowers PEX5 levels in cortical neurons in male and female mouse brains.

Ndidi-Ese Uzor, Diego Morales Scheihing, Gab Seok Kim, Jose Felix Moruno-Manchon, Liang Zhu, Caroline R Reynolds, Jessica M Stephenson, Aleah Holmes, Louise D McCullough, Andrey S Tsvetkov

Open access · greenAbstract read
In one paragraph

Article in Molecular and cellular neurosciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 46% 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

3 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
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 2 institutions in 1 country.

Ndidi-Ese UzorUniversity of Texas MD Anderson UTHealth Graduate School of Biomedical Sciences, Houston, TX 77030, USA; Department of Neurology, the University of Texas McGovern Medical School at Houston, Houston 77030, TX, USA.
Diego Morales ScheihingDepartment of Neurology, the University of Texas McGovern Medical School at Houston, Houston 77030, TX, USA.
Gab Seok KimDepartment of Neurology, the University of Texas McGovern Medical School at Houston, Houston 77030, TX, USA.
Jose Felix Moruno-ManchonDepartment of Neurology, the University of Texas McGovern Medical School at Houston, Houston 77030, TX, USA.
Liang ZhuBiostatistics and Epidemiology Research Design, University of Texas Health Science Center at Houston, Houston 77030, TX, USA.
Caroline R ReynoldsDepartment of Neurology, the University of Texas McGovern Medical School at Houston, Houston 77030, TX, USA.
Jessica M StephensonDepartment of Neurology, the University of Texas McGovern Medical School at Houston, Houston 77030, TX, USA.
Aleah HolmesDepartment of Neurology, the University of Texas McGovern Medical School at Houston, Houston 77030, TX, USA.
Louise D McCulloughUniversity of Texas MD Anderson UTHealth Graduate School of Biomedical Sciences, Houston, TX 77030, USA; Department of Neurology, the University of Texas McGovern Medical School at Houston, Houston 77030, TX, USA; UTHealth Consortium on Aging, the University of Texas McGovern Medical School, Houston 77030, TX, USA.
Andrey S TsvetkovUniversity of Texas MD Anderson UTHealth Graduate School of Biomedical Sciences, Houston, TX 77030, USA; Department of Neurology, the University of Texas McGovern Medical School at Houston, Houston 77030, TX, USA; UTHealth Consortium on Aging, the University of Texas McGovern Medical School, Houston 77030, TX, USA. Electronic address: andrey.s.tsvetkov@uth.tmc.edu.
The University of Texas Health Science Center at Houston · USThe University of Texas MD Anderson Cancer Center · US

Funding

Reversing Age Related InflammationR01NS094543 · NINDS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI MCCULLOUGH, LOUISE D. · 2016 to 2020
$2.8M
NINDS NIH HHS R01 NS094543
6 · The paper itself

Abstract

Peroxisomes exist in nearly every cell, oxidizing fats, synthesizing lipids and maintaining redox balance. As the brain ages, multiple pathways are negatively affected, but it is currently unknown if peroxisomal proteins are affected by aging in the brain. While recent studies have investigated a PEX5 homolog in aging C. elegans models and found that it is reduced in aging, it is unclear if PEX5, a mammalian peroxisomal protein that plays a role in peroxisomal homeostasis and degradation, is affected in the aging brain. To answer this question, we first determined the amount of PEX5, in brain homogenates from young (3 months) and aged (26 through 32+ months of age) wild-type mice of both sexes. PEX5 protein was decreased in aged male brains, but this reduction was not significant in female brains. RNAScope and real-time qPCR analyses showed that Pex5 mRNA was also reduced in aged male brain cortices, but not in females. Immunohistochemistry assays of cortical neurons in young and aged male brains showed that the amount of neuronal PEX5 was reduced in aged male brains. Cortical neurons in aged female mice also had reduced PEX5 levels in comparison to younger female mice. In conclusion, total PEX5 levels and Pex5 gene expression both decrease with age in male brains, and neuronal PEX5 levels lower in an age-dependent manner in the cortices of animals of both sexes.

Indexed as

AgingAnimalsBrainCytosolFemaleMaleMiceNeuronsPeroxisomesPeroxisome-Targeting Signal 1 ReceptorProtein TransportReceptors, Cytoplasmic and NuclearUbiquitinationPeroxisome-Targeting Signal 1 ReceptorPex5 protein, mouseReceptors, Cytoplasmic and NuclearAging brainPeroxisomal proteinPEX5

Identifiers

PMID32777345
PMCPMC7484460
OpenAlexW3047703070

What OpenQuestion holds

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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.