Evidence map›Paper›PMID 29472585›Full record

ArticleCell death & disease2018

Estradiol signaling mediates gender difference in visceral adiposity via autophagy.

Zhipeng Tao, Louise D Zheng, Cayleen Smith, Jing Luo, Alex Robinson, Fabio A Almeida, Zongwei Wang, Aria F Olumi, Dongmin Liu, Zhiyong Cheng

Open access · goldAbstract read
In one paragraph

Article in Cell death & disease, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed
2.6field-weighted citation impact, top 10% 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

37 citing papers in PubMed, 55 citations in OpenAlex.

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  13. Hallmarks of Cancer Cachexia: Sexual Dimorphism in Related Pathways.International journal of molecular sciences · 2025
    Review
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  20. Observational
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 1 country.

Zhipeng TaoDepartment of Human Nutrition, Foods, and Exercise, Fralin Life Science Institute, College of Agriculture and Life Science, Virginia Tech, Blacksburg, VA, 24061, USA.
Louise D ZhengDepartment of Human Nutrition, Foods, and Exercise, Fralin Life Science Institute, College of Agriculture and Life Science, Virginia Tech, Blacksburg, VA, 24061, USA.
Cayleen SmithDepartment of Human Nutrition, Foods, and Exercise, Fralin Life Science Institute, College of Agriculture and Life Science, Virginia Tech, Blacksburg, VA, 24061, USA.
Jing LuoDepartment of Human Nutrition, Foods, and Exercise, Fralin Life Science Institute, College of Agriculture and Life Science, Virginia Tech, Blacksburg, VA, 24061, USA.
Alex RobinsonDepartment of Human Nutrition, Foods, and Exercise, Fralin Life Science Institute, College of Agriculture and Life Science, Virginia Tech, Blacksburg, VA, 24061, USA.
Fabio A AlmeidaDepartment of Health Promotion, Social & Behavioral Health, College of Public Health, University of Nebraska Medical Center, Omaha, NE, USA.
Zongwei WangDepartment of Urology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Aria F OlumiDepartment of Urology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Dongmin LiuDepartment of Human Nutrition, Foods, and Exercise, Fralin Life Science Institute, College of Agriculture and Life Science, Virginia Tech, Blacksburg, VA, 24061, USA. doliu@vt.edu.
Zhiyong ChengDepartment of Human Nutrition, Foods, and Exercise, Fralin Life Science Institute, College of Agriculture and Life Science, Virginia Tech, Blacksburg, VA, 24061, USA. zcheng@vt.edu.ORCID 0000-0001-7615-9788
Virginia Tech · USHarvard University · USUniversity of Nebraska Medical Center · USVirginia Cooperative Extension · US

Funding

The Reach and Effectiveness of Technology-Enhanced Diabetes Prevention ProgramsR18DK091811 · NIDDK · VIRGINIA POLYTECHNIC INST AND ST UNIV · PI ALMEIDA, FABIO ARAUJO · 2012 to 2016
$3.2M
Identification and molecular characterization of anti-diabetic flavonoidsR01AT007077 · NCCIH · VIRGINIA POLYTECHNIC INST AND ST UNIV · PI LIU, DONGMIN · 2012 to 2016
$1.9M
NCCIH NIH HHS R01 AT007077NIDDK NIH HHS R18 DK091811
6 · The paper itself

Abstract

Excessive adiposity (particularly visceral fat mass) increases the risks of developing metabolic syndrome. Women have lower deposit of visceral fat than men, and this pattern becomes diminished postmenopausally, but the underlying mechanism remains largely unknown. Here, we show that the gender difference in visceral fat distribution is controlled by an estradiol-autophagy axis. In C57BL/6J and wild-type control mice, a higher visceral fat mass was detected in the males than in the females, which was associated with lower expression of estrogen receptor α (ERα) and more active autophagy in males vs. females. However, deletion of ERα normalized autophagy activity and abolished the gender difference in visceral adiposity. In line with the adiposity-reducing effect of the ERα-autophagy axis, we found that downregulation of ERα and increased autophagy activity were required for adipogenesis, while induction of estradiol signaling dampened autophagy and drastically prevented adipogenesis. Mechanistically, the estradiol-ERα signaling activated mTOR, which phosphorylated and inhibited ULK1, thereby suppressing autophagy and adipogenesis. Together, our study suggests that the lower visceral adiposity in the females (vs. the males) arises from a more active estradiol-ERα signaling, which tunes down autophagy and adipogenesis.

Indexed as

AdipogenesisAdiposityAnimalsAutophagyEstradiolEstrogen Receptor alphaEstrogensFemaleIntra-Abdominal FatMaleMiceMice, Inbred C57BLSex FactorsSignal TransductionEstradiolEstrogen Receptor alphaEstrogens

Identifiers

PMID29472585
PMCPMC5833393
OpenAlexW2793686614

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.