Evidence map›Paper›PMID 36973679›Full record

ArticleJournal of translational medicine2023

Cholesterol suppresses human iTreg differentiation and nTreg function through mitochondria-related mechanisms.

Huanzhi Zhang, Ni Xia, Tingting Tang, Shaofang Nie, Lingfeng Zha, Min Zhang, Bingjie Lv, Yuzhi Lu, Jiao Jiao, Jingyong Li and 1 more

Open access · goldFull text read
In one paragraph

Article in Journal of translational medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.1field-weighted citation impact, top 13% 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

8 citing papers in PubMed, 13 citations in OpenAlex.

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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

11 authors at 3 institutions in 1 country.

Huanzhi Zhang *Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Ni Xia *Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Tingting TangDepartment of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Shaofang NieDepartment of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Lingfeng ZhaDepartment of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Min ZhangDepartment of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Bingjie LvDepartment of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Yuzhi LuDepartment of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Jiao JiaoDepartment of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Jingyong LiDepartment of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Xiang ChengDepartment of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. nathancx@hust.edu.cn.
Union Hospital · CNHuazhong University of Science and Technology · CNUnion Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBoth the crystalline and soluble forms of cholesterol increase macrophage secretion of interleukin 1β (IL-1β), aggravating the inflammatory response in atherosclerosis (AS). However, the link between cholesterol and regulatory T cells (Tregs) remains unclear. This study aimed to investigate the effect of cholesterol treatment on Tregs.

methodsDifferentiation of induced Tregs (iTregs) was analyzed using flow cytometry. The expression of hypoxia-inducible factor-1a (HIF-1a) and its target genes was measured by western blotting and/or RT-qPCR. Two reporter jurkat cell lines were constructed by lentiviral transfection. Mitochondrial function and the structure of natural Tregs (nTregs) were determined by tetramethylrhodamine (TMRM) and mitoSOX staining, Seahorse assay, and electron microscopy. The immunoregulatory function of nTregs was determined by nTreg-macrophage co-culture assay and ELISA.

resultsCholesterol treatment suppressed iTreg differentiation and impaired nTreg function. Mechanistically, cholesterol induced the production of mitochondrial reactive oxygen species (mtROS) in naïve T cells, inhibiting the degradation of HIF-1α and unleashing its inhibitory effects on iTreg differentiation. Furthermore, cholesterol-induced mitochondrial oxidative damage impaired the immunosuppressive function of nTregs. Mixed lymphocyte reaction and nTreg-macrophage co-culture assays revealed that cholesterol treatment compromised the ability of nTregs to inhibit pro-inflammatory conventional T cell proliferation and promote the anti-inflammatory functions of macrophages. Finally, mitoTEMPO (MT), a specific mtROS scavenger, restored iTreg differentiation and protected nTreg from further deterioration.

conclusionOur findings suggest that cholesterol may aggravate inflammation within AS plaques by acting on both iTregs and nTregs, and that MT may be a promising anti-atherogenic drug.

Indexed as

InflammationT-Lymphocytes, RegulatoryCell DifferentiationCoculture TechniquesForkhead Transcription FactorsHumansMitochondriaForkhead Transcription FactorsAtherosclerosisCholesterolMitochondrial reactive oxygen speciesmitoTEMPORegulatory T cells

Identifiers

PMID36973679
PMCPMC10045251
OpenAlexW4361017902

What OpenQuestion holds

Textfull text, public
LicenceCC BY
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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.