Evidence map›Paper›PMID 35777903›Full record

ArticleJournal of advanced research2022

Multi-omics data reveals the disturbance of glycerophospholipid metabolism caused by disordered gut microbiota in depressed mice.

Tian Tian, Qiang Mao, Jing Xie, Ying Wang, Wei-Hua Shao, Qi Zhong, Jian-Jun Chen

Open access · goldAbstract read
In one paragraph

Article in Journal of advanced research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 74 papers.

0numbers the graph read from it
0cells of the map it votes in
74citing papers in PubMed
7.1field-weighted citation impact, top 2% 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

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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

74 citing papers in PubMed, 149 citations in OpenAlex.

  1. Article
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  6. Butyrate Is Associated with the Antidepressant Effects ofInternational journal of molecular sciences · 2026
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  9. COVID-19 Infection and Gut Microbial Dysbiosis Among Filipinos with Type 2 Diabetes Mellitus.Journal of the ASEAN Federation of Endocrine Societies · 2026
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  14. International journal of nanomedicine · 2026
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  18. Co-fermentation ofFrontiers in nutrition · 2026
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  20. Review

14 more citing papers are in PubMed but not listed here.

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

7 authors at 6 institutions in 1 country.

Tian TianDepartment of Neurology, Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou Province 550004, China.
Qiang MaoDepartment of Pharmacy, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China.
Jing XieChongqing Emergency Medical Center, Department of Endocrinology, The Fourth People's Hospital of Chongqing, Central Hospital of Chongqing University, Chongqing 400016, China.
Ying WangDepartment of Rehabilitation, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400000, China.
Wei-Hua ShaoDepartment of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Qi ZhongInstitute of Life Sciences, Chongqing Medical University, Chongqing 400016, China.
Jian-Jun ChenInstitute of Life Sciences, Chongqing Medical University, Chongqing 400016, China. Electronic address: chenjianjun@cqmu.edu.cn.
Chongqing Medical University · CNAffiliated Hospital of Guizhou Medical University · CNChongqing University · CNDalian Medical University · CNFirst Affiliated Hospital of Chongqing Medical University · CNSecond Affiliated Hospital of Chongqing Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAlthough researchers have done intensive research on depression, its pathogenesis is still not fully explained. More and more evidence suggests that gut microbiota is closely related to the onset of depression; but its specific functional ways are not clearly identified.

objectivesThe purpose of our work was to find out how the gut microbiota was involved in the onset of depression, and to identify the potential ways to link the gut and brain in mice with depressive-like behaviors (DLB).

methodsWe used the chronic restraint stress (CRS)-induced depression model here. Gut microbiota compositions in fecal samples, lipid metabolism (in fecal, serum and hippocampus samples) and neurotransmitters in hippocampus samples were detected.

resultsWe found that the 7 of 13 differential genera that significantly correlated with DLB belonged to phylum Firmicutes. The differential lipid metabolites in fecal samples mainly belonged to glycerophospholipids (GP) and fatty acids (FA) metabolism, and three important "metabolite type-bacterial taxa" correlated pairs were identified: "FA/GP-Firmicutes", "FA/GP-Akkermansia", and "FA/GP-Bifidobacterium". The key differential lipid metabolites significantly correlated with DLB mainly belonged to FA and GP, and the DLB-related metagenomic genes were consistently enriched in GP metabolism and FA metabolism. Three significantly changed short-chain fatty acids (SCFAs) were significantly correlated with the majority of differential genera. Meanwhile, we found that the differential lipid metabolites in serum and hippocampus samples were mainly mapped into the GP metabolism, and there were four differential neurotransmitters from the tryptophan pathway in hippocampus samples.

conclusionTogether, our findings could provide novel insights into the role of "microbiota-gut-brain" (MGB) axis in depression, and indicate that the gut microbiota might have a vital role in the onset of DLB by affecting the peripheral/central GP metabolism and tryptophan pathway. The "Firmicutes-SCFAs-GP metabolism-Tryptophan pathway" might be a possible way to link the gut and brain in depressed mice.

Indexed as

Gastrointestinal MicrobiomeAnimalsBacillotaFatty Acids, VolatileGlycerophospholipidsLipid MetabolismMiceTryptophanFatty Acids, VolatileGlycerophospholipidsTryptophanDepressionGlycerophospholipidsGut microbiotaNeurotransmitter

Identifiers

PMID35777903
PMCPMC9263645
OpenAlexW3205792946

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.