Evidence map›Paper›PMID 36495344›Full record

SynthesisCellular and molecular life sciences : CMLS2022

Multi-cohort analysis of depression-associated gut bacteria sheds insight on bacterial biomarkers across populations.

Suisha Liang, Zhen Ye Sin, Juelei Yu, Shilin Zhao, Zhang Xi, Roberto Bruzzone, Hein M Tun

Abstract readMeta-Analysis
In one paragraph

Synthesis in Cellular and molecular life sciences : CMLS, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

32 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  17. A Mechanistic Study ofJournal of microbiology and biotechnology · 2025
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  18. Marine drugs · 2025
    Article
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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

7 authors.

Suisha LiangHKU-Pasteur Research Pole, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
Zhen Ye SinHKU-Pasteur Research Pole, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
Juelei YuMicrobiota I-Center (MagIC), Hong Kong SAR, China.
Shilin ZhaoMicrobiota I-Center (MagIC), Hong Kong SAR, China.
Zhang XiHKU-Pasteur Research Pole, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
Roberto BruzzoneHKU-Pasteur Research Pole, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
Hein M TunThe Jockey Club School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China. heintun@cuhk.edu.hk.ORCID http://orcid.org/0000-0001-7597-5062

Funding

Health and Medical Research Fund CFS-HKU2University Grants Committee 27117022
6 · The paper itself

Abstract

Gut microbes are associated with the development of depression based on extensive evidence. However, previous studies have led to conflicting reports on this association, posing challenges to the application of gut bacteria in the diagnostics and treatment of depression. To minimise heterogenicity in data analysis, the present meta-analysis adopted a standardised bioinformatics and statistical pipeline to analyse 16S rRNA sequences of 1827 samples from eight different cohorts. Although changes in the overall bacterial community were identified by our meta-analysis, depressive-correlated changes in alpha-diversity were absent. Enrichment of Bacteroidetes, Parabacteroides, Barnesiella, Bacteroides, and Bacteroides vulgatus, along with depletion in Firmicutes, Dialister, Oscillospiraceae UCG 003 and UCG 002, and Bacteroides plebeius, were observed in depressive-associated bacteria. By contrast, elevated L-glutamine degradation, and reduced L-glutamate and L-isoleucine biosynthesis were identified in depressive-associated microbiomes. After systemically reviewing the data of these collected cohorts, we have established a bacterial classifier to identify depressive symptoms with AUC 0.834 and 0.685 in the training and external validation dataset, respectively. Moreover, a low-risk bacterial cluster for depressive symptoms was identified, which was represented by a lower abundance of Escherichia-Shigella, and a higher abundance of Faecalibacterium, Oscillospiraceae UCG 002, Ruminococcus, and Christensenellaceae R.7 group.

Indexed as

BacteriaBacteroidetesBiomarkersCohort StudiesDNA, BacterialFecesHumansRNA, Ribosomal, 16SBiomarkersDNA, BacterialRNA, Ribosomal, 16SBacteria-based identificationDepressionGut bacteriaGut-brain axisMulti-cohort

Identifiers

PMID36495344
PMCPMC11072413

What OpenQuestion holds

Textmetadata
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.