Evidence map›Paper›PMID 39048972›Full record

ArticleBMC psychiatry2024

Gut microbiome and metabolism alterations in schizophrenia with metabolic syndrome severity.

Hongxia Zhao, Guang Zhu, Tong Zhu, Binbin Ding, Ahong Xu, Songyan Gao, Yufan Chao, Na Li, Yongchun Chen, Zuowei Wang and 2 more

Abstract read
In one paragraph

Article in BMC psychiatry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

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

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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

12 authors.

Hongxia Zhao *School of Medicine, Shanghai University, Shanghai, 200444, China.
Guang Zhu *Hongkou Mental Health Center, Shanghai, 200083, China.
Tong Zhu *School of Medicine, Shanghai University, Shanghai, 200444, China.
Binbin DingHongkou Mental Health Center, Shanghai, 200083, China.
Ahong XuHongkou Mental Health Center, Shanghai, 200083, China.
Songyan GaoInstitute of Translational Medicine, Shanghai University, Shanghai, 200444, China.
Yufan ChaoSchool of Medicine, Shanghai University, Shanghai, 200444, China.
Na LiSchool of Medicine, Shanghai University, Shanghai, 200444, China.
Yongchun ChenDepartment of Pharmacy, The First Naval Hospital of Southern Theater Command, Zhanjiang, 524000, China.
Zuowei WangHongkou Mental Health Center, Shanghai, 200083, China. wzwhk@163.com.
Yong JieHongkou Mental Health Center, Shanghai, 200083, China. jy96jw@163.com.
Xin DongSchool of Medicine, Shanghai University, Shanghai, 200444, China. dongxinsmmu@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSchizophrenia (SCZ) patients undergoing antipsychotic treatment demonstrated a high prevalence and harmful effects of metabolic syndrome (MetS), which acted as the major cause of cardiovascular disease. The major clinical challenge is the lack of biomarkers to identify MetS episodes and prevent further damage, while the mechanisms underlying these drug-induced MetS remain unknown.

methodsThis study divided 173 participants with SCZ into 3 groups (None, High risk, and MetS, consisting of 22, 88, and 63 participants, respectively). The potential biomarkers were searched based on 16S rRNA gene sequence together with metabolism analysis. Logistic regression was used to test the effects of the genus-metabolites panel on early MetS diagnoses.

resultsA genus-metabolites panel, consisting of Senegalimassilia, sphinganine, dihomo-gamma-linolenoylcholine, isodeoxycholic acid, and MG (0:0/22:5/0:0), which involved in sphigolipid metabolism, fatty acid metabolism, secondary bile acid biosynthesis and glycerolipid metabolism, has a great discrimination efficiency to MetS with an area under the curve (AUC) value of 0.911 compared to the None MetS group (P = 1.08E-8). Besides, Senegalimassilia, 3-Hydroxytetradecanoyl carnitine, isodeoxycholic acid, and DG(TXB2/0:0/2:0) distinguished between subgroups robustly and exhibited a potential correlation with the severity of MetS in patients with SCZ, and may act as the biomarkers for early MetS diagnosis.

conclusionsOur multi-omics study showed that one bacterial genus-five lipid metabolites panel is the potential risk factor for MetS in SCZ. Furthermore, Senegalimassilia, 3-Hydroxytetradecanoyl carnitine, isodeoxycholic acid, and DG(TXB2/0:0/2:0) could serve as novel diagnostic markers in the early stage. So, it is obvious that the combination of bacterial genus and metabolites yields excellent discriminatory power, and the lipid metabolism provide new understanding to the pathogenesis, prevention, and therapy for MetS in SCZ.

Indexed as

BiomarkersGastrointestinal MicrobiomeMetabolic SyndromeSchizophreniaAdultAntipsychotic AgentsFemaleHumansMaleMiddle AgedRNA, Ribosomal, 16SAntipsychotic AgentsBiomarkersRNA, Ribosomal, 16SBiomarkerMetabolic syndromeMulti–omicsSchizophrenia

Identifiers

PMID39048972
PMCPMC11267952

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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.