Evidence mapPaperPMID 39716136Full record

Trial reportBMC psychiatry2024

Identification of serum metabolic traits of AIWG in first-episode schizophrenia patients.

Suzhen Zhang, Zhaolin Zhai, Tianhao Gao, Xinping Kuai, Xuan Li, Yuke Dong, Chang Lu, Kaiming Zhuo, Qiong Xiang, Dengtang Liu

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in BMC psychiatry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
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

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Suzhen Zhang *Division of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Zhaolin Zhai *Division of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Tianhao GaoDivision of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Xinping KuaiDivision of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Xuan LiDivision of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yuke DongDivision of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Chang LuDivision of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Kaiming ZhuoDivision of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Qiong XiangDivision of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China. xiangqiongxl@126.com.
Dengtang LiuDivision of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China. liudengtang@smhc.org.cn.

Funding

Key Program of SMHC Clinical Research Center CRC2017ZD03Medical innovation research project of science and technology innovation action of Shanghai Science and Technology Commission 22Y11903400Multidisciplinary Cross Research Foundation of Shanghai Jiao Tong University YG2024QNA55National Natural Science Foundation of China 82171496
6 · The paper itself

Abstract

backgroundAntipsychotic-induced weight gain (AIWG) is a common side effect of antipsychotic drugs and may lead to cardiometabolic comorbidities. There is an urgent public health need to identify patients at high risk of AIWG and determine potential biomarkers for AIWG.

methodsIn the Sequential Multiple-Assignment Randomized Trials to Compare Antipsychotic Treatments (SMART-CAT) trail, first-episode schizophrenia patients were randomly assigned to olanzapine, risperidone, perphenazine, amisulpride or aripiprazole for 8 weeks. We applied absolute quantitative lipidomics at baseline and after 8 weeks of antipsychotic treatment in 80 patients. To evaluate the effects of AIWG on lipid profile, 25 patients with ≥ 7% weight changes (weight gain, WG) and 28 patients with <|3|% weight changes (weight stable, WS) were investigated, separately.

resultsWe found that baseline CerP(d40:3) and PC(20:1_22:6) were positively associated with weight changes at follow-up (r > 0.4, pFDR < 0.05). Additionally, baseline CerP(d40:3) and PC(20:1_22:6) independently predicted rapid weight gain, with receiver operating curve (ROC) of 0.76 (95% CI: 0.63-0.90), and 0.75 (95% CI: 0.62-0.88), respectively. Compared with baseline, levels of 45 differential lipid metabolites (fold change > 1.2, VIP > 1 and pFDR < 0.05) were significantly higher in the WG group. Interestingly, no differential lipid metabolites were identified in the WS group. The LASSO regression model identified 18 AIWG lipid signatures, including 2 cholesterol esters (ChEs), 1 diglyceride (DG), 12 phosphatidylcholines (PCs), 1 phosphatidylglycerol (PG), 1 phosphatidylinositol (PI), and 1 sphingomyelin (SM), with the ChE(16:1) contributing the most. Furthermore, the level changes of ChE(16:1) were positively associated with weight gain(r = 0.67, pFDR < 0.05).

conclusionOur findings indicate that lipid profile may serve as predictors of rapid weight gain in schizophrenia and provide useful markers for AIWG intervention.

Indexed as

BiomarkersSchizophreniaAdultAntipsychotic AgentsFemaleHumansLipidomicsLipidsMaleWeight GainYoung AdultAntipsychotic AgentsBiomarkersLipidsAntipsychoticLipidSchizophreniaWeight gain

Identifiers

PMID39716136
PMCPMC11667919

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.