Evidence map›Paper›PMID 36204590›Full record

ArticleMedComm2022

Systematic metabolic characterization of mental disorders reveals age-related metabolic disturbances as potential risk factors for depression in older adults.

Yu Liu, Wanyu Zhao, Ying Lu, Yunli Zhao, Yan Zhang, Miao Dai, Shan Hai, Ning Ge, Shuting Zhang, Mingjin Huang and 7 more

Open access · goldAbstract read
In one paragraph

Article in MedComm, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.6field-weighted citation impact, top 43% 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

4 citing papers in PubMed, 9 citations in OpenAlex.

  1. Review
  2. Article
  3. Lactate: A Theranostic Biomarker for Metabolic Psychiatry?Antioxidants (Basel, Switzerland) · 2023
    Review
  4. 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

17 authors at 5 institutions in 2 countries.

Yu LiuNational Clinical Research Center for Geriatrics and Department of General Practice State Key Laboratory of Biotherapy West China Hospital Sichuan University Chengdu China.
Wanyu ZhaoNational Clinical Research Center for Geriatrics and Department of General Practice State Key Laboratory of Biotherapy West China Hospital Sichuan University Chengdu China.
Ying LuNational Clinical Research Center for Geriatrics and Department of General Practice State Key Laboratory of Biotherapy West China Hospital Sichuan University Chengdu China.
Yunli ZhaoDepartment of Health Research Methods, Evidence, and Impact McMaster University Hamilton Ontario Canada.
Yan ZhangNational Clinical Research Center for Geriatrics and Department of General Practice State Key Laboratory of Biotherapy West China Hospital Sichuan University Chengdu China.
Miao DaiNational Clinical Research Center for Geriatrics and Department of General Practice State Key Laboratory of Biotherapy West China Hospital Sichuan University Chengdu China.
Shan HaiNational Clinical Research Center for Geriatrics and Department of General Practice State Key Laboratory of Biotherapy West China Hospital Sichuan University Chengdu China.
Ning GeNational Clinical Research Center for Geriatrics and Department of General Practice State Key Laboratory of Biotherapy West China Hospital Sichuan University Chengdu China.
Shuting ZhangDepartment of Neurology, West China Hospital Sichuan University Chengdu China.
Mingjin HuangThe Third Hospital of Mianyang Sichuan Mental Health Center Mianyang China.
Xiaohui LiuSchool of Life Sciences Tsinghua University Beijing China.
Shuangqing LiNational Clinical Research Center for Geriatrics and Department of General Practice State Key Laboratory of Biotherapy West China Hospital Sichuan University Chengdu China.
Jirong YueNational Clinical Research Center for Geriatrics and Department of General Practice State Key Laboratory of Biotherapy West China Hospital Sichuan University Chengdu China.
Peng LeiNational Clinical Research Center for Geriatrics and Department of General Practice State Key Laboratory of Biotherapy West China Hospital Sichuan University Chengdu China.
Biao DongNational Clinical Research Center for Geriatrics and Department of General Practice State Key Laboratory of Biotherapy West China Hospital Sichuan University Chengdu China.
Lunzhi DaiNational Clinical Research Center for Geriatrics and Department of General Practice State Key Laboratory of Biotherapy West China Hospital Sichuan University Chengdu China.
Birong DongNational Clinical Research Center for Geriatrics and Department of General Practice State Key Laboratory of Biotherapy West China Hospital Sichuan University Chengdu China.
Sichuan University · CNState Key Laboratory of BiotherapyImpact · CAMianyang Third People's Hospital · CNTsinghua University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mental disorders are associated with dysregulated metabolism, but comprehensive investigations of their metabolic similarities and differences and their clinical relevance are few. Here, based on the plasma metabolome and lipidome of subcohort1, comprising 100 healthy participants, 55 cases with anxiety, 52 persons with depression, and 41 individuals with comorbidity, which are from WCHAT, a perspective cohort study of community-dwelling older adults aged over 50, multiple metabolites as potential risk factors of mental disorders were identified. Furthermore, participants with mental illnesses were classified into three subtypes (S1, S2, and S3) by unsupervised classification with lipidomic data. Among them, S1 showed higher triacylglycerol and lower sphingomyelin, while S2 displayed opposite features. The metabolic profile of S3 was like that of the normal group. Compared with S3, individuals in S1 and S2 had worse quality of life, and suffered more from sleep and cognitive disorders. Notably, an assessment of 6,467 individuals from the WCHAT showed an age-related increase in the incidence of depression. Seventeen depression-related metabolites were significantly correlated with age, which were validated in an independent subcohort2. Collectively, this work highlights the clinical relevance of metabolic perturbation in mental disorders, and age-related metabolic disturbances may be a bridge-linking aging and depressive.

Indexed as

aginglipidomicsmental illnessmetabolomicsmolecular classification

Identifiers

PMID36204590
PMCPMC9523679
OpenAlexW4298142737

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.