Evidence map›Paper›PMID 27650680›Full record

Trial reportScientific reports2016

Discovery, screening and evaluation of a plasma biomarker panel for subjects with psychological suboptimal health state using (1)H-NMR-based metabolomics profiles.

Jun-Sheng Tian, Xiao-Tao Xia, Yan-Fei Wu, Lei Zhao, Huan Xiang, Guan-Hua Du, Xiang Zhang, Xue-Mei Qin

Abstract readClinical Trial
In one paragraph

Trial report in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

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

  1. Pooled it
  2. A chronic stress-induced microbiome perturbation, highly enriched inInternational journal of medical sciences · 2024
    Article
  3. Untargeted serum metabolomic profiling for early detection ofFrontiers in cellular and infection microbiology · 2022
    Article
  4. Review
  5. Article
  6. Article
  7. Title: Human Serum/Plasma Glycoprotein Analysis byJournal of clinical medicine · 2020
    Review
  8. Article
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  10. Review
  11. Review
  12. Article
  13. Article
  14. 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

8 authors.

Jun-Sheng TianModern Research Center for Traditional Chinese Medicine of Shanxi University, Taiyuan 030006, P. R. China.
Xiao-Tao XiaModern Research Center for Traditional Chinese Medicine of Shanxi University, Taiyuan 030006, P. R. China.
Yan-Fei WuDepartment of traditional Chinese medicine, First Hospital of Shanxi Medical University, Taiyuan 030001, P. R. China.
Lei ZhaoModern Research Center for Traditional Chinese Medicine of Shanxi University, Taiyuan 030006, P. R. China.
Huan XiangPhysical Education Departments of Shanxi University, Taiyuan 030006, P. R. China.
Guan-Hua DuInstitute of Materia Medica, Chinese Academy of Medical Sciences &Peking Union Medical College, Beijing 100050, P. R. China.
Xiang ZhangDepartment of Chemistry of University of Louisville, Louisville, KY40292 United States.
Xue-Mei QinModern Research Center for Traditional Chinese Medicine of Shanxi University, Taiyuan 030006, P. R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Individuals in the state of psychological suboptimal health keep increasing, only scales and questionnaires were used to diagnose in clinic under current conditions, and symptoms of high reliability and accuracy are destitute. Therefore, the noninvasive and precise laboratory diagnostic methods are needed. This study aimed to develop an objective method through screen potential biomarkers or a biomarker panel to facilitate the diagnosis in clinic using plasma metabolomics. Profiles were based on H-nuclear magnetic resonance ((1)H-NMR) metabolomics techniques combing with multivariate statistical analysis. Furthermore, methods of correlation analysis with Metaboanalyst 3.0 for selecting a biomarker panel, traditional Chinese medicine (TCM) drug intervention for validating the close relations between the biomarker panel and the state and the receiver operating characteristic curves (ROC curves) analysis for evaluation of clinical diagnosis ability were carried out. 9 endogenous metabolites containing trimethylamine oxide (TMAO), glutamine, N-acetyl-glycoproteins, citrate, tyrosine, phenylalanine, isoleucine, valine and glucose were identified and considered as potential biomarkers. Then a biomarker panel consisting of phenylalanine, glutamine, tyrosine, citrate, N-acetyl-glycoproteins and TMAO was selected, which exhibited the highest area under the curve (AUC = 0.971). This study provided critical insight into the pathological mechanism of psychological suboptimal health and would supply a novel and valuable diagnostic method.

Indexed as

AdultBiomarkersDrugs, Chinese HerbalFemaleHumansMaleMedicine, Chinese TraditionalMental DisordersMetabolomicsMiddle AgedNuclear Magnetic Resonance, BiomolecularBiomarkersDrugs, Chinese Herbal

Identifiers

PMID27650680
PMCPMC5030673

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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.