Evidence map›Paper›PMID 30386416›Full record

ArticleChinese medicine2018

Blood and urinary metabolomic evidence validating traditional Chinese medicine diagnostic classification of major depressive disorder.

Lan-Ying Liu, Hong-Jian Zhang, Li-Yuan Luo, Jin-Bao Pu, Wei-Qing Liang, Chun-Qin Zhu, Ya-Ping Li, Pei-Rong Wang, Yuan-Yuan Zhang, Chun-Yu Yang and 1 more

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Chinese medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02346682 (Neurochemical,Metabonomics and Neuroimaging Characterization of TCM Diagnostic Subtypes of Major Depression Disorder), which is not on this map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 20% 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.

NCT02346682 phase4unknown statusnot on this map

Neurochemical,Metabonomics and Neuroimaging Characterization of TCM Diagnostic Subtypes of Major Depression Disorder

TypeinterventionalSponsorZhejiang Provincial Tongde HospitalRan2015 to 2017Enrolled75ConditionsSevere Major Depression DisorderArmsvenlafaxine
3 · Its place in the literature

Who cites it

20 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.

  1. Pooled it
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  12. Clinical efficacy ofAmerican journal of translational research · 2021
    Article
  13. Metabolomic Biomarkers in Anxiety Disorders.International journal of molecular sciences · 2020
    Review
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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

11 authors at 2 institutions in 2 countries.

Lan-Ying Liu1Department of Psychiatry, Tongde Hospital of Zhejiang Province, Hangzhou, 310012 Zhejiang China.
Hong-Jian Zhang2Zhejiang Academy of Traditional Chinese Medicine, Hangzhou, 310007 Zhejiang China.
Li-Yuan Luo1Department of Psychiatry, Tongde Hospital of Zhejiang Province, Hangzhou, 310012 Zhejiang China.
Jin-Bao Pu2Zhejiang Academy of Traditional Chinese Medicine, Hangzhou, 310007 Zhejiang China.
Wei-Qing Liang2Zhejiang Academy of Traditional Chinese Medicine, Hangzhou, 310007 Zhejiang China.
Chun-Qin Zhu1Department of Psychiatry, Tongde Hospital of Zhejiang Province, Hangzhou, 310012 Zhejiang China.
Ya-Ping Li3Department of Internal Chinese Medicine, Tongde Hospital of Zhejiang Province, Hangzhou, 310012 Zhejiang China.
Pei-Rong Wang1Department of Psychiatry, Tongde Hospital of Zhejiang Province, Hangzhou, 310012 Zhejiang China.
Yuan-Yuan Zhang1Department of Psychiatry, Tongde Hospital of Zhejiang Province, Hangzhou, 310012 Zhejiang China.
Chun-Yu Yang1Department of Psychiatry, Tongde Hospital of Zhejiang Province, Hangzhou, 310012 Zhejiang China.
Zhang-Jin Zhang4School of Chinese Medicine, LKS Faculty of Medicine, The University of Hong Kong, 10 Sassoon Road, Pokfulam, Hong Kong, China.
Tongde Hospital of Zhejiang Province · CNUniversity of Hong Kong · HK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMajor depressive disorder (MDD) is a highly heterogeneous disease. Further classification may characterize its heterogeneity. The purpose of this study was to examine whether metabolomic variables could differentiate traditional Chinese medicine (TCM) diagnostic subtypes of MDD.

methodsFifty medication-free patients who were experiencing a recurrent depressive episode were classified into Liver Qi Stagnation (LQS, n = 30) and Heart and Spleen Deficiency (HSD, n = 20) subtypes according to TCM diagnosis. Healthy volunteers (n = 28) were included as controls. Gas chromatography-mass spectrometry (GC-MS) was used to examine serum and urinary metabolomic profiles.

resultsTwenty-eight metabolites were identified for good separations between TCM subtypes and healthy controls in serum samples. Both TCM subtypes had similar profiles in proteinogenic branched-chain amino acids (BCAAs) (valine, leucine, and isoleucine) and energy metabolism-related metabolites that were differentiated from healthy controls. The LQS subtype additionally differed from healthy controls in multiple amino acid metabolites that are involved in biosynthesis of monoamine and amino acid neurotransmitters, including phenylalanine, 3-hydroxybutric acid,

conclusionsWhile both TCM subtypes are associated with aberrant BCAA and energy metabolism, the LQS subtype may represent an MDD subpopulation characterized by abnormalities in the biosynthesis of monoamine and amino acid neurotransmitters and closer associations with stress-related pathophysiology. The metabolites differentially associated with the two subtypes are promising biomarkers for predicting TCM subtype-specific antidepressant response [registered at http://www.clinicaltrials.gov (NCT02346682) on January 27, 2015].

Indexed as

ClassificationMajor depressive disorderMetabolomicsTraditional Chinese medicine

Identifiers

PMID30386416
PMCPMC6203264
OpenAlexW2898213268

What OpenQuestion holds

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Registered trials

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.