Evidence map›Paper›PMID 31062333›Full record

ArticleNeuroscience bulletin2019

White Matter Abnormalities in Major Depression Biotypes Identified by Diffusion Tensor Imaging.

Sugai Liang, Qiang Wang, Xiangzhen Kong, Wei Deng, Xiao Yang, Xiaojing Li, Zhong Zhang, Jian Zhang, Chengcheng Zhang, Xin-Min Li and 4 more

Abstract read
In one paragraph

Article in Neuroscience bulletin, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

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

  1. Pooled it
  2. Trial
  3. Review
  4. Article
  5. Article
  6. Article
  7. Demyelination in Patients with POST-COVID Depression.Journal of clinical medicine · 2024
    Article
  8. Review
  9. Article
  10. Review
  11. Review
  12. Article
  13. Article
  14. Article
  15. Review
  16. Review
  17. Article
  18. Article
  19. Review
  20. 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

14 authors.

Sugai LiangMental Health Centre, West China Hospital, Sichuan University, Chengdu, 610041, China.
Qiang WangMental Health Centre, West China Hospital, Sichuan University, Chengdu, 610041, China.
Xiangzhen KongLanguage and Genetics Department, Max Planck Institute for Psycholinguistics, 6525 XD, Nijmegen, Netherlands.
Wei DengMental Health Centre, West China Hospital, Sichuan University, Chengdu, 610041, China.
Xiao YangMental Health Centre, West China Hospital, Sichuan University, Chengdu, 610041, China.
Xiaojing LiMental Health Centre, West China Hospital, Sichuan University, Chengdu, 610041, China.
Zhong ZhangBig Data Research Center, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China.
Jian ZhangMental Health Centre, West China Hospital, Sichuan University, Chengdu, 610041, China.
Chengcheng ZhangMental Health Centre, West China Hospital, Sichuan University, Chengdu, 610041, China.
Xin-Min LiDepartment of Psychiatry, University of Alberta, Edmonton, T6G 2B7, Canada.
Xiaohong MaMental Health Centre, West China Hospital, Sichuan University, Chengdu, 610041, China.
Junming ShaoBig Data Research Center, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China.
Andrew J GreenshawDepartment of Psychiatry, University of Alberta, Edmonton, T6G 2B7, Canada.
Tao LiMental Health Centre, West China Hospital, Sichuan University, Chengdu, 610041, China. xuntao26@hotmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identifying data-driven biotypes of major depressive disorder (MDD) has promise for the clarification of diagnostic heterogeneity. However, few studies have focused on white-matter abnormalities for MDD subtyping. This study included 116 patients with MDD and 118 demographically-matched healthy controls assessed by diffusion tensor imaging and neurocognitive evaluation. Hierarchical clustering was applied to the major fiber tracts, in conjunction with tract-based spatial statistics, to reveal white-matter alterations associated with MDD. Clinical and neurocognitive differences were compared between identified subgroups and healthy controls. With fractional anisotropy extracted from 20 fiber tracts, cluster analysis revealed 3 subgroups based on the patterns of abnormalities. Patients in each subgroup versus healthy controls showed a stepwise pattern of white-matter alterations as follows: subgroup 1 (25.9% of patient sample), widespread white-matter disruption; subgroup 2 (43.1% of patient sample), intermediate and more localized abnormalities in aspects of the corpus callosum and left cingulate; and subgroup 3 (31.0% of patient sample), possible mild alterations, but no statistically significant tract disruption after controlling for family-wise error. The neurocognitive impairment in each subgroup accompanied the white-matter alterations: subgroup 1, deficits in sustained attention and delayed memory; subgroup 2, dysfunction in delayed memory; and subgroup 3, no significant deficits. Three subtypes of white-matter abnormality exist in individuals with major depression, those having widespread abnormalities suffering more neurocognitive impairments, which may provide evidence for parsing the heterogeneity of the disorder and help optimize type-specific treatment approaches.

Indexed as

AdolescentAdultCross-Sectional StudiesDiffusion Tensor ImagingGyrus CinguliHumansMajor Depressive DisorderMental Status and Dementia TestsMiddle AgedWhite MatterYoung AdultBiotypeDiffusion tensor imagingHeterogeneityHierarchal clusteringMajor depressive disorder

Identifiers

PMID31062333
PMCPMC6754492

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.