Evidence map›Paper›PMID 24949867›Full record

SynthesisJournal of psychiatry & neuroscience : JPN2014

Brain grey matter volume alterations in late-life depression.

Mingying Du, Jia Liu, Ziqi Chen, Xiaoqi Huang, Jing Li, Weihong Kuang, Yanchun Yang, Wei Zhang, Dong Zhou, Feng Bi and 2 more

Abstract readMeta-AnalysisReview
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Journal of psychiatry & neuroscience : JPN, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 82 papers, 21 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
82citing papers in PubMed, 21 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

82 citing papers in PubMed, 21 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Pooled it
  7. Pooled it
  8. Pooled it
  9. Pooled it
  10. Pooled it
  11. Pooled it
  12. Pooled it
  13. Pooled it
  14. Pooled it
  15. Pooled it
  16. Pooled it
  17. Pooled it
  18. Pooled it
  19. Pooled it
  20. Pooled it

22 more citing papers are in PubMed but not listed here.

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

12 authors.

Mingying DuHuaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.
Jia LiuHuaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.
Ziqi ChenHuaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.
Xiaoqi HuangHuaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.
Jing LiThe Department of Psychiatry, West China Hospital of Sichuan University, Chengdu, China.
Weihong KuangThe Department of Psychiatry, West China Hospital of Sichuan University, Chengdu, China.
Yanchun YangThe Department of Psychiatry, West China Hospital of Sichuan University, Chengdu, China.
Wei ZhangThe Department of Psychiatry, West China Hospital of Sichuan University, Chengdu, China.
Dong ZhouThe Department of Neurology, West China Hospital of Sichuan University, Chengdu, China.
Feng BiThe Department of Oncology, State Key Lab of Biotherapy, West China Hospital of Sichuan University, Chengdu, China.
Keith M KendrickKey Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
Qiyong GongHuaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundVoxel-based morphometry (VBM) studies have demonstrated that grey matter abnormalities are involved in the pathophysiology of late-life depression (LLD), but the findings are inconsistent and have not been quantitatively reviewed. The aim of the present study was to conduct a meta-analysis that integrated the reported VBM studies, to determine consistent grey matter alterations in individuals with LLD.

methodsA systematic search was conducted to identify VBM studies that compared patients with LLD and healthy controls. We performed a meta-analysis using the effect size signed differential mapping method to quantitatively estimate regional grey matter abnormalities in patients with LLD.

resultsWe included 9 studies with 11 data sets comprising 292 patients with LLD and 278 healthy controls in our meta-analysis. The pooled and subgroup meta-analyses showed robust grey matter reductions in the right lentiform nucleus extending into the parahippocampus, the hippocampus and the amygdala, the bilateral medial frontal gyrus and the right subcallosal gyrus as well as a grey matter increase in the right lingual gyrus. Meta-regression analyses showed that mean age and the percentage of female patients with LLD were not significantly related to grey matter changes. LIMITATIONS: The analysis techniques, patient characteristics and clinical variables of the studies included were heterogeneous, and most participants were medicated.

conclusionThe present meta-analysis is, to our knowledge, the first to overcome previous inconsistencies in the VBM studies of LLD and provide robust evidence for grey matter alterations within fronto-striatal-limbic networks, thereby implicating them in the pathophysiology of LLD. The mean age and the percentage of female patients with LLD did not appear to have a measurable impact on grey matter changes, although we cannot rule out the contributory effects of medication.

Indexed as

AgedBrainDepressive DisorderGray MatterHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingOrgan SizeRegression Analysis

Identifiers

PMID24949867
PMCPMC4214874

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.