Evidence map›Paper›PMID 30519998›Full record

ArticleBrain imaging and behavior2020

Morphological changes in subregions of hippocampus and amygdala in major depressive disorder patients.

Zhijun Yao, Yu Fu, Jianfeng Wu, Wenwen Zhang, Yue Yu, Zicheng Zhang, Xia Wu, Yalin Wang, Bin Hu

Open access · greenAbstract read
In one paragraph

Article in Brain imaging and behavior, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
2.8field-weighted citation impact, top 9% 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

36 citing papers in PubMed, 85 citations in OpenAlex.

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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

9 authors at 4 institutions in 2 countries.

Zhijun YaoSchool of Information Science and Engineering, Lanzhou University, P.O. Box 730000, Lanzhou, China.
Yu FuSchool of Information Science and Engineering, Lanzhou University, P.O. Box 730000, Lanzhou, China.
Jianfeng WuSchool of Computing, Informatics, and Decision Systems Engineering, Arizona State University, P.O. Box 878809, Tempe, AZ, 85287, USA.
Wenwen ZhangDepartment of Radiology, Gansu Provincial Hospital, Lanzhou, China.
Yue YuSchool of Information Science and Engineering, Lanzhou University, P.O. Box 730000, Lanzhou, China.
Zicheng ZhangSchool of Information Science and Engineering, Lanzhou University, P.O. Box 730000, Lanzhou, China.
Xia WuState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China. wuxia@bnu.edu.cn.
Yalin WangSchool of Computing, Informatics, and Decision Systems Engineering, Arizona State University, P.O. Box 878809, Tempe, AZ, 85287, USA. ylwang@asu.edu.
Bin HuSchool of Information Science and Engineering, Lanzhou University, P.O. Box 730000, Lanzhou, China. bh@lzu.edu.cn.ORCID http://orcid.org/0000-0003-3514-5413
Lanzhou University · CNDecision Systems (United States) · USBeijing Normal University · CNGansu Provincial Hospital · CN

Funding

Multi-Source Sparse Learning to Identify MCI and Predict DeclineRF1AG051710 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI THOMPSON, PAUL M, WANG, YALIN · 2016 to 2016
$2.8M
National Natural Science Foundation of China No.61210010National Natural Science Foundation of China No.61571047National Natural Science Foundation of China No.61632014NIA NIH HHS RF1 AG051710the Fundamental Research Funds for the Central Universities lzujbky-2017-kb08the National Basic Research Program of China (973 Program) No.2014CB744600the National Key Research and Development Program of China No.2016YFC1307203the Program of Beijing Municipal Science & Technology Commission No.Z17110000011700the Program of International S&T Cooperation of MOST No.2013DFA11140
6 · The paper itself

Abstract

Despite many neuroimaging studies in the past years, the neuroanatomical substrates of major depressive disorder (MDD) subcortical structures are still not well understood. Since hippocampus and amygdala are the two vital subcortical structures that most susceptible to MDD, finding the evidence of morphological changes in their subregions may bring some new insights for MDD research. Combining structural magnetic resonance imaging (MRI) with novel morphometry analysis methods, we recruited 25 MDD patients and 28 healthy controls (HC), and investigated their volume and morphological differences in hippocampus and amygdala. Relative to volumetric method, our methods detected more significant global morphological atrophies (p<0.05). More precisely, subiculum and cornu ammonis (CA) 1 subregions of bilateral hippocampus, lateral (LA) and basolateral ventromedial (BLVM) of left amygdala and LA, BLVM, central (CE), amygdalostriatal transition area (ASTR), anterior cortical (ACO) and anterior amygdaloid area (AAA) of right amygdala were demonstrated prone to atrophy. Correlation analyses between each subject's surface eigenvalues and Hamilton Depression Scale (HAMD) were then performed. Correlation results showed that atrophy areas in hippocampus and amygdala have slight tendencies of expanding into other subregions with the development of MDD. Finally, we performed group morphometric analysis and drew the atrophy and expansion areas between MDD-Medicated group (only 19 medicated subjects in MDD group were included) and HC group, found some preliminary evidence about subregional morphological resilience of hippocampus and amygdala. These findings revealed new pathophysiologic patterns in the subregions of hippocampus and amygdala, which can help with subsequent smaller-scale MDD research.

Indexed as

Major Depressive DisorderAmygdalaAtrophyHippocampusHumansMagnetic Resonance ImagingAmygdalaHippocampusMajor depressive disorderMorphometrySubcortical structures

Identifiers

PMID30519998
PMCPMC6551316
OpenAlexW2903364434

What Socratic holds

Textmetadata
LicenceTDM
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.