Evidence map›Paper›PMID 32844059›Full record

ArticlePeerJ2020

The brain-derived neurotrophic factor Val66Met polymorphism increases segregation of structural correlation networks in healthy adult brains.

Issei Ueda, Kazuhiro Takemoto, Keita Watanabe, Koichiro Sugimoto, Atsuko Ikenouchi, Shingo Kakeda, Asuka Katsuki, Reiji Yoshimura, Yukunori Korogi

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PeerJ, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.6field-weighted citation impact, top 36% 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

4 citing papers in PubMed, 6 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 2 institutions in 1 country.

Issei UedaDepartment of Radiology, University of Occupational and Environmental Health, Kitakyusyu, Japan.
Kazuhiro TakemotoDepartment of Bioscience and Bioinformatics, Kyushu Institute of Technology, Iizuka, Japan.
Keita WatanabeDepartment of Radiology, University of Occupational and Environmental Health, Kitakyusyu, Japan.
Koichiro SugimotoDepartment of Radiology, University of Occupational and Environmental Health, Kitakyusyu, Japan.
Atsuko IkenouchiDepartment of Psychiatry, University of Occupational and Environmental Health, Kitakyusyu, Japan.
Shingo KakedaDepartment of Radiology, University of Occupational and Environmental Health, Kitakyusyu, Japan.
Asuka KatsukiDepartment of Psychiatry, University of Occupational and Environmental Health, Kitakyusyu, Japan.
Reiji YoshimuraDepartment of Psychiatry, University of Occupational and Environmental Health, Kitakyusyu, Japan.
Yukunori KorogiDepartment of Radiology, University of Occupational and Environmental Health, Kitakyusyu, Japan.
University of Occupational and Environmental Health Japan · JPKyushu Institute of Technology · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough structural correlation network (SCN) analysis is an approach to evaluate brain networks, the neurobiological interpretation of SCNs is still problematic. Brain-derived neurotrophic factor (BDNF) is well-established as a representative protein related to neuronal differentiation, maturation, and survival. Since a valine-to-methionine substitution at codon 66 of the BDNF gene (BDNF Val66Met single nucleotide polymorphism (SNP)) is well-known to have effects on brain structure and function, we hypothesized that SCNs are affected by the BDNF Val66Met SNP. To gain insight into SCN analysis, we investigated potential differences between BDNF valine (Val) homozygotes and methionine (Met) carriers in the organization of their SCNs derived from inter-regional cortical thickness correlations.

methodsForty-nine healthy adult subjects (mean age = 41.1 years old) were divided into two groups according to their genotype (n: Val homozygotes = 16, Met carriers = 33). We obtained regional cortical thickness from their brain T1 weighted images. Based on the inter-regional cortical thickness correlations, we generated SCNs and used graph theoretical measures to assess differences between the two groups in terms of network integration, segregation, and modularity.

resultsThe average local efficiency, a measure of network segregation, of BDNF Met carriers' network was significantly higher than that of the Val homozygotes' (permutation DISCUSSION AND

conclusionOur results suggest that the BDNF Val66Met polymorphism may potentially influence the pattern of brain regional morphometric (cortical thickness) correlations. Comparing networks derived from inter-regional cortical thickness correlations, Met carrier SCNs have denser connections with neighbors and are more distant from random networks than Val homozygote networks. Thus, it may be necessary to consider potential effects of BDNF gene mutations in SCN analyses. This is the first study to demonstrate a difference between Val homozygotes and Met carriers in brain SCNs.

Indexed as

BDNFBrain-derived neurotrophic factorBrain networkGraph theoryNetwork analysisStructural corrletation networkStructural covariance networkVal66Met

Identifiers

PMID32844059
PMCPMC7414771
OpenAlexW3047377520

What OpenQuestion holds

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LicenceCC BY
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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.