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

BDNF Brain network Brain-derived neurotrophic factor Graph theory Network analysis Structural corrletation network Structural covariance network Val66Met

Journal

PeerJ
ISSN: 2167-8359
Titre abrégé: PeerJ
Pays: United States
ID NLM: 101603425

Informations de publication

Date de publication:
2020
Historique:
received: 30 04 2020
accepted: 09 07 2020
entrez: 27 8 2020
pubmed: 28 8 2020
medline: 28 8 2020
Statut: epublish

Résumé

Although 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. Forty-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. The average local efficiency, a measure of network segregation, of BDNF Met carriers' network was significantly higher than that of the Val homozygotes' (permutation Our 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.

Sections du résumé

BACKGROUND BACKGROUND
Although 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.
METHODS METHODS
Forty-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.
RESULTS RESULTS
The 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 CONCLUSION CONCLUSIONS
Our 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.

Identifiants

pubmed: 32844059
doi: 10.7717/peerj.9632
pii: 9632
pmc: PMC7414771
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e9632

Informations de copyright

©2020 Ueda et al.

Déclaration de conflit d'intérêts

The authors declare there are no competing interests.

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Auteurs

Issei Ueda (I)

Department of Radiology, University of Occupational and Environmental Health, Kitakyusyu, Japan.

Kazuhiro Takemoto (K)

Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, Iizuka, Japan.

Keita Watanabe (K)

Department of Radiology, University of Occupational and Environmental Health, Kitakyusyu, Japan.

Koichiro Sugimoto (K)

Department of Radiology, University of Occupational and Environmental Health, Kitakyusyu, Japan.

Atsuko Ikenouchi (A)

Department of Psychiatry, University of Occupational and Environmental Health, Kitakyusyu, Japan.

Shingo Kakeda (S)

Department of Radiology, University of Occupational and Environmental Health, Kitakyusyu, Japan.

Asuka Katsuki (A)

Department of Psychiatry, University of Occupational and Environmental Health, Kitakyusyu, Japan.

Reiji Yoshimura (R)

Department of Psychiatry, University of Occupational and Environmental Health, Kitakyusyu, Japan.

Yukunori Korogi (Y)

Department of Radiology, University of Occupational and Environmental Health, Kitakyusyu, Japan.

Classifications MeSH