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The brain-derived neurotrophic factor Val66Met polymorphism increases segregation of structural correlation networks in healthy adult brains
http://hdl.handle.net/10228/00008099
http://hdl.handle.net/10228/0000809936040104-c43f-49f5-82ed-173c16123dd7
| 名前 / ファイル | ライセンス | アクション |
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peerj.9632.pdf (9.2 MB)
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| Item type | 学術雑誌論文 = Journal Article(1) | |||||||||||||
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| 公開日 | 2021-03-23 | |||||||||||||
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| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||||||
| 資源タイプ | journal article | |||||||||||||
| タイトル | ||||||||||||||
| タイトル | The brain-derived neurotrophic factor Val66Met polymorphism increases segregation of structural correlation networks in healthy adult brains | |||||||||||||
| 言語 | en | |||||||||||||
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| 言語 | eng | |||||||||||||
| 著者 |
Ueda, Issei
× Ueda, Issei× 竹本, 和広
WEKO
24877
× Watanabe, Keita× Sugimoto, Koichiro× Ikenouchi, Atsuko× Kakeda, Shingo× Katsuki, Asuka× Yoshimura, Reiji× Korogi, Yukunori |
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| 抄録 | ||||||||||||||
| 内容記述タイプ | Abstract | |||||||||||||
| 内容記述 | 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 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 The average local efficiency, a measure of network segregation, of BDNF Met carriers’ network was significantly higher than that of the Val homozygotes’ (permutation p-value = 0.002). Average shortest path lengths (a measure of integration), average local clustering coefficient (another measure of network segregation), small-worldness (a balance between integration and segregation), and modularity (a representative measure for modular architecture) were not significantly different between group (permutation p-values ≧ 0.01). / Discussion and Conclusion 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. | |||||||||||||
| 言語 | en | |||||||||||||
| 書誌情報 |
en : PeerJ 巻 8, p. e9632, 発行日 2020-08-05 |
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| 出版者 | PeerJ | |||||||||||||
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| 関連タイプ | isIdenticalTo | |||||||||||||
| 識別子タイプ | DOI | |||||||||||||
| 関連識別子 | https://doi.org/10.7717/peerj.9632 | |||||||||||||
| 日本十進分類法 | ||||||||||||||
| 主題Scheme | NDC | |||||||||||||
| 主題 | 491 | |||||||||||||
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| 収録物識別子タイプ | EISSN | |||||||||||||
| 収録物識別子 | 2167-8359 | |||||||||||||
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| 権利情報 | Copyright (c) 2020 Ueda et al. | |||||||||||||
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| 権利情報Resource | http://creativecommons.org/licenses/by/4.0/ | |||||||||||||
| 権利情報 | This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. | |||||||||||||
| キーワード | ||||||||||||||
| 主題Scheme | Other | |||||||||||||
| 主題 | BDNF | |||||||||||||
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| 主題Scheme | Other | |||||||||||||
| 主題 | Val66Met | |||||||||||||
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| 主題Scheme | Other | |||||||||||||
| 主題 | Network analysis | |||||||||||||
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| 主題Scheme | Other | |||||||||||||
| 主題 | Graph theory | |||||||||||||
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| 主題Scheme | Other | |||||||||||||
| 主題 | Structural covariance network | |||||||||||||
| キーワード | ||||||||||||||
| 主題Scheme | Other | |||||||||||||
| 主題 | Structural corrletation network | |||||||||||||
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| 主題Scheme | Other | |||||||||||||
| 主題 | Brain-derived neurotrophic factor | |||||||||||||
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| 主題Scheme | Other | |||||||||||||
| 主題 | Brain network | |||||||||||||
| 出版タイプ | ||||||||||||||
| 出版タイプ | VoR | |||||||||||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||||||||
| 査読の有無 | ||||||||||||||
| 値 | yes | |||||||||||||
| 研究者情報 | ||||||||||||||
| URL | https://hyokadb02.jimu.kyutech.ac.jp/html/100000509_ja.html | |||||||||||||
| 論文ID（連携） | ||||||||||||||
| 値 | 10358807 | |||||||||||||
| 連携ID | ||||||||||||||
| 値 | 8623 | |||||||||||||
