Cargando…

Brain structural networks and connectomes: the brain–obesity interface and its impact on mental health

PURPOSE: Obesity is a complex and multifactorial disease identified as a global epidemic. Convergent evidence indicates that obesity differentially influences patients with neuropsychiatric disorders providing a basis for hypothesizing that obesity alters brain structure and function associated with...

Descripción completa

Detalles Bibliográficos
Autores principales: Chen, Vincent Chin-Hung, Liu, Yi-Chun, Chao, Seh-Huang, McIntyre, Roger S, Cha, Danielle S, Lee, Yena, Weng, Jun-Cheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6263220/
https://www.ncbi.nlm.nih.gov/pubmed/30538478
http://dx.doi.org/10.2147/NDT.S180569
_version_ 1783375248723279872
author Chen, Vincent Chin-Hung
Liu, Yi-Chun
Chao, Seh-Huang
McIntyre, Roger S
Cha, Danielle S
Lee, Yena
Weng, Jun-Cheng
author_facet Chen, Vincent Chin-Hung
Liu, Yi-Chun
Chao, Seh-Huang
McIntyre, Roger S
Cha, Danielle S
Lee, Yena
Weng, Jun-Cheng
author_sort Chen, Vincent Chin-Hung
collection PubMed
description PURPOSE: Obesity is a complex and multifactorial disease identified as a global epidemic. Convergent evidence indicates that obesity differentially influences patients with neuropsychiatric disorders providing a basis for hypothesizing that obesity alters brain structure and function associated with the brain’s propensity toward disturbances in mood and cognition. Herein, we characterize alterations in brain structures and networks among obese subjects (ie, body mass index [BMI] ≥30 kg/m(2)) when compared with non-obese controls. PATIENTS AND METHODS: We obtained noninvasive diffusion tensor imaging and generalized q-sampling imaging scans of 20 obese subjects (BMI=37.9±5.2 SD) and 30 non-obese controls (BMI=22.6±3.4 SD). Graph theoretical analysis and network-based statistical analysis were performed to assess structural and functional differences between groups. We additionally assessed for correlations between diffusion indices, BMI, and anxiety and depressive symptom severity (ie, Hospital Anxiety and Depression Scale total score). RESULTS: The diffusion indices of the posterior limb of the internal capsule, corona radiata, and superior longitudinal fasciculus were significantly lower among obese subjects when compared with controls. Moreover, obese subjects were more likely to report anxiety and depressive symptoms. There were fewer structural network connections observed in obese subjects compared with non-obese controls. Topological measures of clustering coefficient (C), local efficiency (E(local)), global efficiency (E(global)), and transitivity were significantly lower among obese subjects. Similarly, three sub-networks were identified to have decreased structural connectivity among frontal–temporal regions in obese subjects compared with non-obese controls. CONCLUSION: We extend knowledge further by delineating structural interconnectivity alterations within and across brain regions that are adversely affected in individuals who are obese.
format Online
Article
Text
id pubmed-6263220
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher Dove Medical Press
record_format MEDLINE/PubMed
spelling pubmed-62632202018-12-11 Brain structural networks and connectomes: the brain–obesity interface and its impact on mental health Chen, Vincent Chin-Hung Liu, Yi-Chun Chao, Seh-Huang McIntyre, Roger S Cha, Danielle S Lee, Yena Weng, Jun-Cheng Neuropsychiatr Dis Treat Original Research PURPOSE: Obesity is a complex and multifactorial disease identified as a global epidemic. Convergent evidence indicates that obesity differentially influences patients with neuropsychiatric disorders providing a basis for hypothesizing that obesity alters brain structure and function associated with the brain’s propensity toward disturbances in mood and cognition. Herein, we characterize alterations in brain structures and networks among obese subjects (ie, body mass index [BMI] ≥30 kg/m(2)) when compared with non-obese controls. PATIENTS AND METHODS: We obtained noninvasive diffusion tensor imaging and generalized q-sampling imaging scans of 20 obese subjects (BMI=37.9±5.2 SD) and 30 non-obese controls (BMI=22.6±3.4 SD). Graph theoretical analysis and network-based statistical analysis were performed to assess structural and functional differences between groups. We additionally assessed for correlations between diffusion indices, BMI, and anxiety and depressive symptom severity (ie, Hospital Anxiety and Depression Scale total score). RESULTS: The diffusion indices of the posterior limb of the internal capsule, corona radiata, and superior longitudinal fasciculus were significantly lower among obese subjects when compared with controls. Moreover, obese subjects were more likely to report anxiety and depressive symptoms. There were fewer structural network connections observed in obese subjects compared with non-obese controls. Topological measures of clustering coefficient (C), local efficiency (E(local)), global efficiency (E(global)), and transitivity were significantly lower among obese subjects. Similarly, three sub-networks were identified to have decreased structural connectivity among frontal–temporal regions in obese subjects compared with non-obese controls. CONCLUSION: We extend knowledge further by delineating structural interconnectivity alterations within and across brain regions that are adversely affected in individuals who are obese. Dove Medical Press 2018-11-26 /pmc/articles/PMC6263220/ /pubmed/30538478 http://dx.doi.org/10.2147/NDT.S180569 Text en © 2018 Chen et al. This work is published and licensed by Dove Medical Press Limited The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.
spellingShingle Original Research
Chen, Vincent Chin-Hung
Liu, Yi-Chun
Chao, Seh-Huang
McIntyre, Roger S
Cha, Danielle S
Lee, Yena
Weng, Jun-Cheng
Brain structural networks and connectomes: the brain–obesity interface and its impact on mental health
title Brain structural networks and connectomes: the brain–obesity interface and its impact on mental health
title_full Brain structural networks and connectomes: the brain–obesity interface and its impact on mental health
title_fullStr Brain structural networks and connectomes: the brain–obesity interface and its impact on mental health
title_full_unstemmed Brain structural networks and connectomes: the brain–obesity interface and its impact on mental health
title_short Brain structural networks and connectomes: the brain–obesity interface and its impact on mental health
title_sort brain structural networks and connectomes: the brain–obesity interface and its impact on mental health
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6263220/
https://www.ncbi.nlm.nih.gov/pubmed/30538478
http://dx.doi.org/10.2147/NDT.S180569
work_keys_str_mv AT chenvincentchinhung brainstructuralnetworksandconnectomesthebrainobesityinterfaceanditsimpactonmentalhealth
AT liuyichun brainstructuralnetworksandconnectomesthebrainobesityinterfaceanditsimpactonmentalhealth
AT chaosehhuang brainstructuralnetworksandconnectomesthebrainobesityinterfaceanditsimpactonmentalhealth
AT mcintyrerogers brainstructuralnetworksandconnectomesthebrainobesityinterfaceanditsimpactonmentalhealth
AT chadanielles brainstructuralnetworksandconnectomesthebrainobesityinterfaceanditsimpactonmentalhealth
AT leeyena brainstructuralnetworksandconnectomesthebrainobesityinterfaceanditsimpactonmentalhealth
AT wengjuncheng brainstructuralnetworksandconnectomesthebrainobesityinterfaceanditsimpactonmentalhealth