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Abnormal degree centrality in first-episode medication-free adolescent depression at rest: A functional magnetic resonance imaging study and support vector machine analysis
BACKGROUND: Depression in adolescents is more heterogeneous and less often diagnosed than depression in adults. At present, reliable approaches to differentiating between adolescents who are and are not affected by depression are lacking. This study was designed to assess voxel-level whole-brain fun...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9556654/ https://www.ncbi.nlm.nih.gov/pubmed/36245889 http://dx.doi.org/10.3389/fpsyt.2022.926292 |
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author | Guo, Xin Wang, Wei Kang, Lijun Shu, Chang Bai, Hanpin Tu, Ning Bu, Lihong Gao, Yujun Wang, Gaohua Liu, Zhongchun |
author_facet | Guo, Xin Wang, Wei Kang, Lijun Shu, Chang Bai, Hanpin Tu, Ning Bu, Lihong Gao, Yujun Wang, Gaohua Liu, Zhongchun |
author_sort | Guo, Xin |
collection | PubMed |
description | BACKGROUND: Depression in adolescents is more heterogeneous and less often diagnosed than depression in adults. At present, reliable approaches to differentiating between adolescents who are and are not affected by depression are lacking. This study was designed to assess voxel-level whole-brain functional connectivity changes associated with adolescent depression in an effort to define an imaging-based biomarker associated with this condition. MATERIALS AND METHODS: In total, 71 adolescents affected by major depressive disorder (MDD) and 71 age-, sex-, and education level-matched healthy controls were subjected to resting-state functional magnetic resonance imaging (rs-fMRI) based analyses of brain voxel-wise degree centrality (DC), with a support vector machine (SVM) being used for pattern classification analyses. RESULTS: DC patterns derived from 16-min rs-fMRI analyses were able to effectively differentiate between adolescent MDD patients and healthy controls with 95.1% accuracy (136/143), and with respective sensitivity and specificity values of 92.1% (70/76) and 98.5% (66/67) based upon DC abnormalities detected in the right cerebellum. Specifically, increased DC was evident in the bilateral insula and left lingual area of MDD patients, together with reductions in the DC values in the right cerebellum and bilateral superior parietal lobe. DC values were not significantly correlated with disease severity or duration in these patients following correction for multiple comparisons. CONCLUSION: These results suggest that whole-brain network centrality abnormalities may be present in many brain regions in adolescent depression patients. Accordingly, these DC maps may hold value as candidate neuroimaging biomarkers capable of differentiating between adolescents who are and are not affected by MDD, although further validation of these results will be critical. |
format | Online Article Text |
id | pubmed-9556654 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95566542022-10-14 Abnormal degree centrality in first-episode medication-free adolescent depression at rest: A functional magnetic resonance imaging study and support vector machine analysis Guo, Xin Wang, Wei Kang, Lijun Shu, Chang Bai, Hanpin Tu, Ning Bu, Lihong Gao, Yujun Wang, Gaohua Liu, Zhongchun Front Psychiatry Psychiatry BACKGROUND: Depression in adolescents is more heterogeneous and less often diagnosed than depression in adults. At present, reliable approaches to differentiating between adolescents who are and are not affected by depression are lacking. This study was designed to assess voxel-level whole-brain functional connectivity changes associated with adolescent depression in an effort to define an imaging-based biomarker associated with this condition. MATERIALS AND METHODS: In total, 71 adolescents affected by major depressive disorder (MDD) and 71 age-, sex-, and education level-matched healthy controls were subjected to resting-state functional magnetic resonance imaging (rs-fMRI) based analyses of brain voxel-wise degree centrality (DC), with a support vector machine (SVM) being used for pattern classification analyses. RESULTS: DC patterns derived from 16-min rs-fMRI analyses were able to effectively differentiate between adolescent MDD patients and healthy controls with 95.1% accuracy (136/143), and with respective sensitivity and specificity values of 92.1% (70/76) and 98.5% (66/67) based upon DC abnormalities detected in the right cerebellum. Specifically, increased DC was evident in the bilateral insula and left lingual area of MDD patients, together with reductions in the DC values in the right cerebellum and bilateral superior parietal lobe. DC values were not significantly correlated with disease severity or duration in these patients following correction for multiple comparisons. CONCLUSION: These results suggest that whole-brain network centrality abnormalities may be present in many brain regions in adolescent depression patients. Accordingly, these DC maps may hold value as candidate neuroimaging biomarkers capable of differentiating between adolescents who are and are not affected by MDD, although further validation of these results will be critical. Frontiers Media S.A. 2022-09-29 /pmc/articles/PMC9556654/ /pubmed/36245889 http://dx.doi.org/10.3389/fpsyt.2022.926292 Text en Copyright © 2022 Guo, Wang, Kang, Shu, Bai, Tu, Bu, Gao, Wang and Liu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychiatry Guo, Xin Wang, Wei Kang, Lijun Shu, Chang Bai, Hanpin Tu, Ning Bu, Lihong Gao, Yujun Wang, Gaohua Liu, Zhongchun Abnormal degree centrality in first-episode medication-free adolescent depression at rest: A functional magnetic resonance imaging study and support vector machine analysis |
title | Abnormal degree centrality in first-episode medication-free adolescent depression at rest: A functional magnetic resonance imaging study and support vector machine analysis |
title_full | Abnormal degree centrality in first-episode medication-free adolescent depression at rest: A functional magnetic resonance imaging study and support vector machine analysis |
title_fullStr | Abnormal degree centrality in first-episode medication-free adolescent depression at rest: A functional magnetic resonance imaging study and support vector machine analysis |
title_full_unstemmed | Abnormal degree centrality in first-episode medication-free adolescent depression at rest: A functional magnetic resonance imaging study and support vector machine analysis |
title_short | Abnormal degree centrality in first-episode medication-free adolescent depression at rest: A functional magnetic resonance imaging study and support vector machine analysis |
title_sort | abnormal degree centrality in first-episode medication-free adolescent depression at rest: a functional magnetic resonance imaging study and support vector machine analysis |
topic | Psychiatry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9556654/ https://www.ncbi.nlm.nih.gov/pubmed/36245889 http://dx.doi.org/10.3389/fpsyt.2022.926292 |
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