Abnormal degree centrality in first-episode medication-free adolescent depression at rest: A functional magnetic resonance imaging study and support vector machine analysis

Xin Guo; Wei Wang; Lijun Kang; Chang Shu; Hanpin Bai; Ning Tu; Lihong Bu; Yujun Gao; Gaohua Wang; Zhongchun Liu

doi:10.3389/fpsyt.2022.926292

Abnormal degree centrality in first-episode medication-free adolescent depression at rest: A functional magnetic resonance imaging study and support vector machine analysis

Front Psychiatry. 2022 Sep 29:13:926292. doi: 10.3389/fpsyt.2022.926292. eCollection 2022.

Authors

Xin Guo^{1

2}, Wei Wang¹, Lijun Kang¹, Chang Shu¹, Hanpin Bai¹, Ning Tu³, Lihong Bu³, Yujun Gao¹, Gaohua Wang¹, Zhongchun Liu¹

Affiliations

¹ Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.
² Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College of London, London, United Kingdom.
³ PET/CT/MRI and Molecular Imaging Center, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.

Abstract

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.

Keywords: adolescent depression; degree centrality; functional magenetic resonance imaging; resting state; support vector machine (SVM).