Hostname: page-component-75d7c8f48-665pl Total loading time: 0 Render date: 2026-03-14T00:39:14.165Z Has data issue: false hasContentIssue false
  • English
  • Français

Common and distinct functional brain network abnormalities in adolescent, early-middle adult, and late adult major depressive disorders

Published online by Cambridge University Press:  09 August 2023

Yicheng Long ,
Xuemei Li ,
Hengyi Cao ,
Manqi Zhang ,
Bing Lu ,
Yang Huang ,
Mengqi Liu ,
Ming Xu ,
Zhening Liu  and
Chaogan Yan
...Show all authors
Yicheng Long
Affiliation:
Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
Xuemei Li
Affiliation:
Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
Hengyi Cao
Affiliation:
Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA
Manqi Zhang
Affiliation:
Center for Studies of Psychological Application, South China Normal University, Guangzhou, China
Bing Lu
Affiliation:
CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
Yang Huang
Affiliation:
Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
Mengqi Liu
Affiliation:
Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
Ming Xu
Affiliation:
Department of Psychology, University of Chinese Academy of Sciences, Beijing, China Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
Zhening Liu
Affiliation:
Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
Chaogan Yan
Affiliation:
CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
Jing Sui*
Affiliation:
IDG/McGovern Institute for Brain Research, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
Xuan Ouyang*
Affiliation:
Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
Xinyu Zhou*
Affiliation:
Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
*
Corresponding authors: Jing Sui; Email: jsui@bnu.edu.cn; Xuan Ouyang; Email: ouyangxuan@csu.edu.cn; Xinyu Zhou; Email: zhouxinyu@cqmu.edu.cn
Corresponding authors: Jing Sui; Email: jsui@bnu.edu.cn; Xuan Ouyang; Email: ouyangxuan@csu.edu.cn; Xinyu Zhou; Email: zhouxinyu@cqmu.edu.cn
Corresponding authors: Jing Sui; Email: jsui@bnu.edu.cn; Xuan Ouyang; Email: ouyangxuan@csu.edu.cn; Xinyu Zhou; Email: zhouxinyu@cqmu.edu.cn
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

The age-related heterogeneity in major depressive disorder (MDD) has received significant attention. However, the neural mechanisms underlying such heterogeneity still need further investigation. This study aimed to explore the common and distinct functional brain abnormalities across different age groups of MDD patients from a large-sample, multicenter analysis.

Methods

The analyzed sample consisted of a total of 1238 individuals including 617 MDD patients (108 adolescents, 12–17 years old; 411 early-middle adults, 18–54 years old; and 98 late adults, > = 55 years old) and 621 demographically matched healthy controls (60 adolescents, 449 early-middle adults, and 112 late adults). MDD-related abnormalities in brain functional connectivity (FC) patterns were investigated in each age group separately and using the whole pooled sample, respectively.

Results

We found shared FC reductions among the sensorimotor, visual, and auditory networks across all three age groups of MDD patients. Furthermore, adolescent patients uniquely exhibited increased sensorimotor-subcortical FC; early-middle adult patients uniquely exhibited decreased visual-subcortical FC; and late adult patients uniquely exhibited wide FC reductions within the subcortical, default-mode, cingulo-opercular, and attention networks. Analysis of covariance models using the whole pooled sample further revealed: (1) significant main effects of age group on FCs within most brain networks, suggesting that they are decreased with aging; and (2) a significant age group × MDD diagnosis interaction on FC within the default-mode network, which may be reflective of an accelerated aging-related decline in default-mode FCs.

Conclusions

To summarize, these findings may deepen our understanding of the age-related biological and clinical heterogeneity in MDD.

Keywords

Agingbrain networkconnectomefunctional connectivitymajor depressive disorder

Information

Type
Original Article
Information
Psychological Medicine , Volume 54 , Issue 3 , February 2024 , pp. 582 - 591
Check for updates
Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

Footnotes

*

These authors contributed equally to this work.

References

Alexopoulos, G. S., Hoptman, M. J., Kanellopoulos, D., Murphy, C. F., Lim, K. O., & Gunning, F. M. (2012). Functional connectivity in the cognitive control network and the default mode network in late-life depression. Journal of Affective Disorders, 139(1), 56–65. https://doi.org/10.1016/j.jad.2011.12.002.Google Scholar
Ballester, P. L., Romano, M. T., Azevedo Cardoso, T., Hassel, S., Strother, S. C., Kennedy, S. H., & Frey, B. N. (2022). Brain age in mood and psychotic disorders: A systematic review and meta-analysis. Acta Psychiatrica Scandinavica, 145(1), 42–55. https://doi.org/10.1111/acps.13371.Google Scholar
Ballester, P. L., Suh, J. S., Nogovitsyn, N., Hassel, S., Strother, S. C., Arnott, S. R., … Frey, B. N. (2021). Accelerated brain aging in major depressive disorder and antidepressant treatment response: A CAN-BIND report. NeuroImage: Clinical, 32, 102864. https://doi.org/10.1016/j.nicl.2021.102864.Google Scholar
Blank, T. S., Meyer, B. M., Wieser, M., Rabl, U., Schögl, P., & Pezawas, L. (2022). Brain morphometry and connectivity differs between adolescent- and adult-onset major depressive disorder. Depression and Anxiety, 39(5), 387–396. https://doi.org/10.1002/da.23254.Google Scholar
Chen, C., Liu, Z., Zuo, J., Xi, C., Long, Y., Li, M. D., … Yang, J. (2021). Decreased cortical folding of the fusiform gyrus and its hypoconnectivity with sensorimotor areas in major depressive disorder. Journal of Affective Disorders, 295, 657–664. https://doi.org/10.1016/j.jad.2021.08.148.Google Scholar
Chen, X., Lu, B., & Yan, C. G. (2018). Reproducibility of R-fMRI metrics on the impact of different strategies for multiple comparison correction and sample sizes. Human Brain Mapping, 39(1), 300–318. https://doi.org/10.1002/hbm.23843.Google Scholar
Chen, Y., Wang, C., Zhu, X., Tan, Y., & Zhong, Y. (2015). Aberrant connectivity within the default mode network in first-episode, treatment-naïve major depressive disorder. Journal of Affective Disorders, 183, 49–56. https://doi.org/10.1016/j.jad.2015.04.052.Google Scholar
Chopra, S., Francey, S. M., O'Donoghue, B., Sabaroedin, K., Arnatkeviciute, A., Cropley, V., … Fornito, A. (2021). Functional connectivity in antipsychotic-treated and antipsychotic-naive patients with first-episode psychosis and low risk of self-harm or aggression. JAMA Psychiatry, 78(9), 994. https://doi.org/10.1001/jamapsychiatry.2021.1422.Google Scholar
Cole, M. W., Reynolds, J. R., Power, J. D., Repovs, G., Anticevic, A., & Braver, T. S. (2013). Multi-task connectivity reveals flexible hubs for adaptive task control. Nature Neuroscience, 16(9), 1348–1355. https://doi.org/10.1038/nn.3470.Google Scholar
Cuijpers, P., Karyotaki, E., Eckshtain, D., Ng, M. Y., Corteselli, K. A., Noma, H., … Weisz, J. R. (2020). Psychotherapy for depression across different age groups: A systematic review and meta-analysis. JAMA Psychiatry, 77(7), 694. https://doi.org/10.1001/jamapsychiatry.2020.0164.Google Scholar
Deng, K., Yue, J., Xu, J., Ma, P., Chen, X., Li, L., … Cheng, Y. (2022). Impaired robust interhemispheric function integration of depressive brain from REST-meta-MDD database in China. Bipolar Disorders, 24(4), 400–411. https://doi.org/10.1111/bdi.13139.Google Scholar
Ding, Y.-D., Yang, R., Yan, C.-G., Chen, X., Bai, T.-J., Bo, Q.-J., … Guo, W.-B. (2021). Disrupted hemispheric connectivity specialization in patients with major depressive disorder: Evidence from the REST-meta-MDD Project. Journal of Affective Disorders, 284, 217–228. https://doi.org/10.1016/j.jad.2021.02.030.Google Scholar
Dong, H. M., Castellanos, F. X., Yang, N., Zhang, Z., Zhou, Q., He, Y., … Zuo, X. N. (2020). Charting brain growth in tandem with brain templates at school age. Science Bulletin, 65(22), 1924–1934. https://doi.org/10.1016/j.scib.2020.07.027.Google Scholar
Eyre, H. A., Yang, H., Leaver, A. M., van Dyk, K., Siddarth, P., Cyr, N. S., … Lavretsky, H. (2016). Altered resting-state functional connectivity in late-life depression: A cross-sectional study. Journal of Affective Disorders, 189, 126–133. https://doi.org/10.1016/j.jad.2015.09.011.Google Scholar
Feng, J., Chen, C., Cai, Y., Ye, Z., Feng, K., Liu, J., … Xue, G. (2020). Partitioning heritability analyses unveil the genetic architecture of human brain multidimensional functional connectivity patterns. Human Brain Mapping, 41(12), 3305–3317. https://doi.org/10.1002/hbm.25018.Google Scholar
Findling, R. L., DelBello, M. P., Zuddas, A., Emslie, G. J., Ettrup, A., Petersen, M. L., … Rosen, M. (2022). Vortioxetine for major depressive disorder in adolescents: 12-week randomized, placebo-controlled, fluoxetine-referenced, fixed-dose study. Journal of the American Academy of Child & Adolescent Psychiatry, 61(9), 1106–1118.e2. https://doi.org/10.1016/j.jaac.2022.01.004.Google Scholar
Gandelman, J. A., Albert, K., Boyd, B. D., Park, J. W., Riddle, M., Woodward, N. D., … Taylor, W. D. (2019). Intrinsic functional network connectivity is associated with clinical symptoms and cognition in late-life depression. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 4(2), 160–170. https://doi.org/10.1016/j.bpsc.2018.09.003.Google Scholar
Geerligs, L., Renken, R. J., Saliasi, E., Maurits, N. M., & Lorist, M. M. (2015). A brain-wide study of age-related changes in functional connectivity. Cerebral Cortex, 25(7), 1987–1999. https://doi.org/10.1093/cercor/bhu012.Google Scholar
Goldman, D. A., Sankar, A., Rich, A., Kim, J. A., Pittman, B., Constable, R. T., … Blumberg, H. P. (2022). A graph theory neuroimaging approach to distinguish the depression of bipolar disorder from major depressive disorder in adolescents and young adults. Journal of Affective Disorders, 319, 15–26. https://doi.org/10.1016/j.jad.2022.09.016.Google Scholar
Guan, C., Amdanee, N., Liao, W., Zhou, C., Wu, X., Zhang, X., & Zhang, C. (2022). Altered intrinsic default mode network functional connectivity in patients with remitted geriatric depression and amnestic mild cognitive impairment. International Psychogeriatrics, 34(8), 703–714. https://doi.org/10.1017/S1041610221001174.Google Scholar
Han, L. K. M., Dinga, R., Hahn, T., Ching, C. R. K., Eyler, L. T., Aftanas, L., … Schmaal, L. (2021). Brain aging in major depressive disorder: Results from the ENIGMA major depressive disorder working group. Molecular Psychiatry, 26(9), 5124–5139. https://doi.org/10.1038/s41380-020-0754-0.Google Scholar
Hardcastle, C., Hausman, H. K., Kraft, J. N., Albizu, A., Evangelista, N. D., Boutzoukas, E. M., … Woods, A. J. (2022). Higher-order resting state network association with the useful field of view task in older adults. GeroScience, 44(1), 131–145. https://doi.org/10.1007/s11357-021-00441-y.Google Scholar
Hasin, D. S., Sarvet, A. L., Meyers, J. L., Saha, T. D., Ruan, W. J., Stohl, M., & Grant, B. F. (2018). Epidemiology of adult DSM-5 major depressive disorder and its specifiers in the United States. JAMA Psychiatry, 75(4), 336. https://doi.org/10.1001/jamapsychiatry.2017.4602.Google Scholar
Hausman, H. K., O'Shea, A., Kraft, J. N., Boutzoukas, E. M., Evangelista, N. D., Van Etten, E. J., … Woods, A. J. (2020). The role of resting-state network functional connectivity in cognitive aging. Frontiers in Aging Neuroscience, 12, 177. https://doi.org/10.3389/fnagi.2020.00177.Google Scholar
Hegeman, J. M., Kok, R. M., van der Mast, R. C., & Giltay, E. J. (2012). Phenomenology of depression in older compared with younger adults: Meta-analysis. British Journal of Psychiatry, 200(4), 275–281. https://doi.org/10.1192/bjp.bp.111.095950.Google Scholar
Hu, L., Xiao, M., Ai, M., Wang, W., Chen, J., Tan, Z., … Kuang, L. (2019). Disruption of resting-state functional connectivity of right posterior insula in adolescents and young adults with major depressive disorder. Journal of Affective Disorders, 257, 23–30. https://doi.org/10.1016/j.jad.2019.06.057.Google Scholar
Iancu, S. C., Wong, Y. M., Rhebergen, D., van Balkom, A. J. L. M., & Batelaan, N. M. (2020). Long-term disability in major depressive disorder: A 6-year follow-up study. Psychological Medicine, 50(10), 1644–1652. https://doi.org/10.1017/S0033291719001612.Google Scholar
Jacob, Y., Morris, L. S., Huang, K.-H., Schneider, M., Rutter, S., Verma, G., … Balchandani, P. (2020). Neural correlates of rumination in major depressive disorder: A brain network analysis. NeuroImage: Clinical, 25, 102142. https://doi.org/10.1016/j.nicl.2019.102142.Google Scholar
Javaheripour, N., Li, M., Chand, T., Krug, A., Kircher, T., Dannlowski, U., … Wagner, G. (2021). Altered resting-state functional connectome in major depressive disorder: A mega-analysis from the PsyMRI consortium. Translational Psychiatry, 11(1), 511. https://doi.org/10.1038/s41398-021-01619-w.Google Scholar
Jha, M. K., Chin Fatt, C., Minhajuddin, A., Mayes, T. L., & Trivedi, M. H. (2023). Accelerated brain aging in adults with major depressive disorder predicts poorer outcome with sertraline: Findings from the EMBARC study. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 8(4), 462–470. https://doi.org/10.1016/j.bpsc.2022.09.006.Google Scholar
Jiao, Q., Ding, J., Lu, G., Su, L., Zhang, Z., Wang, Z., … Liu, Y. (2011). Increased activity imbalance in fronto-subcortical circuits in adolescents with major depression. PLoS One, 6(9), e25159. https://doi.org/10.1371/journal.pone.0025159.Google Scholar
Kaiser, R. H., Andrews-Hanna, J. R., Wager, T. D., & Pizzagalli, D. A. (2015). Large-scale network dysfunction in major depressive disorder. JAMA Psychiatry, 72(6), 603. https://doi.org/10.1001/jamapsychiatry.2015.0071.Google Scholar
Li, L., Su, Y. A., Wu, Y. K., Castellanos, F. X., Li, K., Li, J. T., … Yan, C. G. (2021). Eight-week antidepressant treatment reduces functional connectivity in first-episode drug-naïve patients with major depressive disorder. Human Brain Mapping, 42(8), 2593–2605. https://doi.org/10.1002/hbm.25391.Google Scholar
Liang, S., Deng, W., Li, X., Greenshaw, A. J., Wang, Q., Li, M., … Li, T. (2020). Biotypes of major depressive disorder: Neuroimaging evidence from resting-state default mode network patterns. NeuroImage: Clinical, 28, 102514. https://doi.org/10.1016/j.nicl.2020.102514.Google Scholar
Liu, P.-h., Li, Y., Zhang, A.-X., Sun, N., Li, G.-Z., Chen, X., … Zhang, K.-R. (2021). Brain structural alterations in MDD patients with gastrointestinal symptoms: Evidence from the REST-meta-MDD project. Progress in Neuro-Psychopharmacology and Biological Psychiatry, 111, 110386. https://doi.org/10.1016/j.pnpbp.2021.110386.Google Scholar
Long, Y., Cao, H., Yan, C., Chen, X., Li, L., Castellanos, F. X., … Liu, Z. (2020). Altered resting-state dynamic functional brain networks in major depressive disorder: Findings from the REST-meta-MDD consortium. NeuroImage: Clinical, 26, 102163. https://doi.org/10.1016/j.nicl.2020.102163.Google Scholar
Long, Y., Ouyang, X., Yan, C., Wu, Z., Huang, X., Pu, W., … Palaniyappan, L. (2023). Evaluating test–retest reliability and sex-/age-related effects on temporal clustering coefficient of dynamic functional brain networks. Human Brain Mapping, 44(6), 2191–2208. https://doi.org/10.1002/hbm.26202.Google Scholar
Lu, F., Cui, Q., Huang, X., Li, L., Duan, X., Chen, H., … Chen, H. (2020). Anomalous intrinsic connectivity within and between visual and auditory networks in major depressive disorder. Progress in Neuro-Psychopharmacology and Biological Psychiatry, 100, 109889. https://doi.org/10.1016/j.pnpbp.2020.109889.Google Scholar
Lu, J., Xu, X., Huang, Y., Li, T., Ma, C., Xu, G., … Zhang, N. (2021). Prevalence of depressive disorders and treatment in China: A cross-sectional epidemiological study. The Lancet Psychiatry, 8(11), 981–990. https://doi.org/10.1016/S2215-0366(21)00251-0.Google Scholar
Luo, L., Wu, H., Xu, J., Chen, F., Wu, F., Wang, C., & Wang, J. (2021). Abnormal large-scale resting-state functional networks in drug-free major depressive disorder. Brain Imaging and Behavior, 15(1), 96–106. https://doi.org/10.1007/s11682-019-00236-y.Google Scholar
Mohr, H., Wolfensteller, U., Betzel, R. F., Mišić, B., Sporns, O., Richiardi, J., & Ruge, H. (2016). Integration and segregation of large-scale brain networks during short-term task automatization. Nature Communications, 7(1), 13217. https://doi.org/10.1038/ncomms13217.Google Scholar
Nguyen, T.-D., Harder, A., Xiong, Y., Kowalec, K., Hägg, S., Cai, N., … Lu, Y. (2022). Genetic heterogeneity and subtypes of major depression. Molecular Psychiatry, 27(3), 1667–1675. https://doi.org/10.1038/s41380-021-01413-6.Google Scholar
Niu, Y., Sun, J., Wang, B., Yang, Y., Wen, X., & Xiang, J. (2022). Trajectories of brain entropy across lifetime estimated by resting state functional magnetic resonance imaging. Human Brain Mapping, 43(14), 4359–4369. https://doi.org/10.1002/hbm.25959.Google Scholar
Park, J. E., Jung, S. C., Ryu, K. H., Oh, J. Y., Kim, H. S., Choi, C. G., … Shim, W. H. (2017). Differences in dynamic and static functional connectivity between young and elderly healthy adults. Neuroradiology, 59(8), 781–789. https://doi.org/10.1007/s00234-017-1875-2.Google Scholar
Pine, D. S. (2019). Heterogeneity in major depressive disorder: Lessons from developmental research on irritability. American Journal of Psychiatry, 176(5), 331–332. https://doi.org/10.1176/appi.ajp.2019.19020214.Google Scholar
Power, J. D., Cohen, A. L., Nelson, S. M., Wig, G. S., Barnes, K. A., Church, J. A., … Petersen, S. E. (2011). Functional network organization of the human brain. Neuron, 72(4), 665–678. https://doi.org/10.1016/j.neuron.2011.09.006.Google Scholar
Ray, D., Bezmaternykh, D., Mel'nikov, M., Friston, K. J., & Das, M. (2021). Altered effective connectivity in sensorimotor cortices is a signature of severity and clinical course in depression. Proceedings of the National Academy of Sciences, 118(40), e2105730118. https://doi.org/10.1073/pnas.2105730118.Google Scholar
Rep, C., Peyre, H., Sánchez-Rico, M., Blanco, C., Dosquet, M., Schuster, J.-P., … Hoertel, N. (2022). Contributing factors to heterogeneity in the timing of the onset of major depressive episode: Results from a national study. Journal of Affective Disorders, 299, 585–595. https://doi.org/10.1016/j.jad.2021.12.082.Google Scholar
Rice, F., Riglin, L., Lomax, T., Souter, E., Potter, R., Smith, D. J., … Thapar, A. (2019). Adolescent and adult differences in major depression symptom profiles. Journal of Affective Disorders, 243, 175–181. https://doi.org/10.1016/j.jad.2018.09.015.Google Scholar
Saberi, A., Mohammadi, E., Zarei, M., Eickhoff, S. B., & Tahmasian, M. (2022). Structural and functional neuroimaging of late-life depression: A coordinate-based meta-analysis. Brain Imaging and Behavior, 16(1), 518–531. https://doi.org/10.1007/s11682-021-00494-9.Google Scholar
Sanders, A. F. P., Harms, M. P., Kandala, S., Marek, S., Somerville, L. H., Bookheimer, S. Y., … Barch, D. M. (2023). Age-related differences in resting-state functional connectivity from childhood to adolescence. Cerebral Cortex, 33(11), 6928–6942. https://doi.org/10.1093/cercor/bhad011.Google Scholar
Scalabrini, A., Vai, B., Poletti, S., Damiani, S., Mucci, C., Colombo, C., … Northoff, G. (2020). All roads lead to the default-mode network—global source of DMN abnormalities in major depressive disorder. Neuropsychopharmacology, 45(12), 2058–2069. https://doi.org/10.1038/s41386-020-0785-x.Google Scholar
Schaakxs, R., Comijs, H. C., Lamers, F., Kok, R. M., Beekman, A. T. F., & Penninx, B. W. J. H. (2018). Associations between age and the course of major depressive disorder: A 2-year longitudinal cohort study. The Lancet Psychiatry, 5(7), 581–590. https://doi.org/10.1016/S2215-0366(18)30166-4.Google Scholar
Staffaroni, A. M., Brown, J. A., Casaletto, K. B., Elahi, F. M., Deng, J., Neuhaus, J., … Kramer, J. H. (2018). The longitudinal trajectory of default mode network connectivity in healthy older adults varies as a function of age and is associated with changes in episodic memory and processing speed. Journal of Neuroscience, 38(11), 2809–2817. https://doi.org/10.1523/JNEUROSCI.3067-17.2018.Google Scholar
Stallwood, E., Monsour, A., Rodrigues, C., Monga, S., Terwee, C., Offringa, M., & Butcher, N. J. (2021). Systematic review: The measurement properties of the children's depression rating scale−revised in adolescents with major depressive disorder. Journal of the American Academy of Child & Adolescent Psychiatry, 60(1), 119–133. https://doi.org/10.1016/j.jaac.2020.10.009.Google Scholar
Straub, J., Brown, R., Malejko, K., Bonenberger, M., Grön, G., Plener, P. L., … Abler, B. (2019). Adolescent depression and brain development: Evidence from voxel-based morphometry. Journal of Psychiatry and Neuroscience, 44(4), 237–245. https://doi.org/10.1503/jpn.170233.Google Scholar
Sun, J., Zhao, R., He, Z., Chang, M., Wang, F., Wei, W., … Yang, X. (2022). Abnormal dynamic functional connectivity after sleep deprivation from temporal variability perspective. Human Brain Mapping, 43(12), 3824–3839.Google Scholar
Supekar, K., Musen, M., & Menon, V. (2009). Development of large-scale functional brain networks in children. PLoS Biology, 7(7), e1000157. https://doi.org/10.1371/journal.pbio.1000157.Google Scholar
Tan, W., Ouyang, X., Huang, D., Wu, Z., Liu, Z., He, Z., & Long, Y. (2023). Disrupted intrinsic functional brain network in patients with late-life depression: Evidence from a multi-site dataset. Journal of Affective Disorders, 323, 631–639. https://doi.org/10.1016/j.jad.2022.12.019.Google Scholar
Tang, S., Lu, L., Zhang, L., Hu, X., Bu, X., Li, H., … Huang, X. (2018). Abnormal amygdala resting-state functional connectivity in adults and adolescents with major depressive disorder: A comparative meta-analysis. EBioMedicine, 36, 436–445. https://doi.org/10.1016/j.ebiom.2018.09.010.Google Scholar
Tang, S., Wu, Z., Cao, H., Chen, X., Wu, G., Tan, W., … Liu, Z. (2022). Age-Related decrease in default-mode network functional connectivity is accelerated in patients with major depressive disorder. Frontiers in Aging Neuroscience, 13, 809853. https://doi.org/10.3389/fnagi.2021.809853.Google Scholar
Thomas, A. J., Gallagher, P., Robinson, L. J., Porter, R. J., Young, A. H., Ferrier, I. N., & O'Brien, J. T. (2009). A comparison of neurocognitive impairment in younger and older adults with major depression. Psychological Medicine, 39(5), 725–733. https://doi.org/10.1017/S0033291708004042.Google Scholar
Tsurugizawa, T., & Yoshimaru, D. (2021). Impact of anesthesia on static and dynamic functional connectivity in mice. NeuroImage, 241, 118413. https://doi.org/10.1016/j.neuroimage.2021.118413.Google Scholar
Wagner, S., Wollschläger, D., Dreimüller, N., Engelmann, J., Herzog, D. P., Roll, S. C., … Lieb, K. (2020). Effects of age on depressive symptomatology and response to antidepressant treatment in patients with major depressive disorder aged 18 to 65 years. Comprehensive Psychiatry, 99, 152170. https://doi.org/10.1016/j.comppsych.2020.152170.Google Scholar
Whittle, S., Lichter, R., Dennison, M., Vijayakumar, N., Schwartz, O., Byrne, M. L., … Allen, N. B. (2014). Structural brain development and depression onset during adolescence: A prospective longitudinal study. American Journal of Psychiatry, 171(5), 564–571. https://doi.org/10.1176/appi.ajp.2013.13070920.Google Scholar
Wu, M., Andreescu, C., Butters, M. A., Tamburo, R., Reynolds, C. F., & Aizenstein, H. (2011). Default-mode network connectivity and white matter burden in late-life depression. Psychiatry Research - Neuroimaging, 194(1), 39–46. https://doi.org/10.1016/j.pscychresns.2011.04.003.Google Scholar
Xia, M., Wang, J., & He, Y. (2013). BrainNet viewer: A network visualization tool for human brain connectomics. PLoS One, 8(7), e68910. https://doi.org/10.1371/journal.pone.0068910.Google Scholar
Yan, C G, Chen, X., Li, L., Castellanos, F. X., Bai, T. J., Bo, Q. J., … Zang, Y. F. (2019). Reduced default mode network functional connectivity in patients with recurrent major depressive disorder. Proceedings of the National Academy of Sciences of the United States of America, 116(18), 9078–9083. https://doi.org/10.1073/pnas.1900390116.Google Scholar
Yan, C. G., Wang, X. di, Zuo, X. N., & Zang, Y. F. (2016). DPABI: Data processing & analysis for (resting-state) brain imaging. Neuroinformatics, 14(3), 339–351. https://doi.org/10.1007/s12021-016-9299-4.Google Scholar
Yang, H., Chen, X., Chen, Z. B., Li, L., Li, X. Y., Castellanos, F. X., … Yan, C. G. (2021). Disrupted intrinsic functional brain topology in patients with major depressive disorder. Molecular Psychiatry, 26(12), 7363–7371. https://doi.org/10.1038/s41380-021-01247-2.Google Scholar
Yang, M., Chen, B., Zhong, X., Zhou, H., Mai, N., Zhang, M., … Ning, Y. (2022). Disrupted olfactory functional connectivity in patients with late-life depression. Journal of Affective Disorders, 306, 174–181. https://doi.org/10.1016/j.jad.2022.03.014.Google Scholar
Ye, J., Shen, Z., Xu, X., Yang, S., Chen, W., Liu, X., … Cheng, Y. (2017). Abnormal functional connectivity of the amygdala in first-episode and untreated adult major depressive disorder patients with different ages of onset. NeuroReport, 28(4), 214–221. https://doi.org/10.1097/WNR.0000000000000733.Google Scholar
Zalesky, A., Fornito, A., & Bullmore, E. T. (2010). Network-based statistic: Identifying differences in brain networks. NeuroImage, 53(4), 1197–1207. https://doi.org/10.1016/J.NEUROIMAGE.2010.06.041.Google Scholar
Zhang, M., Palaniyappan, L., Deng, M., Zhang, W., Pan, Y., Fan, Z., … Pu, W. (2021). Abnormal thalamocortical circuit in adolescents with early-onset schizophrenia. Journal of the American Academy of Child and Adolescent Psychiatry, 60(4), 479–489. https://doi.org/10.1016/j.jaac.2020.07.903.Google Scholar
Zhukovsky, P., Anderson, J. A. E., Coughlan, G., Mulsant, B. H., Cipriani, A., & Voineskos, A. N. (2021). Coordinate-based network mapping of brain structure in major depressive disorder in younger and older adults: A systematic review and meta-analysis. American Journal of Psychiatry, 178(12), 1119–1128. https://doi.org/10.1176/appi.ajp.2021.21010088.Google Scholar
Zhuo, C., Zhu, J., Wang, C., Qu, H., Ma, X., & Qin, W. (2017). Different spatial patterns of brain atrophy and global functional connectivity impairments in major depressive disorder. Brain Imaging and Behavior, 11(6), 1678–1689. https://doi.org/10.1007/s11682-016-9645-z.Google Scholar
Zonneveld, H. I., Pruim, R. HR., Bos, D., Vrooman, H. A., Muetzel, R. L., Hofman, A., … Vernooij, M. W. (2019). Patterns of functional connectivity in an aging population: The Rotterdam study. NeuroImage, 189, 432–444. https://doi.org/10.1016/j.neuroimage.2019.01.041.Google Scholar
Supplementary material: File

S0033291723002234sup001.docx

Long et al. supplementary material
Download S0033291723002234sup001.docx(File)
File 1.3 MB