Hostname: page-component-84b7d79bbc-c654p Total loading time: 0 Render date: 2024-07-27T14:38:18.778Z Has data issue: false hasContentIssue false
  • English
  • Français

Structure-function coupling and hierarchy-specific antidepressant response in major depressive disorder

Published online by Cambridge University Press:  04 April 2024

Xinyi Wang ,
Li Xue ,
Lingling Hua ,
Junneng Shao ,
Rui Yan ,
Zhijian Yao  and
Qing Lu Open the ORCID record for Qing Lu [Opens in a new window]
Xinyi Wang
Affiliation:
School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, China Child Development and Learning Science, Key Laboratory of Ministry of Education, Southeast University, Nanjing, China
Li Xue
Affiliation:
School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, China Child Development and Learning Science, Key Laboratory of Ministry of Education, Southeast University, Nanjing, China
Lingling Hua
Affiliation:
Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
Junneng Shao
Affiliation:
School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, China Child Development and Learning Science, Key Laboratory of Ministry of Education, Southeast University, Nanjing, China
Rui Yan
Affiliation:
Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
Zhijian Yao*
Affiliation:
Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China Nanjing Brain Hospital, Clinical Teaching Hospital of Medical School, Nanjing University, Nanjing, China
Qing Lu*
Affiliation:
School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, China Child Development and Learning Science, Key Laboratory of Ministry of Education, Southeast University, Nanjing, China
*
Corresponding author: Qing Lu; Email: luq@seu.edu.cn; Zhijian Yao; Email: zjyao@njmu.edu.cn
Corresponding author: Qing Lu; Email: luq@seu.edu.cn; Zhijian Yao; Email: zjyao@njmu.edu.cn
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

Extensive research has explored altered structural and functional networks in major depressive disorder (MDD). However, studies examining the relationships between structure and function yielded heterogeneous and inconclusive results. Recent work has suggested that the structure-function relationship is not uniform throughout the brain but varies across different levels of functional hierarchy. This study aims to investigate changes in structure-function couplings (SFC) and their relevance to antidepressant response in MDD from a functional hierarchical perspective.

Methods

We compared regional SFC between individuals with MDD (n = 258) and healthy controls (HC, n = 99) using resting-state functional magnetic resonance imaging and diffusion tensor imaging. We also compared antidepressant non-responders (n = 55) and responders (n = 68, defined by a reduction in depressive severity of >50%). To evaluate variations in altered and response-associated SFC across the functional hierarchy, we ranked significantly different regions by their principal gradient values and assessed patterns of increase or decrease along the gradient axis. The principal gradient value, calculated from 219 healthy individuals in the Human Connectome Project, represents a region's position along the principal gradient axis.

Results

Compared to HC, MDD patients exhibited increased SFC in unimodal regions (lower principal gradient) and decreased SFC in transmodal regions (higher principal gradient) (p < 0.001). Responders primarily had higher SFC in unimodal regions and lower SFC in attentional networks (median principal gradient) (p < 0.001).

Conclusions

Our findings reveal opposing SFC alterations in low-level unimodal and high-level transmodal networks, underscoring spatial variability in MDD pathology. Moreover, hierarchy-specific antidepressant effects provide valuable insights into predicting treatment outcomes.

Keywords

antidepressant responsebrain hierarchyfunctional connectivity gradientstructure-function coupling
Type
Original Article
Information
Psychological Medicine , First View , pp. 1 - 10
Check for updates
Copyright
Copyright © The Author(s), 2024. 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.)

References

Baum, G. L., Cui, Z., Roalf, D. R., Ciric, R., Betzel, R. F., Larsen, B., … Satterthwaite, T. D. (2020). Development of structure-function coupling in human brain networks during youth. Proceedings of the National Academy of Sciences of the United States of America, 117(1), 771–778. https://doi.org/10.1073/pnas.1912034117CrossRefGoogle ScholarPubMed
Braga, R. M., Sharp, D. J., Leeson, C., Wise, R. J. S., & Leech, R. (2013). Echoes of the brain within default mode, association, and heteromodal cortices. The Journal of Neuroscience, 33, 14031–14039.CrossRefGoogle ScholarPubMed
Cocchi, L., Harding, I. H., Lord, A., Pantelis, C., Yucel, M., & Zalesky, A. (2014). Disruption of structure-function coupling in the schizophrenia connectome. NeuroImage: Clinical, 4, 779–787. https://doi.org/10.1016/j.nicl.2014.05.004CrossRefGoogle ScholarPubMed
Coifman, R. R., & Lafon, S. (2006). Diffusion maps. Applied and Computational Harmonic Analysis, 21(1), 5–30. https://doi.org/10.1016/j.acha.2006.04.006CrossRefGoogle Scholar
Crossley, N. A., Mechelli, A., Scott, J., Carletti, F., Fox, P. T., McGuire, P., & Bullmore, E. T. (2014). The hubs of the human connectome are generally implicated in the anatomy of brain disorders. Brain, 137(Pt 8), 2382–2395. https://doi.org/10.1093/brain/awu132CrossRefGoogle ScholarPubMed
Dai, Z., Lin, Q., Li, T., Wang, X., Yuan, H., Yu, X., … Wang, H. (2019). Disrupted structural and functional brain networks in Alzheimer's disease. Neurobiology of Aging, 75, 71–82. https://doi.org/10.1016/j.neurobiolaging.2018.11.005CrossRefGoogle ScholarPubMed
de Kwaasteniet, B., Ruhe, E., Caan, M., Rive, M., Olabarriaga, S., Groefsema, M., … Denys, D. (2013). Relation between structural and functional connectivity in major depressive disorder. Biological Psychiatry, 74(1), 40–47. https://doi.org/10.1016/j.biopsych.2012.12.024CrossRefGoogle ScholarPubMed
Fonseka, T. M., MacQueen, G. M., & Kennedy, S. H. (2018). Neuroimaging biomarkers as predictors of treatment outcome in major depressive disorder. Journal of Affective Disorders, 233, 21–35. https://doi.org/10.1016/j.jad.2017.10.049CrossRefGoogle ScholarPubMed
Gong, Q., & He, Y. (2015). Depression, neuroimaging and connectomics: A selective overview. Biological Psychiatry, 77(3), 223–235. https://doi.org/10.1016/j.biopsych.2014.08.009CrossRefGoogle ScholarPubMed
Gudayol-Ferre, E., Pero-Cebollero, M., Gonzalez-Garrido, A. A., & Guardia-Olmos, J. (2015). Changes in brain connectivity related to the treatment of depression measured through fMRI: A systematic review. Frontiers in Human Neuroscience, 9, 582. https://doi.org/10.3389/fnhum.2015.00582CrossRefGoogle Scholar
Helm, K., Viol, K., Weiger, T. M., Tass, P. A., Grefkes, C., Del Monte, D., & Schiepek, G. (2018). Neuronal connectivity in major depressive disorder: A systematic review. Neuropsychiatric Disease and Treatment, 14, 2715–2737. https://doi.org/10.2147/NDT.S170989CrossRefGoogle ScholarPubMed
Henkel, V., Seemüller, F., Obermeier, M., Adli, M., Bauer, M., Mundt, C., … Riedel, M. (2009). Does early improvement triggered by antidepressants predict response/remission? Analysis of data from a naturalistic study on a large sample of inpatients with major depression. Journal of Affective Disorders, 115(3), 439–449. https://doi.org/10.1016/j.jad.2008.10.011CrossRefGoogle Scholar
Huntenburg, J. M., Bazin, P. L., & Margulies, D. S. (2018). Large-scale gradients in human cortical organization. Trends in Cognitive Sciences, 22(1), 21–31. https://doi.org/10.1016/j.tics.2017.11.002CrossRefGoogle ScholarPubMed
James, G. M., Baldinger-Melich, P., Philippe, C., Kranz, G. S., Vanicek, T., Hahn, A., … Lanzenberger, R. (2017). Effects of selective serotonin reuptake inhibitors on interregional relation of serotonin transporter availability in major depression. Frontiers in Human Neuroscience, 11, 48. https://doi.org/10.3389/fnhum.2017.00048CrossRefGoogle ScholarPubMed
Jiang, H., Zhu, R., Tian, S., Wang, H., Chen, Z., Wang, X., … Lu, Q. (2020). Structural-functional decoupling predicts suicide attempts in bipolar disorder patients with a current major depressive episode. Neuropsychopharmacology, 45(10), 1735–1742. https://doi.org/10.1038/s41386-020-0753-5CrossRefGoogle ScholarPubMed
Jiang, X. Y., Shen, Y. D., Yao, J. S., Zhang, L., Xu, L. Y., Feng, R., … Wang, J. H. (2019). Connectome analysis of functional and structural hemispheric brain networks in major depressive disorder. Translational Psychiatry, 9(1), 136. https://doi.org/10.1038/s41398-019-0467-9CrossRefGoogle ScholarPubMed
Kaiser, R. H., Andrews-Hanna, J. R., Wager, T. D., & Pizzagalli, D. A. (2015). Large-scale network dysfunction in major depressive disorder: A meta-analysis of resting-state functional connectivity. JAMA Psychiatry, 72(6), 603–611. https://doi.org/10.1001/jamapsychiatry.2015.0071CrossRefGoogle ScholarPubMed
Kessler, R. C., Angermeyer, M., Anthony, J. C., De Graaf, R., Demyttenaere, K., Gasquet, I., … Ustun, T. B. (2007). Lifetime prevalence and age-of-onset distributions of mental disorders in the World Health Organization's World Mental Health Survey Initiative. World Psychiatry, 6(3), 168–176.Google ScholarPubMed
Knyazev, G. G. (2012). Extraversion and anterior vs. posterior DMN activity during self-referential thoughts. Frontiers in Human Neuroscience, 6, 348. https://doi.org/10.3389/fnhum.2012.00348Google ScholarPubMed
Koga, K., Yamada, A., Song, Q., Li, X. H., Chen, Q. Y., Liu, R. H., … Chen, T. (2020). Ascending noradrenergic excitation from the locus coeruleus to the anterior cingulate cortex. Molecular Brain, 13(1), 49. https://doi.org/10.1186/s13041-020-00586-5CrossRefGoogle ScholarPubMed
Koubiyr, I., Besson, P., Deloire, M., Charre-Morin, J., Saubusse, A., Tourdias, T., … Ruet, A. (2019). Dynamic modular-level alterations of structural-functional coupling in clinically isolated syndrome. Brain, 142(11), 3428–3439. https://doi.org/10.1093/brain/awz270CrossRefGoogle ScholarPubMed
Kupfer, D. J., Frank, E., & Phillips, M. L. (2012). Major depressive disorder: New clinical, neurobiological, and treatment perspectives. The Lancet, 379(9820), 1045–1055. https://doi.org/10.1016/s0140-6736(11)60602-8CrossRefGoogle ScholarPubMed
Li, B., Liu, L., Friston, K. J., Shen, H., Wang, L., Zeng, L. L., & Hu, D. (2013). A treatment-resistant default mode subnetwork in major depression. Biological Psychiatry, 74(1), 48–54. https://doi.org/10.1016/j.biopsych.2012.11.007CrossRefGoogle ScholarPubMed
Liu, X., He, C., Fan, D., Zhu, Y., Zang, F., Wang, Q., … Xie, C. (2020). Disrupted rich-club network organization and individualized identification of patients with major depressive disorder. Progress in Neuro-Psychopharmacology & Biological Psychiatry, 108, 110074. https://doi.org/10.1016/j.pnpbp.2020.110074CrossRefGoogle ScholarPubMed
Margulies, D. S., Ghosh, S. S., Goulas, A., Falkiewicz, M., Huntenburg, J. M., Langs, G., … Smallwood, J. (2016). Situating the default-mode network along a principal gradient of macroscale cortical organization. Proceedings of the National Academy of Sciences, 113(44), 12574–12579. https://doi.org/10.1073/pnas.1608282113CrossRefGoogle ScholarPubMed
Mulders, P. C., van Eijndhoven, P. F., Schene, A. H., Beckmann, C. F., & Tendolkar, I. (2015). Resting-state functional connectivity in major depressive disorder: A review. Neuroscience & Biobehavioral Reviews, 56, 330–344. https://doi.org/10.1016/j.neubiorev.2015.07.014CrossRefGoogle ScholarPubMed
Nabulsi, L., McPhilemy, G., Kilmartin, L., Whittaker, J. R., Martyn, F. M., Hallahan, B., … Cannon, D. M. (2020). Frontolimbic, frontoparietal, and default mode involvement in functional dysconnectivity in psychotic bipolar disorder. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 5(2), 140–151. https://doi.org/10.1016/j.bpsc.2019.10.015Google ScholarPubMed
Nixon, N. L., Liddle, P. F., Nixon, E., Worwood, G., Liotti, M., & Palaniyappan, L. (2014). Biological vulnerability to depression: Linked structural and functional brain network findings. British Journal of Psychiatry, 204, 283–289. https://doi.org/10.1192/bjp.bp.113.129965CrossRefGoogle ScholarPubMed
Osmanlioglu, Y., Tunc, B., Parker, D., Elliott, M. A., Baum, G. L., Ciric, R., … Verma, R. (2019). System-level matching of structural and functional connectomes in the human brain. NeuroImage, 199, 93–104. https://doi.org/10.1016/j.neuroimage.2019.05.064CrossRefGoogle ScholarPubMed
Paquola, C., Vos De Wael, R., Wagstyl, K., Bethlehem, R. A. I., Hong, S. J., Seidlitz, J., … Bernhardt, B. C. (2019). Microstructural and functional gradients are increasingly dissociated in transmodal cortices. PLoS Biology, 17(5), e3000284. https://doi.org/10.1371/journal.pbio.3000284CrossRefGoogle ScholarPubMed
Preti, M. G., & Van De Ville, D. (2019). Decoupling of brain function from structure reveals regional behavioral specialization in humans. Nature Communications, 10(1), 4747. doi:10.1038/s41467-019-12765-7CrossRefGoogle ScholarPubMed
Qin, P., Liu, Y., Shi, J., Wang, Y., Duncan, N., Gong, Q., … Northoff, G. (2012). Dissociation between anterior and posterior cortical regions during self-specificity and familiarity: A combined fMRI-meta-analytic study. Human Brain Mapping, 33(1), 154–164. doi:10.1002/hbm.21201CrossRefGoogle ScholarPubMed
Reinder, V., Larivière, S., Caldairou, B., Hong, S. J., Margulies, D. S., Jefferies, E., … Bernhardt, B. C. (2018). Anatomical and microstructural determinants of hippocampal subfield functional connectome embedding. Proceedings of the National Academy of Sciences, 115(40), 10154–10159.Google Scholar
Rush, A. J., Warden, D., Wisniewski, S. R., Fava, M., Trivedi, M. H., Gaynes, B. N., & Nierenberg, A. A. (2009). STAR*D: Revising conventional wisdom. CNS Drugs, 23(8), 627–647. doi:10.2165/00023210-200923080-00001Google ScholarPubMed
Schaefer, A., Kong, R., Gordon, E. M., Laumann, T. O., Zuo, X. N., Holmes, A. J., … Yeo, B. T. T. (2018). Local-global parcellation of the human cerebral cortex from intrinsic functional connectivity MRI. Cerebral Cortex, 28(9), 3095–3114. doi:10.1093/cercor/bhx179CrossRefGoogle ScholarPubMed
Scheepens, D. S., van Waarde, J. A., Lok, A., de Vries, G., Denys, D., & van Wingen, G. A. (2020). The link between structural and functional brain abnormalities in depression: A systematic review of multimodal neuroimaging studies. Frontiers in Psychiatry, 11, Article 485. https://doi.org/10.3389/fpsyt.2020.00485CrossRefGoogle ScholarPubMed
Scheinost, D., Holmes, S. E., DellaGioia, N., Schleifer, C., Matuskey, D., Abdallah, C. G., … Esterlis, I. (2018). Multimodal investigation of network level effects using intrinsic functional connectivity, anatomical covariance, and structure-to-function correlations in unmedicated major depressive disorder. Neuropsychopharmacology, 43(5), 1119–1127. https://doi.org/10.1038/npp.2017.229CrossRefGoogle ScholarPubMed
Shafiei, G., Zeighami, Y., Clark, C. A., Coull, J. T., Nagano-Saito, A., Leyton, M., … Misic, B. (2019). Dopamine signaling modulates the stability and integration of intrinsic brain networks. Cerebral Cortex, 29(1), 397–409. https://doi.org/10.1093/cercor/bhy264CrossRefGoogle ScholarPubMed
Spati, J., Hänggi, J., Doerig, N., Ernst, J., Sambataro, F., Brakowski, J., … Spinelli, S. (2015). Prefrontal thinning affects functional connectivity and regional homogeneity of the anterior cingulate cortex in depression. Neuropsychopharmacology, 40(7), 1640–1648. https://doi.org/10.1038/npp.2015.8CrossRefGoogle ScholarPubMed
Suarez, L. E., Markello, R. D., Betzel, R. F., & Misic, B. (2020). Linking structure and function in macroscale brain networks. Trends in Cognitive Sciences, 24(4), 302–315. https://doi.org/10.1016/j.tics.2020.01.008CrossRefGoogle ScholarPubMed
Thase, M. E., Friedman, E. S., Biggs, M. M., Wisniewski, S. R., Trivedi, M. H., Luther, J. F., … Rush, A. J. (2007). Cognitive therapy versus medication in augmentation and switch strategies as second-step treatments: A STAR*D report. American Journal of Psychiatry, 164(5), 739–752. https://doi.org/10.1176/ajp.2007.164.5.739CrossRefGoogle ScholarPubMed
Tian, Z., Yamanaka, M., Bernabucci, M., Zhao, M. G., & Zhuo, M. (2017). Characterization of serotonin-induced inhibition of excitatory synaptic transmission in the anterior cingulate cortex. Molecular Brain, 10(1), Article 21. https://doi.org/10.1186/s13041-017-0303-1CrossRefGoogle ScholarPubMed
Tozzi, L., Goldstein-Piekarski, A. N., Korgaonkar, M. S., & Williams, L. M. (2020). Connectivity of the cognitive control network during response inhibition as a predictive and response biomarker in major depression: Evidence from a randomized clinical trial. Biological Psychiatry, 87(5), 462–472. https://doi.org/10.1016/j.biopsych.2019.08.005CrossRefGoogle ScholarPubMed
Tzourio-Mazoyer, N., Landeau, B., Papathanassiou, D., Crivello, F., Etard, O., Delcroix, N., … Joliot, M. (2002). Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. NeuroImage, 15(1), 273–289. https://doi.org/10.1006/nimg.2001.0978CrossRefGoogle ScholarPubMed
van den Heuvel, M. P., Sporns, O., Collin, G., Scheewe, T., Mandl, R. C., Cahn, W., … Kahn, R. S. (2013). Abnormal rich club organization and functional brain dynamics in schizophrenia. JAMA Psychiatry, 70(8), 783–792. https://doi.org/10.1001/jamapsychiatry.2013.1328CrossRefGoogle ScholarPubMed
Van Essen, D. C., Smith, S. M., Barch, D. M., Behrens, T. E., Yacoub, E., Ugurbil, K., & Consortium, W. U.-M. H. (2013). The WU-Minn human connectome project: An overview. NeuroImage, 80, 62–79. https://doi.org/10.1016/j.neuroimage.2013.05.041CrossRefGoogle ScholarPubMed
Vazquez-Rodriguez, B., Suarez, L. E., Markello, R. D., Shafiei, G., Paquola, C., Hagmann, P., … Misic, B. (2019). Gradients of structure-function tethering across neocortex. Proceedings of the National Academy of Sciences, 116(42), 21219–21227. https://doi.org/10.1073/pnas.1903403116CrossRefGoogle ScholarPubMed
Vos de Wael, R., Benkarim, O., Paquola, C., Lariviere, S., Royer, J., Tavakol, S., … Bernhardt, B. C. (2020). BrainSpace: A toolbox for the analysis of macroscale gradients in neuroimaging and connectomics datasets. Communications Biology, 3(1), Article 103. https://doi.org/10.1038/s42003-020-0794-7CrossRefGoogle ScholarPubMed
Whitfield-Gabrieli, S., Moran, J. M., Nieto-Castanon, A., Triantafyllou, C., Saxe, R., & Gabrieli, J. D. (2011). Associations and dissociations between default and self-reference networks in the human brain. NeuroImage, 55(1), 225–232. https://doi.org/10.1016/j.neuroimage.2010.11.048CrossRefGoogle ScholarPubMed
Yeo, B. T., Krienen, F. M., Eickhoff, S. B., Yaakub, S. N., Fox, P. T., Buckner, R. L., … Chee, M. W. (2016). Functional specialization and flexibility in human association cortex. Cerebral Cortex, 26(1), 465. https://doi.org/10.1093/cercor/bhv260CrossRefGoogle ScholarPubMed
Zhang, J., Zhang, Y., Wang, L., Sang, L., Yang, J., Yan, R., … Qiu, M. (2017). Disrupted structural and functional connectivity networks in ischemic stroke patients. Neuroscience, 364, 212–225. https://doi.org/10.1016/j.neuroscience.2017.09.009CrossRefGoogle ScholarPubMed
Zhang, Z., Liao, W., Chen, H., Mantini, D., Ding, J. R., Xu, Q., … Lu, G. (2011). Altered functional-structural coupling of large-scale brain networks in idiopathic generalized epilepsy. Brain, 134(Pt 10), 2912–2928. https://doi.org/10.1093/brain/awr223CrossRefGoogle ScholarPubMed
Zhao, Y., Zhang, F., Zhang, W., Chen, L., Chen, Z., Lui, S., & Gong, Q. (2021). Decoupling of gray and white matter functional networks in medication-naive patients with major depressive disorder. Journal of Magnetic Resonance Imaging, 53(3), 742–752. https://doi.org/10.1002/jmri.27392CrossRefGoogle ScholarPubMed
Zhou, H. X., Chen, X., Shen, Y. Q., Li, L., Chen, N. X., Zhu, Z. C., … Yan, C. G. (2020). Rumination and the default mode network: Meta-analysis of brain imaging studies and implications for depression. NeuroImage, 206, Article 116287. https://doi.org/10.1016/j.neuroimage.2019.116287CrossRefGoogle ScholarPubMed
Supplementary material: File

Wang et al. supplementary material

Wang et al. supplementary material
Download Wang et al. supplementary material(File)
File 14.6 KB