Hostname: page-component-cd9895bd7-8ctnn Total loading time: 0 Render date: 2024-12-27T19:14:05.613Z Has data issue: false hasContentIssue false

White matter fiber microstructure is associated with prior hospitalizations rather than acute symptomatology in major depressive disorder

Published online by Cambridge University Press:  14 September 2020

Susanne Meinert
Affiliation:
Department of Psychiatry, University of Münster, Münster, Germany
Elisabeth J. Leehr
Affiliation:
Department of Psychiatry, University of Münster, Münster, Germany
Dominik Grotegerd
Affiliation:
Department of Psychiatry, University of Münster, Münster, Germany
Jonathan Repple
Affiliation:
Department of Psychiatry, University of Münster, Münster, Germany
Katharina Förster
Affiliation:
Department of Psychiatry, University of Münster, Münster, Germany Clinical Psychology and Behavioral Neuroscience, Faculty of Psychology, Technische Universität Dresden, Dresden, Germany
Nils R. Winter
Affiliation:
Department of Psychiatry, University of Münster, Münster, Germany
Verena Enneking
Affiliation:
Department of Psychiatry, University of Münster, Münster, Germany
Stella M. Fingas
Affiliation:
Department of Psychiatry, University of Münster, Münster, Germany
Hannah Lemke
Affiliation:
Department of Psychiatry, University of Münster, Münster, Germany
Lena Waltemate
Affiliation:
Department of Psychiatry, University of Münster, Münster, Germany
Frederike Stein
Affiliation:
Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
Katharina Brosch
Affiliation:
Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
Simon Schmitt
Affiliation:
Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
Tina Meller
Affiliation:
Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
Anna Linge
Affiliation:
Department of Psychiatry, University of Münster, Münster, Germany
Axel Krug
Affiliation:
Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany
Igor Nenadić
Affiliation:
Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
Andreas Jansen
Affiliation:
Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany Core-Unit Brainimaging, Faculty of Medicine, University of Marburg, Marburg, Germany
Tim Hahn
Affiliation:
Department of Psychiatry, University of Münster, Münster, Germany
Ronny Redlich
Affiliation:
Department of Psychiatry, University of Münster, Münster, Germany
Nils Opel
Affiliation:
Department of Psychiatry, University of Münster, Münster, Germany Interdisciplinary Centre for Clinical Research (IZKF) Münster, University of Münster, Münster, Germany
Ricarda I. Schubotz
Affiliation:
Department of Psychology, University of Münster, Münster, Germany
Bernhard T. Baune
Affiliation:
Department of Psychiatry, University of Münster, Münster, Germany Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Melbourne, VIC, Australia The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
Tilo Kircher
Affiliation:
Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
Udo Dannlowski*
Affiliation:
Department of Psychiatry, University of Münster, Münster, Germany
*
Author for correspondence: Udo Dannlowski, E-mail: [email protected]

Abstract

Background

Eighty percent of all patients suffering from major depressive disorder (MDD) relapse at least once in their lifetime. Thus, understanding the neurobiological underpinnings of the course of MDD is of utmost importance. A detrimental course of illness in MDD was most consistently associated with superior longitudinal fasciculus (SLF) fiber integrity. As similar associations were, however, found between SLF fiber integrity and acute symptomatology, this study attempts to disentangle associations attributed to current depression from long-term course of illness.

Methods

A total of 531 patients suffering from acute (N = 250) or remitted (N = 281) MDD from the FOR2107-cohort were analyzed in this cross-sectional study using tract-based spatial statistics for diffusion tensor imaging. First, the effects of disease state (acute v. remitted), current symptom severity (BDI-score) and course of illness (number of hospitalizations) on fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity were analyzed separately. Second, disease state and BDI-scores were analyzed in conjunction with the number of hospitalizations to disentangle their effects.

Results

Disease state (pFWE < 0.042) and number of hospitalizations (pFWE< 0.032) were associated with decreased FA and increased MD and RD in the bilateral SLF. A trend was found for the BDI-score (pFWE > 0.067). When analyzed simultaneously only the effect of course of illness remained significant (pFWE < 0.040) mapping to the right SLF.

Conclusions

Decreased FA and increased MD and RD values in the SLF are associated with more hospitalizations when controlling for current psychopathology. SLF fiber integrity could reflect cumulative illness burden at a neurobiological level and should be targeted in future longitudinal analyses.

Type
Original Article
Copyright
Copyright © The Author(s), 2020. 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

Abe, O., Yamasue, H., Kasai, K., Yamada, H., Aoki, S., Inoue, H., … Ohtomo, K. (2010). Voxel-based analyses of gray/white matter volume and diffusion tensor data in major depression. Psychiatry Research, 181, 6470.CrossRefGoogle ScholarPubMed
Andersson, J. L. R., & Sotiropoulos, S. N. (2016). An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging. NeuroImage, 125, 10631078.CrossRefGoogle ScholarPubMed
Bae, J. N., MacFall, J. R., Krishnan, K. R. R., Payne, M. E., Steffens, D. C., & Taylor, W. D. (2006). Dorsolateral prefrontal cortex and anterior cingulate cortex white matter alterations in late-life depression. Biological Psychiatry, 60, 13561363.CrossRefGoogle ScholarPubMed
Bao, A.-M., & Swaab, D. F. (2019). The human hypothalamus in mood disorders: The HPA axis in the center. IBRO Reports, 6, 4553.CrossRefGoogle ScholarPubMed
Barbu, M. C., Zeng, Y., Shen, X., Cox, S. R., Clarke, T.-K., Gibson, J., … Whalley, H. C. (2019). Association of whole-genome and NETRIN1 signaling pathway-derived polygenic risk scores for major depressive disorder and white matter microstructure in the UK biobank. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 4, 91100.Google ScholarPubMed
Beck, A. T., Ward, C. H., Mendelson, M., Mock, J., & Erbaugh, J. (1961). An inventory for measuring depression. Archives of General Psychiatry, 4, 561571.CrossRefGoogle ScholarPubMed
Behrens, T. E. J., Woolrich, M. W., Jenkinson, M., Johansen-Berg, H., Nunes, R. G., Clare, S., … Smith, S. M. (2003). Characterization and propagation of uncertainty in diffusion-weighted MR imaging. Magnetic Resonance in Medicine, 50, 10771088.CrossRefGoogle ScholarPubMed
Bergamino, M., Kuplicki, R., Victor, T. A., Cha, Y.-H., & Paulus, M. P. (2017). Comparison of two different analysis approaches for DTI free-water corrected and uncorrected maps in the study of white matter microstructural integrity in individuals with depression. Human Brain Mapping, 38, 46904702.CrossRefGoogle Scholar
Bora, E., Harrison, B. J., Yücel, M., & Pantelis, C. (2013). Cognitive impairment in euthymic major depressive disorder: A meta-analysis. Psychological Medicine, 43, 20172026.CrossRefGoogle ScholarPubMed
Bracht, T., Jones, D. K., Müller, T. J., Wiest, R., & Walther, S. (2015). Limbic white matter microstructure plasticity reflects recovery from depression. Journal of Affective Disorders, 170, 143149.CrossRefGoogle ScholarPubMed
Burcusa, S. L., & Iacono, W. G. (2007). Risk for recurrence in depression. Clinical Psychology Review, 27, 959985.CrossRefGoogle ScholarPubMed
Campbell, S., & MacQueen, G. (2004). The role of the hippocampus in the pathophysiology of major depression. Journal of Psychiatry and Neuroscience, 29, 417426.Google ScholarPubMed
Cross, D., Fani, N., Powers, A., & Bradley, B. (2017). Neurobiological development in the context of childhood trauma. Clinical Psychology, 24, 111124.Google ScholarPubMed
Dalby, R. B., Frandsen, J., Chakravarty, M. M., Ahdidan, J., Sørensen, L., Rosenberg, R., … Ostergaard, L. (2010). Depression severity is correlated to the integrity of white matter fiber tracts in late-onset major depression. Psychiatry Research, 184, 3848.CrossRefGoogle Scholar
de Carlo, V., Calati, R., & Serretti, A. (2016). Socio-demographic and clinical predictors of non-response/non-remission in treatment resistant depressed patients: A systematic review. Psychiatry Research, 240, 421430.CrossRefGoogle ScholarPubMed
de Diego-Adeliño, J., Pires, P., Gómez-Ansón, B., Serra-Blasco, M., Vives-Gilabert, Y., Puigdemont, D., … Portella, M. J. (2014). Microstructural white-matter abnormalities associated with treatment resistance, severity and duration of illness in major depression. Psychological Medicine, 44, 11711182.CrossRefGoogle ScholarPubMed
Doolin, K., Andrews, S., Carballedo, A., McCarthy, H., O'Hanlon, E., Tozzi, L., & Frodl, T. (2019). Longitudinal diffusion weighted imaging of limbic regions in patients with major depressive disorder after 6 years and partial to full remission. Psychiatry Research. Neuroimaging, 287, 7586.CrossRefGoogle ScholarPubMed
Evans, V. C., Iverson, G. L., Yatham, L. N., & Lam, R. W. (2014). The relationship between neurocognitive and psychosocial functioning in major depressive disorder: A systematic review. The Journal of Clinical Psychiatry, 75, 13591370.CrossRefGoogle ScholarPubMed
Feldman, H. M., Yeatman, J. D., Lee, E. S., Barde, L. H. F., & Gaman-Bean, S. (2010). Diffusion tensor imaging: A review for pediatric researchers and clinicians. Journal of Developmental and Behavioral Pediatrics : JDBP, 31, 346356.CrossRefGoogle ScholarPubMed
Ferrari, A. J., Charlson, F. J., Norman, R. E., Patten, S. B., Freedman, G., Murray, C. J. L., … Whiteford, H. A. (2013). Burden of depressive disorders by country, sex, age, and year: Findings from the global burden of disease study 2010. PLoS Medicine, 10, e1001547.CrossRefGoogle ScholarPubMed
Gorwood, P., Corruble, E., Falissard, B., & Goodwin, G. M. (2008). Toxic effects of depression on brain function: Impairment of delayed recall and the cumulative length of depressive disorder in a large sample of depressed outpatients. The American Journal of Psychiatry, 165, 731739.CrossRefGoogle Scholar
Guo, W.-B., Liu, F., Chen, J.-D., Xu, X.-J., Wu, R.-R., Ma, C.-Q., … Zhao, J.-P. (2012a). Altered white matter integrity of forebrain in treatment-resistant depression: A diffusion tensor imaging study with tract-based spatial statistics. Progress in Neuro-Psychopharmacology & Biological Psychiatry, 38, 201206.CrossRefGoogle Scholar
Guo, W.-B., Liu, F., Xue, Z.-M., Gao, K., Wu, R.-R., Ma, C.-Q., … Zhao, J.-P. (2012b). Altered white matter integrity in young adults with first-episode, treatment-naive, and treatment-responsive depression. Neuroscience Letters, 522, 139144.CrossRefGoogle Scholar
Harada, K., Ikuta, T., Nakashima, M., Watanuki, T., Hirotsu, M., Matsubara, T., … Matsuo, K. (2018). Altered connectivity of the anterior cingulate and the posterior superior temporal gyrus in a longitudinal study of later-life depression. Frontiers in Aging Neuroscience, 10, 31.CrossRefGoogle Scholar
Hovens, J. G. F. M., Giltay, E. J., Wiersma, J. E., Spinhoven, P., Penninx, B. W. J. H., & Zitman, F. G. (2012). Impact of childhood life events and trauma on the course of depressive and anxiety disorders. Acta Psychiatrica Scandinavica, 126, 198207.CrossRefGoogle ScholarPubMed
Hua, K., Zhang, J., Wakana, S., Jiang, H., Li, X., Reich, D. S., … Mori, S. (2008). Tract probability maps in stereotaxic spaces: Analyses of white matter anatomy and tract-specific quantification. NeuroImage, 39, 336347.CrossRefGoogle ScholarPubMed
Huang, H., Gundapuneedi, T., & Rao, U. (2012). White matter disruptions in adolescents exposed to childhood maltreatment and vulnerability to psychopathology. Neuropsychopharmacology, 37, 26932701.CrossRefGoogle ScholarPubMed
Jauregui-Huerta, F., Ruvalcaba-Delgadillo, Y., Gonzalez-Castañeda, R., Garcia-Estrada, J., Gonzalez-Perez, O., & Luquin, S. (2010). Responses of glial cells to stress and glucocorticoids. Current Immunology Reviews, 6, 195204.CrossRefGoogle ScholarPubMed
Jenkinson, M., Beckmann, C. F., Behrens, T. E. J., Woolrich, M. W., & Smith, S. M. (2012). FSL. NeuroImage, 62, 782790.CrossRefGoogle ScholarPubMed
Jia, Z., Huang, X., Wu, Q., Zhang, T., Lui, S., Zhang, J., … Gong, Q. (2010). High-field magnetic resonance imaging of suicidality in patients with major depressive disorder. The American Journal of Psychiatry, 167, 13811390.CrossRefGoogle ScholarPubMed
Jones, D. K., Knösche, T. R., & Turner, R. (2013). White matter integrity, fiber count, and other fallacies: The do's and don'ts of diffusion MRI. NeuroImage, 73, 239254.CrossRefGoogle ScholarPubMed
Kanai, T., Takeuchi, H., Furukawa, T. A., Yoshimura, R., Imaizumi, T., Kitamura, T., & Takahashi, K. (2003). Time to recurrence after recovery from major depressive episodes and its predictors. Psychological Medicine, 33, 839845.CrossRefGoogle ScholarPubMed
Keller, M. B., & Boland, R. J. (1998). Implications of failing to achieve successful long-term maintenance treatment of recurrent unipolar major depression. Biological Psychiatry, 44, 348360.CrossRefGoogle ScholarPubMed
Kennedy, N., Abbott, R., & Paykel, E. S. (2004). Longitudinal syndromal and sub-syndromal symptoms after severe depression: 10-year follow-up study. The British Journal of Psychiatry, 184, 330336.CrossRefGoogle ScholarPubMed
Kerchner, G. A., Racine, C. A., Hale, S., Wilheim, R., Laluz, V., Miller, B. L., & Kramer, J. H. (2012). Cognitive processing speed in older adults: Relationship with white matter integrity. PLoS One, 7, e50425.CrossRefGoogle ScholarPubMed
Kircher, T., Wöhr, M., Nenadic, I., Schwarting, R., Schratt, G., Alferink, J., … Dannlowski, U. (2019). Neurobiology of the major psychoses: A translational perspective on brain structure and function-the FOR2107 consortium. European Archives of Psychiatry and Clinical Neuroscience, 269, 949962.CrossRefGoogle ScholarPubMed
Kraus, C., Kadriu, B., Lanzenberger, R. Jr., Carlos, A. Z. Jr., & Kasper, S. (2019). Prognosis and improved outcomes in major depression: A review. Translational Psychiatry 9, 127.CrossRefGoogle ScholarPubMed
Le Bihan, D. (2003). Looking into the functional architecture of the brain with diffusion MRI. Nature Reviews. Neuroscience, 4, 469480.CrossRefGoogle ScholarPubMed
Li, L., Ma, N., Li, Z., Tan, L., Liu, J., Gong, G., … Xu, L. (2007). Prefrontal white matter abnormalities in young adult with major depressive disorder: A diffusion tensor imaging study. Brain Research, 1168, 124128.CrossRefGoogle ScholarPubMed
Madhavan, K. M., McQueeny, T., Howe, S. R., Shear, P., & Szaflarski, J. (2014). Superior longitudinal fasciculus and language functioning in healthy aging. Brain Research, 1562, 1122.CrossRefGoogle ScholarPubMed
McEwen, B. S. (2003). Interacting mediators of allostasis and allostatic load: Towards an understanding of resilience in aging. Metabolism: Clinical and Experimental, 52, 1016.CrossRefGoogle Scholar
Meinert, S., Repple, J., Nenadic, I., Krug, A., Jansen, A., Grotegerd, D., … Dannlowski, U. (2019). Reduced fractional anisotropy in depressed patients due to childhood maltreatment rather than diagnosis. Neuropsychopharmacology, 44, 20652072.CrossRefGoogle ScholarPubMed
Meinert, S., Repple, J., Nenadic, I., Krug, A., Jansen, A., Grotegerd, D., … Dannlowski, U. (accepted). Changes in white matter fiber structure in depressed patients due to childhood maltreatment rather than diagnosis. Neuropsychopharmacology.Google Scholar
Mori, S., Wakana, S., van Zijl, P. C. M., & Nagae-Poetscher, L. M. (2005). MRI atlas of human white matter. Amsterdam, The Netherlands: Elsevier.Google Scholar
Murphy, M. L., & Frodl, T. (2011). Meta-analysis of diffusion tensor imaging studies shows altered fractional anisotropy occurring in distinct brain areas in association with depression. Biology of Mood & Anxiety Disorders, 1, 3.CrossRefGoogle ScholarPubMed
Nichols, T. E., & Holmes, A. P. (2002). Nonparametric permutation tests for functional neuroimaging: A primer with examples. Human Brain Mapping, 15, 125.CrossRefGoogle ScholarPubMed
Nobuhara, K., Okugawa, G., Sugimoto, T., Minami, T., Tamagaki, C., Takase, K., … Kinoshita, T. (2006). Frontal white matter anisotropy and symptom severity of late-life depression: A magnetic resonance diffusion tensor imaging study. Journal of Neurology, Neurosurgery, and Psychiatry, 77, 120122.CrossRefGoogle ScholarPubMed
Oberlander, T. F., Weinberg, J., Papsdorf, M., Grunau, R., Misri, S., & Devlin, A. M. (2008). Prenatal exposure to maternal depression, neonatal methylation of human glucocorticoid receptor gene (NR3C1) and infant cortisol stress responses. Epigenetics, 3, 97106.CrossRefGoogle ScholarPubMed
Oguz, I., Farzinfar, M., Matsui, J., Budin, F., Liu, Z., Gerig, G., … Styner, M. (2014). DTIPrep: Quality control of diffusion-weighted images. Frontiers in Neuroinformatics, 8, 4.CrossRefGoogle ScholarPubMed
Ormel, J., Oldehinkel, A. J., Nolen, W. A., & Vollebergh, W. (2004). Psychosocial disability before, during, and after a major depressive episode: A 3-wave population-based study of state, scar, and trait effects. Archives of General Psychiatry, 61, 387392.CrossRefGoogle Scholar
Otte, C., Gold, S. M., Penninx, B. W., Pariante, C. M., Etkin, A., Fava, M., … Schatzberg, A. F. (2016). Major depressive disorder. Nature Reviews. Disease Primers, 2, 16065.CrossRefGoogle ScholarPubMed
Paykel, E. S. (2008). Partial remission, residual symptoms, and relapse in depression. Dialogues in Clinical Neuroscience, 10, 431437.CrossRefGoogle ScholarPubMed
PDR (2017). Physicians' desk reference (71st ed., 2017). Montvale, NJ: PDR Network.Google Scholar
Penninx, B. W. J. H., Nolen, W. A., Lamers, F., Zitman, F. G., Smit, J. H., Spinhoven, P., … Beekman, A. T. F. (2011). Two-year course of depressive and anxiety disorders: Results from the Netherlands study of depression and anxiety (NESDA). Journal of Affective Disorders, 133, 7685.CrossRefGoogle Scholar
Post, R. M., Leverich, G. S., Xing, G., & Weiss, R. B. (2001). Developmental vulnerabilities to the onset and course of bipolar disorder. Development and Psychopathology, 13, 581598.CrossRefGoogle Scholar
Redlich, R., Dohm, K., Grotegerd, D., Opel, N., Zwitserlood, P., Heindel, W., … Dannlowski, U. (2015). Reward processing in unipolar and bipolar depression: A functional MRI study. Neuropsychopharmacology, 40, 26232631.CrossRefGoogle ScholarPubMed
Repple, J., Mauritz, M., Meinert, S., de Lange, S. C., Grotegerd, D., Opel, N., … van den Heuvel, M. P. (2020). Severity of current depression and remission status are associated with structural connectome alterations in major depressive disorder. Molecular Psychiatry, 25, 15501558.CrossRefGoogle ScholarPubMed
Repple, J., Zaremba, D., Meinert, S., Grotegerd, D., Redlich, R., Förster, K., … Dannlowski, U. (2019). Time heals all wounds? A 2-year longitudinal diffusion tensor imaging study in major depressive disorder. Journal of Psychiatry & Neuroscience: JPN, 44, 407413.CrossRefGoogle ScholarPubMed
Rock, P. L., Roiser, J. P., Riedel, W. J., & Blackwell, A. D. (2014). Cognitive impairment in depression: A systematic review and meta-analysis. Psychological Medicine, 44, 20292040.CrossRefGoogle ScholarPubMed
Salami, A., Eriksson, J., Nilsson, L.-G., & Nyberg, L. (2012). Age-related white matter microstructural differences partly mediate age-related decline in processing speed but not cognition. Biochimica et Biophysica Acta, 1822, 408415.CrossRefGoogle Scholar
Shen, X., Adams, M. J., Ritakari, T. E., Cox, S. R., McIntosh, A. M., & Whalley, H. C. (2019). White matter microstructure and its relation to longitudinal measures of depressive symptoms in mid- and late life. Biological Psychiatry, 86, 759768.CrossRefGoogle ScholarPubMed
Smith, S. M. (2002). Fast robust automated brain extraction. Human Brain Mapping, 17, 143155.CrossRefGoogle ScholarPubMed
Smith, S. M., Jenkinson, M., Johansen-Berg, H., Rueckert, D., Nichols, T. E., Mackay, C. E., … Behrens, T. E. J. (2006). Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data. NeuroImage, 31, 14871505.CrossRefGoogle ScholarPubMed
Smith, S. M., Jenkinson, M., Woolrich, M. W., Beckmann, C. F., Behrens, T. E. J., Johansen-Berg, H., … Matthews, P. M. (2004). Advances in functional and structural MR image analysis and implementation as FSL. NeuroImage, 23(Suppl 1), S208S219.CrossRefGoogle ScholarPubMed
Smith, S. M., & Nichols, T. E. (2009). Threshold-free cluster enhancement: Addressing problems of smoothing, threshold dependence and localisation in cluster inference. NeuroImage, 44, 8398.CrossRefGoogle ScholarPubMed
Solomon, D. A., Keller, M. B., Leon, A. C., Mueller, T. I., Lavori, P. W., Shea, M. T., … Endicott, J. (2000). Multiple recurrences of major depressive disorder. The American Journal of Psychiatry, 157, 229233.CrossRefGoogle ScholarPubMed
Spijker, J., de Graaf, R., Bijl, R. V., Beekman, A. T. F., Ormel, J., & Nolen, W. A. (2004). Determinants of persistence of major depressive episodes in the general population. Results from the Netherlands Mental Health Survey and Incidence Study (NEMESIS). Journal of Affective Disorders, 81, 231240.CrossRefGoogle Scholar
Targum, S. D. (1984). Persistent neuroendocrine dysregulation in major depressive disorder: A marker for early relapse. Biological Psychiatry, 19, 305318.Google ScholarPubMed
Tarullo, A. R., & Gunnar, M. R. (2006). Child maltreatment and the developing HPA axis. Hormones and Behavior, 50, 632639.CrossRefGoogle ScholarPubMed
Terenina, E. E., Cavigelli, S., Mormede, P., Zhao, W., Parks, C., Lu, L., … Mulligan, M. K. (2019). Genetic factors mediate the impact of chronic stress and subsequent response to novel acute stress. Frontiers in Neuroscience, 13, 438.CrossRefGoogle ScholarPubMed
Tozzi, L., Carballedo, A., Wetterling, F., McCarthy, H., O'Keane, V., Gill, M., … Frodl, T. (2016). Single-Nucleotide polymorphism of the FKBP5 gene and childhood maltreatment as predictors of structural changes in brain areas involved in emotional processing in depression. Neuropsychopharmacology, 41, 487497.CrossRefGoogle ScholarPubMed
Turken, A., Whitfield-Gabrieli, S., Bammer, R., Baldo, J. V., Dronkers, N. F., & Gabrieli, J. D. E. (2008). Cognitive processing speed and the structure of white matter pathways: Convergent evidence from normal variation and lesion studies. NeuroImage, 42, 10321044.CrossRefGoogle ScholarPubMed
Varghese, F. P., & Brown, E. S. (2001). The hypothalamic-pituitary-adrenal axis in Major depressive disorder: A brief primer for primary care physicians. Primary Care Companion to The Journal of Clinical Psychiatry, 3, 151155.CrossRefGoogle ScholarPubMed
Vogelbacher, C., Möbius, T. W. D., Sommer, J., Schuster, V., Dannlowski, U., Kircher, T., … Bopp, M. H. A. (2018). The Marburg-Münster affective disorders cohort study (MACS): A quality assurance protocol for MR neuroimaging data. NeuroImage, 172, 450460.CrossRefGoogle ScholarPubMed
Vos, T., Haby, M. M., Barendregt, J. J., Kruijshaar, M., Corry, J., & Andrews, G. (2004). The burden of major depression avoidable by longer-term treatment strategies. Archives of General Psychiatry, 61, 10971103.CrossRefGoogle ScholarPubMed
Wakana, S., Caprihan, A., Panzenboeck, M. M., Fallon, J. H., Perry, M., Gollub, R. L., … Mori, S. (2007). Reproducibility of quantitative tractography methods applied to cerebral white matter. NeuroImage, 36, 630644.CrossRefGoogle ScholarPubMed
Williams, J. M. G., Barnhofer, T., Crane, C., Herman, D., Raes, F., Watkins, E., & Dalgleish, T. (2007). Autobiographical memory specificity and emotional disorder. Psychological Bulletin, 133, 122148.CrossRefGoogle ScholarPubMed
Winston, G. P. (2012). The physical and biological basis of quantitative parameters derived from diffusion MRI. Quantitative Imaging in Medicine and Surgery, 2, 254265.Google ScholarPubMed
Wise, T., Radua, J., Nortje, G., Cleare, A. J., Young, A. H., & Arnone, D. (2016). Voxel-based meta-analytical evidence of structural disconnectivity in major depression and bipolar disorder. Biological Psychiatry, 79, 293302.CrossRefGoogle ScholarPubMed
Wittchen, H.-U., Wunderlich, U., Gruschwitz, S., & Zaudig, M. (1997). SKID I. Strukturiertes klinisches interview für DSM-IV. Achse I: Psychische störungen. Interviewheft und beurteilungsheft. Eine deutschsprachige, erweiterte bearbeitung der amerikanischen originalversion des SKID I. Göttingen: Hogrefe.Google Scholar
Woolrich, M. W., Jbabdi, S., Patenaude, B., Chappell, M., Makni, S., Behrens, T. E. J., … Smith, S. M. (2009). Bayesian Analysis of neuroimaging data in FSL. NeuroImage, 45, S173S186.CrossRefGoogle ScholarPubMed
Wu, F., Tang, Y., Xu, K., Kong, L., Sun, W., Wang, F., … Liu, Y. (2010). Whiter matter abnormalities in single-episode, medication-naive, short term duration of illness subjects with major depressive disorder. Psychiatry Research, 191, 8083.CrossRefGoogle Scholar
Zaremba, D., Dohm, K., Redlich, R., Grotegerd, D., Strojny, R., Meinert, S., … Dannlowski, U. (2018a). Association of brain cortical changes with relapse in patients with major depressive disorder. JAMA Psychiatry, 75, 484492.CrossRefGoogle Scholar
Zaremba, D., Enneking, V., Meinert, S., Förster, K., Bürger, C., Dohm, K., … Dannlowski, U. (2018b). Effects of cumulative illness severity on hippocampal gray matter volume in major depression: A voxel-based morphometry study. Psychological Medicine, 48, 23912398.CrossRefGoogle Scholar
Supplementary material: File

Meinert et al. supplementary material

Meinert et al. supplementary material

Download Meinert et al. supplementary material(File)
File 29.1 KB