Hostname: page-component-cd9895bd7-7cvxr Total loading time: 0 Render date: 2024-12-26T08:57:11.289Z Has data issue: false hasContentIssue false
  • English
  • Français

Anxious/depressed symptoms are related to microstructural maturation of white matter in typically developing youths

Published online by Cambridge University Press:  14 June 2016

Matthew D. Albaugh ,
Simon Ducharme ,
Sherif Karama ,
Richard Watts ,
John D. Lewis ,
Catherine Orr ,
Tuong-Vi Nguyen ,
Robert C. Mckinstry ,
Kelly N. Botteron  and
Alan C. Evans
...Show all authors
Matthew D. Albaugh*
Affiliation:
University of Vermont College of Medicine
Simon Ducharme
Affiliation:
McGill University
Sherif Karama
Affiliation:
McGill University
Richard Watts
Affiliation:
University of Vermont College of Medicine
John D. Lewis
Affiliation:
McGill University
Catherine Orr
Affiliation:
University of Vermont College of Medicine
Tuong-Vi Nguyen
Affiliation:
McGill University
Robert C. Mckinstry
Affiliation:
Washington University in St. Louis School of Medicine
Kelly N. Botteron
Affiliation:
Washington University in St. Louis School of Medicine
Alan C. Evans
Affiliation:
McGill University
James J. Hudziak
Affiliation:
University of Vermont College of Medicine
*
Address correspondence and reprint requests to: Matthew D. Albaugh, Vermont Center for Children, Youth and Families, University of Vermont College of Medicine, University Health Center Campus, 1 South Prospect Street, Burlington, VT 05401; E-mail: malbaugh@uvm.edu.
Get access Rights & Permissions [Opens in a new window]

Abstract

There are multiple recent reports of an association between anxious/depressed (A/D) symptomatology and the rate of cerebral cortical thickness maturation in typically developing youths. We investigated the degree to which anxious/depressed symptoms are tied to age-related microstructural changes in cerebral fiber pathways. The participants were part of the NIH MRI Study of Normal Brain Development. Child Behavior Checklist A/D scores and diffusion imaging were available for 175 youths (84 males, 91 females; 241 magnetic resonance imagings) at up to three visits. The participants ranged from 5.7 to 18.4 years of age at the time of the scan. Alignment of fractional anisotropy data was implemented using FSL/Tract-Based Spatial Statistics, and linear mixed model regression was carried out using SPSS. Child Behavior Checklist A/D was associated with the rate of microstructural development in several white matter pathways, including the bilateral anterior thalamic radiation, bilateral inferior longitudinal fasciculus, left superior longitudinal fasciculus, and right cingulum. Across these pathways, greater age-related fractional anisotropy increases were observed at lower levels of A/D. The results suggest that subclinical A/D symptoms are associated with the rate of microstructural development within several white matter pathways that have been implicated in affect regulation, as well as mood and anxiety psychopathology.

Type
Regular Articles
Information
Development and Psychopathology , Volume 29 , Issue 3 , August 2017 , pp. 751 - 758
Copyright
Copyright © Cambridge University Press 2016 

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.)

Footnotes

This project was funded in whole or in part with federal funds from the National Institute of Child Health and Human Development, the National Institute on Drug Abuse, the National Institute of Mental Health, and the National Institute of Neurological Disorders and Stroke (Contract Numbers N01-HD02-3343, N01-MH9-0002, N01-NS-9-2314, N01-NS-9-2315, N01-NS-9-2316, N01-NS-9-2317, N01-NS-9-2319, and N01-NS-9-2320). Key personnel from the six pediatric study centers may be found online at http://www.nih-pediatricmri.org. Dr. Albaugh is funded by a grant from the Child and Adolescent Psychology Training and Research Foundation, Dr. Ducharme has received funding from the Fonds de Recherche du Québec-Santé and the Montreal General Hospital Foundation, and Dr. Karama is supported by the Fonds de Recherche en Santé du Québec. The authors report no biomedical financial interests or potential conflicts of interest related to this article. The views herein do not necessarily represent the official views of the National Institute of Child Health and Human Development, the National Institute on Drug Abuse, the National Institute of Mental Health, the National Institute of Neurological Disorders and Stroke, the National Institutes of Health, the US Department of Health and Human Services, or any other agency of the United States government.

References

Achenbach, T. M. (1991). Manual for the Child Behavior Checklist 4–18 and 1991 Profile. Burlington VT: University of Vermont, Department of Psychiatry.Google Scholar
Achenbach, T. M., & Rescorla, L. A. (2001). Manual for the ASEBA School-Age Forms & Profiles. Burlington VT: University of Vermont, Research Center for Children, Youth and Families.Google Scholar
Basser, P. J., & Pierpaoli, C. (1996). Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. Journal of Magnetic Resonance B, 111, 209–219. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/8661285 CrossRefGoogle ScholarPubMed
Beaulieu, C. (2002). The basis of anisotropic water diffusion in the nervous system—A technical review. NMR in Biomedicine, 15, 435–455. doi:10.1002/nbm.782 CrossRefGoogle ScholarPubMed
Cascio, C. J., Gerig, G., & Piven, J. (2007). Diffusion tensor imaging: Application to the study of the developing brain. Journal of the American Academy of Child & Adolescent Psychiatry, 46, 213–223. doi:10.1097/01.chi.0000246064.93200.e8 CrossRefGoogle Scholar
Colman, I., Jones, P. B., Kuh, D., Weeks, M., Naicker, K., Richards, M., et al. (2014). Early development, stress and depression across the life course: Pathways to depression in a national British birth cohort. Psychological Medicine, 44, 2845–2854. doi:10.1017/S0033291714000385 CrossRefGoogle Scholar
Diggle, P. (2002). Analysis of longitudinal data (2nd ed.). Oxford: Oxford University Press.CrossRefGoogle Scholar
Ducharme, S., Albaugh, M. D., Hudziak, J. J., Botteron, K. N., Nguyen, T. V., Truong, C., et al. (2014). Anxious/depressed symptoms are linked to right ventromedial prefrontal cortical thickness maturation in healthy children and young adults. Cerebral Cortex, 24, 2941–2950. doi:10.1093/cercor/bht151 CrossRefGoogle ScholarPubMed
Ducharme, S., Hudziak, J., Botteron, K., Albaugh, M., Nguyen, T., Karama, S., et al. (2012). Decreased regional cortical thickness and thinning rate are associated with inattention symptoms in healthy children. Journal of the American Academy of Child & Adolescent Psychiatry, 51, 18–27.CrossRefGoogle ScholarPubMed
Evans, A. C. (2006). The NIH MRI study of normal brain development. NeuroImage, 30, 184–202. doi:10.1016/j.neuroimage.2005.09.068 CrossRefGoogle ScholarPubMed
Giedd, J. N., Lenroot, R. K., Shaw, P., Lalonde, F., Celano, M., White, S., et al. (2008). Trajectories of anatomic brain development as a phenotype. Novartis Foundation Symposium Journal, 289, 101–112; discussion 112–108, 193–105. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/18497098 CrossRefGoogle ScholarPubMed
Hudziak, J. J., Achenbach, T. M., Althoff, R. R., & Pine, D. S. (2007). A dimensional approach to developmental psychopathology. International Journal of Methods in Psychiatric Research, 16(Suppl. 1), S16–S23. doi:10.1002/mpr.217 CrossRefGoogle ScholarPubMed
Insel, T., Cuthbert, B., Garvey, M., Heinssen, R., Pine, D. S., Quinn, K., et al. (2010). Research domain criteria (RDoC): Toward a new classification framework for research on mental disorders. American Journal of Psychiatry, 167, 748–751. doi:10.1176/appi.ajp.2010.09091379 CrossRefGoogle Scholar
Kim, M. J., & Whalen, P. J. (2009). The structural integrity of an amygdala-prefrontal pathway predicts trait anxiety. Journal of Neuroscience, 29, 11614–11618. doi:10.1523/jneurosci.2335-09.2009 CrossRefGoogle ScholarPubMed
Kochunov, P., Glahn, D. C., Lancaster, J., Thompson, P. M., Kochunov, V., Rogers, B., et al. (2011). Fractional anisotropy of cerebral white matter and thickness of cortical gray matter across the lifespan. NeuroImage, 58, 41–49. doi:10.1016/j.neuroimage.2011.05.050 CrossRefGoogle ScholarPubMed
Lai, C. H., & Wu, Y. T. (2014). Alterations in white matter micro-integrity of the superior longitudinal fasciculus and anterior thalamic radiation of young adult patients with depression. Psychological Medicine, 44, 2825–2832. doi:10.1017/S0033291714000440 CrossRefGoogle ScholarPubMed
Lebel, C., Gee, M., Camicioli, R., Wieler, M., Martin, W., & Beaulieu, C. (2012). Diffusion tensor imaging of white matter tract evolution over the lifespan. NeuroImage, 60, 340–352. doi:10.1016/j.neuroimage.2011.11.094 CrossRefGoogle ScholarPubMed
Lebel, C., Walker, L., Leemans, A., Phillips, L., & Beaulieu, C. (2008). Microstructural maturation of the human brain from childhood to adulthood. NeuroImage, 40, 1044–1055. doi:10.1016/j.neuroimage.2007.12.053 CrossRefGoogle ScholarPubMed
Mabbott, D. J., Noseworthy, M., Bouffet, E., Laughlin, S., & Rockel, C. (2006). White matter growth as a mechanism of cognitive development in children. NeuroImage, 33, 936–946. doi:10.1016/j.neuroimage.2006.07.024 CrossRefGoogle ScholarPubMed
Makris, N., Worth, A. J., Sorensen, A. G., Papadimitriou, G. M., Wu, O., Reese, T. G., et al. (1997). Morphometry of in vivo human white matter association pathways with diffusion-weighted magnetic resonance imaging. Annals of Neurology, 42, 951–962. doi:10.1002/ana.410420617 CrossRefGoogle ScholarPubMed
Mukherjee, P., Miller, J. H., Shimony, J. S., Conturo, T. E., Lee, B. C., Almli, C. R., et al. (2001). Normal brain maturation during childhood: Developmental trends characterized with diffusion-tensor MR imaging. Radiology, 221, 349–358. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/11687675 CrossRefGoogle ScholarPubMed
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 and Anxiety Disorders, 1, 3. doi:10.1186/2045-5380-1-3 CrossRefGoogle ScholarPubMed
Newman, E., Thompson, W. K., Bartsch, H., Hagler, D. J. Jr., Chen, C. H., Brown, T. T., et al. (2015). Anxiety is related to indices of cortical maturation in typically developing children and adolescents. Brain Structure and Function. Advance online publication. doi:10.1007/s00429-015-1085-9 Google ScholarPubMed
Ni, H., Kavcic, V., Zhu, T., Ekholm, S., & Zhong, J. (2006). Effects of number of diffusion gradient directions on derived diffusion tensor imaging indices in human brain. American Journal of Neuroradiology, 27, 1776–1781. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/16971635 Google ScholarPubMed
North, C. R., Wild, T. C., Zwaigenbaum, L., & Colman, I. (2013). Early neurodevelopment and self-reported adolescent symptoms of depression and anxiety in a National Canadian Cohort Study. PLOS ONE, 8, e56804. doi:10.1371/journal.pone.0056804 CrossRefGoogle Scholar
Phelps, E. A., Delgado, M. R., Nearing, K. I., & LeDoux, J. E. (2004). Extinction learning in humans: Role of the amygdala and vmPFC. Neuron, 43, 897–905. doi:10.1016/j.neuron.2004.08.042 CrossRefGoogle ScholarPubMed
Pierpaoli, C., Jezzard, P., Basser, P. J., Barnett, A., & Di Chiro, G. (1996). Diffusion tensor MR imaging of the human brain. Radiology, 201, 637–648. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/8939209 CrossRefGoogle ScholarPubMed
Pierpaoli, C., Walker, L., Irfanoglu, M. O., Barnett, A., Basser, P., Chang, L.-C., et al. (2010). TORTOISE: An integrated software package for processing of diffusion MRI data. Paper presented at the ISMRM 18th annual meeting, Stockholm.Google Scholar
Quirk, G. J., & Beer, J. S. (2006). Prefrontal involvement in the regulation of emotion: Convergence of rat and human studies. Current Opinion in Neurobiology, 16, 723–727. doi:10.1016/j.conb.2006.07.004 CrossRefGoogle ScholarPubMed
Quirk, G. J., Garcia, R., & Gonzalez-Lima, F. (2006). Prefrontal mechanisms in extinction of conditioned fear. Biological Psychiatry, 60, 337–343. doi:10.1016/j.biopsych.2006.03.010 CrossRefGoogle ScholarPubMed
Quirk, G. J., Likhtik, E., Pelletier, J. G., & Pare, D. (2003). Stimulation of medial prefrontal cortex decreases the responsiveness of central amygdala output neurons. Journal of Neuroscience, 23, 8800–8807. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/14507980 CrossRefGoogle ScholarPubMed
Rohde, G. K., Barnett, A. S., Basser, P. J., Marenco, S., & Pierpaoli, C. (2004). Comprehensive approach for correction of motion and distortion in diffusion-weighted MRI. Magnetic Resonance in Medicine, 51, 103–114. doi:10.1002/mrm.10677 CrossRefGoogle ScholarPubMed
Rueckert, D., Sonoda, L. I., Hayes, C., Hill, D. L., Leach, M. O., & Hawkes, D. J. (1999). Nonrigid registration using free-form deformations: Application to breast MR images. IEEE Transactions on Medical Imaging, 18, 712–721. doi:10.1109/42.796284 CrossRefGoogle ScholarPubMed
Schmithorst, V. J., Wilke, M., Dardzinski, B. J., & Holland, S. K. (2002). Correlation of white matter diffusivity and anisotropy with age during childhood and adolescence: A cross-sectional diffusion-tensor MR imaging study. Radiology, 222, 212–218. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/11756728 CrossRefGoogle ScholarPubMed
Shaw, P., Eckstrand, K., Sharp, W., Blumenthal, J., Lerch, J. P., Greenstein, D., et al. (2007). Attention-deficit/hyperactivity disorder is characterized by a delay in cortical maturation. Proceedings of the National Academy of Sciences, 104, 19649–19654. doi:10.1073/pnas.0707741104 CrossRefGoogle ScholarPubMed
Shaw, P., Gilliam, M., Liverpool, M., Weddle, C., Malek, M., Sharp, W., et al. (2011). Cortical development in typically developing children with symptoms of hyperactivity and impulsivity: Support for a dimensional view of attention deficit hyperactivity disorder. American Journal of Psychiatry, 168, 143–151. doi:10.1176/appi.ajp.2010.10030385 CrossRefGoogle ScholarPubMed
Shaw, P., Greenstein, D., Lerch, J., Clasen, L., Lenroot, R., Gogtay, N., et al. (2006). Intellectual ability and cortical development in children and adolescents. Nature, 440, 676–679.CrossRefGoogle ScholarPubMed
Singer, J. D., & Willett, J. B. (2003). Applied longitudinal data analysis: Modeling change and event occurrence. Oxford: Oxford University Press.CrossRefGoogle Scholar
Smith, S. M., Jenkinson, M., Johansen-Berg, H., Rueckert, D., Nichols, T. E., Mackay, C. E., et al. (2006). Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data. NeuroImage, 31, 1487–1505. doi:10.1016/j.neuroimage.2006.02.024 CrossRefGoogle ScholarPubMed
Smith, S. M., Jenkinson, M., Woolrich, M. W., Beckmann, C. F., Behrens, T. E., Johansen-Berg, H., et al. (2004). Advances in functional and structural MR image analysis and implementation as FSL. NeuroImage, 23(Suppl. 1), S208–S219. doi:10.1016/j.neuroimage.2004.07.051 CrossRefGoogle ScholarPubMed
Snook, L., Paulson, L. A., Roy, D., Phillips, L., & Beaulieu, C. (2005). Diffusion tensor imaging of neurodevelopment in children and young adults. NeuroImage, 26, 1164–1173. doi:10.1016/j.neuroimage.2005.03.016 CrossRefGoogle ScholarPubMed
Takao, H., Hayashi, N., Inano, S., & Ohtomo, K. (2011). Effect of head size on diffusion tensor imaging. NeuroImage, 57, 958–967. doi:10.1016/j.neuroimage.2011.05.019 CrossRefGoogle ScholarPubMed
Waber, D. P., De Moor, C., Forbes, P. W., Almli, C. R., Botteron, K. N., Leonard, G., et al. (2007). The NIH MRI study of normal brain development: Performance of a population based sample of healthy children aged 6 to 18 years on a neuropsychological battery. Journal of the International Neuropsychology Society, 13, 729–746. doi:10.1017/S1355617707070841 CrossRefGoogle ScholarPubMed
Walker, L., Chang, L. C., Nayak, A., Irfanoglu, M. O., Botteron, K. N., McCracken, J., et al. (2015). The diffusion tensor imaging (DTI) component of the NIH MRI study of normal brain development (PedsDTI). NeuroImage. Advance online publication. doi:10.1016/j.neuroimage.2015.05.083 Google ScholarPubMed
Walker, L., Chang, L. C., Nayak, A., Irfanoglu, M. O., Botteron, K. N., McCracken, J., et al. (2016). The diffusion tensor imaging (DTI) component of the NIH MRI study of normal brain development (PedsDTI). NeuroImage, 124(Pt. B), 1125–1130. doi:10.1016/j.neuroimage.2015.05.083 CrossRefGoogle ScholarPubMed
Walker, L., Curry, M., Nayak, A., Lange, N., & Pierpaoli, C. (2013). A framework for the analysis of phantom data in multicenter diffusion tensor imaging studies. Human Brain Mapping, 34, 2439–2454. doi:10.1002/hbm.22081 CrossRefGoogle ScholarPubMed
Westlye, L. T., Bjornebekk, A., Grydeland, H., Fjell, A. M., & Walhovd, K. B. (2011). Linking an anxiety-related personality trait to brain white matter microstructure: Diffusion tensor imaging and harm avoidance. Archives of General Psychiatry, 68, 369–377. doi:10.1001/archgenpsychiatry.2011.2468/4/369 CrossRefGoogle ScholarPubMed
Wu, M., Chang, L. C., Walker, L., Lemaitre, H., Barnett, A. S., Marenco, S., et al. (2008). Comparison of EPI distortion correction methods in diffusion tensor MRI using a novel framework. Medical Image Computing and Computer-Assisted Intervention, 11(Pt. 2), 321–329. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/18982621 Google ScholarPubMed
Supplementary material: File

Albaugh supplementary material

Figures S1-S2

Download Albaugh supplementary material(File)
File 142.8 KB