Objective/Hypothesis: Adolescence is a time period notable for significant brain maturation and refinement of neuronal connections, and also for a marked increase in prevalence of Major Depressive Disorder (MDD). Fronto-limbic neural networks mediate emotional processing and are implicated in the pathophysiology of MDD. Our over-arching hypothesis is that MDD results from abnormal development of fronto-limbic neural circuitry. Recent advances in neuroimaging methodology have allowed for measuring the strength of neural connections, or """"""""connectivity"""""""". For instance, diffusion tensor imaging (DTI) can be used to measure """"""""structural connectivity"""""""", and resting-state functional magnetic resonance imaging (rsfMRI) can be used to measure """"""""functional connectivity"""""""". In a preliminary study using these methods in 14 adolescents with MDD and 14 healthy comparison subjects, we identified a reduction in both structural and functional connectivity between the subgenual anterior cingulate cortex and other key fronto-limbic areas in the depressed group. Conclusions from these findings are limited due to confounds related to small sample size and medication exposure in the depressed group. In order to better characterize the developmental abnormalities in fronto-limbic networks in depressed adolescents, we now propose to conduct a multi-modal neuroimaging investigation to examine structural and functional connectivity in a larger, treatment-naive sample. Proposed Methods: 30 adolescents aged 13-17 with familial, adolescent onset, moderate-severe MDD and 30 healthy comparisons matched for sex, handedness, SES and IQ will be recruited from clinical settings at the University of Minnesota and the community. Assessment will include the K-SADS-PL, BDI, CDRS, and WASI. Neuorimaging scans will be obtained at a research-dedicated Siemens 3T scanner at UMN. Structural, diffusion tensor, and resting-state functional images will be collected. Structural connectivity data will be analyzed using a voxel-wise comparison and also using probabilistic tractography. Functional connectivity will be analyzed using a seed-based approach. Discussion/Significance: Demonstration of abnormal connectivity within fronto-limbic neural networks in depressed teens will inform our understanding of the neurodevelopmental mechanisms of adolescent MDD. The dataset from the proposed project will provide the foundation for future longitudinal investigations to (1) delineate trajectories of neural development in individuals with MDD, (2) identify predictors for treatment response, (3) examine the impact of treatment on neural circuitry, and (4) investigate the genetic and environmental underpinnings of abnormal neural development in adolescent MDD. By identifying neurodevelopmental abnormalities that underlie the pediatric depression, our hope is to inform the development of interventions that will alter negative trajectories.

Public Health Relevance

Neurobiological research is urgently needed to address the significant public health burden posed by Major Depressive Disorder (MDD). This illness frequently begins in adolescence. Since early interventions hold promise for impacting malleable systems and altering trajectories, advancement in the neurodevelopmental biology of MDD during adolescence is especially critical.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Mentored Patient-Oriented Research Career Development Award (K23)
Project #
5K23MH090421-03
Application #
8212487
Study Section
Special Emphasis Panel (ZRG1-BBBP-R (02))
Program Officer
Garvey, Marjorie A
Project Start
2010-03-29
Project End
2015-01-31
Budget Start
2012-02-01
Budget End
2013-01-31
Support Year
3
Fiscal Year
2012
Total Cost
$162,833
Indirect Cost
$12,062
Name
University of Minnesota Twin Cities
Department
Psychiatry
Type
Schools of Medicine
DUNS #
555917996
City
Minneapolis
State
MN
Country
United States
Zip Code
55455
Koenig, Julian; Westlund Schreiner, Melinda; Klimes-Dougan, Bonnie et al. (2018) Increases in orbitofrontal cortex thickness following antidepressant treatment are associated with changes in resting state autonomic function in adolescents with major depression - Preliminary findings from a pilot study. Psychiatry Res Neuroimaging 281:35-42
Koenig, Julian; Westlund Schreiner, Melinda; Klimes-Dougan, Bonnie et al. (2018) Brain structural thickness and resting state autonomic function in adolescents with major depression. Soc Cogn Affect Neurosci 13:741-753
Cullen, Kathryn R; LaRiviere, Lori L; Vizueta, Nathalie et al. (2016) Brain activation in response to overt and covert fear and happy faces in women with borderline personality disorder. Brain Imaging Behav 10:319-31
Cullen, Kathryn R; Klimes-Dougan, Bonnie; Vu, Dung Pham et al. (2016) Neural Correlates of Antidepressant Treatment Response in Adolescents with Major Depressive Disorder. J Child Adolesc Psychopharmacol 26:705-712
Musgrove, Donald R; Hughes, John; Eberly, Lynn E (2016) Fast, fully Bayesian spatiotemporal inference for fMRI data. Biostatistics 17:291-303
Sommerfeldt, Sasha L; Cullen, Kathryn R; Han, Georges et al. (2016) Executive Attention Impairment in Adolescents With Major Depressive Disorder. J Clin Child Adolesc Psychol 45:69-83
Westlund Schreiner, Melinda; Klimes-Dougan, Bonnie; Begnel, Erin D et al. (2015) Conceptualizing the neurobiology of non-suicidal self-injury from the perspective of the Research Domain Criteria Project. Neurosci Biobehav Rev 57:381-91
Musgrove, Donald R; Eberly, Lynn E; Klimes-Dougan, Bonnie et al. (2015) Impaired Bottom-Up Effective Connectivity Between Amygdala and Subgenual Anterior Cingulate Cortex in Unmedicated Adolescents with Major Depression: Results from a Dynamic Causal Modeling Analysis. Brain Connect 5:608-19
Cullen, Kathryn R; Westlund, Melinda K; Klimes-Dougan, Bonnie et al. (2014) Abnormal amygdala resting-state functional connectivity in adolescent depression. JAMA Psychiatry 71:1138-47
Xu, Tingting; Cullen, Kathryn R; Houri, Alaa et al. (2014) Classification of borderline personality disorder based on spectral power of resting-state fMRI. Conf Proc IEEE Eng Med Biol Soc 2014:5036-9

Showing the most recent 10 out of 23 publications