Structural brain development and depression onset during adolescence: a prospective longitudinal study.

OBJECTIVE The authors sought to investigate whether the structural development of limbic, striatal, and prefrontal regions that are critically implicated in the pathophysiology of depression is associated with adolescent-onset depression. METHOD In a longitudinal design, a risk enriched community sample of 86 adolescents (41 of them female) who had no history of depressive disorders participated in neuroimaging assessments conducted during early (age 12) and midadolescence (age 16). Onset of depressive disorders was assessed for the period spanning early to late adolescence (ages 12 to 18). Thirty participants experienced a first episode of a depressive disorder during the follow-up period. The authors assessed whether onset of depressive disorder was associated with structural change in limbic, striatal, and prefrontal cortical regions from early to mid-adolescence. RESULTS Volumetric change in the hippocampus, amygdala, and putamen from early to mid-adolescence was associated with the onset of depression during adolescence. Attenuated growth of the hippocampus and attenuated reduction in putamen volume over time were associated with the onset of depression. Sex moderated the association between amygdala growth and depression such that exaggerated growth and attenuated growth of the amygdala were associated with depression in females and males, respectively. Across time, smaller nucleus accumbens volume was associated with depression in females only. CONCLUSIONS These findings suggest that alterations in the developmental trajectories of limbic and striatal regions during adolescence may represent a neurobiological manifestation of a risk factor for the development of depression during this critical period and thus may provide clues as to etiological mechanisms of this disorder.

[1]  Alan C. Evans,et al.  Anxious/depressed symptoms are linked to right ventromedial prefrontal cortical thickness maturation in healthy children and young adults. , 2014, Cerebral cortex.

[2]  A. Petersen,et al.  A self-report measure of pubertal status: Reliability, validity, and initial norms , 1988, Journal of youth and adolescence.

[3]  M. Shad,et al.  Gray matter differences between healthy and depressed adolescents: a voxel-based morphometry study. , 2012, Journal of child and adolescent psychopharmacology.

[4]  R. C. Oldfield The assessment and analysis of handedness: the Edinburgh inventory. , 1971, Neuropsychologia.

[5]  A. Beck,et al.  An inventory for measuring clinical anxiety: psychometric properties. , 1988, Journal of consulting and clinical psychology.

[6]  H. Manji,et al.  Life Stress, Genes, and Depression: Multiple Pathways Lead to Increased Risk and New Opportunities for Intervention , 2004, Science's STKE.

[7]  C. Hammen,et al.  Hippocampal Changes Associated with Early-Life Adversity and Vulnerability to Depression , 2010, Biological Psychiatry.

[8]  Phil A. Silva,et al.  Development of depression from preadolescence to young adulthood: emerging gender differences in a 10-year longitudinal study. , 1998, Journal of abnormal psychology.

[9]  Kathryn R. Cullen,et al.  Toward dysfunctional connectivity: a review of neuroimaging findings in pediatric major depressive disorder , 2011, Brain Imaging and Behavior.

[10]  C. Dowrick,et al.  Can adjustment disorder and depressive episode be distinguished? Results from ODIN. , 2006, Journal of affective disorders.

[11]  Martin H. Teicher,et al.  Stress, sensitive periods and maturational events in adolescent depression , 2008, Trends in Neurosciences.

[12]  N. Ryan,et al.  Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime Version (K-SADS-PL): initial reliability and validity data. , 1997, Journal of the American Academy of Child and Adolescent Psychiatry.

[13]  L. Radloff The CES-D Scale , 1977 .

[14]  Gregory McCarthy,et al.  Scan–rescan reliability of subcortical brain volumes derived from automated segmentation , 2010, Human brain mapping.

[15]  Michael I. Miller,et al.  Amygdala Volume Analysis in Female Twins with Major Depression , 2007, Biological Psychiatry.

[16]  F. Jones,et al.  Scoring Occupational Categories for Social Research: A Review of Current Practice, with , 2001 .

[17]  F. Tarazi,et al.  Comparative postnatal development of dopamine D1, D2 and D4 receptors in rat forebrain , 2000, International Journal of Developmental Neuroscience.

[18]  A. Toga,et al.  In vivo evidence for post-adolescent brain maturation in frontal and striatal regions , 1999, Nature Neuroscience.

[19]  M. Weissman,et al.  Cortical thinning in persons at increased familial risk for major depression , 2009, Proceedings of the National Academy of Sciences.

[20]  Anders M. Fjell,et al.  Heterogeneity in Subcortical Brain Development: A Structural Magnetic Resonance Imaging Study of Brain Maturation from 8 to 30 Years , 2009, The Journal of Neuroscience.

[21]  Dean F. Wong,et al.  Sex Differences in Striatal Dopamine Release in Healthy Adults , 2006, Biological Psychiatry.

[22]  E. Phelps Human emotion and memory: interactions of the amygdala and hippocampal complex , 2004, Current Opinion in Neurobiology.

[23]  R. Schnabel,et al.  Separation-Induced Receptor Changes in the Hippocampus and Amygdala of Octodon degus: Influence of Maternal Vocalizations , 2003, The Journal of Neuroscience.

[24]  Satrajit S. Ghosh,et al.  Evaluating the validity of volume-based and surface-based brain image registration for developmental cognitive neuroscience studies in children 4 to 11years of age , 2010, NeuroImage.

[25]  D R Fish,et al.  Methods for normalization of hippocampal volumes measured with MR. , 1995, AJNR. American journal of neuroradiology.

[26]  C. Hammen,et al.  Toward an interpersonal life-stress model of depression: the developmental context of stress generation. , 2000, Development and psychopathology.

[27]  Jan Wacker,et al.  The role of the nucleus accumbens and rostral anterior cingulate cortex in anhedonia: Integration of resting EEG, fMRI, and volumetric techniques , 2009, NeuroImage.

[28]  E. Bora,et al.  Gray matter abnormalities in Major Depressive Disorder: a meta-analysis of voxel based morphometry studies. , 2012, Journal of affective disorders.

[29]  D. Rosenberg,et al.  Striatal volume abnormalities in treatment-naïve patients diagnosed with pediatric major depressive disorder. , 2008, Journal of child and adolescent psychopharmacology.

[30]  R. Olvera,et al.  Medial temporal lobe abnormalities in pediatric unipolar depression , 2007, Neuroscience Letters.

[31]  A. Simmons,et al.  Structural neuroimaging studies in major depressive disorder. Meta-analysis and comparison with bipolar disorder. , 2011, Archives of general psychiatry.

[32]  Jens C. Pruessner,et al.  The brain and the stress axis: The neural correlates of cortisol regulation in response to stress , 2009, NeuroImage.

[33]  JaneR . Taylor,et al.  Developmental neurocircuitry of motivation in adolescence: a critical period of addiction vulnerability. , 2003, The American journal of psychiatry.

[34]  R. Duman,et al.  A Neurotrophic Model for Stress-Related Mood Disorders , 2006, Biological Psychiatry.

[35]  K. Krishnan,et al.  Magnetic-resonance morphometry in patients with major depression , 1998, Psychiatry Research: Neuroimaging.

[36]  Jagath C. Rajapakse,et al.  Sexual dimorphism of the developing human brain , 1997, Progress in Neuro-Psychopharmacology and Biological Psychiatry.

[37]  M. Yücel,et al.  Childhood maltreatment and psychopathology affect brain development during adolescence. , 2013, Journal of the American Academy of Child and Adolescent Psychiatry.

[38]  A. Meyer-Lindenberg,et al.  5-HTTLPR polymorphism impacts human cingulate-amygdala interactions: a genetic susceptibility mechanism for depression , 2005, Nature Neuroscience.

[39]  E. Bora,et al.  Meta-analysis of volumetric abnormalities in cortico-striatal-pallidal-thalamic circuits in major depressive disorder , 2011, Psychological Medicine.

[40]  T. Achenbach Manual for the Youth Self-Report and 1991 profile , 1991 .