Early and late onset, first-episode, treatment-naive depression: same clinical symptoms, different regional neural activities.

BACKGROUND Patients with early onset depression (EOD) and late onset depression (LOD) have distinctive risk factors and clinical pictures. Using regional homogeneity (ReHo) approach, we were to test the hypothesis of the different abnormal neural activity between patients with EOD or LOD. METHODS Fifteen patients with EOD, 15 patients with LOD, 15 young healthy subjects (HS) and 15 old HS participated in the study. ReHo approach was employed to analyze the scans. RESULTS ANOVA analysis revealed widespread differences in ReHo values among the four groups throughout frontal, parietal, temporal, occipital cortex, cerebellum and limbic regions. Compared to LOD group, EOD group had higher ReHo in right precuneus (PCu) and bilateral superior frontal gyrus, and lower ReHo in left superior temporal gyrus. Compared to young HS, lower ReHo in left parahippocampal gyrus and higher ReHo in left fusiform gyrus and bilateral superior frontal gyrus were seen in EOD group; in contrast, in LOD group, lower ReHo in right PCu and higher ReHo in left superior temporal gyrus and left Crus I of the cerebellum were observed. Further ROC analysis suggested that the mean ReHo values in right PCu and bilateral superior frontal gyrus could serve as markers to identify patients with EOD from individuals with LOD. LIMITATION The large age gap may limit the translational value of our findings. CONCLUSIONS Patients with EOD and those with LOD have abnormal neural activities in different brain regions, although the two groups share the same symptoms.

[1]  Z. Y. Wang,et al.  A Chinese version of the Mini-Mental State Examination; impact of illiteracy in a Shanghai dementia survey. , 1988, Journal of clinical epidemiology.

[2]  M. Hamilton,et al.  Development of a rating scale for primary depressive illness. , 1967, The British journal of social and clinical psychology.

[3]  Feng Liu,et al.  Alterations of the amplitude of low-frequency fluctuations in treatment-resistant and treatment-response depression: A resting-state fMRI study , 2012, Progress in Neuro-Psychopharmacology and Biological Psychiatry.

[4]  Gwenn S. Smith,et al.  Functional neuroimaging in geriatric depression. , 2011, The Psychiatric clinics of North America.

[5]  P. Fransson.  How default is the default mode of brain function? Further evidence from intrinsic BOLD signal fluctuations , 2006, Neuropsychologia.

[6]  P. Oulis,et al.  Clinical correlates of age of onset in psychotic depression. , 2011, Archives of gerontology and geriatrics (Print).

[7]  R. O. Voshaar,et al.  Suicide in later life: a comparison between cases with early-onset and late-onset depression. , 2011, Journal of affective disorders.

[8]  G L Shulman,et al.  INAUGURAL ARTICLE by a Recently Elected Academy Member:A default mode of brain function , 2001 .

[9]  Abraham Z. Snyder,et al.  A default mode of brain function: A brief history of an evolving idea , 2007, NeuroImage.

[10]  Sylvain Houle,et al.  Lower dopamine transporter binding potential in striatum during depression , 2001, Neuroreport.

[11]  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.

[12]  Yufeng Zang,et al.  DPARSF: A MATLAB Toolbox for “Pipeline” Data Analysis of Resting-State fMRI , 2010 .

[13]  Gaojun Teng,et al.  Regional homogeneity in depression and its relationship with separate depressive symptom clusters: a resting-state fMRI study. , 2009, Journal of affective disorders.

[14]  Moo K. Chung,et al.  Integrating VBM into the General Linear Model with voxelwise anatomical covariates , 2007, NeuroImage.

[15]  B. Biswal,et al.  Functional connectivity in the motor cortex of resting human brain using echo‐planar mri , 1995, Magnetic resonance in medicine.

[16]  Feng Liu,et al.  Abnormal neural activities in first-episode, treatment-naïve, short-illness-duration, and treatment-response patients with major depressive disorder: a resting-state fMRI study. , 2011, Journal of affective disorders.

[17]  Alan C. Evans,et al.  Structural Insights into Aberrant Topological Patterns of Large-Scale Cortical Networks in Alzheimer's Disease , 2008, The Journal of Neuroscience.

[18]  George S Alexopoulos,et al.  Depression in the elderly , 2005, The Lancet.

[19]  Guy Marchal,et al.  Automated multi-moda lity image registration based on information theory , 1995 .

[20]  J R Moeller,et al.  Regional cerebral blood flow in mood disorders. I. Comparison of major depressives and normal controls at rest. , 1990, Archives of general psychiatry.

[21]  R. Baldwin.  Is vascular depression a distinct sub‐type of depressive disorder? A review of causal evidence , 2005, International journal of geriatric psychiatry.

[22]  M. Lowe,et al.  Functional Connectivity in Single and Multislice Echoplanar Imaging Using Resting-State Fluctuations , 1998, NeuroImage.

[23]  Yingli Lu,et al.  Regional homogeneity approach to fMRI data analysis , 2004, NeuroImage.

[24]  E. Schramm,et al.  Cognitive behavioral analysis system of psychotherapy versus interpersonal psychotherapy for early-onset chronic depression: a randomized pilot study. , 2011, Journal of affective disorders.

[25]  M. Fava,et al.  Factors that differentiate early vs. later onset of major depression disorder , 2004, Psychiatry Research.

[26]  M. Mintun,et al.  Resting-state functional MRI in depression unmasks increased connectivity between networks via the dorsal nexus , 2010, Proceedings of the National Academy of Sciences.

[27]  Semir Zeki,et al.  Neural Correlates of Hate , 2008, PloS one.

[28]  W. Drevets.  Neuroimaging studies of mood disorders , 2000, Biological Psychiatry.

[29]  P. Mitchell,et al.  Age and gender in the phenomenology of depression. , 2005, The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry.

[30]  K. Kendrick,et al.  Depression uncouples brain hate circuit , 2011, Molecular Psychiatry.

[31]  C. Mazure,et al.  Depression in late life: age of onset as marker of a subtype. , 1989, Journal of affective disorders.

[32]  K. Krishnan,et al.  Clinical and phenomenological comparisons of late-onset and early-onset depression. , 1995, The American journal of psychiatry.

[33]  M. Kendall,et al.  Rank Correlation Methods , 1949 .

[34]  J. Gollan,et al.  Course profiles of early- and adult-onset depression. , 2005, Journal of affective disorders.

[35]  Karl J. Friston,et al.  A Voxel-Based Morphometric Study of Ageing in 465 Normal Adult Human Brains , 2001, NeuroImage.

[36]  M. First,et al.  Structured clinical interview for DSM-IV axis I disorders : SCID-I : clinical version : scoresheet , 1997 .

[37]  Amy Fiske,et al.  Depression in older adults. , 2009, Annual review of clinical psychology.

[38]  J. Morris,et al.  The Cortical Signature of Alzheimer's Disease: Regionally Specific Cortical Thinning Relates to Symptom Severity in Very Mild to Mild AD Dementia and is Detectable in Asymptomatic Amyloid-Positive Individuals , 2008, Cerebral cortex.

[39]  Vinod Menon,et al.  Functional connectivity in the resting brain: A network analysis of the default mode hypothesis , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[40]  P. Mitchell,et al.  Distinguishing early and late onset non-melancholic unipolar depression. , 2003, Journal of affective disorders.

[41]  Jeffrey L. Birk,et al.  Reduced caudate and nucleus accumbens response to rewards in unmedicated individuals with major depressive disorder. , 2009, The American journal of psychiatry.

[42]  Qiang Xu,et al.  Disrupted regional homogeneity in treatment-resistant depression: A resting-state fMRI study , 2011, Progress in Neuro-Psychopharmacology and Biological Psychiatry.

[43]  Raymond C K Chan,et al.  Abnormal regional spontaneous neural activity in treatment‐refractory depression revealed by resting‐state fMRI , 2011, Human brain mapping.

[44]  E. Caine,et al.  Age of Onset and Medical Illness in Older Depressed Inpatients , 1995, International Psychogeriatrics.

[45]  A. Alavi,et al.  Regional cerebral glucose metabolism in late-life depression and Alzheimer disease: a preliminary positron emission tomography study. , 1993, Proceedings of the National Academy of Sciences of the United States of America.

[46]  Guy Marchal,et al.  Automated multi-modality image registration based on information theory , 1995 .

[47]  G. Alexopoulos,et al.  Predictors of early recovery from major depression among persons admitted to community-based clinics: an observational study. , 2002, Archives of general psychiatry.

[48]  Angela R Laird,et al.  A meta‐analytic study of changes in brain activation in depression , 2008, Human brain mapping.

[49]  T. Higuchi,et al.  Regional cerebral blood flow in mood disorders , 1997 .

[50]  G. Glover,et al.  Resting-State Functional Connectivity in Major Depression: Abnormally Increased Contributions from Subgenual Cingulate Cortex and Thalamus , 2007, Biological Psychiatry.

[51]  Tianzi Jiang,et al.  Regional coherence changes in the early stages of Alzheimer’s disease: A combined structural and resting-state functional MRI study , 2007, NeuroImage.

[52]  F. Benazzi.  Early onset vs late onset non‐psychotic, non‐melancholic unipolar depression , 2004, International journal of geriatric psychiatry.

[53]  I. Hickie,et al.  Early and late onset depression in old age: different aetiologies, same phenomenology. , 2001, Journal of affective disorders.

[54]  Maurizio Corbetta,et al.  The human brain is intrinsically organized into dynamic, anticorrelated functional networks. , 2005, Proceedings of the National Academy of Sciences of the United States of America.