Altered brain structures in patients with major depressive disorder and high-risk for suicide: A structural MRI study

2010 ◽  
Vol 122 ◽  
pp. S68 ◽  
Author(s):  
G. Wagner⁎ ◽  
K. Koch ◽  
C. Schachtzabel ◽  
R.G.M. Schlösser
2019 ◽  
Vol 50 (3) ◽  
pp. 384-395 ◽  
Author(s):  
Yamin Zhang ◽  
Mingli Li ◽  
Qiang Wang ◽  
Jacob Shujui Hsu ◽  
Wei Deng ◽  
...  

AbstractBackgroundMajor depressive disorder (MDD) is a leading cause of disability worldwide and influenced by both environmental and genetic factors. Genetic studies of MDD have focused on common variants and have been constrained by the heterogeneity of clinical symptoms.MethodsWe sequenced the exome of 77 cases and 245 controls of Han Chinese ancestry and scanned their brain. Burden tests of rare variants were performed first to explore the association between genes/pathways and MDD. Secondly, parallel Independent Component Analysis was conducted to investigate genetic underpinnings of gray matter volume (GMV) changes of MDD.ResultsTwo genes (CSMD1, p = 5.32×10−6; CNTNAP5, p = 1.32×10−6) and one pathway (Neuroactive Ligand Receptor Interactive, p = 1.29×10−5) achieved significance in burden test. In addition, we identified one pair of imaging-genetic components of significant correlation (r = 0.38, p = 9.92×10−6). The imaging component reflected decreased GMV in cases and correlated with intelligence quotient (IQ). IQ mediated the effects of GMV on MDD. The genetic component enriched in two gene sets, namely Singling by G-protein coupled receptors [false discovery rate (FDR) q = 3.23×10−4) and Alzheimer Disease Up (FDR q = 6.12×10−4).ConclusionsBoth rare variants analysis and imaging–genetic analysis found evidence corresponding with the neuroinflammation and synaptic plasticity hypotheses of MDD. The mediation of IQ indicates that genetic component may act on MDD through GMV alteration and cognitive impairment.


2011 ◽  
Vol 124 (6) ◽  
pp. 435-446 ◽  
Author(s):  
Hanna Järnum ◽  
Simon F. Eskildsen ◽  
Elena G. Steffensen ◽  
Søren Lundbye-Christensen ◽  
Carsten W. Simonsen ◽  
...  

2000 ◽  
Vol 57 (9) ◽  
pp. 867 ◽  
Author(s):  
Boris Birmaher ◽  
Ronald E. Dahl ◽  
Douglas E. Williamson ◽  
James M. Perel ◽  
David A. Brent ◽  
...  

2016 ◽  
Vol 46 (11) ◽  
pp. 2351-2361 ◽  
Author(s):  
T. Nickson ◽  
S. W. Y. Chan ◽  
M. Papmeyer ◽  
L. Romaniuk ◽  
A. Macdonald ◽  
...  

BackgroundPrevious neuroimaging studies indicate abnormalities in cortico-limbic circuitry in mood disorder. Here we employ prospective longitudinal voxel-based morphometry to examine the trajectory of these abnormalities during early stages of illness development.MethodUnaffected individuals (16–25 years) at high and low familial risk of mood disorder underwent structural brain imaging on two occasions 2 years apart. Further clinical assessment was conducted 2 years after the second scan (time 3). Clinical outcome data at time 3 was used to categorize individuals: (i) healthy controls (‘low risk’, n = 48); (ii) high-risk individuals who remained well (HR well, n = 53); and (iii) high-risk individuals who developed a major depressive disorder (HR MDD, n = 30). Groups were compared using longitudinal voxel-based morphometry. We also examined whether progress to illness was associated with changes in other potential risk markers (personality traits, symptoms scores and baseline measures of childhood trauma), and whether any changes in brain structure could be indexed using these measures.ResultsSignificant decreases in right amygdala grey matter were found in HR MDD v. controls (p = 0.001) and v. HR well (p = 0.005). This structural change was not related to measures of childhood trauma, symptom severity or measures of sub-diagnostic anxiety, neuroticism or extraversion, although cross-sectionally these measures significantly differentiated the groups at baseline.ConclusionsThese longitudinal findings implicate structural amygdala changes in the neurobiology of mood disorder. They also provide a potential biomarker for risk stratification capturing additional information beyond clinically ascertained measures.


Author(s):  
BORIS BIRMAHER ◽  
JEFFREY A. BRIDGE ◽  
DOUGLAS E. WILLIAMSON ◽  
DAVID A. BRENT ◽  
RONALD E. DAHL ◽  
...  

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