Amygdala Volume Marks the Acute State in the Early Course of Depression

doi:10.1016/j.biopsych.2008.10.027

Biological Psychiatry

Volume 65, Issue 9, 1 May 2009, Pages 812-818

https://doi.org/10.1016/j.biopsych.2008.10.027 Get rights and content

Background

The amygdala and hippocampus play a key role in the neural circuitry mediating depression. It remains unclear how much structural and functional changes of amygdala and hippocampus reflect the acute state of depression or an underlying neurobiological trait marker of depression.

Methods

High-resolution anatomical images were acquired in 20 medication-naïve major depressive disorder (MDD) patients with a current first episode, 20 medication-free patients recovered from a first episode of MDD, and 20 healthy control subjects that were matched for age, gender, and level of education. Manual volumetry of amygdala and hippocampus was performed on coronal images. Volumetric measurements of brain volume and intracranial volume were acquired with automatic segmentation procedures.

Results

Both amygdalae were significantly enlarged in currently depressed patients, whereas there was no significant difference between recovered patients and control subjects. The amygdala enlargement correlated positively with the severity of depressive state but with no other clinical or neuropsychological variable. The hippocampal volume did not differ between groups.

Conclusions

A state related increase of amygdala volume can be detected early in the course of MDD. Neurotoxic effects might account for the fact that state-related amygdala enlargement has not been found in recurrent depression with relative long illness duration.

Section snippets

Subjects

Twenty medication-naïve MDD patients with a current first episode (mean age ± SD 34.1 ± 11.6 years; range 18–56 years), 20 medication-free MDD patients recovered from a first episode (mean age ± SD 35.8 ± 11.6 years; range 18–53 years), and 20 healthy control subjects (mean age ± SD 37.3 ± 12.7 years; range 18–53 years) were included in this study. Major depressive disorder was diagnosed with the Structured Clinical Interview for DSM-IV (SCID) (22) by a trained psychiatrist (P.v.E.). Inclusion

Subject Characteristics

Table 1 shows the clinical variables and results of neuropsychological assessment of the subjects. There were no significant differences between the three groups on any of the variables, except for psychopathological differences between the currently depressed and the recovered and control group on HDRS score and STAI, as expected. A follow-up contact 1 year after the initial experiment for the current depression group revealed that 14 of 20 subjects fully recovered in the year after initial

Discussion

In the present study we found that, in first-episode, medication-naïve MDD patients, amygdala volume was bilaterally enlarged, both in comparison with recovered MDD patients and with healthy control subjects. There were no significant differences in amygdala volume between recovered MDD patients and healthy control subjects. Finally, no differences in hippocampal volume were found between groups.

Our results indicate that in the early course of depression the amygdala enlargement is a state

References (41)

M.L. Phillips et al.
Neurobiology of emotion perception II: Implications for major psychiatric disorders
Biol Psychiatry
(2003)
M.L. Phillips et al.
Neurobiology of emotion perception I: The neural basis of normal emotion perception
Biol Psychiatry
(2003)
W.C. Drevets et al.
Glucose metabolism in the amygdala in depression: Relationship to diagnostic subtype and plasma cortisol levels
Pharmacol Biochem Behav
(2002)
G.J. Siegle et al.
Increased amygdala and decreased dorsolateral prefrontal BOLD responses in unipolar depression: Related and independent features
Biol Psychiatry
(2007)
G.J. Siegle et al.
Can't shake that feeling: Event-related fMRI assessment of sustained amygdala activity in response to emotional information in depressed individuals
Biol Psychiatry
(2002)
Y.I. Sheline et al.
Increased amygdala response to masked emotional faces in depressed subjects resolves with antidepressant treatment: An fMRI study
Biol Psychiatry
(2001)
T. Frodl et al.
Enlargement of the amygdala in patients with a first episode of major depression
Biol Psychiatry
(2002)
S.C. Caetano et al.
Anatomical MRI study of hippocampus and amygdala in patients with current and remitted major depression
Psychiatry Res
(2004)
E.J. Nestler et al.
Neurobiology of depression
Neuron
(2002)
R.C. Oldfield
The assessment and analysis of handedness: The Edinburgh inventory
Neuropsychologia
(1971)

C.L. Fales et al.

Altered emotional interference processing in affective and cognitive-control brain circuitry in major depression

Biol Psychiatry

(2008)

Y. Tang et al.

Reduced ventral anterior cingulate and amygdala volumes in medication-naive females with major depressive disorder: A voxel-based morphometric magnetic resonance imaging study

Psychiatry Res

(2007)

E.S. Brown et al.

Amygdala volume in patients receiving chronic corticosteroid therapy

Biol Psychiatry

(2008)

W.C. Drevets et al.

A functional anatomical study of unipolar depression

J Neurosci

(1992)

H.C. Abercrombie et al.

Metabolic rate in the right amygdala predicts negative affect in depressed patients

Neuroreport

(1998)

C.H. Fu et al.

Attenuation of the neural response to sad faces in major depression by antidepressant treatment: A prospective, event-related functional magnetic resonance imaging study

Arch Gen Psychiatry

(2004)

C. Lange et al.

Enlarged amygdala volume and reduced hippocampal volume in young women with major depression

Psychol Med

(2004)

M. Inagaki et al.

Hippocampal volume and first major depressive episode after cancer diagnosis in breast cancer survivors

Am J Psychiatry

(2004)

E. Mervaala et al.

Quantitative MRI of the hippocampus and amygdala in severe depression

Psychol Med

(2000)

R.S. Hastings et al.

Volumetric analysis of the prefrontal cortex, amygdala, and hippocampus in major depression

Neuropsychopharmacology

(2004)

Cited by (137)

An empirical analysis of structural neuroimaging profiles in a staging model of depression
2024, Journal of Affective Disorders
We examine structural brain characteristics across three diagnostic categories: at risk for serious mental illness; first-presenting episode and recurrent major depressive disorder (MDD). We investigate whether the three diagnostic groups display a stepwise pattern of brain changes in the cortico-limbic regions.
Integrated clinical and neuroimaging data from three large Canadian studies were pooled (total n = 622 participants, aged 12-66 years). Four clinical profiles were used in the classification of a clinical staging model: healthy comparison individuals with no history of depression (HC, n = 240), individuals at high risk for serious mental illness due to the presence of subclinical symptoms (SC, n = 80), first-episode depression (FD, n = 82), and participants with recurrent MDD in a current major depressive episode (RD, n = 220). Whole-brain volumetric measurements were extracted with FreeSurfer 7.1 and examined using three different types of analyses.
Hippocampal volume decrease and cortico-limbic thinning were the most informative features for the RD vs HC comparisons. FD vs HC revealed that FD participants were characterized by a focal decrease in cortical thickness and global enlargement in amygdala volumes. Greater total amygdala volumes were significantly associated with earlier onset of illness in the FD but not the RD group.
We did not confirm the construct validity of a tested clinical staging model, as a differential pattern of brain alterations was identified across the three diagnostic groups that did not parallel a stepwise clinical staging approach. The pathological processes during early stages of the illness may fundamentally differ from those that occur at later stages with clinical progression.
Identifying two distinct neuroanatomical subtypes of first-episode depression using heterogeneity through discriminative analysis
2024, Journal of Affective Disorders
Neurobiological heterogeneity in depression remains largely unknown, leading to inconsistent neuroimaging findings.
Here, we adopted a novel proposed machine learning method ground on gray matter volumes (GMVs) to investigate neuroanatomical subtypes of first-episode treatment-naïve depression. GMVs were obtained from high-resolution T1-weighted images of 195 patients with first-episode, treatment-naïve depression and 78 matched healthy controls (HCs). Then we explored distinct subtypes of depression by employing heterogeneity through discriminative analysis (HYDRA) with regional GMVs as features.
Two prominently divergent subtypes of first-episode depression were identified, exhibiting opposite structural alterations compared with HCs but no different demographic features. Subtype 1 presented widespread increased GMVs mainly located in frontal, parietal, temporal cortex and partially located in limbic system. Subtype 2 presented widespread decreased GMVs mainly located in thalamus, cerebellum, limbic system and partially located in frontal, parietal, temporal cortex. Subtype 2 had smaller TIV and longer illness duration than Subtype 1. And TIV in Subtype 1 was positively correlated with age of onset while not in Subtype 2, probably implying the different potential neuropathological mechanisms.
Despite results obtained in this study were validated by employing another brain atlas, the conclusions were acquired from a single dataset.
This study revealed two distinguishing neuroanatomical subtypes of first-episode depression, which provides new insights into underlying biological mechanisms of the heterogeneity in depression and might be helpful for accurate clinical diagnosis and future treatment.
A voxel-based meta-analysis comparing medication-naive patients of major depression with treated longer-term ill cases
2023, Neuroscience and Biobehavioral Reviews
Structural neuroimaging studies have identified brain areas implicated in the pathogenesis of major depressive disorder (MDD). However, findings have been inconsistent, potentially due to variable illness duration and effects of antidepressant treatment. Using a meta-analytic approach, we compared gray matter (GM) volumes in patients grouped by medication status (naïve and treated) and illness duration (early course and long-term ill) to identify potential treatment and illness duration effects on brain structure. A total of 70 studies were included, including 3682 patients and 3469 controls. The pooled analysis found frontal, temporal and limbic regions with decreased GM volume in MDD patients. Additional analyses indicated that larger GM volume in the right striatum and smaller GM volume in the right precuneus are likely to be associated with drug effects, while smaller GM volume in the right temporal gyrus may correlate with longer illness duration. Similar GM decreases in bilateral medial frontal cortex between patient subgroups suggest that this alteration may persist over the course of illness and drug treatment.
Classification of Major Depressive Disorder using Machine Learning on brain structure and functional connectivity
2022, Journal of Affective Disorders Reports
Timely identification of the risk of having Major Depressive Disorder (MDD) using the advanced machine learning (ML) approach has been popularized to generate neural indicators of MDD. However, past ML studies have usually employed a comprehensive whole-brain approach, resulting in high computational cost that is hardly affordable in practical and clinical contexts.
In this study, we took an alternative approach by first conducting a meta-analysis to identify brain regions of interest (ROIs) where structural and/or functional alterations had been consistently reported in MDD patients. We then utilized a nonlinear multilayer deep neural network method to evaluate the classification accuracies of MDD patients (N = 41, 29 females) and healthy individuals (N = 20, 12 females) based on the structural volume and resting-state functional connectivity (rsFC) of the ROIs.
We found that the ML model based on brain volumes, with the inferior frontal cortex (IFC), amygdala, and the pons receiving the highest weights, achieved higher classification accuracy and sensitivity relative to the model based on rsFC.
For ethical reasons, people with MDD remained taking antidepressants at the time of the study.
Our findings highlight the critical role of the pons-cortico-limbic network in MDD, which is a significant insight for early identification and diagnosis of the illness for timely intervention.
Sex and age differences in cognitive bias and neural activation in response to cognitive bias testing
2022, Neurobiology of Stress
Cognitive symptoms of depression, including negative cognitive bias, are more severe in women than in men. Current treatments to reduce negative cognitive bias are not effective and sex differences in the neural activity underlying cognitive bias may play a role. Here we examined sex and age differences in cognitive bias and functional connectivity in a novel paradigm. Male and female rats underwent an 18-day cognitive bias procedure, in which they learned to discriminate between two contexts (shock paired context A, no-shock paired context B), during either adolescence (postnatal day (PD 40)), young adulthood (PD 100), or middle-age (PD 210). Cognitive bias was measured as freezing behaviour in response to an ambiguous context (context C), with freezing levels akin to the shock paired context coded as negative bias. All animals learned to discriminate between the two contexts, regardless of sex or age. However, adults (young adults, middle-aged) displayed a greater negative cognitive bias compared to adolescents, and middle-aged males had a greater negative cognitive bias than middle-aged females. Females had greater neural activation of the nucleus accumbens, amygdala, and hippocampal regions to the ambiguous context compared to males, and young rats (adolescent, young adults) had greater neural activation in these regions compared to middle-aged rats. Functional connectivity between regions involved in cognitive bias differed by age and sex, and only adult males had negative correlations between the frontal regions and hippocampal regions. These findings highlight the importance of examining age and sex when investigating the underpinnings of negative cognitive bias and lay the groundwork for determining what age- and sex-specific regions to target in future cognitive bias studies.
Age-dependent brain morphometry in Major Depressive disorder
2022, NeuroImage: Clinical
Major depressive disorder (MDD) is a complex disorder that affects nearly 264 million people worldwide. Structural brain abnormalities in multiple neuroanatomical networks have been implicated in the etiology of MDD, but the degree to which MDD affects brain structure during early to late adulthood is unclear.
We examined morphometry of brain regions commonly implicated in MDD, including the amygdala, hippocampus, anterior cingulate gyrus, lateral orbitofrontal gyrus, subgenual cortex, and insular cortex subregions, from early to late adulthood. Harmonized measures for gray matter (GM) volume and cortical thickness of each region were estimated cross-sectionally for 305 healthy controls (CTLs) and 247 individuals with MDD (MDDs), collated from four research cohorts. We modeled the nonlinear associations of age with GM volume and cortical thickness using generalized additive modeling and tested for age-dependent group differences.
Overall, all investigated regions exhibited smaller GM volume and thinner cortical measures with increasing age. Compared to age matched CTLs, MDDs had thicker cortices and greater GM volume from early adulthood until early middle age (average 35 years), but thinner cortices and smaller GM volume during and after middle age in the lateral orbital gyrus and all insular subregions. Deviations of the MDD and CTL models for both GM volume and cortical thickness in these regions started as early as age 18.
The analyses revealed that brain morphometry differences between MDDs and CTLs are dependent on age and brain region. The significant age-by-group interactions in the lateral orbital frontal gyrus and insular subregions make these regions potential targets for future longitudinal studies of MDD.

View all citing articles on Scopus

View full text

Research ReportAmygdala Volume Marks the Acute State in the Early Course of Depression

Background

Methods

Results

Conclusions

Section snippets

Subjects

Subject Characteristics

Discussion

Biol Psychiatry

Biol Psychiatry

Pharmacol Biochem Behav

Biol Psychiatry

Biol Psychiatry

Biol Psychiatry

Biol Psychiatry

Psychiatry Res

Neuron

Neuropsychologia

Biol Psychiatry

Psychiatry Res

Biol Psychiatry

A functional anatomical study of unipolar depression

J Neurosci

Metabolic rate in the right amygdala predicts negative affect in depressed patients

Neuroreport

Attenuation of the neural response to sad faces in major depression by antidepressant treatment: A prospective, event-related functional magnetic resonance imaging study

Arch Gen Psychiatry

Enlarged amygdala volume and reduced hippocampal volume in young women with major depression

Psychol Med

Hippocampal volume and first major depressive episode after cancer diagnosis in breast cancer survivors

Am J Psychiatry

Quantitative MRI of the hippocampus and amygdala in severe depression

Psychol Med

Volumetric analysis of the prefrontal cortex, amygdala, and hippocampus in major depression

Neuropsychopharmacology

Research Report
Amygdala Volume Marks the Acute State in the Early Course of Depression