Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2022 Mar 8.
Published in final edited form as: J Affect Disord. 2016 May 24;203:136–142. doi: 10.1016/j.jad.2016.05.036

Relationship of recent stress to amygdala volume in depressed and healthy adults

M Elizabeth Sublette 1,2,*, Hanga C Galfalvy 1,2, Maria A Oquendo 1,2, Corinne P Bart 1, Noam Schneck 1,2, Victoria Arango 1,2, J John Mann 1,2,3
PMCID: PMC8903078  NIHMSID: NIHMS789813  PMID: 27288958

Abstract

Background:

The amygdala is an integral part of the extrahypothalamic stress-response system, and its volume related to childhood trauma has been studied, but less is known of associations with recent stressful life events. Amygdala volume differences also have been studied in depression, with conflicting results. We hypothesized that effects of stress may be a confound for amygdala volumetric differences in the context of depression.

Methods:

Right-handed participants (n=61) experiencing a major depressive episode during major depressive disorder (n=40) or bipolar depression (n=21) and healthy volunteers (n=60) underwent 1.5 T magnetic resonance imaging (MRI). The amygdala perimeter was manually traced with an electronic mouse, based on anatomical landmarks on consecutive coronal slices, by raters blind to diagnosis. The effects of stress on amygdala volume were examined in linear regression models with self-reported physical/sexual abuse or highest category score on the St. Paul-Ramsey scale of stressful life events within the past 6 months as predictors, testing separately for age, sex, race, and depression status as covariates.

Results:

Diagnostic groups did not differ significantly with respect to mean age (depressed, 37.8± 11.8 yrs; healthy, 34.9±13.8 yrs) or proportion of males (depressed, 39%, healthy, 50%). We found no association between physical and/or sexual abuse history and amygdala volume. Life stress within the last six months, however, was associated with smaller left amygdala volume. The association between stress and amygdala volume did not differ by diagnostic group.

Limitations:

Most depressed patients were off medications for at least 2 weeks; however, this may not have been long enough to reverse effects of medications on amygdala structure.

Conclusions:

That life stress of relatively short duration was associated with amygdala size in the entire sample, while temporally distant life stress was not, suggests that amygdala volume changes may occur rapidly and reversibly, and independent of depression status.

INTRODUCTION

Efforts to understand environmental contributions to psychopathology have increasingly focused on the role of stress, e.g. the stress-diathesis model of suicidal behavior proposed by Mann et al. (Mann et al., 1999); the role of childhood adversity in development of psychosis (Fisher et al., 2013, Wolke et al., 2014, Fisher et al., 2012, Marwaha and Bebbington, 2015, Sitko et al., 2014, van Nierop et al., 2014), and the association between stressful life events and depression risk (Risch et al., 2009). These relationships may indicate that stressful events ‘prime the pump’, i.e. the experience of adversity can lead to alterations in later physiological responses (Lovallo et al., 2012).

Having established the relevance of stress to the trajectory of illness, it is then important to map the neurobiological changes attendant on stress. A key brain region implicated in stress response and psychopathology is the amygdala, which, as a component of the extrahypothalamic stress-response system, plays a major role in responding to systemic threat and regulating emotional behavior (Shirazi et al., 2015). The amygdala is sensitive to glucocorticoids released in response to acute stress, which results in a cascade of adaptive responses. However, the inability to terminate the stress response, e.g. in the presence of ongoing chronic stress, can result in persistently altered levels of glucocorticoids, with maladaptive effects such as suppression of neurogenesis, and remodeling of synapses and dendritic anatomy of the amygdala (Mitra et al., 2005). The ensuing alterations in amygdala activity and functional connectivity may translate to impaired cognition, dysregulated emotional valence to aversive and rewarding experiences, and neuronal excitability.

In rats, for example, the amygdala activates the hypothalamic-pituitary-adrenal (HPA) axis in response to direct stimulation or acute stressors such as forced swimming or immobilization (Cullinan et al., 1995) that promote increased extracellular glutamate levels in basolateral (BLA) and central nuclei of amygdala (Reznikov et al., 2007) and release of norepinephrine in the medial amygdala (Ma and Morilak, 2005). Chronic stress, on the other hand, leads to lower reuptake of glutamate, with concomitant activation of extracellular glutamate receptors (Yuan and Hou, 2015).

Duration and type of stress, precise location within the amygdala, and neuronal type are determinants of dendritic remodeling. Acute stress leads to increased density of dendritic spines on BLA neurons, while chronic stress causes expanded BLA dendrites but loss of spines in the medial amygdala (reviewed in (McEwen et al., 2015)). As opposed to chronic immobilization, in which increased dendritic arborization occurs in stellate and pyramidal neurons in the BLA, the chronic unpredictable stress paradigm produces atrophy in bipolar neurons in the same region (Vyas et al., 2002). At the level of volumetric measurement, recombinant mouse strains with the greatest glucocorticoid responses to stress and the strongest fear conditioning exhibit smaller BLA volumes (Yang et al., 2008).

Clinical evidence concerning the effects of stress on amygdala volume in humans is sparse and conflicting. Congenital adrenal hyperplasia, a condition that results from gene mutations of enzymes crucial for cortisol production, results in increased cortisol secretion and is accompanied by smaller amygdala volume in children (Merke et al., 2003). Other pediatric studies report larger amygdala volumes among 10-year old children exposed since birth to depressed mothers (Lupien et al., 2011), and in children reared in orphanages (Tottenham et al., 2010, Mehta et al., 2009), particularly with longer duration of institutionalization (Tottenham et al., 2010). In contrast, another study of early life trauma on brain structure found childhood adversity to be associated with smaller amygdala volumes in adolescents but not adults (Korgaonkar et al., 2013). This is consistent with most studies in adults that find no significant amygdala volumetric differences associated with post-traumatic stress disorder (PTSD) (Gurvits et al., 1996, Bremner et al., 1997, Fennema-Notestine et al., 2002, Lindauer et al., 2004, Wignall et al., 2004, Levy-Gigi et al., 2013, Gilbertson et al., 2002, Bonne et al., 2001) with few exceptions in which more recent trauma was associated with smaller amygdala volumes (Morey et al., 2012, Depue et al., 2014, Matsuoka et al., 2003).

Amygdala volume also has been studied in depression, with even more conflicting results. Compared with healthy volunteers, studies have variously reported no amygdala volume differences in major depressive disorder (MDD) (Axelson et al., 1993, Coffey et al., 1993, Pantel et al., 1997, Sheline et al., 1999, Ashtari et al., 1999, Bremner et al., 2000, Mervaala et al., 2000, Frodl et al., 2003, Caetano et al., 2004, Frodl et al., 2004, Munn et al., 2007, Lorenzetti et al., 2009) or bipolar disorder (BD) (Swayze et al., 1992, Noga et al., 2001); smaller volumes in MDD (Sheline et al., 1999, von Gunten et al., 2000, Siegle et al., 2003, Hastings et al., 2004b, Xia et al., 2004, Tang et al., 2007) and BD (Pearlson et al., 1997, Rosso et al., 2006, Blumberg et al., 2003); or larger volumes in MDD (Frodl et al., 2003, Lange and Irle, 2004, Weniger et al., 2006) and BD (Strakowski et al., 1999, Altshuler et al., 2000, Brambilla et al., 2003, Frangou, 2005).

We have previously studied amygdala volume in depressed (Hastings et al., 2004a) and healthy (Sublette et al., 2008) populations. We reasoned that the lack of consensus concerning depression effects on amygdala volume might be due to independent effects of stress. Therefore, we examined effects of stress and diagnosis on amygdala volume in a new, large clinical sample comprised of depressed patients and healthy volunteers, predicting that effects of stress would constitute a confound with regard to effects of depression on amygdala volume. To examine the effects that timing of stress might have on the amygdala, we chose two paradigms of stress with different temporal ranges: 1) history of childhood abuse and 2) recent self-reported stressful life events.

METHODS AND MATERIALS

Participants and assessments

Right-handed depressed participants (n=61) and healthy volunteers (n=60) were recruited from community referrals and advertisements to participate in neuroimaging protocols that comprised magnetic resonance imaging (MRI) and positron emission tomography (not discussed here). All participants gave written informed consent for participation in the study, which was approved by the New York State Psychiatric Institute IRB. Participants were not on medications at time of study enrollment or underwent a medication washout so they were off medications for > 2 weeks (6 weeks for fluoxetine), with the exception of 10 individuals who were on medication at the time of MRI scanning. Participants met DSM-IV criteria for MDD or BD based on the Structured Clinical Interview I (SCID-I) for Axis I disorders (First et al., 1997). Depression severity was assessed with the Hamilton Depression Rating Scale (17-item) (Hamilton, 1967, Hamilton, 1960). Healthy volunteers did not have an Axis I diagnosis, based on the non-patient (NP) version of the SCID, or first-degree relatives with a mood disorder or schizophrenia, based on a DSM-IV checklist of diagnostic criteria for family history. All participants underwent physical examination and routine laboratory screening to exclude pregnancy, neurologic illness, active major medical disease, and evidence of current illicit drug use. A detailed psychiatric history was obtained including self-reported history of physical or sexual abuse. Stressful life experiences within the prior six months were assessed using the St. Paul-Ramsey Scale (Paykel, 1983), which rates the impact of specific stressful life experiences on a 7-point severity scale, from “none” to “catastrophic.” The outcome variable used was the highest rating score in any of six categories of life events, called the “global rating”. The St. Paul Ramsey scale is an example of semi-structured, interviewer-conducted recent life event interviews, known as the ‘Paykel method’, which by psychometric validation study have been shown to demonstrate good intra-class reliability and excellent test-retest reliability (r=0.95), with a highly significant correlation between interviewer and subject ratings of the degree of stress evoked by a given life event (Paykel, 1983). Used to predict post-partum depression (Gutierrez-Zotes et al., 2015) and suicide attempter status (Baca-Garcia et al., 2007), the St. Paul Ramsey interview is reliable in our hands with an intra-class correlation of 0.96 (Zalsman et al., 2006).

MRI acquisition and analysis

MRI scans were acquired as described previously (Parsey et al., 2006). Briefly, a sagittal scout localizer scan was performed on a GE 1.5 T Signa Advantage system, followed by a transaxial T1 weighted sequence (1.5 mm slice thickness) in a coronal plane orthogonal to the AC-PC plane, over the whole brain. Scan parameters of the 3-dimensional Spoiled Gradient Recalled Acquisition in the Steady State (SPGR) sequence were as follows: TR 34 msec, TE 5 msec, flip angle 45°, no gap, 124 slices, field of view 22 × 16 cm, 256 × 192 matrix, reformatted to 256 × 256 (yielding a voxel size 1.5 mm × 0.9 mm × 0.9 mm), time of acquisition 11 min.

Coronal MRI images were cropped to remove non-brain material, utilizing the Exbrain v.2 utility (Lemieux et al., 2003). In some cases, the Brain Extraction Tool (BET) v1.2 of the Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB) (Smith, 2002) was used, followed by manual removal of any imaged non-brain matter.

Amygdala volume measurements

Criteria for delineation of the amygdala region of interest (ROI) were developed by author V.A., based on anatomical landmarks, as follows. On consecutive 1.5-mm-thick coronal slices, the amygdala perimeter was manually traced with an electronic mouse using 3D image analysis software (MEDX, Sensor); corresponding sagittal and axial views aided in the accuracy of border definition (see Figure 1). For each participant, the entire rostrocaudal extent of the amygdala was measured and the summed areas were multiplied by the slice thickness to obtain the volume. Anteriorly, the amygdala appeared as an oval mass of gray matter that increased in size in subsequent slices (Bogerts et al., 1990, Niu et al., 2004). Temporal lobe white matter comprised the lateral border; the medial border was separated from the entorhinal cortex by the thin white matter strip, the angular bundle, in the parahippocampal gyrus (Hammers et al., 2003, Niu et al., 2004). The entorhinal sulcus served as the superior border (Hammers et al., 2003, Pruessner et al., 2000). In anterior slices, the inferior border was defined by white matter, whereas in more posterior slices the hippocampus and ventricle served as the inferior border. In the most caudal slices, the amygdala thinned out to a strip of gray matter just dorsal to the alveus and inferior horn of the lateral ventricle (Convit et al., 1999, Pruessner et al., 2000). The optic tract and fundus of the inferior portion of the circular sulcus of the insula defined the dorsal border (Pruessner et al., 2000). Repeated measurements (two raters each traced left and right amygdalae in the same 9 participants) yielded an intraclass coefficient (ICC) of 0.87 for left amygdala and 0.92 for right amygdala. Raters were blind to diagnosis.

Figure 1. Amygdala region of interest measurement from magnetic resonance images.

Figure 1.

Open in a new tab

Representative amygdala tracings from coronal images of a single subject are shown. The series is pictured here from caudal to rostral, with 6 intervening slices omitted for clarity of visualization.

Statistical analyses

Statistical analyses were conducted using IBM SPSS Statistics (version 23, Armonk, NY). Distribution of the continuous variables was examined for outliers or inconsistency. Demographic and clinical characteristics were compared across groups using independent t-tests or Mann–Whitney U-tests for continuous variables and χ2 tests for dichotomous variables, α = 0.05. The effects of stress on amygdala volume corrected for mean total cerebral volume (TCV) were examined in separate linear regression models using the following two independent variables: presence or absence of self-reported physical/sexual abuse, and highest category score on the St. Paul-Ramsey scale of stressful life events within the past 6 months. Depression status (depressed vs healthy volunteers) also was entered separately into the models as a covariate. The effects of age, sex, and race were additionally tested as covariates/cofactors in separate models. In sensitivity analyses, to control for possible confounds of illness phase or current medication treatment, we removed from the models participants whose depression was in remission (n=8) and (in a separate analysis) those who were on medications (n=10) at time of scan.

RESULTS

Participant characteristics

At the time of scan, all participants with BD (n=21) and 32/40 participants with MDD were acutely depressed, having a Hamilton Depression Rating Scale (HDRS) 17-item score > 16. The remaining 8 participants with MDD were in remission (having had at least two lifetime episodes of major depression but not meeting criteria for a major depressive episode during the last 12 months, with an HDRS score of less than 8 on presentation). There were no differences between BD and MDD with respect to depression severity. Eighty-four percent of depressed participants (n=51) were off psychotropic medications for at least 14 days (6 weeks for fluoxetine and 4 weeks for oral antipsychotics) prior to scanning except for short-acting benzodiazepines or chloral hydrate, which were stopped 3 days prior to scan. Mean duration of time since first lifetime episode of major depression or mania was 16.1 + 10.3 years (median 15 years, range 49 years). The depressed group contained a higher proportion of white participants, but depressed and healthy volunteer groups did not differ on the basis of sex, mean age, or years of education (see Table 1).

Table 1.

Characteristics of depressed and healthy volunteers.

Variable Depressed Healthy
Demographic characteristics n Number (%) n Number (%) χ2 df p
Male sex 61 24 (39) 60 30 (50) 1.39 1 0.275
White race 52 43 (70.5) 50 27 (45) 9.747 1 0.003
Mean ± SD Mean ± SD t df p
Mean age, yrs 60 37.8 ± 11.8 60 34.9 ± 13.8 1.247 118 0.215
Total education, yrs 61 15.5 ± 2.8 60 16.4 ± 2.9 −1.624 119 0.107
Mean ± SD Median IQ range Mean ± SD Median IQ range
Annual incomea, $K 59 23.1 ± 23.4 18 32 59 31.3 ± 28.5 28 30 – – 0.049
Clinical characteristics Mean ± SD
Illness duration, yrs 60 16.1 ± 10.3
Number of depressive episodes 60 15.0 ± 28.8
Age of onset, yrs 61 22.2 ± 12.2
Open in a new tab

Abbreviations: IQ=Interquartile; SD=Standard deviation.

a

Mann-Whitney test.

A history of physical and/or sexual abuse was reported by 28 participants; in 22/28 this occurred prior to age 15. Of depressed participants, 38% reported abuse, compared with 8% of healthy volunteers (χ2 = 14.7, df=1, p<0.001). There were no differences between MDD and BD with respect to incidence of self-reported abuse (χ2=0.286, df=1, p=0.405). The St. Paul-Ramsey Life Events Scale mean score was higher in depressed participants (3.9 + 1.0) compared with healthy volunteers (2.8 + 1.2; t = 5.09, df =117, p<0.001). Mean St. Paul-Ramsey scores did not significantly differ between MDD and BD, but trended higher in BD (t-score=−1.894, df=58, p=0.063).

Amygdala volumes

There were no differences in amygdala volumes between depressed and healthy participants or between MDD and BD patients (see Table 2).

Table 2.

Volumetric characteristics of depressed and healthy volunteers.

Volumetric characteristics Side Depressed Healthy
n=61 n = 60 t df p
Total cerebral volume (TCV), L 1.43 ± 0.15 1.42 ± 0.16 −0.216 119 0.829
Raw amygdala volume, cm3 Left 1.40 ± 0.25 1.41 ± 0.27 −0.347 119 0.729
Right 1.49 ± 0.31 1.51 ± 0.32 −0.295 119 0.769
Normalized amygdala volume, % (Regional volume/TCV*100) Left 0.098 ± 0.015 0.100 ± 0.018 −0.667 119 0.506
Right 0.105 ± 0.019 0.107 ± 0.022 −0.606 119 0.606
MDD BD
n = 40 n = 21 F df p
Left 0.099 ± 0.014 0.095 ± 0.016 0.100 ± 0.018 0.416 3 0.742
Right 0.106 ± 0.016 0.102 ± 0.024 0.107 ± 0.022 0.348 3 0.791
Open in a new tab

Abbreviations: MDD=Major depressive disorder; BD=Bipolar disorder

Effects of environmental stress on amygdala volume

Analyses in all participants (depressed and healthy volunteers) found no association between self-reported physical and/or sexual abuse history and amygdala volume (left amygdala, F=0.902, df=1,119, p=0.344; right amygdala, F=0.077, df=1,119, p=0.781). However, life stress within the last six months, as represented by the highest category scores on the St. Paul-Ramsey Scale, was associated with smaller amygdala volume (F=4.59; df=1,116; p=0.034), and the association did not differ by side (within-subject side by stress interaction, F=1.024; df=1,116; p=0.314). When right and left sides were analyzed separately, however, only the left side was significant (left: Pearson’s r = −0.247, F=7.580, df=1,117; p=0.007; right: Pearson’s r = −0.124, F=1.83, df=1,117, p=0.179). The association between stress and amygdala volume did not differ significantly between depressed and healthy groups (interaction, F=1.402; df=1,115; p=0.239; see Figure 2.) Thus, the negative correlation between left amygdala volume and life stress was still observed when only the healthy volunteer group (n=60) was considered for recent life stressors (right amygdala, Pearson’s r = −0.222, p=0.091; left amygdala, Pearson’s r = −0.287, p=0.028). These results remained essentially the same when sex, race, or age were included in the models; no interactions or main effects were observed (data not shown), so they were removed from the models. Sensitivity analyses excluding remitted depressed patients and those on medications, or adjusting for depression severity did not change the results. Likewise, comparison of MDD and BD groups did not find any differences with respect to amygdala volumes (left amygdala, t-test=0.999, df=59, p=0.322; right amygdala, t-test=0.818, df=59, p=0.417).

Figure 2. Associations between St. Paul Ramsey Life Events Scale and left amygdala volume, stratified by diagnosis.

Figure 2.

Open in a new tab

Correlations between left amygdala volume, normalized for total cerebral volume, and highest score (range 0–6) on the St. Paul-Ramsey Life Events Scale (F=7.58, r=0.24, df=117, p = 0.007). Gray markers = depressed participants; black markers = healthy volunteers. Data are jittered for easier visibility.

DISCUSSION

Temporal aspects of amygdala volume changes

Our finding that recent life stresses correlate inversely with amygdala volume opens up the possibility that volumetric change may occur rapidly and, if so, future work needs to determine whether it is also rapidly reversible. Consistent with this premise, a study found that early life stress in 3 to 5 year-old children (n=120) predicted decreased amygdala volume when these participants reached 7–12 years of age (Pagliaccio et al., 2014), while a larger-scale MRI study (n=352) of the effects of early life trauma on brain structure across the life span found that childhood adversity was associated with smaller amygdala volumes in adolescents (Korgaonkar et al., 2013), but not in adults, suggesting that volumetric effects were reversed by the time of attaining adulthood. From this we may hypothesize that effects of adversity on amygdala volume are related to the temporal proximity of the stressor, although in the Korgaonker study (Korgaonkar et al., 2013), specific maturation processes could be responsible for brain repair during the transition to adulthood. Additional studies, in young children exposed to very prolonged stress, found larger amygdala volumes (Lupien et al., 2011, Tottenham et al., 2010, Mehta et al., 2009), suggesting that duration of stress, and developmental stage are important dimensions that should be assessed in future studies.

Supporting the premise of recent stress as a volumetric influence that is not exclusively a maturation-specific process, we note that the majority of adult studies in PTSD find no volumetric associations, but several studies that did find smaller amygdala size were investigating trauma that had occurred within 5–10 years previously (Morey et al., 2012, Depue et al., 2014, Matsuoka et al., 2003). Our findings of no volumetric differences associated with childhood abuse history, and smaller left amygdala volumes associated with recent stressful life events comport with this hypothesis and extend it by demonstrating that quite recent events, i.e. within 6 months, may impact amygdala volume, although we cannot be certain whether high stress levels in the past 6 months may reflect characteristically high levels of stress extending back for longer periods of time.

Laterality of amygdala findings

The right amygdala tends to be larger than the left amygdala across diagnostic categories (Woon and Hedges, 2009), and there is a growing body of evidence for different functional roles of right and left amygdala. Meta-analyses and systematic reviews of functional MRI studies of emotion tasks in healthy adults tend to support left lateralized as opposed to bilateral findings (Wager et al., 2003, Baas et al., 2004, Murphy et al., 2003, Sergerie et al., 2008). There is also some evidence for sex-related differences in functional amygdala lateralization, with males showing greater right amygdala activity in emotional contexts (Schneider et al., 2011). These patterns suggest that lateralized amygdala findings are not simply a product of measurement error or acquisition artifact (Mathiak et al., 2012). Multiple theories have been proposed for functional amygdala differences across hemispheres. Some have proposed that amygdala laterality corresponds to emotional valence (Davidson, 1992) however, this has not borne out in meta-analyses (Sergerie et al., 2008, Wager et al., 2003). An alternative suggestion, based on meta-analytic neuroimaging data of amygdala responses to perception of emotional visual stimuli (Sergerie et al., 2008), is that the right amygdala appears to be involved in rapid detection while the left amygdala subserves longer, more sustained signal processing. If true, then in the context of our study, stress-induced changes to left amygdala may influence the interpretation of emotional stimuli rather than the immediate attentional response to them.

Amygdala volume and depression

Depression status was not a determinant of amygdala size in this study, even controlling for sex and other relevant variables. Previous discrepant findings may be due in part to the effects of psychotropic medications on atrophy through increasing neurotrophic factors (reviewed in (Gray et al., 2003)). This is supported by a meta-regression analysis of thirteen studies in depression which found that the proportion of patients taking antidepressant medication was associated with greater amygdala volume in depressed compared to healthy participants, and also found larger amygdala volumes in studies of only-medicated depressed patients and smaller volumes in studies of only-unmedicated patients, compared with healthy volunteers (Hamilton et al., 2008). Our current findings also suggest that association of recent life stress and amygdala size could be a confound contributing to heterogeneity of previous results among studies of amygdala volume and depression.

We did not find the reverse to be true, i.e. depression status did not influence the association of amygdala volumes with stressful life events. However, others (Klimes-Dougan et al., 2014) report that larger amygdala volumes predict HPA functioning differently in MDD and healthy volunteer participants. Using structural MRI and the Trier Social Stress Test (TSST) (Kirschbaum et al., 1993), designed to measure stress responses in a laboratory setting, larger amygdala volumes in healthy volunteers predicted more effective stress responses, i.e. lower cortisol levels, as opposed to depressed individuals, in whom larger amygdala volumes predicted higher cortisol levels (Klimes-Dougan et al., 2014). Thus it may be that larger amygdala volumes indicate maladaptive stress responses in depressed individuals, but not in healthy participants.

Limitations of the study

Most of the depressed patients in our study were off medications for at least 2 weeks, and this may not have been long enough to reverse any medication effects on brain structure. Other potential clinical confounds were not examined, as being outside the scope of our project, including the effects of comorbid anxiety, personality disorders, or history of psychosis. Also, we have not assessed for any other types of early life stressors apart from presence of self-reported physical or sexual abuse. Although we have considered the differences between recent vs. more distant past stress as potentially important, we have not proven that it is the temporal aspects of the stress, as opposed to the type of stress (stressful life experiences vs. abuse), that was the most relevant factor accounting for the volumetric relationships we observed. Duration of stress is another potentially important factor (Mitra et al., 2005, Tottenham et al., 2010), that we were not able to quantify in either stress paradigm.

Conclusions

We find smaller left amygdala volume in association with more life stresses in the preceding 6 months, independent of the presence of depression. In contrast, our finding of a lack of association between past history of sexual/physical abuse and amygdala volume suggests that structural remodeling of neural architecture after damage may be an important form of resilience. What remains to be demonstrated by future, longitudinal studies is whether a causal relationship exists between stressful life events and amygdala volume, the effects of stress type, duration and severity, and the time course of potential reversibility of volume changes.

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

CONFLICT OF INTERESTS: Drs. Mann and Oquendo receive royalties for commercial use of the Columbia-Suicide Severity Rating Scale (C-SSRS). Dr. Oquendo receives an honorarium as President-Elect of the American Psychiatric Association. Her family owns stock in Bristol Myers Squibb. Other authors have no conflicts of interest to report.

References

  1. Altshuler LL, Bartzokis G, Grieder T, Curran J, Jimenez T, Leight K, Wilkins J, Gerner R Mintz J, 2000. An MRI study of temporal lobe structures in men with bipolar disorder or schizophrenia. Biol Psychiatry. 48, 147–62. [DOI] [PubMed] [Google Scholar]
  2. Ashtari M, Greenwald BS, Kramer-Ginsberg E, Hu J, Wu H, Patel M, Aupperle P Pollack S, 1999. Hippocampal/amygdala volumes in geriatric depression. Psychol Med. 29, 629–38. [DOI] [PubMed] [Google Scholar]
  3. Axelson DA, Doraiswamy PM, Mcdonald WM, Boyko OB, Tupler LA, Patterson LJ, Nemeroff CB, Ellinwood EH Jr. Krishnan KR, 1993. Hypercortisolemia and hippocampal changes in depression. Psychiatry Res. 47, 163–73. [DOI] [PubMed] [Google Scholar]
  4. Baas D, Aleman A Kahn RS, 2004. Lateralization of amygdala activation: a systematic review of functional neuroimaging studies. Brain Res Brain Res Rev. 45, 96–103. [DOI] [PubMed] [Google Scholar]
  5. Baca-Garcia E, Parra CP, Perez-Rodriguez MM, Sastre CD, Torres RR, Saiz-Ruiz J De Leon J, 2007. Psychosocial stressors may be strongly associated with suicide attempts. Stress and Health. 23, 191–198. [Google Scholar]
  6. Blumberg HP, Kaufman J, Martin A, Whiteman R, Zhang JH, Gore JC, Charney DS, Krystal JH Peterson BS, 2003. Amygdala and hippocampal volumes in adolescents and adults with bipolar disorder. Arch Gen Psychiatry. 60, 1201–8. [DOI] [PubMed] [Google Scholar]
  7. Bogerts B, Ashtari M, Degreef G, Alvir JM, Bilder RM Lieberman JA, 1990. Reduced temporal limbic structure volumes on magnetic resonance images in first episode schizophrenia. Psychiatry Res. 35, 1–13. [DOI] [PubMed] [Google Scholar]
  8. Bonne O, Brandes D, Gilboa A, Gomori JM, Shenton ME, Pitman RK Shalev AY, 2001. Longitudinal MRI study of hippocampal volume in trauma survivors with PTSD. Am J Psychiatry. 158, 1248–51. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Brambilla P, Harenski K, Nicoletti M, Sassi RB, Mallinger AG, Frank E, Kupfer DJ, Keshavan MS Soares JC, 2003. MRI investigation of temporal lobe structures in bipolar patients. J Psychiatr Res. 37, 287–95. [DOI] [PubMed] [Google Scholar]
  10. Bremner JD, Narayan M, Anderson ER, Staib LH, Miller HL Charney DS, 2000. Hippocampal volume reduction in major depression. Am J Psychiatry. 157, 115–8. [DOI] [PubMed] [Google Scholar]
  11. Bremner JD, Randall P, Vermetten E, Staib L, Bronen RA, Mazure C, Capelli S, Mccarthy G, Innis RB Charney DS, 1997. Magnetic resonance imaging-based measurement of hippocampal volume in posttraumatic stress disorder related to childhood physical and sexual abuse--a preliminary report. Biol Psychiatry. 41, 23–32. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Caetano SC, Hatch JP, Brambilla P, Sassi RB, Nicoletti M, Mallinger AG, Frank E, Kupfer DJ, Keshavan MS Soares JC, 2004. Anatomical MRI study of hippocampus and amygdala in patients with current and remitted major depression. Psychiatry Res. 132, 141–7. [DOI] [PubMed] [Google Scholar]
  13. Coffey CE, Wilkinson WE, Weiner RD, Parashos IA, Djang WT, Webb MC, Figiel GS Spritzer CE, 1993. Quantitative cerebral anatomy in depression. A controlled magnetic resonance imaging study. Arch Gen Psychiatry. 50, 7–16. [DOI] [PubMed] [Google Scholar]
  14. Convit A, Mchugh P, Wolf OT, De Leon MJ, Bobinski M, De Santi S, Roche A Tsui W, 1999. MRI volume of the amygdala: a reliable method allowing separation from the hippocampal formation. Psychiatry Res. 90, 113–23. [DOI] [PubMed] [Google Scholar]
  15. Cullinan WE, Herman JP, Battaglia DF, Akil H Watson SJ, 1995. Pattern and time course of immediate early gene expression in rat brain following acute stress. Neuroscience. 64, 477–505. [DOI] [PubMed] [Google Scholar]
  16. Davidson RJ, 1992. Anterior cerebral asymmetry and the nature of emotion. Brain Cogn. 20, 125–51. [DOI] [PubMed] [Google Scholar]
  17. Depue BE, Olson-Madden JH, Smolker HR, Rajamani M, Brenner LA Banich MT, 2014. Reduced amygdala volume is associated with deficits in inhibitory control: a voxel- and surface-based morphometric analysis of comorbid PTSD/mild TBI. Biomed Res Int. 2014, 691505. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Fennema-Notestine C, Stein MB, Kennedy CM, Archibald SL Jernigan TL, 2002. Brain morphometry in female victims of intimate partner violence with and without posttraumatic stress disorder. Biol Psychiatry. 52, 1089–101. [DOI] [PubMed] [Google Scholar]
  19. First M, Williams J, Spitzer R Gibbon M 1997. Structured Clinical Interview for DSM-IV Axis I Disorders, Washington D.C., American Psychiatric Publishing, Inc. [Google Scholar]
  20. Fisher HL, Appiah-Kusi E Grant C, 2012. Anxiety and negative self-schemas mediate the association between childhood maltreatment and paranoia. Psychiatry Res. 196, 323–4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Fisher HL, Schreier A, Zammit S, Maughan B, Munafo MR, Lewis G Wolke D, 2013. Pathways between childhood victimization and psychosis-like symptoms in the ALSPAC birth cohort. Schizophr Bull. 39, 1045–55. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Frangou S, 2005. The Maudsley bipolar disorder project. Epilepsia. 46 Suppl 4, 19–25. [DOI] [PubMed] [Google Scholar]
  23. Frodl T, Meisenzahl EM, Zetzsche T, Born C, Jager M, Groll C, Bottlender R, Leinsinger G Moller HJ, 2003. Larger amygdala volumes in first depressive episode as compared to recurrent major depression and healthy control subjects. Biol Psychiatry. 53, 338–44. [DOI] [PubMed] [Google Scholar]
  24. Frodl T, Meisenzahl EM, Zetzsche T, Hohne T, Banac S, Schorr C, Jager M, Leinsinger G, Bottlender R, Reiser M Moller HJ, 2004. Hippocampal and amygdala changes in patients with major depressive disorder and healthy controls during a 1-year follow-up. J Clin Psychiatry. 65, 492–9. [DOI] [PubMed] [Google Scholar]
  25. Gilbertson MW, Shenton ME, Ciszewski A, Kasai K, Lasko NB, Orr SP Pitman RK, 2002. Smaller hippocampal volume predicts pathologic vulnerability to psychological trauma. Nat Neurosci. 5, 1242–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Gray N, Zhou R, Du J, Moore G Manji H, 2003. The use of mood stabilizers as plasticity enhancers in the treatment of neuropsychiatric disorders. J Clin Psychiatry. 64 Suppl 5, 3–17. [PubMed] [Google Scholar]
  27. Gurvits TV, Shenton ME, Hokama H, Ohta H, Lasko NB, Gilbertson MW, Orr SP, Kikinis R, Jolesz FA, Mccarley RW Pitman RK, 1996. Magnetic resonance imaging study of hippocampal volume in chronic, combat-related posttraumatic stress disorder. Biol Psychiatry. 40, 1091–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Gutierrez-Zotes A, Labad J, Martin-Santos R, Garcia-Esteve L, Gelabert E, Jover M, Guillamat R, Mayoral F, Gornemann I, Canellas F, Gratacos M, Guitart M, Roca M, Costas J, Luis Ivorra J, Navines R, De Diego-Otero Y, Vilella E Sanjuan J, 2015. Coping strategies and postpartum depressive symptoms: A structural equation modelling approach. Eur Psychiatry. 30, 701–8. [DOI] [PubMed] [Google Scholar]
  29. Hamilton JP, Siemer M Gotlib IH, 2008. Amygdala volume in major depressive disorder: a meta-analysis of magnetic resonance imaging studies. Mol Psychiatry. 13, 993–1000. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Hamilton M, 1960. A rating scale for depression. J Neurol Neurosurg Psychiatry. 23, 56–62. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Hamilton M, 1967. Development of a rating scale for primary depressive illness. Br J Soc Clin Psychol. 6, 278–96. [DOI] [PubMed] [Google Scholar]
  32. Hammers A, Allom R, Koepp MJ, Free SL, Myers R, Lemieux L, Mitchell TN, Brooks DJ Duncan JS, 2003. Three-dimensional maximum probability atlas of the human brain, with particular reference to the temporal lobe. Hum Brain Mapp. 19, 224–47. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Hastings R, Parsey R, Oquendo M, Arango V Mann J, 2004a. Volumetric Analysis of the Prefrontal Cortex, Amygdala, and Hippocampus in Major Depression. Neuropsychopharmacology. 29, 952–959. [DOI] [PubMed] [Google Scholar]
  34. Hastings RS, Parsey RV, Oquendo MA, Arango V Mann JJ, 2004b. Volumetric analysis of the prefrontal cortex, amygdala, and hippocampus in major depression. Neuropsychopharmacology. 29, 952–9. [DOI] [PubMed] [Google Scholar]
  35. Kirschbaum C, Pirke KM Hellhammer DH, 1993. The ‘Trier Social Stress Test’--a tool for investigating psychobiological stress responses in a laboratory setting. Neuropsychobiology. 28, 76–81. [DOI] [PubMed] [Google Scholar]
  36. Klimes-Dougan B, Eberly LE, Westlund Schreiner M, Kurkiewicz P, Houri A, Schlesinger A, Thomas KM, Mueller BA, Lim KO Cullen KR, 2014. Multilevel assessment of the neurobiological threat system in depressed adolescents: interplay between the limbic system and hypothalamic-pituitary-adrenal axis. Dev Psychopathol. 26, 1321–35. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Korgaonkar MS, Antees C, Williams LM, Gatt JM, Bryant RA, Cohen R, Paul R, O’hara R Grieve SM, 2013. Early exposure to traumatic stressors impairs emotional brain circuitry. PLoS One. 8, e75524. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Lange C Irle E, 2004. Enlarged amygdala volume and reduced hippocampal volume in young women with major depression. Psychol Med. 34, 1059–64. [DOI] [PubMed] [Google Scholar]
  39. Lemieux L, Hammers A, Mackinnon T Liu RS, 2003. Automatic segmentation of the brain and intracranial cerebrospinal fluid in T1-weighted volume MRI scans of the head, and its application to serial cerebral and intracranial volumetry. Magn Reson Med. 49, 872–84. [DOI] [PubMed] [Google Scholar]
  40. Levy-Gigi E, Szabo C, Kelemen O Keri S, 2013. Association among clinical response, hippocampal volume, and FKBP5 gene expression in individuals with posttraumatic stress disorder receiving cognitive behavioral therapy. Biol Psychiatry. 74, 793–800. [DOI] [PubMed] [Google Scholar]
  41. Lindauer RJ, Vlieger EJ, Jalink M, Olff M, Carlier IV, Majoie CB, Den Heeten GJ Gersons BP, 2004. Smaller hippocampal volume in Dutch police officers with posttraumatic stress disorder. Biol Psychiatry. 56, 356–63. [DOI] [PubMed] [Google Scholar]
  42. Lorenzetti V, Allen NB, Whittle S Yücel M, 2009. Amygdala volumes in a sample of current depressed and remitted depressed patients and healthy controls. Journal of Affective Disorders. [DOI] [PubMed] [Google Scholar]
  43. Lovallo WR, Farag NH, Sorocco KH, Cohoon AJ Vincent AS, 2012. Lifetime adversity leads to blunted stress axis reactivity: studies from the Oklahoma Family Health Patterns Project. Biol Psychiatry. 71, 344–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Lupien SJ, Parent S, Evans AC, Tremblay RE, Zelazo PD, Corbo V, Pruessner JC Seguin JR, 2011. Larger amygdala but no change in hippocampal volume in 10-year-old children exposed to maternal depressive symptomatology since birth. Proc Natl Acad Sci U S A. 108, 14324–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Ma S Morilak DA, 2005. Norepinephrine release in medial amygdala facilitates activation of the hypothalamic-pituitary-adrenal axis in response to acute immobilisation stress. J Neuroendocrinol. 17, 22–8. [DOI] [PubMed] [Google Scholar]
  46. Mann JJ, Waternaux C, Haas GL Malone KM, 1999. Toward a clinical model of suicidal behavior in psychiatric patients. Am J Psychiatry. 156, 181–9. [DOI] [PubMed] [Google Scholar]
  47. Marwaha S Bebbington P, 2015. Mood as a mediator of the link between child sexual abuse and psychosis. Soc Psychiatry Psychiatr Epidemiol. 50, 661–3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Mathiak KA, Zvyagintsev M, Ackermann H Mathiak K, 2012. Lateralization of amygdala activation in fMRI may depend on phase-encoding polarity. MAGMA. 25, 177–82. [DOI] [PubMed] [Google Scholar]
  49. Matsuoka Y, Yamawaki S, Inagaki M, Akechi T Uchitomi Y, 2003. A volumetric study of amygdala in cancer survivors with intrusive recollections. Biol Psychiatry. 54, 736–43. [DOI] [PubMed] [Google Scholar]
  50. Mcewen BS, Bowles NP, Gray JD, Hill MN, Hunter RG, Karatsoreos IN Nasca C, 2015. Mechanisms of stress in the brain. Nat Neurosci. 18, 1353–63. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Mehta MA, Golembo NI, Nosarti C, Colvert E, Mota A, Williams SC, Rutter M Sonuga-Barke EJ, 2009. Amygdala, hippocampal and corpus callosum size following severe early institutional deprivation: the English and Romanian Adoptees study pilot. J Child Psychol Psychiatry. 50, 943–51. [DOI] [PubMed] [Google Scholar]
  52. Merke DP, Fields JD, Keil MF, Vaituzis AC, Chrousos GP Giedd JN, 2003. Children with classic congenital adrenal hyperplasia have decreased amygdala volume: potential prenatal and postnatal hormonal effects. J Clin Endocrinol Metab. 88, 1760–5. [DOI] [PubMed] [Google Scholar]
  53. Mervaala E, Fohr J, Kononen M, Valkonen-Korhonen M, Vainio P, Partanen K, Partanen J, Tiihonen J, Viinamaki H, Karjalainen AK Lehtonen J, 2000. Quantitative MRI of the hippocampus and amygdala in severe depression. Psychol Med. 30, 117–25. [DOI] [PubMed] [Google Scholar]
  54. Mitra R, Jadhav S, Mcewen BS, Vyas A Chattarji S, 2005. Stress duration modulates the spatiotemporal patterns of spine formation in the basolateral amygdala. Proc Natl Acad Sci U S A. 102, 9371–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Morey RA, Gold AL, Labar KS, Beall SK, Brown VM, Haswell CC, Nasser JD, Wagner HR, Mccarthy G Mid-Atlantic MW, 2012. Amygdala volume changes in posttraumatic stress disorder in a large case-controlled veterans group. Arch Gen Psychiatry. 69, 1169–78. [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Munn MA, Alexopoulos J, Nishino T, Babb CM, Flake LA, Singer T, Ratnanather JT, Huang H, Todd RD, Miller MI Botteron KN, 2007. Amygdala volume analysis in female twins with major depression. Biol Psychiatry. 62, 415–22. [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Murphy FC, Nimmo-Smith I Lawrence AD, 2003. Functional neuroanatomy of emotions: a meta-analysis. Cogn Affect Behav Neurosci. 3, 207–33. [DOI] [PubMed] [Google Scholar]
  58. Niu L, Matsui M, Zhou SY, Hagino H, Takahashi T, Yoneyama E, Kawasaki Y, Suzuki M, Seto H, Ono T Kurachi M, 2004. Volume reduction of the amygdala in patients with schizophrenia: a magnetic resonance imaging study. Psychiatry Res. 132, 41–51. [DOI] [PubMed] [Google Scholar]
  59. Noga JT, Vladar K Torrey EF, 2001. A volumetric magnetic resonance imaging study of monozygotic twins discordant for bipolar disorder. Psychiatry Res. 106, 25–34. [DOI] [PubMed] [Google Scholar]
  60. Pagliaccio D, Luby JL, Bogdan R, Agrawal A, Gaffrey MS, Belden AC, Botteron KN, Harms MP Barch DM, 2014. Stress-system genes and life stress predict cortisol levels and amygdala and hippocampal volumes in children. Neuropsychopharmacology. 39, 1245–53. [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Pantel J, Schroder J, Essig M, Popp D, Dech H, Knopp MV, Schad LR, Eysenbach K, Backenstrass M Friedlinger M, 1997. Quantitative magnetic resonance imaging in geriatric depression and primary degenerative dementia. J Affect Disord. 42, 69–83. [DOI] [PubMed] [Google Scholar]
  62. Parsey RV, Kent JM, Oquendo MA, Richards MC, Pratap M, Cooper TB, Arango V Mann JJ, 2006. Acute Occupancy of Brain Serotonin Transporter by Sertraline as Measured by [(11)C]DASB and Positron Emission Tomography. Biol Psychiatry. 59, 821–8. [DOI] [PubMed] [Google Scholar]
  63. Paykel ES, 1983. Methodological aspects of life events research. J Psychosom Res. 27, 341–52. [DOI] [PubMed] [Google Scholar]
  64. Pearlson GD, Barta PE, Powers RE, Menon RR, Richards SS, Aylward EH, Federman EB, Chase GA, Petty RG Tien AY, 1997. Medial and superior temporal gyral volumes and cerebral asymmetry in schizophrenia versus bipolar disorder. Biol Psychiatry. 41, 1–14. [DOI] [PubMed] [Google Scholar]
  65. Pruessner JC, Li LM, Serles W, Pruessner M, Collins DL, Kabani N, Lupien S Evans AC, 2000. Volumetry of hippocampus and amygdala with high-resolution MRI and three-dimensional analysis software: minimizing the discrepancies between laboratories. Cereb Cortex. 10, 433–42. [DOI] [PubMed] [Google Scholar]
  66. Reznikov LR, Grillo CA, Piroli GG, Pasumarthi RK, Reagan LP Fadel J, 2007. Acute stress-mediated increases in extracellular glutamate levels in the rat amygdala: differential effects of antidepressant treatment. Eur J Neurosci. 25, 3109–14. [DOI] [PubMed] [Google Scholar]
  67. Risch N, Herrell R, Lehner T, Liang KY, Eaves L, Hoh J, Griem A, Kovacs M, Ott J Merikangas KR, 2009. Interaction between the serotonin transporter gene (5-HTTLPR), stressful life events, and risk of depression: a meta-analysis. JAMA. 301, 2462–71. [DOI] [PMC free article] [PubMed] [Google Scholar]
  68. Rosso IM, Killgore WD, Cintron CM, Gruber SA, Tohen M Yurgelun-Todd DA, 2006. Reduced Amygdala Volumes in First-Episode Bipolar Disorder and Correlation with Cerebral White Matter. Biol Psychiatry. [DOI] [PubMed] [Google Scholar]
  69. Schneider S, Peters J, Bromberg U, Brassen S, Menz MM, Miedl SF, Loth E, Banaschewski T, Barbot A, Barker G, Conrod PJ, Dalley JW, Flor H, Gallinat J, Garavan H, Heinz A, Itterman B, Mallik C, Mann K, Artiges E, Paus T, Poline JB, Rietschel M, Reed L, Smolka MN, Spanagel R, Speiser C, Strohle A, Struve M, Schumann G, Buchel C Consortium, I., 2011. Boys do it the right way: sex-dependent amygdala lateralization during face processing in adolescents. Neuroimage. 56, 1847–53. [DOI] [PubMed] [Google Scholar]
  70. Sergerie K, Chochol C Armony JL, 2008. The role of the amygdala in emotional processing: a quantitative meta-analysis of functional neuroimaging studies. Neurosci Biobehav Rev. 32, 811–30. [DOI] [PubMed] [Google Scholar]
  71. Sheline YI, Sanghavi M, Mintun MA Gado MH, 1999. Depression duration but not age predicts hippocampal volume loss in medically healthy women with recurrent major depression. J Neurosci. 19, 5034–43. [DOI] [PMC free article] [PubMed] [Google Scholar]
  72. Shirazi SN, Friedman AR, Kaufer D Sakhai SA, 2015. Glucocorticoids and the Brain: Neural Mechanisms Regulating the Stress Response. Adv Exp Med Biol. 872, 235–52. [DOI] [PubMed] [Google Scholar]
  73. Siegle GJ, Konecky RO, Thase ME Carter CS, 2003. Relationships between amygdala volume and activity during emotional information processing tasks in depressed and never-depressed individuals: an fMRI investigation. Ann N Y Acad Sci. 985, 481–4. [DOI] [PubMed] [Google Scholar]
  74. Sitko K, Bentall RP, Shevlin M, O’sullivan N Sellwood W, 2014. Associations between specific psychotic symptoms and specific childhood adversities are mediated by attachment styles: an analysis of the National Comorbidity Survey. Psychiatry Res. 217, 202–9. [DOI] [PubMed] [Google Scholar]
  75. Smith SM, 2002. Fast robust automated brain extraction. Hum Brain Mapp. 17, 143–55. [DOI] [PMC free article] [PubMed] [Google Scholar]
  76. Strakowski SM, Delbello MP, Sax KW, Zimmerman ME, Shear PK, Hawkins JM Larson ER, 1999. Brain magnetic resonance imaging of structural abnormalities in bipolar disorder. Arch Gen Psychiatry. 56, 254–60. [DOI] [PubMed] [Google Scholar]
  77. Sublette ME, Baca-Garcia E, Parsey R, Oquendo M, Rodrigues SM, Galfalvy H, Huang Y, Arango V Mann JJ, 2008. Effect of BDNF val66met polymorphism on age-related amygdala volume changes in healthy subjects. Prog Neuropsychopharmacol Biol Psychiatry. 32, 1652–5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  78. Swayze VW 2nd, Andreasen NC, Alliger RJ, Yuh WT Ehrhardt JC, 1992. Subcortical and temporal structures in affective disorder and schizophrenia: a magnetic resonance imaging study. Biol Psychiatry. 31, 221–40. [DOI] [PubMed] [Google Scholar]
  79. Tang Y, Wang F, Xie G, Liu J, Li L, Su L, Liu Y, Hu X, He Z Blumberg HP, 2007. 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. 156, 83–6. [DOI] [PubMed] [Google Scholar]
  80. Tottenham N, Hare TA, Quinn BT, Mccarry TW, Nurse M, Gilhooly T, Millner A, Galvan A, Davidson MC, Eigsti IM, Thomas KM, Freed PJ, Booma ES, Gunnar MR, Altemus M, Aronson J Casey BJ, 2010. Prolonged institutional rearing is associated with atypically large amygdala volume and difficulties in emotion regulation. Dev Sci. 13, 46–61. [DOI] [PMC free article] [PubMed] [Google Scholar]
  81. Van Nierop M, Van Os J, Gunther N, Van Zelst C, De Graaf R, Ten Have M, Van Dorsselaer S, Bak M, Myin-Germeys I Van Winkel R, 2014. Does social defeat mediate the association between childhood trauma and psychosis? Evidence from the NEMESIS-2 Study. Acta Psychiatr Scand. 129, 467–76. [DOI] [PubMed] [Google Scholar]
  82. Von Gunten A, Fox NC, Cipolotti L Ron MA, 2000. A volumetric study of hippocampus and amygdala in depressed patients with subjective memory problems. J Neuropsychiatry Clin Neurosci. 12, 493–8. [DOI] [PubMed] [Google Scholar]
  83. Vyas A, Mitra R, Shankaranarayana Rao BS Chattarji S, 2002. Chronic stress induces contrasting patterns of dendritic remodeling in hippocampal and amygdaloid neurons. J Neurosci. 22, 6810–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  84. Wager TD, Phan KL, Liberzon I Taylor SF, 2003. Valence, gender, and lateralization of functional brain anatomy in emotion: a meta-analysis of findings from neuroimaging. Neuroimage. 19, 513–31. [DOI] [PubMed] [Google Scholar]
  85. Weniger G, Lange C Irle E, 2006. Abnormal size of the amygdala predicts impaired emotional memory in major depressive disorder. J Affect Disord. 94, 219–29. [DOI] [PubMed] [Google Scholar]
  86. Wignall EL, Dickson JM, Vaughan P, Farrow TF, Wilkinson ID, Hunter MD Woodruff PW, 2004. Smaller hippocampal volume in patients with recent-onset posttraumatic stress disorder. Biol Psychiatry. 56, 832–6. [DOI] [PubMed] [Google Scholar]
  87. Wolke D, Lereya ST, Fisher HL, Lewis G Zammit S, 2014. Bullying in elementary school and psychotic experiences at 18 years: a longitudinal, population-based cohort study. Psychol Med. 44, 2199–211. [DOI] [PubMed] [Google Scholar]
  88. Woon FL Hedges DW, 2009. Amygdala volume in adults with posttraumatic stress disorder: a meta-analysis. J Neuropsychiatry Clin Neurosci. 21, 5–12. [DOI] [PubMed] [Google Scholar]
  89. Xia J, Chen J, Zhou Y, Zhang J, Yang B, Xia L Wang C, 2004. Volumetric MRI analysis of the amygdala and hippocampus in subjects with major depression. J Huazhong Univ Sci Technolog Med Sci. 24, 500–2, 506. [DOI] [PubMed] [Google Scholar]
  90. Yang RJ, Mozhui K, Karlsson RM, Cameron HA, Williams RW Holmes A, 2008. Variation in mouse basolateral amygdala volume is associated with differences in stress reactivity and fear learning. Neuropsychopharmacology. 33, 2595–604. [DOI] [PubMed] [Google Scholar]
  91. Yuan TF Hou G, 2015. The effects of stress on glutamatergic transmission in the brain. Mol Neurobiol. 51, 1139–43. [DOI] [PubMed] [Google Scholar]
  92. Zalsman G, Huang YY, Oquendo MA, Burke AK, Hu XZ, Brent DA, Ellis SP, Goldman D Mann JJ, 2006. Association of a triallelic serotonin transporter gene promoter region (5-HTTLPR) polymorphism with stressful life events and severity of depression. Am J Psychiatry. 163, 1588–93. [DOI] [PubMed] [Google Scholar]

RESOURCES