Amygdalae morphometry in late-life depression

Increased Amygdala-Paracentral Lobule/Precuneus Functional Connectivity Associated With Patients With Mood Disorder and Suicidal Behavior

Mood disorder patients have greater suicide risk than members of the general population, but how suicidal behavior relates to brain functions has not been fully elucidated. This study investigated how functional connectivity (FC) values between the right/left amygdala and the whole brain relate to suicidal behavior in patients with mood disorder. The participants in this study were 100 mood disorder patients with suicidal behavior (SB group), 120 mood disorder patients with non-suicidal behavior (NSB group), and 138 age- and gender-matched healthy controls (HC group). Whole-brain FC values among the three groups were compared using an analysis of covariance (ANCOVA). Compared to the NSB and HC groups, increased FC values in the right amygdala-bilateral paracentral lobule/precuneus circuit were observed in the SB group (Bonferroni-corrected, p < 0.017). The FC values in the NSB group did not differ significantly from those in the HC group (Bonferroni-corrected, p > 0.017). Moreover, there were no significant differences in FC values between mood disorder patients with suicide attempt (SA group) and mood disorder patients with suicidal ideation (SI group), while the FC values between the right amygdala and bilateral paracentral lobule/precuneus in the SA group were higher than the mean in the SI group. These findings suggest that right amygdala-paracentral lobule/precuneus dysfunction has an important role in patients with mood disorder and suicidal behavior.

Impaired biophysical integrity of macromolecular protein pools in the uncinate circuit in late-life depression

Major depressive disorder is a common mood disorder in the elderly. Although the neuroanatomical abnormalities have been identified in patients with late-life depression (LLD), the precise biological basis of LLD remains largely unknown. The purpose of this study was to examine the biophysical integrity of macromolecular protein pools in the nodal regions of the "uncinate circuit," a component of fronto-limbic circuitry that is connected by the uncinate fasciculus and is critical in the regulation of mood and emotions, using novel magnetization transfer (MT) imaging. Twenty-four patients with LLD and 27 non-depressed healthy control subjects (HCs) of comparable age, sex, and race were recruited from the communities of the greater Chicago Area. The nodal regions of the uncinate circuit, i.e., bilateral amygdala, hippocampus, and lateral and medial orbitofrontal cortices (OFCs), were examined. Compared with HCs, patients with LLD had significantly lower magnetization transfer ratio (MTR), a measure of the biophysical integrity of macromolecular protein pools, in bilateral amygdala and hippocampus. The lower MTR was negatively correlated with the depression score. Moreover, the MTR of these regions decreased with age and positively correlated with neuropsychological performance in the LLD group but not in the HC group. These findings suggest that LLD is associated with compromised biophysical integrity of macromolecular protein pools in nodal regions of the uncinate circuit, and that major depression may accentuate age-related attenuation of the biophysical integrity of macromolecular protein pools in this circuit. These findings provide important new insights into the neurobiological mechanisms of the pathophysiology of LLD.

Trauma exposure relates to heightened stress, altered amygdala morphology and deficient extinction learning: Implications for psychopathology

Stress exposure causes a structural reorganization in neurons of the amygdala. In particular, animal models have repeatedly shown that both acute and chronic stress induce neuronal hypertrophy and volumetric increase in the lateral and basolateral nuclei of amygdala. These effects are visible on the behavioral level, where stress enhances anxiety behaviors and provokes greater fear learning. We assessed stress and anxiety levels in a group of 18 healthy human trauma-exposed individuals (TR group) compared to 18 non-exposed matched controls (HC group), and related these measurements to amygdala volume. Traumas included unexpected adverse experiences such as vehicle accidents or sudden loss of a loved one. As a measure of aversive learning, we implemented a cued fear conditioning paradigm. Additionally, to provide a biological marker of chronic stress, we measured the sensitivity of the hypothalamus-pituitary-adrenal (HPA) axis using a dexamethasone suppression test. Compared to the HC, the TR group showed significantly higher levels of chronic stress, current stress and trait anxiety, as well as increased volume of the left amygdala. Specifically, we observed a focal enlargement in its lateral portion, in line with previous animal data. Compared to HC, the TR group also showed enhanced late acquisition of conditioned fear and deficient extinction learning, as well as salivary cortisol hypo-suppression to dexamethasone. Left amygdala volumes positively correlated with suppressed morning salivary cortisol. Our results indicate differences in trauma-exposed individuals which resemble those previously reported in animals exposed to stress and in patients with post-traumatic stress disorder and depression. These data provide new insights into the mechanisms through which traumatic stress might prompt vulnerability for psychopathology.

Long term sertraline effects on neural structures in depressed and nondepressed adult female nonhuman primates

BACKGROUND

Selective serotonin reuptake inhibitors (SSRIs) are widely prescribed for mood and other disorders. However, their neural effects are difficult to study due to patient compliance and drug history variability, and rarely studied in those prescribed SSRIs for non-mood disorders. Here we evaluated SSRI effects on neural volumetrics in depressed and nondepressed monkeys.

METHODS

42 socially-housed cynomolgus monkeys were randomized to treatment balanced on pretreatment depressive behavior and body weight. Monkeys were trained for oral administration of placebo or 20 mg/kg sertraline HCl daily for 18 months and depressive and anxious behavior recorded. Volumes of neural regions of interest in depression were measured in magnetic resonance images and analyzed by 2 (depressed, nondepressed)×2 (placebo, sertraline) ANOVA.

RESULTS

Sertraline reduced anxiety (p=0.04) but not depressive behavior (p=0.43). Left Brodmann's Area (BA) 32 was smaller in depressed than nondepressed monkeys (main effect of depression: p<0.05). Sertraline and depression status interacted to affect volumes of left Anterior Cingulate Cortex (ACC), left BA24, right hippocampus (HC), and right anterior HC (sertraline×depression interactions: all p's<0.05). In the Placebo group, depressed monkeys had smaller right anterior HC and left ACC than nondepressed monkeys. In nondepressed monkeys, sertraline reduced right HC volume, especially right anterior HC volume. In depressed monkeys sertraline increased left ACC volume. In nondepressed monkeys, sertraline reduced left BA24 volumes resulting in smaller BA24 volumes in nondepressed than sertraline-treated depressed monkeys.

CONCLUSIONS

These observations suggest that SSRIs may differentially affect neural structures in depressed and nondepressed individuals.

Brain network dysfunction in late-life depression: a literature review

As a common psychiatric disorder in the growing geriatric population, late-life depression (LLD) has a negative impact on the cognitive, affective, and somatic domains of the lives of the elderly individuals. Accumulating evidence from the structural and functional imaging studies on LLD supports a "network dysfunction model" rather than a "lesion pathology model" for understanding the underlying biological mechanism in this mental disorder. In this work, we used network dysfunction model as a conceptual framework for reviewing recent neuroimaging findings in LLD. Our focus was on 4 major neurocircuits that have been shown to be involved in LLD: default mood network, cognitive control network, affective/frontolimbic network, and corticostriatal circuits. Findings of LLD-related gray and white matter structural abnormalities and resting-state and task-based functional changes were discussed for each network separately. We extended our review by summarizing the latest works that apply graph theory-based network analysis techniques for testing alterations in whole-brain network properties associated with LLD.

Developmental changes in hippocampal shape among preadolescent children

It is known that the largest developmental changes in the hippocampus take place during the prenatal period and during the first two years of postnatal life. Few studies have been conducted to address the normal developmental trajectory of the hippocampus during childhood. In this study shape analysis was applied to study the normal developing hippocampus in a group of 103 typically developing 6- to 10-year-old preadolescent children. The individual brain was normalized to a template, and then the hippocampus was manually segmented and further divided into the head, body, and tail sub-regions. Three different methods were applied for hippocampal shape analysis: radial distance mapping, surface-based template registration using the robust point matching (RPM) algorithm, and volume-based template registration using the Demons algorithm. All three methods show that the older children have bilateral expanded head segments compared to the younger children. The results analyzed based on radial distance to the centerline were consistent with those analyzed using template-based registration methods. In analyses stratified by sex, it was found that the age-associated anatomical changes were similar in boys and girls, but the age-association was strongest in girls. Total hippocampal volume and sub-regional volumes analyzed using manual segmentation did not show a significant age-association. Our results suggest that shape analysis is sensitive to detect sub-regional differences that are not revealed in volumetric analysis. The three methods presented in this study may be applied in future studies to investigate the normal developmental trajectory of the hippocampus in children. They may be further applied to detect early deviations from the normal developmental trajectory in young children for evaluating susceptibility for psychopathological disorders involving hippocampus.

Involvement of brain-derived neurotrophic factor in late-life depression

Brain-derived neurotrophic factor (BDNF), one of the major neurotrophic factors, plays an important role in the maintenance and survival of neurons, synaptic integrity, and synaptic plasticity. Evidence suggests that BDNF is involved in major depression, such that the level of BDNF is decreased in depressed patients and that antidepressants reverse this decrease. Stress, a major factor in depression, also modulates BDNF expression. These studies have led to the proposal of the neurotrophin hypothesis of depression. Late-life depression is associated with disturbances in structural and neural plasticity as well as impairments in cognitive behavior. Stress and aging also play a crucial role in late-life depression. Many recent studies have suggested that not only expression of BDNF is decreased in the serum/plasma of patients with late-life depression, but structural abnormalities in the brain of these patients may be associated with a polymorphism in the BDNF gene, and that there is a relationship between a BDNF polymorphism and antidepressant remission rates. This review provides a critical review of the involvement of BDNF in major depression, in general, and in late-life depression, in particular.

A systematic review and meta-analysis of magnetic resonance imaging studies in late-life depression

Gray matter abnormalities within frontal-subcortical and limbic networks are hypothesized to play a key role in the pathophysiology of late-life depression. In this work, gray matter abnormalities in late-life depression are examined in a systematic review and meta-analysis of magnetic resonance imaging studies. In the systematic review, 27 articles were identified that compared participants with late-life depression with comparison group participants, and 17 studies were suitable for inclusion in meta-analyses of volumes of the whole brain, orbitofrontal cortex, caudate, hippocampus, putamen, and thalamus. Volume reductions were detected in 7 of 15 comparisons of the hippocampus and a meta-analysis revealed a significant, but small, effect size. Although examined by fewer studies, meta-analyses also revealed significant volume reductions in the orbitofrontal cortex, putamen, and thalamus. A more systematic and comprehensive analysis of the global distribution of gray matter abnormalities, and an examination of subcortical abnormalities were identified as key areas for future research.

Towards automated detection of depression from brain structural magnetic resonance images

INTRODUCTION

Depression is a major issue worldwide and is seen as a significant health problem. Stigma and patient denial, clinical experience, time limitations, and reliability of psychometrics are barriers to the clinical diagnoses of depression. Thus, the establishment of an automated system that could detect such abnormalities would assist medical experts in their decision-making process. This paper reviews existing methods for the automated detection of depression from brain structural magnetic resonance images (sMRI).

METHODS

Relevant sources were identified from various databases and online sites using a combination of keywords and terms including depression, major depressive disorder, detection, classification, and MRI databases. Reference lists of chosen articles were further reviewed for associated publications.

RESULTS

The paper introduces a generic structure for representing and describing the methods developed for the detection of depression from sMRI of the brain. It consists of a number of components including acquisition and preprocessing, feature extraction, feature selection, and classification.

CONCLUSION

Automated sMRI-based detection methods have the potential to provide an objective measure of depression, hence improving the confidence level in the diagnosis and prognosis of depression.

Regionally specific increased volume of the amygdala in Williams syndrome: evidence from surface-based modeling

Williams syndrome (WS) is a condition caused by a contiguous deletion of approximately 26-28 genes from chromosome 7, and is characterized by abnormal social and emotional processing and abnormal structure and function of the amygdala. Prior studies show that the amygdala is relatively enlarged in WS, but very little is known regarding the regional specificity of increased amygdalar volume in this condition. Here we investigated the regional specificity of structural alterations of the amygdala in WS, compared to a typically developing (TD) control group. We acquired high resolution brain MRI data from 79 participants (39 WS, 40 TD) and used a surface-based analytical modeling approach. The WS group exhibited several areas of increased radial expansion of the amygdalar surface and no areas of decreased radial expansion of the amygdalar surface compared to TD controls. The areas found to exhibit particularly increased radial expansion in WS included the bilateral posterior cortical nucleus, lateral nucleus, and the central nucleus. This greater regional and anatomical specificity of altered amygdala structure in WS contributes to a model relating genetic risk in WS to the development of key brain regions for social and emotional functioning.

Treatment course with antidepressant therapy in late-life depression

OBJECTIVE

In order to assess the effect of gray matter volumes and cortical thickness on antidepressant treatment response in late-life depression, the authors examined the relationship between brain regions identified a priori and Montgomery-Åsberg Depression Rating Scale (MADRS) scores over the course of an antidepressant treatment trial.

METHOD

In a nonrandomized prospective trial, 168 patients who were at least 60 years of age and met DSM-IV criteria for major depression underwent MRI and were enrolled in a 12-week treatment study. Exclusion criteria included cognitive impairment or severe medical disorders. The volumes or cortical thicknesses of regions of interest that differed between the depressed group and a comparison group (N=50) were determined. These regions of interest were used in analyses of the depressed group to predict antidepressant treatment outcome. Mixed-model analyses adjusting for age, education, age at depression onset, race, baseline MADRS score, scanner, and interaction with time examined predictors of MADRS scores over time.

RESULTS

Smaller hippocampal volumes predicted a slower response to treatment. With the inclusion of white matter hyper-intensity severity and neuropsychological factor scores, the best model included hippocampal volume and cognitive processing speed to predict rate of response over time. A secondary analysis showed that hippocampal volume and frontal pole thickness differed between patients who achieved remission and those who did not.

CONCLUSIONS

These data expand our understanding of the prediction of treatment course in late-life depression. The authors propose that the primary variables of hippocampal volume and cognitive processing speed, subsuming other contributing variables (episodic memory, executive function, language processing) predict antidepressant response.

Surface morphology of amygdala is associated with trait anxiety

Previous neuroimaging studies have suggested a role of amygdala in trait anxiety level, in which amygdala was typically treated as a whole. To date, it remains unknown whether the morphology of specific subregions of amygdala are associated with trait anxiety. Here, we employed a shape analysis approach to locate the association between its morphology and trait anxiety on the surface of amygdala. 24 healthy young participants were included. The boundary of amygdala for each subject was first manually outlined using high-resolution magnetic resonance (MR) image, followed by 3D surface reconstruction and parameterization using spherical harmonic description. Two point-wise metrics, direct displacement between the individual surface and atlas surface and its normal projection, were used to quantify the surface morphology of amygdala. Statistical analysis revealed significant correlations between the two surface metrics and trait anxiety levels, which were located around the lateral and central nucleus of right amygdala. Our results provided localized information for the association between amygdala and trait anxiety, and suggested a central role of the lateral and central nucleus of right amygdala on trait anxiety.

Biological basis of late life depression

Late life depression (LLD) is an important area of research given the growing elderly population. The purpose of this review is to examine the available evidence for the biological basis of LLD. Structural neuroimaging shows specific gray matter structural changes in LLD as well as ischemic lesion burden via white matter hyperintensities. Similarly, specific neuropsychological deficits have been found in LLD. An inflammatory response is another possible underlying contributor to the pathophysiology of LLD. We review the available literature examining these multiple facets of LLD and how each may affect clinical outcome in the depressed elderly.

Sex differences in amygdala subregions: evidence from subregional shape analysis

Each subregion of the amygdala is characterized by a distinct cytoarchitecture and function. However, most previous studies on sexual dimorphism and aging have assessed differences in the structure of the amygdala at the level of the amygdala in its entirety rather than at the subregional level. Using an amygdala subregional shape analysis, we investigated the effects of sex, age, and the sex × age interaction on the subregion after controlling for intracranial volume. We found the main effect of age in the subregions and the effect of sex in the superficial nucleus, which showed that men had a larger mean radius than women. We also found a sex × age interaction in the centromedial nucleus, in that the radius of the centromedial nucleus showed a steeper decline with age in women compared with men. Regarding the amygdala volume as a whole, we found only an age effect and did not find any other significant difference between genders. The sex difference in the amygdala subregion and its relevance to the circulating gonadal hormone were discussed.

Depressive Symptoms and Amygdala Volume in Elderly with Cerebral Small Vessel Disease: The RUN DMC Study

Introduction. Late onset depressive symptoms (LODSs) frequently occur in elderly with cerebral small vessel disease (SVD). SVD cannot fully explain LODS; a contributing factor could be amygdala volume. We investigated the relation between amygdala volume and LODS, independent of SVD in 503 participants with symptomatic cerebral SVD. Methods. Patients underwent FLAIR and T1 scanning. Depressive symptoms were assessed with structured questionnaires; amygdala and WML were manually segmented. The relation between amygdala volume and LODS/EODS was investigated and adjusted for age, sex, intracranial volume, and SVD. Results. Patients with LODS had a significantly lower left amygdala volume than those without (P = 0.02), independent of SVD. Each decrease of total amygdala volume (by mL) was related to an increased risk of LODS (OR = 1.77; 95% CI 1.02–3.08; P = 0.04). Conclusion. Lower left amygdala volume is associated with LODS, independent of SVD. This may suggest differential mechanisms, in which individuals with a small amygdala might be vulnerable to develop LODS.

Amygdala volume in late-life depression: relationship with age of onset

OBJECTIVES

Depression is common in the elderly population. Although numerous neuroimaging studies have examined depressed elders, there is limited research examining how amygdala volume may be related to depression.

DESIGN

A cross-sectional examination of amygdala volume comparing elders with and without a diagnosis of major depressive disorder, and between depressed subjects with early and later initial depression onset.

SETTING

An academic medical center.

PARTICIPANTS

Ninety-one elderly patients meeting Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, criteria for major depression (54 early-onset depressed and 37 late-onset depressed) and 31 elderly subjects without any psychiatric diagnoses.

MEASUREMENTS

Amygdala and cerebral volumes were measured using reliable manual tracing methods.

RESULTS

In models controlling for age, sex, and cerebral volume, there was a significant difference between diagnostic cohorts in amygdala volume bilaterally (left: F[2, 116] = 16.28, p < 0.0001; right: F[2, 116] = 16.28, p < 0.0001). Using least squares mean group analyses, both early- and late-onset depressed subjects exhibited smaller bilateral amygdala volumes than did the nondepressed cohort (all comparisons p < 0.0001), but the two depressed cohorts did not exhibit a statistically significant difference.

LIMITATIONS

Limitations include missing antidepressant treatment data, recall bias, inability to establish a causal relationship between amygdala size and depression given the cross-sectional nature of the design.

CONCLUSIONS

Depression in later life is associated with smaller amygdala volumes, regardless of age of initial onset of depression.

Amygdalar shape analysis method using surface contour aligning, spherical mapping, and probabilistic subregional segmentation

The objective of this study was to develop a reliable method for the shape analysis of the amygdala, a structure that is important in gaining a better understanding of the limbic system in the human brain. The goal of this study was threefold; to develop (1) a robust method for aligning the contour of the amygdala; (2) a reproducible method for extracting surface parameters of the amygdala using a spherical mapping technique; and (3) a standardized approach for statistical assessment and visualization of shape alterations by applying the probabilistic maps of amygdalar subregions. This technique was validated by conducting an artificial phantom study and by assessing sex-related amygdalar shape differences using T1-weighted images from healthy volunteers. In the phantom study, the region with atrophy was detected successfully through the shape analysis process. In the human study, the average radii of the centromedial (CM) subregion in the left amygdala and laterobasal (LB), superficial (SF) and CM subregions in the right amygdala were different between sexes (t-tests, p=0.02, 0.04, 0.04, and 0.002, respectively). In addition, focal regions with larger radii in amygdalae of men than those of women were found predominantly on the surfaces of bilateral SF and bilateral CM subregions, after the volumes of the amygdala had been scaled to the unit volume (1000mm(3)) (Mann-Whitney U-test, false discovery rate corrected p<0.05, clustered vertex points>25). Regions with smaller radii in amygdalae of men were found predominantly on the anterior surfaces of the right LB and SF subregions (Mann-Whitney U-test, false discovery rate corrected p<0.05, clustered vertex points>25). This is generally in agreement with previous findings from animal studies. The current method may be used for measuring subtle local shape changes of the amygdala in various psychiatric or neurologic disorders.

Shells and Spheres: An n-Dimensional Framework for Medial-Based Image Segmentation

We have developed a method for extracting anatomical shape models from n-dimensional images using an image analysis framework we call Shells and Spheres. This framework utilizes a set of spherical operators centered at each image pixel, grown to reach, but not cross, the nearest object boundary by incorporating “shells” of pixel intensity values while analyzing intensity mean, variance, and first-order moment. Pairs of spheres on opposite sides of putative boundaries are then analyzed to determine boundary reflectance which is used to further constrain sphere size, establishing a consensus as to boundary location. The centers of a subset of spheres identified as medial (touching at least two boundaries) are connected to identify the interior of a particular anatomical structure. For the automated 3D algorithm, the only manual interaction consists of tracing a single contour on a 2D slice to optimize parameters, and identifying an initial point within the target structure.