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

Individualized prediction of cognitive test scores from functional brain connectome in patients with first-episode late-life depression

BACKGROUND

In the realm of cognitive screening, the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) are widely utilized for detecting cognitive deficits in patients with late-life depression (LLD), However, the interindividual variability in neuroimaging biomarkers contributing to individual-specific symptom severity remains poorly understood. In this study, we used a connectome-based predictive model (CPM) approach on resting-state functional magnetic resonance imaging data from patients with LLD to establish individualized prediction models for the MoCA and the MMSE scores.

METHODS

We recruited 135 individuals diagnosed with first-episode LLD for this research. Participants underwent the MMSE and MoCA tests, along with resting-state functional magnetic resonance imaging scans. Functional connectivity matrices derived from these scans were utilized in CPM models to predict MMSE or MoCA scores. Predictive precision was assessed by correlating predicted and observed scores, with the significance of prediction performance evaluated through a permutation test.

RESULTS

The negative model of the CPM procedure demonstrated a significant capacity to predict MoCA scores (r = -0.309, p = 0.002). Similarly, the CPM procedure could predict MMSE scores (r = -0.236, p = 0.016). The predictive models for cognitive test scores in LLD primarily involved the visual network, somatomotor network, dorsal attention network, and ventral attention network.

CONCLUSIONS

Brain functional connectivity emerges as a promising predictor of personalized cognitive test scores in LLD, suggesting that functional connectomes are potential neurobiological markers for cognitive performance in patients with LLD.

Multi-modal morphometric association study of subclinical depressive symptoms using voxel-based morphometry, cortical thickness, and diffusion tensor imaging (DTI)

BACKGROUND

Case-control studies in major depression have established numerous regional grey and white matter effects in fronto-limbic brain regions. Yet, brain structural studies of dimensional depressive psychopathology within the subclinical spectrum are still limited, in particular for multi-modal imaging approaches.

METHODS

Using voxel-based and surface-based morphometry (cortical thickness) in combination with diffusion tensor imaging (DTI) in a large non-clinical sample (N = 300), we correlated grey and white matter structural variation with subclinical depressive symptoms assessed with Beck's Depression inventory (BDI).

RESULTS

We found a significant decrease of axial diffusivity associated with higher BDI scores in the left hippocampal part of the cingulum bundle (p < 0.05, threshold free cluster enhanced [TFCE] p-value) and some grey matter trend results e.g., a non-linear negative correlation of cortical thickness with depressive symptom load in the right pre/postcentral cortex (pFWE = 0.054, family wise error [FWE] peak level corrected) and a trend in grey matter volume decrease in women in the inferior frontal gyrus (pFWE = 0.054).

LIMITATIONS

Since all grey matter effects disappear after FWE correction, we assume more stable effects in a larger, less homogenous sample enriched by help-seeking subjects covering a wider range of subclinical psychopathology.

CONCLUSION

Our study adds correlations between single depressive symptoms and brain structure to a growing literature. Since subclinical depression is increasingly recognised to be relevant in our understanding of manifest depression, early detection and identification of potential brain correlates of minor depressive symptoms has the potential to expand and reveal possible biomarkers and early psychological treatment.

Low Functional network integrity in cognitively unimpaired and MCI subjects with depressive symptoms: results from a multi-center fMRI study

Evidence suggests that depressive symptomatology is a consequence of network dysfunction rather than lesion pathology. We studied whole-brain functional connectivity using a Minimum Spanning Tree as a graph-theoretical approach. Furthermore, we examined functional connectivity in the Default Mode Network, the Frontolimbic Network (FLN), the Salience Network, and the Cognitive Control Network. All 183 elderly subjects underwent a comprehensive neuropsychological evaluation and a 3 Tesla brain MRI scan. To assess the potential presence of depressive symptoms, the 13-item version of the Beck Depression Inventory (BDI) or the Geriatric Depression Scale (GDS) was utilized. Participants were assigned into three groups based on their cognitive status: amnestic mild cognitive impairment (MCI), non-amnestic MCI, and healthy controls. Regarding affective symptoms, subjects were categorized into depressed and non-depressed groups. An increased mean eccentricity and network diameter were found in patients with depressive symptoms relative to non-depressed ones, and both measures showed correlations with depressive symptom severity. In patients with depressive symptoms, a functional hypoconnectivity was detected between the Anterior Cingulate Cortex (ACC) and the right amygdala in the FLN, which impairment correlated with depressive symptom severity. While no structural difference was found in subjects with depressive symptoms, the volume of the hippocampus and the thickness of the precuneus and the entorhinal cortex were decreased in subjects with MCI, especially in amnestic MCI. The increase in eccentricity and diameter indicates a more path-like functional network configuration that may lead to an impaired functional integration in depression, a possible cause of depressive symptomatology in the elderly.

Altered resting-state brain oscillation and the associated cognitive impairments in late-life depression with different depressive severity: An EEG power spectrum and functional connectivity study

OBJECTIVE

Cognitive impairments are prevalent in late-life depression (LLD). However, it remains unclear whether there are concurrent brain oscillation alterations in resting condition across varying level of depression severity. This cross-sectional study aims to investigate the characteristics of altered resting-state oscillations, including power spectrum and functional connectivity, and their association with the cognitive impairments in LLD with different depression severity.

METHODS

A total of 65 patients with LLD and 40 elder participants without depression were recruited. Global cognition and subtle cognitive domains were evaluated. A five-minute resting-state electroencephalography (EEG) was conducted under eyes-closed conditions. Measurements included the ln-transformed absolute power for power spectrum analysis and the weighted phase lag index (wPLI) for functional connectivity analysis.

RESULTS

Attentional and executive dysfunction were exhibited in Moderate-Severe LLD group. Enhanced posterior upper gamma power was observed in both LLD groups. Additionally, enhanced parietal and fronto-parietal/occipital theta connectivity were observed in Moderate-Severe LLD group, which were associated with the attentional impairment.

LIMITATIONS

Limitations include a small sample size, concomitant medication use, and a relatively higher proportion of females.

CONCLUSIONS

Current study observed aberrant brain activity patterns in LLD across different levels of depression severity, which were linked to cognitive impairments. The altered posterior brain oscillations may be trait marker of LLD. Moreover, cognitive impairments and associated connectivity alterations were exhibited in moderate-severe group, which may be a state-like marker of moderate-to severe LLD. The study deepens understanding of cognitive impairments with the associated oscillation changes, carrying implications for neuromodulation targets in LLD.

Association of white matter hyperintensities and clinical vascular burden with depressive symptoms in Black older adults

OBJECTIVES

Black older adults have a higher vascular burden compared to non-Hispanic White (NHW) older adults, which may put them at risk for a form of depression known as vascular depression (VaDep). The literature examining VaDep in Black older adults is sparse. The current study addressed this important gap by examining whether vascular burden was associated with depressive symptoms in Black older adults.

METHODS

Participants included 113 Black older adults from the Healthy Brain Project, a substudy of the Health, Aging, and Body Composition Study. In multiple regression analyses, clinical vascular burden (sum of vascular conditions) and white matter hyperintensity (WMH) volume predicted depressive symptoms as measured by the Center for Epidemiologic Studies Depression Scale, controlling for demographic variables. Follow-up analyses compared the associations in the Black subsample and in 179 NHW older adults.

RESULTS

Higher total WMH volume, but not clinically-defined vascular burden, predicted higher concurrent depressive symptoms and higher average depressive symptoms over 4 years. Similar associations were found between uncinate fasciculus (UF) WMHs and concurrent depressive symptoms and between superior longitudinal fasciculus WMHs and average depressive symptoms. The association between depressive symptoms and UF WMH was stronger in Black compared to NHW individuals.

CONCLUSION

This research is consistent with the VaDep hypothesis and extends it to Black older adults, a group that has historically been underrepresented in the literature. Results highlight WMH in the UF as particularly relevant to depressive symptoms in Black older adults and suggest this group may be particularly vulnerable to the negative effects of WMH.

Task-based functional connectivity reveals aberrance with the salience network during emotional interference in late-life depression

OBJECTIVES

Late-life depression (LLD) is a common and debilitating disorder. Previously, resting-state studies have revealed abnormal functional connectivity (FC) of brain networks in LLD. Since LLD is associated with emotional-cognitive control deficits, the aim of this study was to compare FC of large-scale brain networks in older adults with and without a history of LLD during a cognitive control task with emotional stimuli.

METHODS

Cross-sectional case-control study. Twenty participants diagnosed with LLD and 37 never-depressed adults 60-88 years of age underwent functional magnetic resonance imaging during an emotional Stroop task. Network-region-to-region FC was assessed with seed regions in the default mode, the frontoparietal, the dorsal attention, and the salience networks.

RESULTS

FC between salience and sensorimotor network regions and between salience and dorsal attention network regions were reduced in LLD patients compared to controls during the processing of incongruent emotional stimuli. The normally positive FC between these networks were negative in LLD patients and inversely correlated with vascular risk and white matter hyperintensities.

CONCLUSIONS

Emotional-cognitive control in LLD is associated with aberrant functional coupling between salience and other networks. This expands on the network-based LLD model and proposes the salience network as a target for future interventions.

A voxel-based morphometry investigation of brain structure variations in late-life depression with insomnia

Background

Late-life depression (LLD) is linked to various medical conditions and influenced by aging-related processes. Sleep disturbances and insomnia symptoms may be early indicators or risk factors for depression. Neuroimaging studies have attempted to understand the neural mechanisms underlying LLD, focusing on different brain networks. This study aims to further delineate discriminative brain structural profiles for LLD with insomnia using MRI.

Methods

We analyzed 24 cases in the LLD with insomnia group, 26 cases in the LLD group, and 26 in the healthy control (HC) group. Patients were evaluated using the Hamilton Depression Rating Scale (HAMD-17), Hamilton Anxiety Rating Scale (HAMA), Mini-Mental State Examination (MMSE), and Pittsburgh Sleep Quality Index (PSQI). Structural MRI data were gathered and analyzed using voxel-based morphometry (VBM) to identify differences in gray matter volume (GMV) among the groups. Correlation analyses were conducted to explore the relationships between GMV and clinical characteristics.

Results

Significant difference in sex distribution was observed across the groups (p = 0.029). However, no significant differences were detected in age and MMSE scores among the groups. LLD with insomnia group exhibited significantly higher HAMA (p = 0.041) and PSQI scores (p < 0.05) compared to the LLD group. ANOVA identified significant difference in GMV of anterior lobe of cerebellum (peak MNI coordinate: x = 52, y = -40, z = -30) among HC, LLD, and LLD with insomnia. Post-hoc two-sample t-tests revealed that the significant difference in GMV was only found between the LLD group and the HC group (p < 0.05). The mean GMV in the cerebellum was positively correlated with HAMA scale in LLD patients (r = 0.47, p < 0.05).

Conclusion

There is significant difference in GMV in the LLD group, the association between late-life depression and insomnia may be linked to anxiety. This study provides insights into the discriminative brain structural profiles of LLD and LLD with insomnia, advancing the understanding of the underlying neural mechanisms and potential targets for intervention.

The heterogeneity of late-life depression and its pathobiology: a brain network dysfunction disorder

Depression is frequent in older individuals and is often associated with cognitive impairment and increasing risk of subsequent dementia. Late-life depression (LLD) has a negative impact on quality of life, yet the underlying pathobiology is still poorly understood. It is characterized by considerable heterogeneity in clinical manifestation, genetics, brain morphology, and function. Although its diagnosis is based on standard criteria, due to overlap with other age-related pathologies, the relationship between depression and dementia and the relevant structural and functional cerebral lesions are still controversial. LLD has been related to a variety of pathogenic mechanisms associated with the underlying age-related neurodegenerative and cerebrovascular processes. In addition to biochemical abnormalities, involving serotonergic and GABAergic systems, widespread disturbances of cortico-limbic, cortico-subcortical, and other essential brain networks, with disruption in the topological organization of mood- and cognition-related or other global connections are involved. Most recent lesion mapping has identified an altered network architecture with "depressive circuits" and "resilience tracts", thus confirming that depression is a brain network dysfunction disorder. Further pathogenic mechanisms including neuroinflammation, neuroimmune dysregulation, oxidative stress, neurotrophic and other pathogenic factors, such as β-amyloid (and tau) deposition are in discussion. Antidepressant therapies induce various changes in brain structure and function. Better insights into the complex pathobiology of LLD and new biomarkers will allow earlier and better diagnosis of this frequent and disabling psychopathological disorder, and further elucidation of its complex pathobiological basis is warranted in order to provide better prevention and treatment of depression in older individuals.

Late-life depressive symptoms and white matter structural integrity within older Black adults

Introduction

Older Black adults experience a high burden of depressive symptoms and cerebrovascular disease but the specific neurobiological substrates underlying the association between late-life depressive symptoms and brain integrity are understudied, particularly in within-group designs.

Methods

Using the Center for Epidemiologic Studies Depression Scale and diffusion-tensor imaging, within-Black variation in the association between late-life depressive symptoms and white matter structural integrity was examined in 297 older Black participants without dementia that were enrolled across three epidemiological studies of aging and dementia. Linear regression models were used to test associations with DTI metrics (fractional anisotropy, trace of the diffusion tensor) as the outcomes and depressive symptoms as the predictor, while adjusting for age, sex, education, scanner, serotonin-reuptake inhibitor use, total volume of white-matter hyperintensities normalized by intracranial volume, and presence of white-matter hyperintensities at the voxel level.

Results

Higher level of self-reported late-life depressive symptoms was associated with greater diffusion-tensor trace (reduced white matter integrity) in connections between commissural pathways and contralateral prefrontal regions (superior and middle frontal/dorsolateral prefrontal cortex), association pathways connecting dorsolateral prefrontal cortex with insular, striatal and thalamic regions, and association pathways connecting the parietal, temporal and occipital lobes and the thalamus.

Discussion

This study demonstrated a discernable pattern of compromised white matter structural integrity underlying late-life depressive symptoms within older Black adults.

History of major depressive disorder is associated with differences in implicit learning of emotional faces

Major depressive disorder is often associated with worsened reward learning, with blunted reward response persisting after remission. In this study, we developed a probabilistic learning task with social rewards as a learning signal. We examined the impacts of depression on social rewards (facial affect displays) as an implicit learning signal. Fifty-seven participants without a history of depression and sixty-two participants with a history of depression (current or remitted) completed a structured clinical interview and an implicit learning task with social reward. Participants underwent an open-ended interview to evaluate whether they knew the rule consciously. Linear mixed effects models revealed that participants without a history of depression learned faster and showed a stronger preference towards the positive than the negative stimulus when compared to the participants with a history of depression. In contrast, those with a history depression learned slower on average and displayed greater variability in stimulus preference. We did not detect any differences in learning between those with current and remitted depression. The results indicate that on a probabilistic social reward task, people with a history of depression exhibit slower reward learning and greater variability in their learning behavior. Improving our understanding of alterations in social reward learning and their associations with depression and anhedonia may help to develop translatable psychotherapeutic approaches for modification of maladaptive emotion regulation.

Automatic diagnosis of late-life depression by 3D convolutional neural networks and cross-sample Entropy analysis from resting-state fMRI

Resting-state fMRI has been widely used in investigating the pathophysiology of late-life depression (LLD). Unlike the conventional linear approach, cross-sample entropy (CSE) analysis shows the nonlinear property in fMRI signals between brain regions. Moreover, recent advances in deep learning, such as convolutional neural networks (CNNs), provide a timely application for understanding LLD. Accurate and prompt diagnosis is essential in LLD; hence, this study aimed to combine CNN and CSE analysis to discriminate LLD patients and non-depressed comparison older adults based on brain resting-state fMRI signals. Seventy-seven older adults, including 49 patients and 28 comparison older adults, were included for fMRI scans. Three-dimensional CSEs with volumes corresponding to 90 seed regions of interest of each participant were developed and fed into models for disease classification and depression severity prediction. We obtained a diagnostic accuracy > 85% in the superior frontal gyrus (left dorsolateral and right orbital parts), left insula, and right middle occipital gyrus. With a mean root-mean-square error (RMSE) of 2.41, three separate models were required to predict depressive symptoms in the severe, moderate, and mild depression groups. The CSE volumes in the left inferior parietal lobule, left parahippocampal gyrus, and left postcentral gyrus performed best in each respective model. Combined complexity analysis and deep learning algorithms can classify patients with LLD from comparison older adults and predict symptom severity based on fMRI data. Such application can be utilized in precision medicine for disease detection and symptom monitoring in LLD.

A pilot randomized sham controlled trial of bilateral iTBS for depression and executive function in older adults

INTRODUCTION

Executive function deficits (EFD) in late life depression (LLD) are associated with poor outcomes. Dysfunction of the cognitive control network (CCN) has been posited in the pathophysiology of LLD with EFD.

METHODS

Seventeen older adults with depression and EFD were randomized to iTBS or sham for 6 weeks. Intervention was delivered bilaterally using a recognized connectivity target.

RESULTS

A total of 89% (17/19) participants completed all study procedures. No serious adverse events occurred. Pre to post-intervention change in mean Montgomery-Asberg-depression scores was not different between iTBS or sham, p = 0.33. No significant group-by-time interaction for Montgomery-Asberg Depression rating scale scores (F _{3, 44}  = 0.51; p = 0.67) was found. No significant differences were seen in the effects of time between the two groups on executive measures: Flanker scores (F _{1, 14}  = 0.02, p = 0.88), Dimensional-change-card-sort scores F _{1, 14}  = 0.25, p = 0.63, and working memory scores (F _{1, 14}  = 0.98, p = 0.34). The Group-by-time interaction effect for functional connectivity (FC) within the Fronto-parietal-network was not significant (F _{1, 14}  = 0.36, p = 0.56). No significant difference in the effect-of-time between the two groups was found on FC within the Cingulo-opercular-network (F _{1, 14}  = 0, p = 0.98).

CONCLUSION

Bilateral iTBS is feasible in LLD. Preliminary results are unsupportive of efficacy on depression, executive function or target engagement of the CCN. A future Randomized clinical trial requires a larger sample size with stratification of cognitive and executive variables and refinement in the target engagement.

Depressive symptoms in cognitively unimpaired older adults are associated with lower structural and functional integrity in a frontolimbic network

Subclinical depressive symptoms are associated with increased risk of Alzheimer's disease (AD), but the brain mechanisms underlying this relationship are still unclear. We aimed to provide a comprehensive overview of the brain substrates of subclinical depressive symptoms in cognitively unimpaired older adults using complementary multimodal neuroimaging data. We included cognitively unimpaired older adults from the baseline data of the primary cohort Age-Well (n = 135), and from the replication cohort ADNI (n = 252). In both cohorts, subclinical depressive symptoms were assessed using the 15-item version of the Geriatric Depression Scale; based on this scale, participants were classified as having depressive symptoms (>0) or not (0). Voxel-wise between-group comparisons were performed to highlight differences in gray matter volume, glucose metabolism and amyloid deposition; as well as white matter integrity (only available in Age-Well). Age-Well participants with subclinical depressive symptoms had lower gray matter volume in the hippocampus and lower white matter integrity in the fornix and the posterior parts of the cingulum and corpus callosum, compared to participants without symptoms. Hippocampal atrophy was recovered in ADNI, where participants with subclinical depressive symptoms also showed glucose hypometabolism in the hippocampus, amygdala, precuneus/posterior cingulate cortex, medial and dorsolateral prefrontal cortex, insula, and temporoparietal cortex. Subclinical depressive symptoms were not associated with brain amyloid deposition in either cohort. Subclinical depressive symptoms in ageing are linked with neurodegeneration biomarkers in the frontolimbic network including brain areas particularly sensitive to AD. The relationship between depressive symptoms and AD may be partly underpinned by neurodegeneration in common brain regions.

Use of right orbitofrontal repetitive transcranial magnetic stimulation (rTMS) augmentation for treatment-refractory obsessive-compulsive disorder with comorbid major depressive disorder

We examined the safety and efficacy of repetitive Transcranial Magnetic Stimulation (rTMS) of the right orbitofrontal cortex (OFC) in patients with refractory obsessive-compulsive disorder (OCD) and comorbid Major Depressive Disorder. All participants (n = 26) received excitatory stimulation of the left dorsolateral prefrontal cortex followed by inhibitory stimulation of bilateral supplementary motor area for 10 sessions. In 18 patients with poor early OCD response, treatment was augmented with OFC inhibitory stimulation after the tenth treatment session. Augmentation with OFC stimulation was well-tolerated, and associated with further alleviation of both OCD and depression symptoms, particularly in individuals with more severe illnesses.

Resting-state electroencephalography of neural oscillation and functional connectivity patterns in late-life depression

BACKGROUND

The clinical manifestations of late-life depression (LLD) are highly heterogeneous. Currently, abnormal characteristics of resting-state electroencephalography (EEG) power and functional connectivity are considered trait markers of depressive symptoms in major depression. However, the relationship between EEG spectral features and functional connectivity in LLD remains unknown.

METHODS

Forty-one patients with LLD and 44 participants without depression underwent an eyes-closed resting-state EEG. EEG power spectra, alpha asymmetry, and functional connectivity were calculated and analyzed.

RESULTS

Although alpha frontal asymmetry and cortical functional connectivity between the two groups showed no significant differences, the LLD group exhibited abnormal neural oscillation patterns of higher beta frequency activity in the parietal, central, and occipital lobes while alpha activity was increased in the parietal central electrodes.

LIMITATIONS

The number of EEG electrodes used in this study was low, and the sample size was limited.

CONCLUSIONS

Increased alpha and beta frequency band powers were observed in patients with LLD. These abnormal patterns may be associated with a disturbed balance of cortical excitation, inhibition, and hyperactivity. In the future, a neurofeedback protocol based on the findings of neural oscillation patterns in certain types of LLD should be explored.

Mindfulness-based cognitive therapy vs. a health enhancement program for the treatment of late-life depression: Study protocol for a multi-site randomized controlled trial

Background

Late-life depression (LLD) affects up to 18% of older adults and has been linked to elevated dementia risk. Mindfulness-based cognitive therapy (MBCT) holds promise for treating symptoms of depression and ameliorating cognitive deficits in older adults. While preliminary findings are promising, a definitive RCT investigating its effects on late life depression and cognition have not yet been conducted. We present a protocol describing a multi-site blinded randomized controlled trial, comparing the effects of MBCT and of an active control, a Health Enhancement Program (HEP), on depressive symptoms, executive functioning, and brain biomarkers of LLD, among several other exploratory outcomes.

Methods

Two-hundred and thirteen (n = 213) patients with LLD will be recruited at various centers in Montreal, QC, Canada. Participants will undergo stratified randomization to either MBCT or HEP intervention groups. We will assess changes in (1) depression severity using the Hamilton Depression Rating Scale (HAM-D17), (2) processing speed and executive functioning, (3) brain biomarkers of LLD (hippocampal volume, default network resting-state functional connectivity and executive network resting-state functional connectivity), and (4) other exploratory physiological and mood-based measures, at baseline (0 weeks), post intervention (8 weeks), and 26 weeks after baseline.

Discussion

The proposed study will assess the clinical potential of MBCT to improve symptoms of depression, as well as examine its impact on cognitive impairments and neurobiological markers, and thus inform its use as a promising adjunct in the treatment of LLD.

Clinical trial registration

www.ClinicalTrials.gov, identifier: NCT05366088.

Sustained attention alterations in major depressive disorder: A review of fMRI studies employing Go/No-Go and CPT tasks

BACKGROUND

Major depressive disorder (MDD) is a severe psychiatric condition characterized by selective cognitive dysfunctions. In this regard, functional Magnetic Resonance Imaging (fMRI) studies showed, both at resting state and during tasks, alterations in the brain functional networks involved in cognitive processes in MDD patients compared to controls. Among those, it seems that the attention network may have a role in the disease pathophysiology. Therefore, in this review we aim at summarizing the current fMRI evidence investigating sustained attention in MDD patients.

METHODS

We conducted a search on PubMed on case-control studies on MDD employing fMRI acquisitions during Go/No-Go and continuous performance tasks. A total of 12 studies have been included in the review.

RESULTS

Overall, the majority of fMRI studies reported quantitative alterations in the response to attentive tasks in selective brain regions, including the prefrontal cortex, the cingulate cortex, the temporal and parietal lobes, the insula and the precuneus, which are key nodes of the attention, the executive, and the default mode networks.

LIMITATIONS

The heterogeneity in the study designs, fMRI acquisition techniques and processing methods have limited the generalizability of the results.

CONCLUSIONS

The results from the included studies showed the presence of alterations in the activation patterns of regions involved in sustained attention in MDD, which are in line with current evidence and seemed to explain some of the key symptoms of depression. However, given the paucity and heterogeneity of studies available, it may be worthwhile to continue investigating the attentional domain in MDD with ad-hoc study designs to retrieve more robust evidence.

Association of White Matter Integrity With Executive Function and Antidepressant Treatment Outcome in Patients With Late-Life Depression

OBJECTIVE

While patients with late-life depression (LLD) often exhibit microstructural white matter alterations that can be identified with diffusion tensor imaging (DTI), there is a dearth of information concerning the links between DTI findings and specific cognitive performance, as well as between DTI measures and antidepressant treatment outcomes.

DESIGN

Neuroimaging and cognitive tests were conducted at baseline in 71 older adults participating in a larger, 8-week duration antidepressant randomized controlled trial. Correlations between DTI measures of white matter integrity evaluated with tract-based spatial statistics, baseline neurocognitive performance, and prospective antidepressant treatment outcome were evaluated.

RESULTS

Fractional anisotropy (FA), an index of white matter integrity, was significantly positively associated with better cognitive function as measured by the Initiation/Perseveration subscale of the Dementia Rating Scale in the bilateral superior longitudinal fasciculus (SLF), bilateral SLF-temporal, and right corticospinal tract (CST). An exploratory analysis limited to these tracts revealed that increased FA in the right CST, right SLF, and right SLF-temporal tracts was correlated with a greater decrease in depressive symptoms. Increased FA in the right CST predicted a greater chance of remission, while increased FA in the right CST and the right SLF predicted a greater chance of treatment response.

CONCLUSION

In late-life depression LLD subjects, white matter integrity was positively associated with executive function in white matter tracts which act as key connecting structures underlying the cognitive control network. These tracts may play a role as a positive prognostic factor in antidepressant treatment outcome.

Depressive and anxiety symptoms are related to decreased lateral prefrontal cortex functioning during cognitive control in older people

Some studies have found a relationship between negative emotional symptoms and decreased lateral PFC functioning during a cognitive control task in healthy younger adults. Here, we asked whether this relationship is also present in the general older population and across different functional domains of the lateral PFC. Thirty-six older people (13 males) self-reported their recent depressive and anxiety symptoms. They also took two cognitive control tasks known to differentially engage the lateral frontoparietal network (digit n-back task) and the lateral frontotemporal network (Category Fluency Test) while hemodynamic changes in the PFC were monitored by functional near-infrared spectroscopy (fNIRS). Both depressive and anxiety symptoms were associated with decreased activation in the bilateral lateral PFC during cognitive control performance. Interestingly, these relationships were driven by the n-back task. Our findings suggest that depressive and anxiety symptoms are related to decreased lateral PFC functioning in particular domains of cognitive control among older people.

Exploring Signatures of Neurodegeneration in Early-Onset Older-Age Bipolar Disorder and Behavioral Variant Frontotemporal Dementia

Introduction: Older-age bipolar disorder (OABD) may involve neurocognitive decline and behavioral disturbances that could share features with the behavioral variant of frontotemporal dementia (bvFTD), making the differential diagnosis difficult in cases of suspected dementia. Objective: To compare the neuropsychological profile, brain morphometry, and structural connectivity patterns between patients diagnosed with bvFTD, patients classified as OABD with an early onset of the disease (EO-OABD), and healthy controls (HC). Methods: bvFTD patients (n = 25, age: 66 ± 7, female: 64%, disease duration: 6 ± 4 years), EO-OABD patients (n = 17, age: 65 ± 9, female: 71%, disease duration: 38 ± 8 years), and HC (n = 28, age: 62 ± 7, female: 64%) were evaluated through neuropsychological tests concerning attention, memory, executive function, praxis, and language. Brain morphometry was analyzed through surface-based morphometry (SBM), while structural brain connectivity was assessed through diffusion tensor imaging (DTI). Results: Both bvFTD and EO-OABD patients showed lower performance in neuropsychological tests of attention, verbal fluency, working memory, verbal memory, and praxis than HC. Comparisons between EO-OABD and bvFTD showed differences limited to cognitive flexibility delayed recall and intrusion errors in the memory test. SBM analysis demonstrated that several frontal, temporal, and parietal regions were altered in both bvFTD and EO-OABD compared to HC. In contrast, comparisons between bvFTD and EO-OABD evidenced differences exclusively in the right temporal pole and the left entorhinal cortex. DTI analysis showed alterations in association and projection fibers in both EO-OABD and bvFTD patients compared to HC. Commissural fibers were found to be particularly affected in EO-OABD. The middle cerebellar peduncle and the pontine crossing tract were exclusively altered in bvFTD. There were no significant differences in DTI analysis between EO-OABD and bvFTD. Discussion: EO-OABD and bvFTD may share an overlap in cognitive, brain morphometry, and structural connectivity profiles that could reflect common underlying mechanisms, even though the etiology of each disease can be different and multifactorial.

Be Fit, Be Sharp, Be Well: The Case for Exercise as a Treatment for Cognitive Impairment in Late-life Depression

OBJECTIVE

To lay out the argument that exercise impacts neurobiological targets common to both mood and cognitive functioning, and thus more research should be conducted on its use as an alternative or adjunctive treatment for cognitive impairment in late-life depression (LLD).

METHOD

This narrative review summarizes the literature on cognitive impairment in LLD, describes the structural and functional brain changes and neurochemical changes that are linked to both cognitive impairment and mood disruption, and explains how exercise targets these same neurobiological changes and can thus provide an alternative or adjunctive treatment for cognitive impairment in LLD.

RESULTS

Cognitive impairment is common in LLD and predicts recurrence of depression, poor response to antidepressant treatment, and overall disability. Traditional depression treatment with medication, psychotherapy, or both, is not effective in fully reversing cognitive impairment for most depressed older adults. Physical exercise is an ideal treatment candidate based on evidence that it 1) is an effective treatment for depression, 2) enhances cognitive functioning in normal aging and in other patient populations, and 3) targets many of the neurobiological mechanisms that underlie mood and cognitive functioning. Results of the limited existing clinical trials of exercise for cognitive impairment in depression are mixed but overall support this contention.

CONCLUSIONS

Although limited, existing evidence suggests exercise may be a viable alternative or adjunctive treatment to address cognitive impairment in LLD, and thus more research in this area is warranted. Moving forward, additional research is needed in large, diverse samples to translate the growing research findings into clinical practice.

Brain-based mechanisms of late-life depression: Implications for novel interventions

Late-life depression (LLD) is a particularly debilitating illness. Older adults suffering from depression commonly experience poor outcomes in response to antidepressant treatments, medical comorbidities, and declines in daily functioning. This review aims to further our understanding of the brain network dysfunctions underlying LLD that contribute to disrupted cognitive and affective processes and corresponding clinical manifestations. We provide an overview of a network model of LLD that integrates the salience network, the default mode network (DMN) and the executive control network (ECN). We discuss the brain-based structural and functional mechanisms of LLD with an emphasis on their link to clinical subtypes that often fail to respond to available treatments. Understanding the brain networks that underlie these disrupted processes can inform the development of targeted interventions for LLD. We propose behavioral, cognitive, or computational approaches to identifying novel, personalized interventions that may more effectively target the key cognitive and affective symptoms of LLD.

Structural and functional neuroimaging of late-life depression: a coordinate-based meta-analysis

Several neuroimaging studies have investigated localized aberrations in brain structure, function or connectivity in late-life depression, but the ensuing results are equivocal and often conflicting. Here, we provide a quantitative consolidation of neuroimaging in late-life depression using coordinate-based meta-analysis by searching multiple databases up to March 2020. Our search revealed 3252 unique records, among which we identified 32 eligible whole-brain neuroimaging publications comparing 674 patients with 568 controls. The peak coordinates of group comparisons between the patients and the controls were extracted and then analyzed using activation likelihood estimation method. Our sufficiently powered analysis on all the experiments, and more homogenous subsections of the data (patients > controls, controls > patients, and functional imaging experiments) revealed no significant convergent regional abnormality in late-life depression. This inconsistency might be due to clinical and biological heterogeneity of LLD, as well as experimental (e.g., choice of tasks, image modalities) and analytic flexibility (e.g., preprocessing and analytic parameters), and distributed patterns of neural abnormalities. Our findings highlight the importance of clinical/biological heterogeneity of late-life depression, in addition to the need for more reproducible research by using pre-registered and standardized protocols on more homogenous populations to identify potential consistent brain abnormalities in late-life depression.

White matter integrity in alcohol-dependent patients with long-term abstinence

Based on association studies on amounts of alcohol consumed and cortical and subcortical structural shrinkage, we investigated the effect of chronic alcohol consumption on white matter pathways using probabilistic tractography.Twenty-three alcohol-dependent men (with an average sobriety of 13.1 months) from a mental health hospital and 22 age-matched male healthy social drinkers underwent 3T magnetic resonance imaging. Eighteen major white matter pathways were reconstructed using the TRActs Constrained by UnderLying Anatomy tool (provided by the FreeSurfer). The hippocampal volumes were estimated using an automated procedure. The lifetime drinking history interview, Alcohol Use Disorder Identification Test, Brief Michigan Alcoholism Screening Test, and pack-years of smoking were also evaluated.Analysis of covariance controlling for age, cigarette smoking, total motion index indicated that there was no definite difference of diffusion parameters between the 2 groups after multiple comparison correction. As hippocampal volume decreased, the fractional anisotropy of the right cingulum-angular bundle decreased. Additionally, the axial diffusivity of right cingulum-angular bundle was positively correlated with the alcohol abstinence period.The results imply resilience of white matter in patients with alcohol dependence. Additional longitudinal studies with multimodal methods and neuropsychological tests may improve our findings of the changes in white matter pathways in patients with alcohol dependence.

Integrating Multimodal and Longitudinal Neuroimaging Data with Multi-Source Network Representation Learning

Uncovering the complex network of the brain is of great interest to the field of neuroimaging. Mining from these rich datasets, scientists try to unveil the fundamental biological mechanisms in the human brain. However, neuroimaging data collected for constructing brain networks is generally costly, and thus extracting useful information from a limited sample size of brain networks is demanding. Currently, there are two common trends in neuroimaging data collection that could be exploited to gain more information: 1) multimodal data, and 2) longitudinal data. It has been shown that these two types of data provide complementary information. Nonetheless, it is challenging to learn brain network representations that can simultaneously capture network properties from multimodal as well as longitudinal datasets. Here we propose a general fusion framework for multi-source learning of brain networks - multimodal brain network fusion with longitudinal coupling (MMLC). In our framework, three layers of information are considered, including cross-sectional similarity, multimodal coupling, and longitudinal consistency. Specifically, we jointly factorize multimodal networks and construct a rotation-based constraint to couple network variance across time. We also adopt the consensus factorization as the group consistent pattern. Using two publicly available brain imaging datasets, we demonstrate that MMLC may better predict psychometric scores than some other state-of-the-art brain network representation learning algorithms. Additionally, the discovered significant brain regions are synergistic with previous literature. Our new approach may boost statistical power and sheds new light on neuroimaging network biomarkers for future psychometric prediction research by integrating longitudinal and multimodal neuroimaging data.

A digital intervention targeting cognitive control network dysfunction in middle age and older adults with major depression

Nonpharmacological interventions targeting putative network mechanisms of major depressive disorder (MDD) may represent novel treatments. This mechanistic study investigates how a video game-like intervention, designed to improve cognitive control network (CCN) functioning by targeting multitasking, influences the CCN of middle-aged and older adults with MDD. The sample consisted of 34 adults aged 45-75 with SCID-defined diagnosis of MDD, Hamilton depression rating scale scores ≥20, and a deficit in cognitive control. Participants were instructed to play at home for 20-25 min per day, at least 5 times per week, for 4 weeks. Evidence of target engagement was defined a priori as >2/3 of participants showing CCN improvement. CCN engagement was defined as a change in a Z score of ≥0.5 on functional magnetic resonance imaging (fMRI) in activation and functional connectivity of the CCN during task-based and resting-state fMRI, respectively. 74% of participants showed a change in activation of the CCN, and 72% showed an increase in resting-state functional connectivity. Sixty-eight percent demonstrated improved cognitive control function, measured as either improvement on sustained attention or working memory performance or reduced self-reported symptoms of apathy on the frontal systems behavioral scale (FrsBe). Participants also reported a significant reduction in mood symptoms measured by PHQ-9. A remotely deployed neuroscience-informed video game-like intervention improves both CCN functions and mood in middle-aged and older adults with MDD. This easily-disseminated intervention may rescue CCN dysfunction present in a substantial subset of middle-aged and older adults with MDD.

Intrinsic connectivity identifies the sensory-motor network as a main cross-network between remitted late-life depression- and amnestic mild cognitive impairment-targeted networks

Remitted late-life depression (rLLD) and amnestic mild cognitive impairment (aMCI) are both associated with a high risk of developing Alzheimer's disease (AD). Neurodegeneration is considered to spread within pre-existing networks. To investigate whether, in the healthy brain, there was a pre-existing cross-network between the intrinsic networks that are vulnerable to rLLD and aMCI. We performed functional connectivity analyses based on brain areas with the greatest brain neuronal activity differences in 55 rLLD, 87 aMCI, and 114 healthy controls. Intrinsic networks that were differentially vulnerable to rLLD and aMCI converged onto the sensory-motor network (SMN) in the healthy brain. These regions in the SMN within the aMCI- and rLLD-vulnerable networks played different roles in the cognitive functions. This study identifies the SMN as a cross-network between rLLD- and aMCI-vulnerable networks. The common susceptibility of these diseases to AD is likely due to the breakdown of the cross-network. The results further suggest that interventions targeting the amelioration of sensory-motor deficits in the early course of disease in individuals with AD risk may enhance patient function as AD pathology progresses.

Topological changes in white matter connectivity network in patients with Parkinson's disease and depression

Depression is the most common non-motor symptom accompanying Parkinson's disease (PD) with high prevalence but unclear pathophysiological mechanism. Relatively little is known about the topological patterns of white matter structural networks in depressed patients with PD. In this study, we used diffusion-tensor imaging (DTI) and graph theory approaches to explore the brain structural connectome in non-depressed patients with PD (n = 47), depressed patients with PD (n = 20) and healthy controls (n = 46). All three groups exhibited small-world topology. Compared with healthy controls, non-depressed patients with PD and depressed patients with PD showed a significant reduction of network efficiency in the cortico-subcortical circuits. Moreover, depressed patients with PD exhibited higher network efficiency in fronto-limbic system, compared to non-depressed patients with PD. To sum up, our data indicated a disrupted integrity in the large-scale brain systems in depressed patients with PD patients. The structural connectome provided a basis for functional alterations in depressed patients with PD that may advance our current understanding of pathophysiological mechanism underlying Parkinson's disease.

Cerebral amyloid accumulation is associated with distinct structural and functional alterations in the brain of depressed elders with mild cognitive impairment

BACKGROUND

Elderly patients with late-life depression (LLD) often report mild cognitive impairment (MCI), so Alzheimer's disease (AD) is hard to identify in these patients. We aimed to identify the structural and functional differences between prodromal AD and LLD-related MCI.

METHODS

We performed voxel-based morphometry and functional connectivity (FC) analyses in elderly patients with both LLD and MCI to compare alterations between those with cerebral amyloidopathy and those without. We subdivided patients into subthreshold depression (STD) and major depressive disorder (MDD) groups. Using florbetaben positron emission tomography (PET), we compared volume and connectivity between healthy controls and four STD and MDD groups with or without amyloid deposition(A): STD-MCI-A(+), MDD-MCI-A(+), STD-MCI-A(-), and MDD-MCI-A(-).

RESULTS

Subjects with MDD or amyloid deposition showed greater volume reduction in the left middle temporal gyrus. MDD groups had lower FC than STD groups in the frontal, cortical, and limbic areas. The STD-MCI-A(+) group showed greater FC reduction than the MDD-MCI-A(-) and STD-MCI-A(-) groups, particularly in the hippocampus, parahippocampus, and frontal and temporal cortices. The functional differences associated with amyloid plaques were more evident in the STD group than in the MDD group.

LIMITATIONS

Limitations include disproportional sex ratios, inability to determine the longitudinal effects of amyloidopathy in large populations.

CONCLUSIONS

Regional gray matter loss and alterations in brain networks may reflect impairments caused by amyloid deposition and depression. Such changes may facilitate the detection of prodromal AD in elderly patients with both depression and cognitive dysfunction, allowing earlier intervention and more appropriate treatment.

Neural substrates for late-life depression: A selective review of structural neuroimaging studies

Recent neuroimaging studies have characterized the pathophysiology of late-life depression (LLD) as a dysfunction of the brain networks involved in the regulation of emotion, motivational behavior, cognitive control, executive function, and self-referential thinking. In this article, we reviewed LLD-associated structural neuroimaging markers such as white matter hyperintensity (WMH), white matter integrity measured by diffusion tensor imaging, cortical and subcortical volumes, and cortical thickness, which may provide a structural basis for brain network dysfunction in LLD. LLD was associated with greater severity or volumes of deep, periventricular, or overall WMH and with decreased white matter integrity in the brain regions belonging to the fronto-striatal-limbic circuits and reduced white matter tract integrity which connects these circuits, such as the cingulum, corpus callosum, or uncinate fasciculus. Decreased volumes or cortical thickness in the prefrontal cortex, orbitofrontal cortex, anterior and posterior cingulate cortex, several temporal and parietal regions, hippocampus, amygdala, striatum, thalamus, and the insula were associated with LLD. These structural neuroimaging findings were also associated with cognitive dysfunction, which is a prominent clinical feature in LLD. Several structural neuroimaging markers including the WMH burden, white matter integrity, and cortical and subcortical volumes predicted antidepressant response in LLD. These structural neuroimaging findings support the hypothesis that disruption of the brain networks involved in emotion regulation and cognitive processing by impaired structural connectivity is strongly associated with the pathophysiology of LLD.

The alteration of cognitive function networks in remitted patients with major depressive disorder: an independent component analysis

INTRODUCTION

Dysfunctional connectivity of resting-state functional networks has been observed in patients with major depressive disorder (MDD), particularly in cognitive function networks including the central executive network (CEN), default mode network (DMN) and salience network (SN). Findings from studies examining how aberrant functional connectivity (FC) changed after antidepressant treatment, however, have been inconsistent. Thus, the purpose of the present study was to explore potential mechanisms of altered cognitive function networks during resting-state between remitted major depressive disorder (rMDD) patients and healthy controls (HCs) and furthermore, the relationship between dysfunctional connectivity patterns in rMDD and clinical symptoms.

METHODOLOGY

In this study, 19 HCs and 19 rMDD patients were recruited for resting-state functional magnetic resonance imaging (fMRI) scanning. FC was evaluated with independent component analysis for CEN, DMN and SN. Two sample t tests were conducted to compare differences between rMDD and HCs. A Pearson correlation analysis was also performed to examine the relationship between connectivity of networks and cognitive function scores and clinical symptoms.

RESULTS

Compared to healthy controls, remitted patients showed lower connectivity in CEN, mostly in the superior frontal gyrus (SFG), middle frontal gyrus (MFG), inferior parietal lobule (IPL) and part of the supramarginal gyrus (SMG). Conversely, the bilateral insula, part of the SMG (a key node of the CEN) and dorsal anterior cingulate cortex (dACC) of the DMN showed higher connectivity in rMDD patients. Pearson correlation results demonstrated that connectivity of the right IPL in CEN was positively correlated with cognitive function scores, and connectivity of the left insula was negatively correlated with BDI scores.

CONCLUSIONS

Though rMDD patients reached the standard of clinal remission, unique impairments of FC in cognitive function networks remained. Aberrant FC between cognitive function networks responsible for executive control was observed in rMDD and may be associated with residual clinical symptoms.

Frontal-executive and corticolimbic structural brain circuitry in older people with remitted depression, mild cognitive impairment, Alzheimer's dementia, and normal cognition

A history of depression is a risk factor for dementia. Despite strong epidemiologic evidence, the pathways linking depression and dementia remain unclear. We assessed structural brain alterations in white and gray matter of frontal-executive and corticolimbic circuitries in five groups of older adults putatively at-risk for developing dementia- remitted depression (MDD), non-amnestic MCI (naMCI), MDD+naMCI, amnestic MCI (aMCI), and MDD+aMCI. We also examined two other groups: non-psychiatric ("healthy") controls (HC) and individuals with Alzheimer's dementia (AD). Magnetic resonance imaging (MRI) data were acquired on the same 3T scanner. Following quality control in these seven groups, from diffusion-weighted imaging (n = 300), we compared white matter fractional anisotropy (FA), mean diffusivity (MD), and from T1-weighted imaging (n = 333), subcortical volumes and cortical thickness in frontal-executive and corticolimbic regions of interest (ROIs). We also used exploratory graph theory analysis to compare topological properties of structural covariance networks and hub regions. We found main effects for diagnostic group in FA, MD, subcortical volume, and cortical thickness. These differences were largely due to greater deficits in the AD group and to a lesser extent aMCI compared with other groups. Graph theory analysis revealed differences in several global measures among several groups. Older individuals with remitted MDD and naMCI did not have the same white or gray matter changes in the frontal-executive and corticolimbic circuitries as those with aMCI or AD, suggesting distinct neural mechanisms in these disorders. Structural covariance global metrics suggested a potential difference in brain reserve among groups.

A bayesian approach to examining default mode network functional connectivity and cognitive performance in major depressive disorder

To reconcile the inconsistency of the association between the resting-state functional connectivity (RSFC) and cognitive performance in healthy and depressed groups due to high variance of both measures, we proposed a Bayesian spatio-temporal model to precisely and accurately estimate the RSFC in depressed and nondepressed participants. This model was employed to estimate spatially-adjusted functional connectivity (saFC) in the extended default mode network (DMN) that was hypothesized to correlate with cognitive performance in both depressed and nondepressed. Multiple linear regression models were used to study the relationship between DMN saFC and cognitive performance scores measured in the following four cognitive domains while adjusting for age, sex, and education. In ROI pairs including the posterior cingulate (PCC) and anterior cingulate (ACC) cortex regions, the relationship between connectivity and cognition was found only with the Bayesian approach. Moreover, only the Bayesian approach was able to detect a significant diagnostic difference in the association in ROI pairs, including both PCC and ACC regions, due to smaller variance for the saFC estimator. The results confirm that a reliable and precise saFC estimator, based on the Bayesian model, can foster scientific discovery that may not be feasible with the conventional ROI-based FC estimator (denoted as 'AVG-FC').

Linking depressive symptom dimensions to cerebellar subregion volumes in later life

The present study examined the relationship between subthreshold depressive symptoms and gray matter volume in subregions of the posterior cerebellum. Structural magnetic resonance imaging data from 38 adults aged 51 to 80 years were analyzed along with participants' responses to the Center for Epidemiologic Studies Depression Scale. Subscale scores for depressed mood, somatic symptoms, and lack of positive affect were calculated, and multiple regression analyses were used to examine the relationship between symptom dimensions and cerebellar volumes. Greater total depressive symptoms and greater somatic symptoms of depression were significantly related to larger volumes of vermis VI, a region within the salience network, which is altered in depression. Exploratory analyses revealed that higher scores on the lack of positive affect subscale were related to larger vermis VIII volumes. These results support that depressive symptom profiles have unique relationships within the cerebellum that may be important as the field move towards targeted treatment approaches for depression.

A 12-week multidomain intervention for late-life depression: a community-based randomized controlled trial

BACKGROUND

Given that current unimodal strategies for treating late-life depression are insufficient, the awareness of the necessity and importance of multidomain intervention has increased. We assessed the efficacy of multidomain intervention in reducing symptoms of late-life depression.

METHODS

This was a 12-week community-based randomized controlled trial in 78 older adults diagnosed with major depressive disorder. Participants were randomly assigned to the multidomain intervention or supportive therapy group. We provided four home visits and 12 telephone calls over 12 weeks. Four therapeutic approaches (physical activity, healthy diet, social activity, and brief cognitive restructuring) were incorporated into the multidomain intervention. The primary outcome was the change in depressive symptoms, as measured by the Montgomery-Asberg Depression Rating Scale (MADRS). Secondarily, we investigated changes in resting-state functional connectivity.

RESULTS

The MADRS total score was reduced more in the multidomain intervention group than in the supportive therapy group during the 12 weeks (intervention × time interaction, P = =0.007). After correction for multiple comparisons, the multidomain intervention group exhibited a lower MADRS total score at week 12 (score difference 5.117; P = =0.029). At follow-up, the multidomain intervention group also exhibited less functional connectivity between the posterior cingulate cortex and left inferior parietal lobule within the default mode network (FDR < 0.1).

LIMITATIONS

Caution is needed in the interpretation of the results, considering the small sample size and high percentage of female participants.

CONCLUSIONS

A 12-week multidomain intervention resulted in a greater reduction of depressive symptoms among the elderly with major depressive disorder than their counterparts who received supportive therapy.

Cognitive Control Network Homogeneity and Executive Functions in Late-Life Depression

BACKGROUND

Late-life depression is characterized by network abnormalities, especially within the cognitive control network. We used alternative functional connectivity approaches, regional homogeneity (ReHo) and network homogeneity, to investigate late-life depression functional homogeneity. We examined the association between cognitive control network homogeneity and executive functions.

METHODS

Resting-state functional magnetic resonance imaging data were analyzed for 33 older adults with depression and 43 healthy control subjects. ReHo was performed as the correlation between each voxel and the 27 neighbor voxels. Network homogeneity was calculated as global brain connectivity restricted to 7 networks. T-maps were generated for group comparisons. We measured cognitive performance and executive functions with the Dementia Rating Scale, Trail-Making Test (A and B), Stroop Color Word Test, and Digit Span Test.

RESULTS

Older adults with depression showed increased ReHo in the bilateral dorsal anterior cingulate cortex (dACC) and the right middle temporal gyrus, with no significant findings for network homogeneity. Hierarchical linear regression models showed that higher ReHo in the dACC predicted better performance on Trail-Making Test B (p < .001; R2 = .49), Digit Span Backward (p < .05; R2 = .23), and Digit Span Total (p < .05; R2 = .23). Used as a seed, the dACC cluster of higher ReHo showed lower functional connectivity with bilateral precuneus.

CONCLUSIONS

Higher ReHo within the dACC and right middle temporal gyrus distinguish older adults with depression from control subjects. The correlations with executive function performance support increased ReHo in the dACC as a meaningful measure of the organization of the cognitive control network and a potential compensatory mechanism. Lower functional connectivity between the dACC and the precuneus in late-life depression suggests that clusters of increased ReHo may be functionally segregated.

Persistent Intrinsic Functional Network Connectivity Alterations in Middle-Aged and Older Women With Remitted Depression

BACKGROUND

In younger adults, residual alterations in functional neural networks persist during remitted depression. However, there are fewer data for midlife and older adults at risk of recurrence. Such residual network alterations may contribute to vulnerability to recurrence. This study examined intrinsic network functional connectivity in midlife and older women with remitted depression.

METHODS

A total of 69 women (24 with a history of depression, 45 with no psychiatric history) over 50 years of age completed 3T fMRI with resting-state acquisition. Participants with remitted depression met DSM-IV-TR criteria for an episode in the last 10 years but not the prior year. Whole-brain seed-to-voxel resting-state functional connectivity analyses examined the default mode network (DMN), executive control network (ECN), and salience network (SN), plus bilateral hippocampal seeds. All analyses were adjusted for age and used cluster-level correction for multiple comparisons with FDR < 0.05 and a height threshold of p < 0.001, uncorrected.

RESULTS

Women with a history of depression exhibited decreased functional connectivity between the SN (right insula seed) and ECN regions, specifically the left superior frontal gyrus. They also exhibited increased functional connectivity between the left hippocampus and the left postcentral gyrus. We did not observe any group differences in functional connectivity for DMN or ECN seeds.

CONCLUSIONS

Remitted depression in women is associated with connectivity differences between the SN and ECN and between the hippocampus and the postcentral gyrus, a region involved in interoception. Further work is needed to determine whether these findings are related to functional alterations or are predictive of recurrence.

Diagnosing and Treating Depression in Patients with Alzheimer's Disease

Although cognitive and functional impairment are the hallmark features of Alzheimer's disease (AD), neuropsychiatric symptoms associated with AD account for increased rates of disability and profoundly impact the quality of life of both patients and their caregivers. This narrative review of current evidence provides practical guidance in diagnosing and managing depression in patients with AD using pharmacological and nonpharmacological interventions. After apathy, depression is the second most common neuropsychiatric symptom in AD. Diagnosing late-life depression (LLD), particularly in those affected by AD, is complicated because older patients may not meet the criteria for a major depressive disorder. Clinically, late-life depression and dementia can be indistinguishable. Although these two entities are now thought to be related, the pathologic mechanisms remain unclear. Evidence suggests that LLD may be a prodromal symptom of neurodegenerative disease. The various geropsychiatric measures currently used to diagnose, rate the severity of, and monitor the progress of treatment for depression are imperfect. Neuroimaging represents a promising avenue toward understanding the complex pathophysiologic relationships between dementia and LLD, and will support the pursuit of biomarker-driven diagnosis and treatment. Nonpharmacologic interventions to relieve depression in persons with cognitive impairment and dementia include emotion-oriented therapies, behavioral and cognitive-behavioral modification programs, and structured activity programs. Sensory-stimulation therapies and multisensory approaches show some promise for successfully treating depression in patients with dementia, but further rigorous research is needed to establish their validity. Clinical consensus and research appear to support selective serotonin reuptake inhibitors as a first choice for the pharmacological treatment of depression in patients with dementia. However, initial support for these therapies remains variable, and further investigation is needed. Extra care is required in prescribing to this population because of the generally high level of medical and psychiatric comorbidity and the potential difficulty in assessing the cognitively impaired patient's response.

Neurological Changes and Depression: 2020 Update

This article covers current research on the relationship between depression and cognitive impairment in older adults. First, it approaches the clinical assessment of late-life depression and comorbid cognitive impairment. Cognitive risk factors for suicide are discussed. Research is then provided on neuropsychological changes associated with depression, discussing subjective cognitive impairment, mild cognitive impairment, and dementia profiles. In addition, literature regarding neuroimaging and biomarker findings in depressed older adults is presented. Finally, therapeutic models for treatment of late-life depression are discussed, including psychotherapy models, holistic treatments, pharmacologic approaches, and brain stimulation therapies.

The relationship between hippocampal volume, chronic pain, and depressive symptoms in older adults

We aimed to test the hypothesis that the effect of chronic pain on depressive symptoms is mediated through hippocampal volume (HV). Participants were 131 non-demented adults over the age of 70 years from the Einstein Aging Study. Smaller right and left HV were both associated with higher depressive symptoms, but only smaller right HV was associated with chronic pain. In mediation models, right HV was a significant mediator for the effect of chronic pain on depression. Our findings suggest presence of a shared brain substrates between chronic pain and depression as reflected by right HV.

Lifetime major depression and grey-matter volume

BACKGROUND

There is evidence of structural brain alterations in major depressive disorder (MDD), but little is known about how these alterations might be affected by age at onset or genetic vulnerability. This study examines whether lifetime episodes of MDD are associated with specific alterations in grey-matter volume, and whether those alterations vary according to sex or serotonin transporter-linked promoter region (5-HTTLPR) genotype (LL, SL or SS).

METHODS

We used structural MRI to acquire anatomic scans from 610 community-dwelling participants. We derived quantitative regional estimates of grey-matter volume in 16 subregions using FreeSurfer software. We diagnosed MDD according to DSM-IV criteria. We adjusted analyses for age, sex, total brain volume, education level, head injury and comorbidities.

RESULTS

Lifetime MDD was associated with a smaller insula, thalamus, ventral diencephalon, pallidum and nucleus accumbens and with a larger pericalcarine region in both men and women. These associations remained after adjustment for false discovery rate. Lifetime MDD was also associated with a smaller caudate nucleus and amygdala in men and with a larger rostral anterior cingulate cortex in women. Late-onset first episodes of MDD (after age 50 years) were associated with a larger rostral anterior cingulate cortex and lingual and pericalcarine regions; early-onset MDD was associated with a smaller ventral diencephalon and nucleus accumbens. Some associations differed according to 5-HTTLPR genotype: the thalamus was smaller in participants with MDD and the LL genotype; pericalcarine and lingual volumes were higher in those with the SL genotype.

LIMITATIONS

This study was limited by its cross-sectional design.

CONCLUSION

Major depressive disorder was associated with persistent volume reductions in the deep nuclei and insula and with enlargements in visual cortex subregions; alterations varied according to age of onset and genotype.

Aberrant Default Mode Network Underlying the Cognitive Deficits in the Patients With Late-Onset Depression

Late-onset depression (LOD) is regarded as a risk factor or a prodrome of Alzheimer’s disease (AD). Moreover, LOD patients with cognitive deficits have the higher risk of subsequent AD. Thus, it is necessary to understand the neural underpinnings of cognitive deficits and its pathological implications in LOD. Consistent findings show that the default mode network (DMN) is an important and potentially useful brain network for the cognitive deficits in LOD patients. In recent years, genetics has been actively researched as a possible risk factor in the pathogenesis of LOD. So, in this review, we discuss the current research progress on the cognitive deficits and DMN in LOD through a combined view of brain network and genetics. We find that different structural and functional impairments of the DMN might be involved in the etiological mechanisms of different cognitive impairments in LOD patients.