Structural brain changes and neuroticism in late-life depression: a neural basis for depression subtypes

The Role of State Versus Trait Anxiety on Cognition in Older Adults With Major Depressive Disorder

OBJECTIVE

Anxiety superimposed on late life depression (LLD) results in greater changes to prefrontal and medial temporal brain regions compared to depression alone. Yet, the combined impact of anxiety and depression on cognition in LLD has not been thoroughly investigated. The current study investigated whether annual changes in state and trait anxiety were associated with cognitive changes in older adults with major depression. We hypothesized that the presence of anxiety among older depressed adults would be associated with worse cognitive performance in the domains of memory and executive functioning over time.

DESIGN

Three-year longitudinal observational study of older adults with LLD who were offered antidepressant treatment.

SETTING

Academic Health Center.

METHODS

Participants included 124 adults aged 60+ who met criteria for major depression at baseline. The association between anxiety and cognition was examined with separate multilevel linear models that addressed both between-subject and within-person effects of state and trait anxiety on cognitive functioning tests.

RESULTS

Individuals who experienced annual increases in anxiety above his/her personal average also experienced cognitive decline. Increases in state anxiety were associated with declines in memory and global cognition. By contrast, increases in trait anxiety were associated with declines in mental flexibility and memory. These findings remained significant even when controlling for changes in depression over time.

CONCLUSION

In LLD, individual increases in state and trait anxiety were associated with cognitive declines in different domains.

Efficacy of transcranial photobiomodulation in the treatment for major depressive disorder: A TMS-EEG and pilot study

BACKGROUND

Major depressive disorder (MDD) was a prevalent mental condition that may be accompanied by decreased excitability of left frontal pole (FP) and abnormal brain connections. An 820 nm tPBM can induce an increase in stimulated cortical excitability. The purpose of our study was to establish how clinical symptoms and time-varying brain network connectivity of MDD were affected by transcranial photobiomodulation (tPBM).

METHODS

A total of 11 patients with MDD received 820 nm tPBM targeting the left FP for 14 consecutive days. The severity of symptoms was evaluated by neuropsychological assessments at baseline, after treatment, 4-week and 8-week follow-up; 8-min transcranial magnetic stimulation combined electroencephalography (TMS-EEG) was performed for five healthy controls and five patients with MDD before and after treatment, and time-varying EEG network was analyzed using the adaptive-directed transfer function.

RESULTS

All of scales scores in the 11 patients decreased significantly after 14-day tPBM (p < .01) and remained at 8-week follow-up. The time-varying brain network analysis suggested that the brain regions with enhanced connection information outflow in MDD became gradually more similar to healthy controls after treatment.

CONCLUSIONS

This study showed that tPBM of the left FP could improve symptoms of patients with MDD and normalize the abnormal network connections.

Challenges in Identifying Individualized Brain Biomarkers of Late Life Depression

Research into neuroimaging biomarkers for Late Life Depression (LLD) has identified neural correlates of LLD including increased white matter hyperintensities and reduced hippocampal volume. However, studies into neuroimaging biomarkers for LLD largely fail to converge. This lack of replicability is potentially due to challenges linked to construct variability, etiological heterogeneity, and experimental rigor. We discuss suggestions to help address these challenges, including improved construct standardization, increased sample sizes, multimodal approaches to parse heterogeneity, and the use of individualized analytical models.

Neuroticism is associated with increase in depression symptoms over time in older adults with type 2 diabetes

OBJECTIVES

The likelihood of depression symptoms in those with type 2 diabetes (T2D) is high. Psychological risk factors enhancing comorbidity of depression symptoms in T2D are yet to be determined. The present study examines the cross-sectional and longitudinal relationship between personality traits and distinct depression dimensions in older adults with T2D.

METHODS

Participants were older adults (age ≥65yeas) with T2D from the Israel Diabetes and Cognitive Decline (IDCD) study (N = 356), with complete data on depression [Geriatric Depression Scale (GDS) - 15 item version] and its dimensions- namely, dysphoric mood, apathy, hopelessness, memory complains and anxiety, and on personality [Big Five Inventory (BFI)]. Logistic and mixed linear regression models examined cross-sectional and longitudinal associations while adjusting for socio-demographics, cognition, cardiovascular and diabetes-related factors.

RESULTS

Cross-sectionally, high neuroticism was associated with high scores in total GDS and in all depression-dimensions, except memory complaints. Higher extroversion was associated with lower total GDS and with lower scores on all depression dimensions, except anxiety. High levels of neuroticism were associated with increase in total number of depression symptoms over time.

CONCLUSIONS

In older adults with T2D, neuroticism and extroversion are associated with most depression dimensions suggesting that these traits relate to a global depression symptomatology rather than to any specific dimension or phenomenology. High neuroticism was associated with increase in depression symptoms over time, highlighting its role in the development of depression symptoms in older adults with T2D.

Brain morphometric features predict depression symptom phenotypes in late-life depression using a deep learning model

Objectives

Our objective was to use deep learning models to identify underlying brain regions associated with depression symptom phenotypes in late-life depression (LLD).

Participants

Diagnosed with LLD (N = 116) and enrolled in a prospective treatment study.

Design

Cross-sectional.

Measurements

Structural magnetic resonance imaging (sMRI) was used to predict five depression symptom phenotypes from the Hamilton and MADRS depression scales previously derived from factor analysis: (1) Anhedonia, (2) Suicidality, (3) Appetite, (4) Sleep Disturbance, and (5) Anxiety. Our deep learning model was deployed to predict each factor score via learning deep feature representations from 3D sMRI patches in 34 a priori regions-of-interests (ROIs). ROI-level prediction accuracy was used to identify the most discriminative brain regions associated with prediction of factor scores representing each of the five symptom phenotypes.

Results

Factor-level results found significant predictive models for Anxiety and Suicidality factors. ROI-level results suggest the most LLD-associated discriminative regions in predicting all five symptom factors were located in the anterior cingulate and orbital frontal cortex.

Conclusions

We validated the effectiveness of using deep learning approaches on sMRI for predicting depression symptom phenotypes in LLD. We were able to identify deep embedded local morphological differences in symptom phenotypes in the brains of those with LLD, which is promising for symptom-targeted treatment of LLD. Future research with machine learning models integrating multimodal imaging and clinical data can provide additional discriminative information.

Depression as an Embodied Experience: Identifying the Central Role of the Body in Meaning-Making and Identity Processes

Α significant part of the psychological research on mental health and illness is interested in how the body can impact one's mental health. This impact is primarily explored using a biomedical framework, in studies that examine the body's role in the emergence of a mental illness, the ways it can signify the presence of an illness (i.e. physical symptoms) and, finally, its role in the treatment process. Within this literature, the body is conceptualised as an object that can be diagnosed and treated. The current study approaches the body as a subject in the experience of depression. Specifically, it demonstrates that the experience of depression is embodied and that the body mediates meaning-making and identity processes. Using qualitative findings from eight interviews with Greek-Cypriot adults diagnosed with depression, we demonstrate that participants make sense of depression through their bodies, as a painful, uncomfortable and agonising experience. Further, we discuss how the struggle to regain control over the body, experienced as hijacked by depression, leads to a disrupted relation with the self and the world that expands beyond the idea of the loss of self, as described in the literature. Theoretical and clinical implications are examined.

Effects of Longitudinal Changes in Neuroticism and Stress on Cognitive Decline

OBJECTIVE

The relationships among depression, personality factors, stress, and cognitive decline in the elderly are complex. Depressed elders score higher in neuroticism than nondepressed older individuals. Independently, the presence of neuroticism and the number of stressful life events are each associated with worsening cognitive decline in depressed older adults. Yet little is known about combined effects of changes in neuroticism and changes in stress on cognitive decline among older depressed adults.

DESIGN

Longitudinal observational study.

SETTING

Academic Health Center.

PARTICIPANTS

The authors examined 62 participants in the Neurobiology of Late-life depression (NBOLD) study to test the hypothesis that, compared with older depressed subjects who experience improved neuroticism and lower psychosocial stressors over time, those with worsening neuroticism and greater psychosocial stressors will demonstrate more cognitive decline.

MEASUREMENTS

The authors measured neuroticism using the NEO-Personality Inventory-Revised at baseline and 1 year. Study psychiatrists measured depression using the Montgomery-Ǻsberg Depression Rating Scale. At annual assessments, subjects reported the number of psychosocial stressors in the prior year and completed a neuropsychological evaluation. Participants completed a detailed neuropsychological battery at baseline and annually over 3 years. The battery included a test of delayed story memory (Logical Memory-2 or LMII). The outcome 3-year change in cognitive scores was regressed against 3-year change scores of neuroticism and number of psychosocial stressors, plus their interaction, while adjusting for sex, age, race, education, baseline cognitive score, and 3-year change in MADRS score as covariates.

RESULTS

In multivariable linear regression analysis with the above covariates, the interaction effect of 3-year change in Total Neuroticism score and 3-year change in Total Stressors on change in LMII performance was statistically significant (B = -0.080[95%CL: -0.145 to -0.015], T = -2.48, df = 52, p = 0.017). Further exploration of this finding showed that 1) when total stressors increased by 2 or more over 3 years, LMII change was inversely associated with neuroticism change; and 2) when neuroticism improved less, LMII change score was inversely associated with total stressor change. There were no other significant interactions between stress and neuroticism on cognition.

CONCLUSION

Our findings document the importance of tracking change in neuroticism and monitoring psychosocial stress over the long-term course of treatment in geriatric depression. Both factors exert important combined effects on memory over time. Future studies in larger samples are needed to confirm our results and to extend them to examine both cognitive change and development of dementia.

Reliable Cognitive Decline in Late-Life Major Depression

OBJECTIVE

Major depression in older adults increases the statistical likelihood of dementia. It is challenging to translate statistical evidence of cognitive decline at the group level into knowledge of individual cognitive outcomes. The objective of the current study is to investigate 2-year reliable cognitive change in late-life depression (LLD), which will enhance understanding of cognitive changes in LLD and provide a means to assess individual change.

METHODS

In a sample of non-depressed cognitively normal older adults or NDCN (n = 113), we used linear regression to predict tests of global cognition, processing speed-executive functioning, and memory administered 1 and 2 years later. Stepwise regression was used to select covariates among demographics and raw test scores (either baseline or year 1) and we cross-validated the final models using the predicted residual error sum of squares (PRESS). We then derived a z-change score from the difference between actual and predicted follow-up scores and investigated the proportion of LLD patients (n = 199) and NDCN adults who experienced reliable "decline" (a z-score < -1.645), "stability" (z-scores between + - 1.645), and "improvement" (z scores > +1.645).

RESULTS

A greater proportion LLD compared with NDCN experienced cognitive decline in processing speed/executive functioning and global cognition over 2 years. When compared to NDCN, a greater proportion of LLD also significantly improved on one test of processing speed over 2 years.

CONCLUSIONS

Older adults with LLD are at risk of meaningful cognitive decline over a relatively short period, particularly in the domain of executive functioning and processing speed. This study provides a series of reliable change equations for common neuropsychological tests that can be applied clinically.

Age-related intrinsic functional connectivity underlying emotion utilization

Previous studies investigated the age-related positivity effect in terms of emotion perception and management, whereas little is known about whether the positivity effect is shown in emotion utilization (EU). If yes, the EU-related intrinsic functional connectivity and its age-associated alterations remain to be elucidated. In this study, we collected resting-state functional magnetic resonance imaging data from 62 healthy older adults and 72 undergraduates as well as their self-ratings of EU. By using the connectome-based predictive modeling (CPM) method, we constructed a predictive model of the positive relationship between EU self-ratings and resting-state functional connectivity. Lesion simulation analyses revealed that the medial-frontal network, default mode network, frontoparietal network, and subcortical regions played key roles in the EU-related CPM. Older subjects showed significantly higher EU self-ratings than undergraduates, which was associated with strengthened connectivity between the left dorsolateral prefrontal cortex and bilateral frontal poles, and between the left frontal pole and thalamus. A mediation analysis indicated that the age-related EU network mediated the age effect on EU self-ratings. Our findings extend previous research on the age-related "positivity effect" to the EU domain, suggesting that the positivity effect on the self-evaluation of EU is probably associated with emotion knowledge which accumulates with age.

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.

The neuroanatomy of social trust predicts depression vulnerability

Trust attitude is a social personality trait linked with the estimation of others’ trustworthiness. Trusting others, however, can have substantial negative effects on mental health, such as the development of depression. Despite significant progress in understanding the neurobiology of trust, whether the neuroanatomy of trust is linked with depression vulnerability remains unknown. To investigate a link between the neuroanatomy of trust and depression vulnerability, we assessed trust and depressive symptoms and employed neuroimaging to acquire brain structure data of healthy participants. A high depressive symptom score was used as an indicator of depression vulnerability. The neuroanatomical results observed with the healthy sample were validated in a sample of clinically diagnosed depressive patients. We found significantly higher depressive symptoms among low trusters than among high trusters. Neuroanatomically, low trusters and depressive patients showed similar volume reduction in brain regions implicated in social cognition, including the dorsolateral prefrontal cortex (DLPFC), dorsomedial PFC, posterior cingulate, precuneus, and angular gyrus. Furthermore, the reduced volume of the DLPFC and precuneus mediated the relationship between trust and depressive symptoms. These findings contribute to understanding social- and neural-markers of depression vulnerability and may inform the development of social interventions to prevent pathological depression.

Association of 1-year change in neuroticism and 3-year change in cognitive performance among older depressed adults

OBJECTIVES

The relationships among depression, personality factors, and cognitive decline in the elderly are complex. Depressed elders score higher in neuroticism than nondepressed older individuals. Presence of neuroticism worsens cognitive decline in depressed older adults. Yet little is known about changes in neuroticism among older adults being treated for depression and the impact of these changes on cognitive decline.

DESIGN

Longitudinal observational study.

SETTING

Academic Health Center.

PARTICIPANTS

We examined 68 participants in the neurobiology of late-life depression (LLD) study to test the hypothesis that older depressed subjects with more improvement in neuroticism would experience less cognitive decline compared with those with less change in neuroticism.

MEASUREMENTS

We measured neuroticism using the NEO-Personality Inventory-Revised at baseline and 1 year. Study psychiatrists measured depression using the Montgomery-Åsberg depression rating scale (MADRS). Global cognitive performance was measured using the Consortium to Establish a Registry for Alzheimer's disease (CERAD) battery at baseline and annually over 3 years. Regression models of 1-year change in neuroticism and 3-year change in CERAD included sex, age, race, education, and 1-year change in MADRS score as covariates.

RESULTS

We found that among older adults, 1-year change in neuroticism was inversely associated with 3-year change in CERAD total score.

CONCLUSIONS

Our findings challenge the notion of longitudinal stability of measures of personality, especially among older depressed individuals. They highlight the importance of repeated personality assessment, especially of neuroticism, in the management of LLD. Future studies in larger samples followed for longer periods are needed to confirm our results and to extend them to examine both cognitive change and development of dementia.