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Late-life depression (LLD) is a highly prevalent mood disorder occurring in older adults and is frequently accompanied by cognitive impairment (CI). Studies have shown that LLD may increase the risk of Alzheimer's disease (AD). However, the heterogeneity of presentation of geriatric depression suggests that multiple biological mechanisms may underlie it. Current biological research on LLD progression incorporates machine learning that combines neuroimaging data with clinical observations. There are few studies on incident cognitive diagnostic outcomes in LLD based on structural MRI (sMRI). In this paper, we describe the development of a hybrid representation learning (HRL) framework for predicting cognitive diagnosis over 5 years based on T1-weighted sMRI data. Specifically, we first extract prediction-oriented MRI features via a deep neural network, and then integrate them with handcrafted MRI features via a Transformer encoder for cognitive diagnosis prediction. Two tasks are investigated in this work, including (1) identifying cognitively normal subjects with LLD and never-depressed older healthy subjects, and (2) identifying LLD subjects who developed CI (or even AD) and those who stayed cognitively normal over five years. We validate the proposed HRL on 294 subjects with T1-weighted MRIs from two clinically harmonized studies. Experimental results suggest that the HRL outperforms several classical machine learning and state-of-the-art deep learning methods in LLD identification and prediction tasks., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Age-related macular degeneration (AMD) has recently been linked to cognitive impairment. We hypothesized that AMD modifies the brain aging trajectory, and we conducted a longitudinal diffusion MRI study on 40 participants (20 with AMD and 20 controls) to reveal the location, extent, and dynamics of AMD-related brain changes. Voxel-based analyses at the first visit identified reduced volume in AMD participants in the cuneate gyrus, associated with vision, and the temporal and bilateral cingulate gyrus, linked to higher cognition and memory. The second visit occurred 2 years after the first and revealed that AMD participants had reduced cingulate and superior frontal gyrus volumes, as well as lower fractional anisotropy (FA) for the bilateral occipital lobe, including the visual and the superior frontal cortex. We detected faster rates of volume and FA reduction in AMD participants in the left temporal cortex. We identified inter-lingual and lingual-cerebellar connections as important differentiators in AMD participants. Bundle analyses revealed that the lingual gyrus had a lower streamline length in the AMD participants at the first visit, indicating a connection between retinal and brain health. FA differences in select inter-lingual and lingual cerebellar bundles at the second visit showed downstream effects of vision loss. Our analyses revealed widespread changes in AMD participants, beyond brain networks directly involved in vision processing.

Brain structural MRI has been widely used for assessing future progression of cognitive impairment (CI) based on learning-based methods. Previous studies generally suffer from the limited number of labeled training data, while there exists a huge amount of MRIs in large-scale public databases. Even without task-specific label information, brain anatomical structures provided by these MRIs can be used to boost learning performance intuitively. Unfortunately, existing research seldom takes advantage of such brain anatomy prior. To this end, this paper proposes a brain anatomy-guided representation (BAR) learning framework for assessing the clinical progression of cognitive impairment with T1-weighted MRIs. The BAR consists of a pretext model and a downstream model , with a shared brain anatomy-guided encoder for MRI feature extraction. The pretext model also contains a decoder for brain tissue segmentation, while the downstream model relies on a predictor for classification. We first train the pretext model through a brain tissue segmentation task on 9,544 auxiliary T1-weighted MRIs, yielding a generalizable encoder. The downstream model with the learned encoder is further fine-tuned on target MRIs for prediction tasks. We validate the proposed BAR on two CI-related studies with a total of 391 subjects with T1-weighted MRIs. Experimental results suggest that the BAR outperforms several state-of-the-art (SOTA) methods. The source code and pre-trained models are available at https://github.com/goodaycoder/BAR.

Several studies employ multi-site rs-fMRI data for major depressive disorder (MDD) identification, with a specific site as the to-be-analyzed target domain and other site(s) as the source domain. But they usually suffer from significant inter-site heterogeneity caused by the use of different scanners and/or scanning protocols and fail to build generalizable models that can well adapt to multiple target domains. In this article, we propose a dual-expert fMRI harmonization (DFH) framework for automated MDD diagnosis. Our DFH is designed to simultaneously exploit data from a single labeled source domain/site and two unlabeled target domains for mitigating data distribution differences across domains. Specifically, the DFH consists of a domain-generic student model and two domain-specific teacher/expert models that are jointly trained to perform knowledge distillation through a deep collaborative learning module. A student model with strong generalizability is finally derived, which can be well adapted to unseen target domains and analysis of other brain diseases. To the best of our knowledge, this is among the first attempts to investigate multi-target fMRI harmonization for MDD diagnosis. Comprehensive experiments on 836 subjects with rs-fMRI data from 3 different sites show the superiority of our method. The discriminative brain functional connectivities identified by our method could be regarded as potential biomarkers for fMRI-related MDD diagnosis., (© 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Cao, Yang, Wang, Mo, Steffens, Zhang, Liu and Potter.)

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., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Resting-state functional magnetic resonance imaging (rs-fMRI) data have been widely used for automated diagnosis of brain disorders such as major depressive disorder (MDD) to assist in timely intervention. Multi-site fMRI data have been increasingly employed to augment sample size and improve statistical power for investigating MDD. However, previous studies usually suffer from significant inter-site heterogeneity caused for instance by differences in scanners and/or scanning protocols. To address this issue, we develop a novel discrepancy-based unsupervised cross-domain fMRI adaptation framework (called UFA-Net) for automated MDD identification. The proposed UFA-Net is designed to model spatio-temporal fMRI patterns of labeled source and unlabeled target samples via an attention-guided graph convolution module, and also leverage a maximum mean discrepancy constrained module for unsupervised cross-site feature alignment between two domains. To the best of our knowledge, this is one of the first attempts to explore unsupervised rs-fMRI adaptation for cross-site MDD identification. Extensive evaluation on 681 subjects from two imaging sites shows that the proposed method outperforms several state-of-the-art methods. Our method helps localize disease-associated functional connectivity abnormalities and is therefore well interpretable and can facilitate fMRI-based analysis of MDD in clinical practice., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Previous studies have shown that late-life depression (LLD) may be a precursor of neurodegenerative diseases and may increase the risk of dementia. At present, the pathological relationship between LLD and dementia, in particularly Alzheimer's disease (AD) is unclear. Structural MRI (sMRI) can provide objective biomarkers for the computer-aided diagnosis of LLD and AD, providing a promising solution to understand the clinical progression of brain disorders. But few studies have focused on sMRI-based predictive analysis of clinical progression from LLD to AD. In this paper, we develop a deep learning method to predict the clinical progression of LLD to AD up to 5 years after baseline time using T1-weighted structural MRIs. We also analyze several important factors that limit the diagnostic performance of learning-based methods, including data imbalance, small-sample-size, and multi-site data heterogeneity, by leveraging a relatively large-scale database to aid model training. Experimental results on 308 subjects with sMRIs acquired from 2 imaging sites and the publicly available ADNI database demonstrate the potential of deep learning in predicting the clinical progression of LLD to AD. To the best of our knowledge, this is among the first attempts to explore the complex pathophysiological relationship between LLD and AD based on structural MRI using a deep learning method.

Purpose: This study examined trends over time in the prevalence of anxiety and depression among Canadian nurses: 6 months before, 1-month after, and 3 months after COVID-19 was declared a pandemic., Methods: This study adopted a repeated cross-sectional design and surveyed unionized nurses in British Columbia (BC), Canada on three occasions: September 2019 (Time 1, prepandemic), April 2020 (Time 2, early-pandemic) and June 2020 (Time 3)., Results: A total of 10,117 responses were collected across three timepoints. This study found a significant increase of 10% to 15% in anxiety and depression between Time 1 and 2, and relative stability between Time 2 and 3, with Time 3 levels still higher than Time 1 levels. Cross-sector analyses showed similar patterns of findings for acute care and community nurses. Long-term care nurses showed a two-fold increase in the prevalence of anxiety early pandemic, followed by a sharper decline mid pandemic., Conclusions: COVID-19 has had short- and mid-term mental health implications for BC nurses particularly among those in the long-term care sector. Future research should evaluate the impact of COVID-19 on the mental health of health workers in different contexts, such as jurisdictional analyses, and better understand the long-term health and labor market consequences of elevated mental health symptoms over an extended time period., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

Age-related macular degeneration (AMD) is a common retina disease associated with cognitive impairment in older adults. The mechanism(s) that account for the link between AMD and cognitive decline remain unclear. Here we aim to shed light on this issue by investigating whether relationships between cognition and white matter in the brain differ by AMD status. In a direct group comparison of brain connectometry maps from diffusion weighted images, AMD patients showed significantly weaker quantitative anisotropy (QA) than healthy controls, predominantly in the splenium and left optic radiation. The QA of these tracts, however, did not correlate with the visual acuity measure, indicating that this group effect is not directly driven by visual loss. The AMD and control groups did not differ significantly in cognitive performance.Across all participants, better cognitive performance (e.g. verbal fluency) is associated with stronger connectivity strength in white matter tracts including the splenium and the left inferior fronto-occipital fasciculus/inferior longitudinal fasciculus. However, there were significant interactions between group and cognitive performance (verbal fluency, memory), suggesting that the relation between QA and cognitive performance was weaker in AMD patients than in controls.This may be explained by unmeasured determinants of performance that are more common or impactful in AMD or by a recruitment bias whereby the AMD group had higher cognitive reserve. In general, our findings suggest that neural degeneration in the brain might occur in parallel to AMD in the eyes, although the participants studied here do not (yet) exhibit overt cognitive declines per standard assessments., (Published by Elsevier Inc.)

Objective: Evidence suggests a cross-sectional association between personality traits and suicidal ideation in LLD. Yet, it is unclear how personality may influence suicidal ideation over time in LLD, or whether such an association would be moderated by psychosocial and biological individual differences. The present study had three aims: 1) to examine whether personality traits increase suicidal ideation in LLD over time, 2) to understand whether this relationship is influenced by subjective social support, and 3) to determine whether the potential relationship between social support, personality, and suicidal ideation is different for men and women., Design: Participants were enrolled in the Duke University Neurocognitive Outcomes of Depression in the Elderly (NCODE), a longitudinal investigation of the predictors of poor illness course in LLD. Patients were initially enrolled in the NCODE study between December 1994 and June 2000 and were followed for an average of six years., Setting: NCODE operates in a naturalistic treatment milieu., Participants: One hundred twelve participants aged 60 and older with a current diagnosis of major depressive disorder., Measurements: Annual assessments of depression, suicidal ideation, and social support (measured with the Duke Social Support Index). Participants also completed the NEO Personality Inventory-Revised (NEO-PI-R) providing measures of the five major personality dimensions (neuroticism, extraversion, openness, conscientiousness, and agreeableness)., Results: Univariate logistic generalized linear mixed modeling (GLMM) analyses revealed that higher levels of depression at baseline, less subjective social support, higher neuroticism, and lower extraversion were significantly associated with an increased likelihood of suicidal ideation over time. While the relationship between these dimensions and suicidal ideation were no longer significant in multivariate analyses, there was a significant moderating effect of social support on the association between suicidal ideation and certain neuroticism and extraversion personality facets. Decreased subjective social support was associated with an increased likelihood of suicidal ideation in LLD patients with high (but not low) impulsiveness and low (but not high) gregariousness and positive emotions. Across all models, social support was beneficial to women, but not men, in decreasing the likelihood of future suicidal ideation., Conclusion: Changes in social support may contribute to suicidal ideation in older depressed adults with certain personality traits. Irrespective of personality traits, changes in social support had a significant effect on the suicidal ideation of women but not men. These relationships were apparent even when controlling for depression severity, age, and history of suicide attempt., (Copyright © 2020. Published by Elsevier Inc.)

Burnout and depression pose significant threats to emotional and occupational functioning; however, questions exist over how these 2 conditions are associated with each other over time, and how these are related to underlying job stressors. The job demands-resources model provides a useful framework for understanding how job demands and job resources may lead to burnout, but questions remain about their distinct association with depression symptoms. The current study examined these questions in a sample of 402 nursing workers. The Exhaustion subscale of the Oldenburg Burnout Inventory, the Patient Health Questionnaire-9 depression assessment, and items reflecting job demands and job resources from the Copenhagen Psychosocial Questionnaire were assessed at baseline; additionally, Oldenburg Burnout Inventory Exhaustion and Patient Health Questionnaire-9 depression were assessed over 12 monthly follow-ups. Linear mixed models assessed longitudinal bidirectional associations between burnout and depression in both concurrent and lagged models. Longitudinal models found bidirectional relationships between burnout and depression symptoms over time, with relatively stronger associations for concurrent models relative to lagged models. Job demands and job resources each predicted unique variance in burnout and depression symptoms over time. Results provide evidence that burnout and depression symptoms change in the same direction, in tandem, rather than one condition having a distinctly stronger temporal association over the other. Results also indicate that both job demands and job resources are associated with depression symptoms independent from their association with burnout symptoms. Our results highlight the importance of considering burnout symptoms, depression symptoms, and job stressors concurrently in evaluating worker mental health. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Background: Major depressive disorder (MDD) is one of the most prevalent and debilitating psychiatric disorders. Cognitive complaints are commonly reported in MDD and cognitive impairment is a criterion item for MDD diagnosis. As cognitive processes are increasingly understood as the consequences of distributed interactions between brain regions, a network-based approach may provide novel information about the neurobiological basis of cognitive deficits in MDD., Methods: 51 Depressed (MDD, n = 23) and non-depressed (control, n = 28) adult participants completed neuropsychological testing and resting-state fMRI (rsfMRI). Cognitive domain scores (processing speed, working memory, episodic memory, and executive function) were calculated. Anatomical regions of interests were entered as seeds for functional connectivity analyses in: default mode (DMN), salience, and executive control (ECN) networks. Partial correlations controlling for age and sex were conducted for cognitive domain scores and functional connectivity in clusters with significant differences between groups., Results: Significant rsfMRI differences between groups were identified in multiple clusters in the DMN and ECN. Greater positive connectivity within the ECN and between ECN and DMN regions was associated with poorer episodic memory performance in the Non-Depressed group but better performance in the MDD group. Greater connectivity within the DMN was associated with better episodic and working memory performance in the Non-Depressed group but worse performance in the MDD group., Conclusions: These results provide evidence that cognitive performance in MDD may be associated with aberrant functional connectivity in cognitive networks and suggest patterns of alternate brain function that may support cognitive processes in MDD., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Despite increased rates of disease, disability, and social losses with aging, seniors consistently report higher levels of subjective well-being (SWB), a construct closely related to happiness, than younger adults. In this exploratory study, we utilized an available dataset to investigate how aspects of health commonly deteriorating with age, including sensory (i.e., vision and hearing) and cognitive status, relate to variability in self-described contributors to happiness. Community-dwelling seniors ( n = 114) responded to a single-item prompt: "name things that make people happy." 1731 responses were categorized into 13 domains of SWB via structured content analysis. Sensory health and cognition were assessed by Snellen visual acuity, pure-tone audiometry, and in-person administration of the Brief Test of Adult Cognition by Telephone (BTACT) battery. A subset of eligible participants ( n = 57) underwent functional magnetic resonance imaging (fMRI) to assess resting state functional connectivity (FC) within a previously described dopaminergic network associated with reward processing. SWB response patterns were relatively stable across gender, sensory status, and cognitive performance with few exceptions. For example, hearing-impaired participants listed fewer determinants of SWB (13.59 vs. 17.16; p < 0.001) and were less likely to name things in the "special events" category. Participants with a higher proportion of responses in the "accomplishments" domain (e.g., winning, getting good grades) demonstrated increased FC between the ventral tegmental area and nucleus accumbens, regions implicated in reward and motivated behavior. While the framework for determinants of happiness among seniors was largely stable across the factors assessed here, our findings suggest that subtle changes in this construct may be linked to sensory loss. The possibility that perceptions about determinants of happiness might relate to differences in intrinsic connectivity within reward-related brain networks also warrants further investigation.

Background: Cognitive complaints are common in depression, and cognition may be an important treatment target as cognitive problems often remain during remission and may contribute to recurrence risk. Previous studies of cognitive performance in depression have mainly examined late-life depression, with a focus on older adults, or assessed performance in specific cognitive tasks rather than cognitive domains., Methods: This study examined cognitive performance across multiple cognitive domains in antidepressant-free depressed adults with early onset recurrent depression compared to never-depressed controls. Domain scores were calculated for episodic memory, executive function, processing speed, and working memory, and the effect of depression diagnosis, depression severity, and depression duration on each domain score was examined, including interactions with age, sex, and education., Results: Currently depressed adults (n = 91) exhibited poorer performance in the processing speed domain compared with never-depressed adults (n = 105). Additionally, there was an interactive effect of depression duration and age on processing speed and executive function domain performance, such that performance was worse with older age and longer duration of depression. There were no effects of depression severity on performance across the cognitive domains., Conclusions: These findings support that processing speed deficits appear in young adults with early onset depression that may not be related to current mood. Additionally, the effects of cumulative depressive episodes may interact with aging such that cognitive performance deficits worsen with recurrence over the lifespan., (© 2018 Wiley Periodicals, Inc.)

Background: Late-life depression (LLD) is associated with a fragile antidepressant response and high recurrence risk. This study examined what measures predict recurrence in remitted LLD., Methods: Individuals of age 60 years or older with a Diagnostic and Statistical Manual - IV (DSM-IV) diagnosis of major depressive disorder were enrolled in the neurocognitive outcomes of depression in the elderly study. Participants received manualized antidepressant treatment and were followed longitudinally for an average of 5 years. Study analyses included participants who remitted. Measures included demographic and clinical measures, medical comorbidity, disability, life stress, social support, and neuropsychological testing. A subset underwent structural magnetic resonance imaging (MRI)., Results: Of 241 remitted elders, approximately over 4 years, 137 (56.8%) experienced recurrence and 104 (43.2%) maintained remission. In the final model, greater recurrence risk was associated with female sex (hazard ratio [HR] = 1.536; confidence interval [CI] = 1.027-2.297), younger age of onset (HR = 0.990; CI = 0.981-0.999), higher perceived stress (HR = 1.121; CI = 1.022-1.229), disability (HR = 1.060; CI = 1.005-1.119), and less support with activities (HR = 0.885; CI = 0.812-0.963). Recurrence risk was also associated with higher Montgomery-Asberg Depression Rating Scale (MADRS) scores prior to censoring (HR = 1.081; CI = 1.033-1.131) and baseline symptoms of suicidal thoughts by MADRS (HR = 1.175; CI = 1.002-1.377) and sadness by Center for Epidemiologic Studies-Depression (HR = 1.302; CI, 1.080-1.569). Sex, age of onset, and suicidal thoughts were no longer associated with recurrence in a model incorporating report of multiple prior episodes (HR = 2.107; CI = 1.252-3.548). Neither neuropsychological test performance nor MRI measures of aging pathology were associated with recurrence., Conclusions: Over half of the depressed elders who remitted experienced recurrence, mostly within 2 years. Multiple clinical and environmental measures predict recurrence risk. Work is needed to develop instruments that stratify risk., (© 2018 Wiley Periodicals, Inc.)

Age-related macular degeneration (AMD) is a retinal disease associated with significant vision loss among older adults. Previous large-scale behavioral studies indicate that people with AMD are at increased risk of cognitive deficits in language processing, particularly in verbal fluency tasks. The neural underpinnings of any relationship between AMD and higher cognitive functions, such as language processing, remain unclear. This study aims to address this issue using independent component analysis of spontaneous brain activity at rest. In 2 components associated with visual processing, we observed weaker functional connectivity in the primary visual cortex and lateral occipital cortex in AMD patients compared with healthy controls, indicating that AMD might lead to differences in the neural representation of vision. In a component related to language processing, we found that increasing connectivity within the right inferior frontal gyrus was associated with better verbal fluency performance across all older adults, and the verbal fluency effect was greater in AMD patients than controls in both right inferior frontal gyrus and right posterior temporal regions. As the behavioral performance of our patients is as good as that of controls, these findings suggest that preservation of verbal fluency performance in AMD patients might be achieved through higher contribution from right hemisphere regions in bilateral language networks. If that is the case, there may be an opportunity to promote cognitive resilience among seniors with AMD or other forms of late-life vision loss., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Inner retina in Alzheimer's Disease (AD) may experience neuroinflammation resulting in atrophy. The objective of our study was to determine whether retinal GCIPL (ganglion cell-inner plexiform layer) or nerve fiber layer (NFL) thickness may serve as noninvasive biomarkers to diagnose AD. This cross-sectional case-control study enrolled 15 mild cognitive impairment (MCI) patients, 15 mild-moderate AD patients, and 18 cognitively normal adults. NFL and GCIPL thicknesses on optical coherence tomography (OCT) were measured using Duke Optical Coherence Tomography Retinal Analysis Program (DOCTRAP) and Spectralis software. We demonstrated that regional thicknesses of NFL or GCIPL on macular or nerve OCTs did not differ between groups. However, a multi-variate regression analysis identified macular areas with a significant thickening or thinning in NFL and GCIPL in MCI and AD patients. Our primary findings controvert previous reports of thinner NFL in moderate-to-severe AD. The areas of thickening of GCIPL and NFL in the macula adjacent to areas of thinning, as revealed by a more complex statistical model, suggest that NFL and GCIPL may undergo dynamic changes during AD progression.

Background: Dual-task paradigms, in which an individual performs tasks separately and then concurrently, often demonstrate that people with neurodegenerative disorders experience more dual-task interference, defined as worse performance in the dual-task condition compared to the single-task condition., Objective: To examine how gait-cognition dual-task performance differs between cognitively normal older adults with and without an APOE ɛ4 allele., Methods: Twenty-nine individuals ages 60 to 72 with normal cognition completed a dual-task protocol in which walking and cognitive tasks (executive function, memory) were performed separately and concurrently. Fourteen participants carried APOE ɛ4 alleles (ɛ3/ɛ4 or ɛ2/ɛ4); fifteen had APOE genotypes (ɛ2/ɛ2, ɛ2/ɛ3, or ɛ3/ɛ3) associated with lower risk of Alzheimer's disease (AD)., Results: The two risk groups did not differ by age, sex, race, education, or gait or cognitive measures under single-task conditions. Compared to low risk participants, APOE ɛ4 carriers tended to exhibit greater dual-task interference. Both the memory and executive function tasks resulted in dual-task interference on gait, but effect sizes for a group difference were larger when the cognitive task was executive function. In the dual-task protocol that combined walking and the executive function task, effect sizes for group difference in gait interference were larger (0.62- 0.70) than for cognitive interference (0.45- 0.47)., Discussion: Dual-task paradigms may reveal subtle changes in brain function in asymptomatic individuals at heightened risk of AD.

Background: Individuals with major depressive disorder (MDD) may exhibit smaller striatal volumes reflecting deficits in the reward circuit. Deficits may change with age and be more pronounced among the melancholic subtype. Limited research has investigated striatal volume differences in older adults and by depression subtypes., Method: We used baseline data from the Neurocognitive Outcomes of Depression in the Elderly study. We examined volumetric differences in the putamen and caudate nucleus among older adults (60 years and older), comparing healthy control participants (n = 134) to depressed participants (n = 226), and comparing nonmelancholic depressed participants (n = 93) to melancholic depressed participants (n = 133). Group-by-age interactions were examined., Results: There were no significant group differences for the caudate nucleus. For the left putamen, investigation of the significant group-by-age interaction revealed that volume size was greater for the healthy controls compared to the depressed participants but only at younger ages (60-65 years); group differences diminished with increasing age. Examining volume by depression subtype revealed that the melancholic depressed participants had a smaller left putamen compared to the nonmelancholic depressed participants. Anhedonia symptoms were related to both smaller left and right putamen., Conclusion: Structural abnormalities in reward regions may underlie the anhedonic phenotype. Volume loss associated with MDD may attenuate in older age.

Burnout is a syndrome occurring mainly in individuals with long-term stressful work. The main complaints are emotional exhaustion and reduced performance. Burnout also largely overlaps with depression. Both are characterized by increased incidence of infections due to dysregulation of the immune system, overexpression of pro-inflammatory cytokines and cognitive deficits, particularly related to executive functions. To distinguish between burnout and depression already at the pre-clinical stage, the present double-blinded study compared immunological and cognitive parameters in seventy-six employees from emotionally demanding occupations who were post-hoc subdivided into two groups scoring low (EE-) and high (EE+) in emotional exhaustion and low (DE-) and high (DE+) in depression. Immunological parameters were measured from blood samples. Executive functions were studied by analyzing event-related brain potentials (ERPs) and performance during a task switching paradigm. Psychosocial job parameters were measured with standardized questionnaires. Burnout and mild to moderate depression largely overlapped. However, several subjects showed burnout without depressive symptoms. Higher levels of the pro-inflammatory cytokines IL-6 and IL-12 were correlated with burnout severity and depressive symptoms in male individuals. In the switch task a trend for lower performance in the EE+ vs. EE- group and no difference between DE+ and DE- groups were found. In the ERPs, however, differences were observed which distinguished between subclinical burnout and depression: the terminal contingent negative variation (CNV), indicating preparatory activity and the P3b, related to allocation of cognitive resources were generally reduced in EE+ vs. EE-, whereas no differences were found in the DE+ vs. DE- groups. The frontal P3a was selectively reduced in switch trials in the EE+ vs. EE- group and showed only a trend in DE+ vs. DE-, indicating impairment of executive control in subclinical burnout. Taken together, the results unveil specific immunological changes and declines in brain functions in employees with subclinical burnout that are not apparent in persons with moderate depression. Hence, the combination of immunological, behavioral and ERP methods renders a promising method for distinguishing both syndromes and for improving an early diagnosis of burnout before a clinical stage is reached., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Objective: Late-life depression is associated with cognitive deficits and increased risk for cognitive decline. The purpose of the study was to determine whether clinical characteristics could serve as phenotypes informative of subsequent cognitive decline. Age at depression onset and antidepressant remission at 3 months (acute response) and 12 months (chronic response) were examined., Methods: In a longitudinal study of late-life depression in an academic center, 273 depressed and 164 never-depressed community-dwelling elders aged 60 years or older were followed on average for over 5 years. Participants completed annual neuropsychological testing. Neuropsychological measures were converted to z-scores derived from the baseline performance of all participants. Cognitive domain scores at each time were then created by averaging z-scores across tests, grouped into domains of episodic memory, attention-working memory, verbal fluency, and executive function., Results: Depressed participants exhibited poorer performance at baseline and greater subsequent decline in all domains. Early-onset depressed individuals exhibited a greater decline in all domains than late-onset or nondepressed groups. For remission, remitters and nonremitters at both 3 and 12 month exhibited greater decline in episodic memory and attention-working memory than nondepressed subjects. Three-month remitters also exhibited a greater decline in verbal fluency and executive function, whereas 12-month nonremitters exhibited greater decline in executive function than other groups., Conclusion: Consistent with past studies, depressed elders exhibit greater cognitive decline than nondepressed subjects, particularly individuals with early depression onset, supporting the theory that repeated depressive episodes may contribute to decline. Clinical remission is not associated with less cognitive decline., (Published by Elsevier Inc.)

Burnout is a pattern of complaints in individuals with emotionally demanding jobs that is often seen as a precursor of depression. One often reported symptom of burnout is cognitive decline. To analyze cognitive control and to differentiate between subclinical burnout and mild to moderate depression a double-blinded study was conducted that investigates changes in the processing of performance errors and feedback in a task switching paradigm. Fifty-one of 76 employees from emotionally demanding jobs showed a sufficient number of errors to be included in the analysis. The sample was subdivided into groups with low (EE-) and high (EE+) emotional exhaustion and no (DE-) and mild to moderate depression (DE+). The behavioral data did not significantly differ between the groups. In contrast, in the EE+ group, the error negativity (Ne/ERN) was enhanced while the error positivity (Pe) did not differ between the EE+ and EE- groups. After negative feedback the feedback-related negativity (FRN) was enhanced, while the subsequent positivity (FRP) was reduced in EE+ relative to EE-. None of these effects were observed in the DE+ vs. DE-. These results suggest an upregulation of error and negative feedback processing, while the later processing of negative feedback was attenuated in employees with subclinical burnout but not in mild to moderate depression., (Copyright © 2017 Elsevier B.V. All rights reserved.)

There is a larger proportion and number of older adults in the labor force than ever before. Furthermore, older adults in the workforce are working until later ages. Although a great deal of research has examined physical health and well-being of working older adults, less research has focused on cognitive functioning. The purpose of this article is to provide a broad contemporary and multidisciplinary review of the intersection between cognitive functioning, aging, and work as a follow-up to a paper previously written by Fisher et al. (2014). We begin by providing definitions and background about cognitive functioning and how it changes over the life span. Next we discuss theories relevant to the intersection of cognitive functioning and work, including the use-it-or-lose-it hypothesis, the cognitive reserve hypothesis, hypotheses regarding environmental influences on intellectual functioning, and the job-demands-resources model. Then we summarize recent research about the effects of work on cognitive functioning, as well as ways that cognitive functioning may influence work motivation, learning, development, training, and safety. We conclude by emphasizing the importance of person-environment fit, suggesting avenues for future research, and discussing practical implications for the field of occupational health psychology. (PsycINFO Database Record, ((c) 2017 APA, all rights reserved).)

Age-related decline in fluid cognition can be characterized as a disconnection among specific brain structures, leading to a decline in functional efficiency. The potential sources of disconnection, however, are unclear. We investigated imaging measures of cerebral white-matter integrity, resting-state functional connectivity, and white-matter hyperintensity volume as mediators of the relation between age and fluid cognition, in 145 healthy, community-dwelling adults 19-79 years of age. At a general level of analysis, with a single composite measure of fluid cognition and single measures of each of the 3 imaging modalities, age exhibited an independent influence on the cognitive and imaging measures, and the imaging variables did not mediate the age-cognition relation. At a more specific level of analysis, resting-state functional connectivity of sensorimotor networks was a significant mediator of the age-related decline in executive function. These findings suggest that different levels of analysis lead to different models of neurocognitive disconnection, and that resting-state functional connectivity, in particular, may contribute to age-related decline in executive function., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Previous functional magnetic resonance imaging (fMRI) studies have reported that task-irrelevant, emotionally salient events can disrupt target discrimination, particularly when attentional demands are low, while others demonstrate alterations in the distracting effects of emotion in behavior and neural activation in the context of attention-demanding tasks. We used fMRI, in conjunction with an emotional oddball task, at different levels of target discrimination difficulty, to investigate the effects of emotional distractors on the detection of subsequent targets. In addition, we distinguished different behavioral components of target detection representing decisional, nondecisional, and response criterion processes. Results indicated that increasing target discrimination difficulty led to increased time required for both the decisional and nondecisional components of the detection response, as well as to increased target-related neural activation in frontoparietal regions. The emotional distractors were associated with activation in ventral occipital and frontal regions and dorsal frontal regions, but this activation was attenuated with increased difficulty. Emotional distraction did not alter the behavioral measures of target detection, but did lead to increased target-related frontoparietal activation for targets following emotional images as compared to those following neutral images. This latter effect varied with target discrimination difficulty, with an increased influence of the emotional distractors on subsequent target-related frontoparietal activation in the more difficult discrimination condition. This influence of emotional distraction was in addition associated specifically with the decisional component of target detection. These findings indicate that emotion-cognition interactions, in the emotional oddball task, vary depending on the difficulty of the target discrimination and the associated limitations on processing resources., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Physical exercise can improve physical and mental health. A number of imaging studies have examined the role of neuroplasticity in improving cognition with physical exercise; however, such neuroplasticity changes are not consistent across the reports partly due to small sample sizes in some studies. We thought to explore the concept that identifying consistent findings across multi-modality imaging measures would provide relatively reliable results. We designed a 6-week quasi-experiment with Wii-fitness exercise program in 24 healthy adults older than 60, and then examined the changes on neuroimaging measures including brain volume, the amplitude of low-frequency oscillation function (ALFF), regional homogeneity (ReHo), seed-based functional connectivity (FC), and the global efficiency of nodal connectivity during resting state. We focused on whether there were common regions showing changes after exercise across these measures and which measure was closely correlated with cognitive improvement. After the six-week exercise program, participants demonstrated a significant improvement in memory and executive function on neuropsychological tests, and in memory recall on an emotional memory task. The common brain regions that showed significant changes across different measures were the right striatum and the posterior cingulate (PCC). After exercise, the PCC showed decreased ReHo and increased volume, and the striatum did not show volume loss as the control group did and increased its FC with the cingulate, temporal, parietal, and occipital regions. Moreover, the connectivity change between the striatum and the thalamus was correlated with the improvement of executive function. This result implicates the striatum and the PCC associated network in physical exercise. Our work highlights the effectiveness of multi-modality neuroimaging measures in investigating neuroplasticity.

We conducted functional magnetic resonance imaging (fMRI) with a visual search paradigm to test the hypothesis that aging is associated with increased frontoparietal involvement in both target detection and bottom-up attentional guidance (featural salience). Participants were 68 healthy adults, distributed continuously across 19 to 78 years of age. Frontoparietal regions of interest (ROIs) were defined from resting-state scans obtained prior to task-related fMRI. The search target was defined by a conjunction of color and orientation. Each display contained one item that was larger than the others (i.e., a size singleton) but was not informative regarding target identity. Analyses of search reaction time (RT) indicated that bottom-up attentional guidance from the size singleton (when coincident with the target) was relatively constant as a function of age. Frontoparietal fMRI activation related to target detection was constant as a function of age, as was the reduction in activation associated with salient targets. However, for individuals 35 years of age and older, engagement of the left frontal eye field (FEF) in bottom-up guidance was more prominent than for younger individuals. Further, the age-related differences in left FEF activation were a consequence of decreasing resting-state functional connectivity in visual sensory regions. These findings indicate that age-related compensatory effects may be expressed in the relation between activation and behavior, rather than in the magnitude of activation, and that relevant changes in the activation-RT relation may begin at a relatively early point in adulthood. Hum Brain Mapp 38:2128-2149, 2017. © 2017 Wiley Periodicals, Inc., (© 2017 Wiley Periodicals, Inc.)

Objectives: To develop and validate the Dental Activities Test (DAT), a clinical tool for measuring dentally related function in cognitively impaired older adults., Design: Cross-sectional study design., Setting: Three assisted living residences in North Carolina., Participants: Assisted living residents with normal to impaired cognition aged 50 and older; not blind, deaf, or severely physically disabled; and English speaking (N = 90)., Measurements: Items for the DAT were developed based on focus group discussions, literature review, and clinical relevance. Cronbach alpha, interrater reliability, and test-retest reliability were examined, and construct validity was assessed in relation to correlations with cognitive and functional assessments. Correlations between the DAT and oral health measures were also analyzed to evaluate the concurrent validity of the DAT., Results: The DAT has excellent internal consistency reliability (Cronbach alpha 0.90), test-retest reliability (correlation coefficient (r) = 0.84), and interrater reliability (r = 0.90). In terms of construct validity, higher DAT scores were significantly associated with better cognitive function, as well as better activity of daily living and instrumental activity of daily living function. Finally, the DAT was significantly associated with oral hygiene and gingival health., Conclusion: The DAT is a reliable and valid instrument to measure dentally-related function in older adults with cognitive impairment., (© 2017, Copyright the Authors Journal compilation © 2017, The American Geriatrics Society.)

The APOE ε4 allele is associated with cognitive deficits and brain atrophy in older adults, but studies in younger adults are mixed. We examined APOE genotype effects on cognition and brain structure in younger adults and whether genotype effects differed by age and with presence of depression. 157 adults (32 % ε4 carriers, 46 % depressed) between 20 and 50 years of age completed neuropsychological testing, 131 of which also completed 3 T cranial MRI. We did not observe a direct effect of APOE genotype on cognitive performance or structural MRI measures. A significant genotype by age interaction was observed for executive function, where age had less of an effect on executive function in ε4 carriers. Similar interactions were observed for the entorhinal cortex, rostral and caudal anterior cingulate cortex and parahippocampal gyrus, where the effect of age on regional volumes was reduced in ε4 carriers. There were no significant interactions between APOE genotype and depression diagnosis. The ε4 allele benefits younger adults by allowing them to maintain executive function performance and volumes of cingulate and temporal cortex regions with aging, at least through age fifty years.

White matter (WM) lesions have been recognized as a key etiological factor in geriatric depression. However, little is known about the topological pattern changes of WM in geriatric depression in the remitted state (RGD) and its relationship to depressive episodes. To address these questions, we acquired diffusion tensor images in 24 RGD and 24 healthy participants. Among them, 10 patients and 19 healthy controls completed a 1-year follow up. Between-hemisphere connectivity and graph theoretical methods were used to analyze the data. We found significantly reduced WM connectivity between the left and right hemisphere in the RGD group compared with the control group. Those with multiple depression episodes had greater reduction in between-hemisphere connectivity strength than those with fewer episodes. In addition, the RGD group had a reduced global clustering coefficient, global efficiency, and network strength, and an increased shortest path length compared with the controls. A lower clustering coefficient was correlated with poorer memory function. The reduction of nodal clustering coefficient, global efficiency, and network strength in several regions were associated with slower information processing speed. At 1-year follow up, the network properties in the RGD subjects were significantly changed suggesting instability of WM network properties of depressed patients. Together, our study provides direct evidence of reduced between-hemisphere WM connectivity with greater depressive episodes, and of alterations of network properties with cognitive dysfunction in geriatric depression. Hum Brain Mapp 38:53-67, 2017. © 2016 Wiley Periodicals, Inc., (© 2016 Wiley Periodicals, Inc.)

Objective: Identify depression symptoms during active late-life depression (LLD) that predict conversion to dementia., Methods: The authors followed a cohort of 290 participants from the Neurocognitive Outcomes of Depression in the Elderly study. All participants were actively depressed and cognitively normal at enrollment. Depression symptom factors were derived from prior factor analysis: anhedonia and sadness, suicidality and guilt, appetite and weight loss, sleep disturbance, and anxiety and tension. Cox regression analysis modeled time to Alzheimer disease (AD) and non-AD dementia onset on depression symptom factors, along with age, education, sex, and race. Significant dementia predictors were tested for interaction with age at depression onset., Results: Higher scores on the appetite and weight loss symptom factor were associated with an increased hazard of both AD and non-AD dementia. This factor was moderated by age at first depression onset, such that higher scores were associated with higher risk of non-AD dementia when depression first occurred earlier in life. Other depression symptom factors and overall depression severity were not related to risk of AD or non-AD dementia., Conclusion: Results suggest greater appetite/weight loss symptoms in active episodes of LLD are associated with increased likelihood of AD and non-AD dementia, but possibly via different pathways moderated by age at first depression onset. Results may help clinicians identify individuals with LLD at higher risk of developing AD and non-AD dementia and design interventions that reduce this risk., (Copyright © 2016. Published by Elsevier Inc.)

Objective: The aim of this study was to examine the association between physical frailty and neurocognitive performance in late-life depression (LLD)., Methods: Cross-sectional design using baseline data from a treatment study of late-life depression was used in this study. Individuals aged 60 years and older were diagnosed with major depressive disorder at time of assessment (N = 173). All participants received clinical assessment of depression and completed neuropsychological testing during a depressive episode. Physical frailty was assessed using an adaptation of the FRAIL scale. Neuropsychological domains were derived from a factor analysis that yielded three factors: (i) speeded executive and fluency, (ii) episodic memory, and (iii) working memory. Associations were examined with bivariate tests and multivariate models., Results: Depressed individuals with a FRAIL score >1 had worse performance than nonfrail depressed across all three factors; however, speeded executive and fluency was the only factor that remained significant after controlling for depression symptom severity and demographic characteristics., Conclusions: Although physical frailty is associated with broad neurocognitive deficits in LLD, it is most robustly associated with deficits in speeded executive functions and verbal fluency. Causal inferences are limited by the cross-sectional design, and future research would benefit from a comparison group of nondepressed older adults with similar levels of frailty. Research is needed to understand the mechanisms underlying associations among depression symptoms, physical frailty, and executive dysfunction and how they are related to the cognitive and symptomatic course of LLD., (Copyright © 2015 John Wiley & Sons, Ltd.)

The objective of the study was to examine variability across multiple prospective cohort studies in level and rate of cognitive decline by race/ethnicity and years of education. We compare data across studies, we harmonized estimates of common latent factors representing overall or general cognitive performance, memory, and executive function derived from the: (a) Washington Heights, Hamilton Heights, Inwood Columbia Aging Project (N = 4,115), (b) Spanish and English Neuropsychological Assessment Scales (N = 525), (c) Duke Memory, Health, and Aging study (N = 578), and (d) Neurocognitive Outcomes of Depression in the Elderly (N = 585). We modeled cognitive change over age for cognitive outcomes by race, education, and study. We adjusted models for sex, dementia status, and study-specific characteristics. The results found that for baseline levels of overall cognitive performance, memory, and executive function, differences in race and education tended to be larger than between-study differences and consistent across studies. This pattern did not hold for rate of cognitive decline: effects of education and race/ethnicity on cognitive change were not consistently observed across studies, and when present were small, with racial/ethnic minorities and those with lower education declining at faster rates. In this diverse set of datasets, non-Hispanic Whites and those with higher education had substantially higher baseline cognitive test scores. However, differences in the rate of cognitive decline by race/ethnicity and education did not follow this pattern. This study suggests that baseline test scores and longitudinal change have different determinants, and future studies to examine similarities and differences of causes of cognitive decline in racially/ethnically and educationally diverse older groups is needed., ((c) 2015 APA, all rights reserved).)

Objective: Previous investigations into the relationship between late-life depressive symptoms and cognitive functioning have resulted in mixed findings concerning whether or not depressive symptoms and cognitive functioning are related. The mixed reports may be due in part to differences in clinical and nonclinical samples and to inadequate consideration of the dynamic nature (i.e., fluctuating course) of depressive symptoms and cognitive functioning in older adults. The current study examined the chronic, acute, and longitudinal relationships between depressive symptoms and cognitive functioning in older adults in an ongoing treatment study of major depressive disorder (MDD)., Methods: The neurocognitive outcomes of depression in the elderly study operates in a naturalistic treatment milieu using a pharmacological treatment algorithm and regular psychiatric assessment. Four hundred and fifty-three older adults [mean age 70 years, standard deviation (SD) = 7.2] meeting criteria for MDD at study enrollment received annual neuropsychological testing and depressive symptom monitoring for an average of 8.5 years (SD = 4.5)., Results: Hierarchical linear modeling revealed that higher age, lower education, and higher average/chronic levels of depressive symptoms were related to lower cognitive functioning. Additionally, results revealed that when an individual's depressive symptoms are higher than is typical for a specific individual, general cognitive function was worse than average. There was no evidence of lagged/longitudinal relationships between depressive symptoms and cognitive functioning in older adults in treatment for MDD., Conclusions: Cognitive functioning and depressive symptoms are concurrently associated in older adults with MDD, highlighting the potential importance for stabilizing mood symptoms as a means to manage cognitive deficits in late-life depression., (Copyright © 2015 John Wiley & Sons, Ltd.)

Objective: The objective of this study is to determine whether differential item functioning (DIF) due to cognitive status impacted three depressive symptoms measures commonly used with older adults., Methods: Differential item functioning in depressive symptoms was assessed among participants (N = 3558) taking part in four longitudinal studies of cognitive aging, using the Geriatric Depression Scale, the Montgomery-Åsberg Depression Rating Scale, and the Center for Epidemiologic Studies Depression Scale. Participants were grouped by cognitive status using a general cognitive performance score derived from each study's neuropsychological battery and linked to a national average using a population-based survey representative of the US population. The Clinical Dementia Rating score was used as an alternate grouping variable in three of the studies., Results: Although statistically significant DIF based on cognitive status was found for some depressive symptom items (e.g., items related to memory complaints, appetite loss, lack of energy, and mood), the effect of item bias on the total score for each scale was negligible., Conclusions: The depressive symptoms scales in these four studies measured depression in the same way, regardless of cognitive status. This may reduce concerns about using these depression measures in cognitive aging research, as relationships between depression and cognitive decline are unlikely to have been due to item bias, at least in the ways that were measured in the datasets we considered., (Copyright © 2014 John Wiley & Sons, Ltd.)

Objectives: This study aimed to examine the association of appetite loss symptoms to neurocognitive performance in late-life depression (LLD)., Methods: This study used cross-sectional data from individuals aged 60+ years with major depressive disorder (N = 322). Participants received clinical assessment of depression and neuropsychological testing. Factor analysis was used to characterize depression symptom factors, and composite scales were developed for episodic memory, psychomotor-executive functions, verbal fluency, and working memory span., Results: Factor analysis produced a five-factor solution: (1) anhedonia/sadness; (2) suicidality/guilt; (3) appetite/weight loss; (4) sleep disturbance; and (5) anxiety/tension. In separate multivariate models for each neurocognitive domain and including all five depression factors, higher appetite-loss-related symptoms were associated with lower performance in episodic memory, psychomotor-executive functions, and verbal fluency; results were significant with covariates of age, education, race, sex, age of depression onset, and illness burden. No other depression factors were associated with neurocognitive performance in these models. In an additional set of models, the appetite factor mediated the association between global depression severity and neurocognitive performance., Discussion: A factor of appetite and weight loss symptoms in LLD was uniquely associated with neurocognitive performance, in contrast to lack of association among other depression symptom factors., Conclusion: Cognitive deficits are a major adverse outcome of LLD, and prominent appetite loss during acute depression may be a marker for these deficits, independent of overall depression severity. Research is needed to understand the mechanisms that may explain this association, and how it is related to the cognitive and symptomatic course of LLD., (Copyright © 2014 John Wiley & Sons, Ltd.)

Background: Depression in late life is a risk factor for cognitive decline. Depression is also associated with increased disability and social support deficits; these may precede conversion to dementia and inform risk. In this study, we examined if baseline or one-year change in disability and social support predicted later cognitive deterioration., Methods: 299 cognitively intact depressed older adults were followed for an average of approximately seven years. Participants received antidepressant treatment according to a standardized algorithm. Neuropsychological testing and assessment of disability and social support were assessed annually. Cognitive diagnosis was reviewed annually at a consensus conference to determine if participants remained cognitively normal, or if they progressed to either dementia or cognitively impaired, no dementia (CIND)., Results: During study participation, 167 individuals remained cognitively normal (56%), 83 progressed to CIND (28%), and 49 progressed to dementia (16%). Greater baseline instrumental activities of daily living (IADL) deficits predicted subsequent conversion to a cognitive diagnosis (CIND or dementia). However, neither baseline measures nor one-year change in basic ADLs (BADLs) and social support predicted cognitive conversion. In post hoc analyses, two IADL measures (managing finances, preparing meals) significantly increased the odds of cognitive conversion., Conclusions: Greater IADL deficits predicted increased risk of cognitive conversion. Assessment of IADL deficits may provide clues about risk of later cognitive decline.

Age-related macular degeneration (AMD), the leading cause of blindness in developed nations, has been associated with poor performance on tests of phonemic fluency. This pilot study sought to (1) characterize the relationship between phonemic fluency and resting-state functional brain connectivity in AMD patients and (2) determine whether regional connections associated with phonemic fluency in AMD patients were similarly linked to phonemic fluency in healthy participants. Behavior-based connectivity analysis was applied to resting-state, functional magnetic resonance imaging data from seven patients (mean age=79.9±7.5 years) with bilateral AMD who completed fluency tasks prior to imaging. Phonemic fluency was inversely related to the strength of functional connectivity (FC) among six pairs of brain regions, representing eight nodes: left opercular portion of inferior frontal gyrus (which includes Broca's area), left superior temporal gyrus (which includes part of Wernicke's area), inferior parietal lobe (bilaterally), right superior parietal lobe, right supramarginal gyrus, right supplementary motor area, and right precentral gyrus. The FC of these reference links was not related to phonemic fluency among 32 healthy individuals (16 younger adults, mean age=23.5±4.6 years and 16 older adults, mean age=68.3±3.4 years). Compared with healthy individuals, AMD patients exhibited higher mean connectivity within the reference links and within the default mode network, possibly reflecting compensatory changes to support performance in the setting of reduced vision. These findings are consistent with the hypothesis that phonemic fluency deficits in AMD reflect underlying brain changes that develop in the context of AMD.

Although major depression has been considered as a manifestation of discoordinated activity between affective and cognitive neural networks, only a few studies have examined the relationships among neural networks directly. Because of the known disconnection theory, geriatric depression could be a useful model in studying the interactions among different networks. In the present study, using independent component analysis to identify intrinsically connected neural networks, we investigated the alterations in synchronizations among neural networks in geriatric depression to better understand the underlying neural mechanisms. Resting-state fMRI data was collected from thirty-two patients with geriatric depression and thirty-two age-matched never-depressed controls. We compared the resting-state activities between the two groups in the default-mode, central executive, attention, salience, and affective networks as well as correlations among these networks. The depression group showed stronger activity than the controls in an affective network, specifically within the orbitofrontal region. However, unlike the never-depressed controls, geriatric depression group lacked synchronized/antisynchronized activity between the affective network and the other networks. Those depressed patients with lower executive function has greater synchronization between the salience network with the executive and affective networks. Our results demonstrate the effectiveness of the between-network analyses in examining neural models for geriatric depression.

Objective: Previous studies have identified differential item function (DIF) in depressive symptoms measures, but the impact of DIF has been rarely reported. Given the critical importance of depressive symptoms assessment among older adults, we examined whether DIF due to demographic characteristics resulted in salient score changes in commonly used measures., Methods: Four longitudinal studies of cognitive aging provided a sample size of 3754 older adults and included individuals both with and without a clinical diagnosis of major depression. Each study administered at least one of the following measures: the Center for Epidemiologic Studies Depression scale (20-item ordinal response or 10-item dichotomous response versions), the Geriatric Depression Scale, and the Montgomery-Åsberg Depression Rating Scale. Hybrid logistic regression-item response theory methods were used to examine the presence and impact of DIF due to age, sex, race/ethnicity, and years of education on the depressive symptoms items., Results: Although statistically significant DIF due to demographic factors was present on several items, its cumulative impact on depressive symptoms scores was practically negligible., Conclusions: The findings support substantive meaningfulness of previously reported demographic differences in depressive symptoms among older adults, showing that these individual differences were unlikely to have resulted from item bias attributable to demographic characteristics we examined., (Copyright © 2014 John Wiley & Sons, Ltd.)

Background: Memory impairment in geriatric depression is understudied, but may identify individuals at risk for development of dementia and Alzheimer's disease (AD). Using a neuropsychologically based definition of amnestic mild cognitive impairment (aMCI) in patients with geriatric depression, we hypothesized that patients with aMCI, compared with those without it, would have increased incidence of both dementia and AD., Methods: Participants were aged 60 years and older and consisted of depressed participants and non-depressed volunteer controls. The depressed cohort met criteria for unipolar major depression. All participants were free of dementia and other neurological illness at baseline. At study entry, participants were administered a standardized clinical interview, a battery of neurocognitive tests, and provided a blood sample for determination of apolipoprotein E genotype. A cognitive diagnosis was assigned by a panel of experts who convened annually and reviewed available clinical, neuropsychological and laboratory data to achieve a consensus cognitive diagnosis to determine a consensus diagnosis. Survival analysis examined the association between aMCI and later dementia (all-cause) and AD., Results: Among 295 depressed individuals, 63 (21.36%) met criteria for aMCI. Among 161 non-depressed controls, four (2.48%) met aMCI criteria. Participants were followed for 6.28 years on average. Forty-three individuals developed dementia, including 40 (13.6%) depressed and three (1.9%) control participants. Both aMCI and age were associated with incident dementia and AD., Conclusions: The presence of aMCI is a poor prognostic sign among patients with geriatric depression. Clinicians should carefully screen elderly depressed adults for memory impairment.

Activation of frontal and parietal brain regions is associated with attentional control during visual search. We used fMRI to characterize age-related differences in frontoparietal activation in a highly efficient feature search task, detection of a shape singleton. On half of the trials, a salient distractor (a color singleton) was present in the display. The hypothesis was that frontoparietal activation mediated the relation between age and attentional capture by the salient distractor. Participants were healthy, community-dwelling individuals, 21 younger adults (19-29 years of age) and 21 older adults (60-87 years of age). Top-down attention, in the form of target predictability, was associated with an improvement in search performance that was comparable for younger and older adults. The increase in search reaction time (RT) associated with the salient distractor (attentional capture), standardized to correct for generalized age-related slowing, was greater for older adults than for younger adults. On trials with a color singleton distractor, search RT increased as a function of increasing activation in frontal regions, for both age groups combined, suggesting increased task difficulty. Mediational analyses disconfirmed the hypothesized model, in which frontal activation mediated the age-related increase in attentional capture, but supported an alternative model in which age was a mediator of the relation between frontal activation and capture., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Objective: Genetic factors confer risk for neuropsychiatric phenotypes, but the polygenic etiology of these phenotypes makes identification of genetic culprits challenging. An approach to this challenge is to examine the effects of genetic variation on relevant endophenotypes, such as hippocampal volume loss. A smaller hippocampus is associated with gene variants of the renin-angiotensin system (RAS), a system implicated in vascular disease. However, no studies to date have investigated longitudinally the effects of genetic variation of RAS on the hippocampus., Method: The authors examined the effects of polymorphisms of AGTR1, the gene encoding angiotensin-II type 1 receptor of RAS, on longitudinal hippocampal volumes of older adults. In all, 138 older adults (age ≥60 years) were followed for an average of about 4 years. The participants underwent repeated structural MRI and comprehensive neurocognitive testing, and they were genotyped for four AGTR1 single-nucleotide polymorphisms (SNPs) with low pairwise linkage disequilibrium values and apolipoprotein E (APOE) genotype., Results: Genetic variants at three AGTR1 SNPs (rs2638363, rs1492103, and rs2675511) were independently associated with accelerated hippocampal volume loss over the 4-year follow-up period in the right but not left hemisphere. Intriguingly, these AGTR1 risk alleles also predicted worse episodic memory performance but were not related to other cognitive measures. Two risk variants (rs2638363 and rs12721331) interacted with the APOE4 allele to accelerate right hippocampal volume loss., Conclusions: Risk genetic variants of the RAS may accelerate memory decline in older adults, an effect that may be conferred by accelerated hippocampal volume loss. Molecules involved in this system may hold promise as early therapeutic targets for late-life neuropsychiatric disorders.

Background: Neuroticism is a psychological construct that includes tendency to exhibit negative affect (NA), having poor stress tolerance and being at risk for depression and anxiety disorders. The consequences of neuroticism in the elderly adults are understudied. We hypothesized that older depressed patients with comorbid neuroticism at baseline would have worse mood and cognitive outcomes compared with older depressed patients without neuroticism., Methods: One hundred and ten older depressed adults completed baseline self-reports of depression and the NEO-Personality Inventory as a measure of neuroticism, were administered a battery of cognitive tests annually and were seen by a study psychiatrist who assessed patients using the Montgomery Åsberg Depression Rating Scale (MADRS) and treated patients with antidepressants using an established treatment guideline. Patients were followed as clinically indicated for up to three years. We measured remission (defined as MADRS score ≤ 6) rates at one year as a categorical outcome. In addition, we used Cox proportional hazard models to examine the relationship between neuroticism and change in MADRS and cognitive score over time., Results: Non-remitters (30%) at one year had higher scores in total neuroticism (TN), vulnerability to stress (VS), and NA. Over three years, time to achieve remission was associated with higher TN, higher VS, and greater NA. In analyses controlling for baseline cognitive score, age, sex, and education, VS was associated with baseline to two-year change in cognition., Conclusions: Presence of neuroticism in older depressed patients treated with medication is associated with poor mood outcomes and may indicate increased risk of cognitive decline.

Numerous studies have examined the relationship between physical activity and cognitive function, demonstrating that greater physical activity is associated with lower incidence of cognitive impairment in later life. Due to an increasingly large number of older adults at risk for cognitive impairment, the relationship between physical activity and cognition has garnered increasing public health relevance and multiple randomized trials have demonstrated that exercise interventions among sedentary adults improve cognitive performance in multiple domains of function. This article will examine the relationship between physical activity and cognitive function by reviewing several different areas of literature, including the prevalence of cognitive impairment, assessment methods, observational studies examining physical activity and cognition, and intervention studies. The present review is intended to provide a historical tutorial of existing literature linking physical activity, exercise, and cognitive function among both healthy and clinical populations.

Objective: Major depressive disorder is a likely risk factor for dementia, but some cases of major depressive disorder in older adults may actually represent a prodrome of this condition. The purpose of this study was to use neuropsychological test scores to predict conversion to dementia in a sample of depressed older adults diagnosed as nondemented at the time of neuropsychological testing., Design: Longitudinal, with mean follow-up of 5.45 years., Setting: Outpatient depression treatment study at Duke University., Participants: Thirty nondemented individuals depressed at the time of neuropsychological testing and later diagnosed with incident dementia; 149 nondemented individuals depressed at the time of neuropsychological testing and a diagnosis of cognitively normal., Methodology: All participants received clinical assessment of depression, were assessed to rule out prevalent dementia at the time of study enrollment, completed neuropsychological testing at the time of study enrollment, and were diagnosed for cognitive disorders on an annual basis., Results: Nondemented, acutely depressed older adults who converted to dementia during the study period exhibited broadly lower cognitive performances at baseline than acutely depressed individuals who remained cognitively normal. Discriminant function analysis indicated that 2 neuropsychological tests, Recognition Memory (from the Consortium to Establish a Registry for Alzheimer's Disease neuropsychological battery) and Trail Making B, best predicted dementia conversion., Conclusions: Depressed older adults with cognitive deficits in the domains of memory and executive functions during acute depression are at higher risk for developing dementia. Some cases of late-life depression may reflect a prodrome of dementia in which clinical manifestation of mood changes may co-occur with emerging cognitive deficits., (Copyright © 2013 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.)

Slowed information processing is a prominent deficit in late-life depression (LLD). To better differentiate processing speed components in LLD, we examined characteristics of visual search performance in 32 LLD and 32 control participants. Data showed specific slowing in the comparison stage of visual search in LLD, rather than in encoding/response stages, but also greater overall slowing in LLD during inefficient versus efficient search. We found no group differences on traditional neuropsychological measures of processing speed. Slowed processing speed in LLD may be specific rather than general, which underscores the need to link components of processing speed to underlying neural circuitry.

Background: The Alzheimer's Disease Assessment Scale cognitive subscale (ADAS-Cog) is widely used in AD, but may be less responsive to change when used in people with mild cognitive impairment (MCI)., Methods: Participants from the Alzheimer's Disease Neuroimaging Initiative were administered a neuropsychological battery and 1.5 T MRI scans over 2-3 years. Informants were queried regarding functional impairments. Some participants had lumbar punctures to obtain cerebrospinal fluid (CSF). We added executive functioning (EF) and functional ability (FA) items to the ADAS-Cog to generate candidate augmented measures. We calibrated these candidates using baseline data (n = 811) and selected the best candidate that added EF items alone and that added EF and FA items. We selected candidates based on their responsiveness over three years in a training sample of participants with MCI (n = 160). We compared traditional ADAS-Cog scores with the two candidates based on their responsiveness in a validation sample of participants with MCI (n = 234), ability to predict conversion to dementia (n = 394), strength of association with baseline MRI (n = 394) and CSF biomarkers (n = 193)., Results: The selected EF candidate added category fluency (ADAS Plus EF), and the selected EF and FA candidate added category fluency, Digit Symbol, Trail Making, and five items from the Functional Assessment Questionnaire (ADAS Plus EF&FA). The ADAS Plus EF& FA performed as well as or better than traditional ADAS-Cog scores., Conclusion: Adding EF and FA items to the ADAS-Cog may improve responsiveness among people with MCI without impairing validity.