Apathy, but not depression, predicts all-cause dementia in cerebral small vessel disease

Apathy After Stroke: Incidence, Symptom Trajectory, and Impact on Quality of Life and Disability

BACKGROUND AND OBJECTIVES

Apathy is one of the most common symptoms following stroke and is often associated with worse functional outcome and poor quality of life (QoL). The trajectory of apathy symptoms has been previously described, and different trajectories have been identified. We determined group and individual changes in apathy symptomatology from the acute phase until 1 year after stroke. We also examined the association of apathy and depression with disability and QoL 1 year after stroke.

METHODS

We measured apathy in a cohort of ischemic stroke survivors at 4 time points from 0 to 12 months after stroke. The Apathy Evaluation Scale (AES) and Dimensional Apathy Scale (DAS) were administered at each time point. Where possible we obtained apathy measured from carers. Depression was assessed with the Geriatric Depression Scale (GDS). Disability and QoL were assessed with the modified Rankin Scale (mRS) and 36-Item Short Form Survey (SF-36). We examined the cross-sectional and individual trajectory of apathy symptoms in each dimension and looked at associations of apathy and depression soon after stroke with mRS and SF-36 at 1 year.

RESULTS

Of 200 participants enrolled, 165 completed apathy measures at 12 months. Patient-rated apathy scores increased in both tests at the group level (AES: χ2(3) = 9.86, p = 0.019; DAS: χ2(3) = 8.49, p = 0.037) and individual level (AES: β = 0.13, p = 0.002; DAS β = 0.13, p = 0.005; DAS: executive β = 0.08, p < 0.001). By contrast, carer-rated apathy did not significantly increase (AES: χ2(3) = 0.75, p = 0.862; DAS: χ2(3) = 2.45, p = 0.484). Apathy scores were associated with worse mRS and SF-36, although most associations were no longer significant when controlling for depression. GDS was associated with worse mRS and SF-36 after controlling for covariates and apathy (mRS: β = 0.08, p = 0.006; SF-36 Mental Component Summary: β = -1.53, p < 0.001; SF-36 Physical Component Summary: β = -0.57, p = 0.016).

DISCUSSION

Self-reported apathy progressively increases after stroke, especially in the executive dimension. Apathy is associated with worse QoL and greater disability, although some of these associations might be mediated by depression.

Apathy Symptoms, Physical and Cognitive Function, Health-Related Quality of Life, and Mortality in Older Patients With CKD: A Longitudinal Observational Study

RATIONALE & OBJECTIVE

Apathy reflects diminished motivation, goal-directed behavior, and emotions, as well as less engagement in social interactions. Apathy overlaps with depression and is associated with cognitive decline. In the older individuals with chronic kidney disease (CKD), both depression and cognitive impairments are common, but apathy symptoms have been underreported. We investigated the occurrence of apathy symptoms and their associations with physical and cognitive functioning, health-related quality of life (HRQoL), and mortality in older patients with CKD.

STUDY DESIGN

Prospective observational cohort study.

SETTING & PARTICIPANTS

180 outpatients aged≥65 years with estimated glomerular filtration rate≤20mL/min/1.73m2 from 5 Dutch nephrology centers.

EXPOSURE

Apathy symptoms at baseline were considered present when a Geriatric Depression Scale's 3-item apathy subscale score was≥2 points.

OUTCOME

Physical and cognitive functioning, HRQoL (assessed in annual geriatric assessments), and 4-year mortality.

ANALYTICAL APPROACH

Linear regression for cross-sectional associations, linear regression models for longitudinal associations, and Cox regression models for mortality over 4 years of observation.

RESULTS

Apathy symptoms were present in 64 patients (36%; 67% men; median age 75.5 years), of whom 32 (50%) had no depressive symptoms. At baseline, the presence of apathy symptoms was associated with significantly more frailty, more functional dependence, less physical capacity, lower visuoconstructive performance, worse delayed recall, and lower HRQoL scores. The presence of apathy symptoms at baseline was also associated with a higher mortality risk (hazard ratio, 2.3 [95% CI, 1.3-4.2], P=0.005 adjusted for age, sex, and high education level), but not with changes in physical and cognitive functioning or HRQoL during the follow-up period.

LIMITATIONS

Risk of selection bias and residual confounding.

CONCLUSIONS

Apathy symptoms were highly prevalent and associated with concurrent lower physical and cognitive status, lower HRQoL, and increased mortality. These findings highlight apathy as a potentially important clinical phenotype in older CKD patients.

PLAIN-LANGUAGE SUMMARY

We observed that older kidney patients often present apathy symptoms, such as less motivation, fewer goal-directed behaviors, fewer emotions, and less social engagement. Prior research has not extensively described apathy in kidney disease. We investigated the link between apathy symptoms and poor outcomes. We measured physical functioning, cognitive functioning, and quality of life. We learned that one-third of our older kidney patients showed symptoms of apathy, only half of whom had symptoms of depression. Patients with apathy symptoms showed lower quality of life and lower physical and cognitive performance. They also had a higher risk of death. These findings highlight the need for awareness of apathy symptoms in older kidney patients.

Characteristic patterns of functional connectivity-mediated cerebral small vessel disease-related cognitive impairment and depression

Cerebral small vessel disease is common in most individuals aged 60 years or older, and it is associated with cognitive dysfunction, depression, anxiety disorder, and mobility problems. Currently, many cerebral small vessel disease patients have both cognitive impairment and depressive symptoms, but the relationship between the 2 is unclear. The present research combined static and dynamic functional network connectivity methods to explore the patterns of functional networks in cerebral small vessel disease individuals with cognitive impairment and depression (cerebral small vessel disease-mild cognitive impairment with depression) and their relationship. We found specific functional network patterns in the cerebral small vessel disease-mild cognitive impairment with depression individuals (P < 0.05). The cerebral small vessel disease individuals with depression exhibited unstable dynamic functional network connectivity states (transitions likelihood: P = 0.040). In addition, we found that the connections within the lateral visual network between the sensorimotor network and ventral attention network could mediate white matter hyperintensity-related cognitive impairment (indirect effect: 0.064; 95% CI: 0.003, 0.170) and depression (indirect effect: -0.415; 95% CI: -1.080, -0.011). Cognitive function can negatively regulate white matter hyperintensity-related depression. These findings elucidate the association between cognitive impairment and depression and provide new insights into the underlying mechanism of cerebral small vessel disease-related cognitive dysfunction and depression.

Post-Stroke Neuropsychiatric Complications: Types, Pathogenesis, and Therapeutic Intervention

Almost all stroke survivors suffer physical disabilities and neuropsychiatric disturbances, which can be briefly divided into post-stroke neurological diseases and post-stroke psychiatric disorders. The former type mainly includes post-stroke pain, post-stroke epilepsy, and post-stroke dementia while the latter one includes post-stroke depression, post-stroke anxiety, post-stroke apathy and post-stroke fatigue. Multiple risk factors are related to these post-stroke neuropsychiatric complications, such as age, gender, lifestyle, stroke type, medication, lesion location, and comorbidities. Recent studies have revealed several critical mechanisms underlying these complications, namely inflammatory response, dysregulation of the hypothalamic pituitary adrenal axis, cholinergic dysfunction, reduced level of 5-hydroxytryptamine, glutamate-mediated excitotoxicity and mitochondrial dysfunction. Moreover, clinical efforts have successfully given birth to many practical pharmaceutic strategies, such as anti-inflammatory medications, acetylcholinesterase inhibitors, and selective serotonin reuptake inhibitors, as well as diverse rehabilitative modalities to help patients physically and mentally. However, the efficacy of these interventions is still under debate. Further investigations into these post-stroke neuropsychiatric complications, from both basic and clinical perspectives, are urgent for the development of effective treatment strategies.

Evaluation of apathy in non-clinical populations: validation, psychometric properties, and normative data of the Italian version of Apathy-Motivation Index (AMI)

INTRODUCTION

Evaluation of apathy in non-clinical populations is relevant to identify individuals at risk for developing cognitive decline in later stages of life, and it should be performed with questionnaires specifically designed for healthy individuals, such as the Apathy-Motivation Index (AMI); therefore, the aim of the present study was to validate the AMI in a healthy Italian population, and to provide normative data of the scale.

MATERIALS AND METHODS

Data collection was performed using a survey completed by 500 healthy participants; DAS, MMQ-A, BIS-15, PHQ-9, and GAD-7 were used to investigate convergent and divergent validity. Internal consistency and factorial structure were also evaluated. A regression-based procedure and receiver operating characteristics (ROC) analyses were used to evaluate the influence of socio-demographic variables on AMI scores and to provide adjusting factors and three cut-offs for the detection of mild, moderate, and severe apathy.

RESULTS

The Italian version of the AMI included 17 items (one item was removed because it was not internally consistent) and demonstrated good psychometric properties. The three-factor structure of AMI was confirmed. Multiple regression analysis revealed no effect of sociodemographic variables on the total AMI score. ROC analyses revealed three cut-offs of 1.5, 1.66, and 2.06 through the Youden's J statistic to detect mild, moderate, and severe apathy, respectively.

CONCLUSION

The Italian version of the AMI reported similar psychometric properties, factorial structure, and cut-offs to the original scale. This may help researchers and clinicians to identify people at risk and address them in specific interventions to lower their apathy levels.

Apathy is associated with striatal atrophy and cognitive impairment in cerebral small vessel disease

BACKGROUND

Apathy has been considered a common neuropsychiatric symptom and an important contributor to cognitive impairment in cerebral small vessel disease (SVD). However, the mechanism leading to apathy in SVD and the process whereby apathy promotes cognitive impairments remain largely unknown. We aimed to explore the relationship between apathy, cognition, and structural changes of deep grey matter (DGM) in SVD patients.

METHODS

Participants were screened for SVD, completed assessments of apathy cognition, underwent magnetic resonance imaging (MRI) scanning, and then stratified into apathy and non-apathy groups. We used region of interest (ROI)-based, voxel-based volume, and vertex-based shape analyses to compare DGM structures between study groups. Using linear regression analysis, we examined the association between apathy, structural changes, and cognition, followed by a mediation analysis of these factors.

RESULTS

A total of sixty-four SVD participants were included, with thirty in the apathy group and thirty-four in the non-apathy group. Intergroup comparison showed significantly lower volumes in bilateral caudate, right putamen, and pallidum and smaller vertex-based shapes in the right caudate and pallidum in participants with apathy compared to those without apathy. Apathy was associated with the striatal atrophy (i.e., lower volumes and smaller shape) and independently contributed to cognitive impairments in SVD. However, the above structural differences did not mediate the association between apathy and cognitive impairments.

CONCLUSION

These results highlight the important role of striatal atrophy in apathy in SVD and call for additional studies to explore the relationship between apathy, cognition, and DGM.

Network structure-function coupling and neurocognition in cerebral small vessel disease

BACKGROUND

Cerebral small vessel disease is a leading cause of cognitive decline and vascular dementia. Small vessel disease pathology changes structural brain networks, but its impact on functional networks remains poorly understood. Structural and functional networks are closely coupled in healthy individuals, and decoupling is associated with clinical symptoms in other neurological conditions. We tested the hypothesis that structural-functional network coupling is related to neurocognitive outcomes in 262 small vessel disease patients.

METHODS

Participants underwent multimodal magnetic resonance imaging and cognitive assessment in 2011 and 2015. Structural connectivity networks were reconstructed using probabilistic diffusion tractography, while functional connectivity networks were estimated from resting-state functional magnetic resonance imaging. Structural and functional networks were then correlated to calculate a measure of structural-functional network coupling for each participant.

RESULTS

Lower whole-brain coupling was associated with reduced processing speed and greater apathy both cross-sectionally and longitudinally. In addition, coupling within the cognitive control network was associated with all cognitive outcomes, suggesting that neurocognitive outcomes in small vessel disease may be related to the functioning of this intrinsic connectivity network.

CONCLUSIONS

Our work demonstrates the influence of structural-functional connectivity network decoupling in small vessel disease symptomatology. Cognitive control network function may be investigated in future studies.

Machine Learning for Dementia Prediction: A Systematic Review and Future Research Directions

Nowadays, Artificial Intelligence (AI) and machine learning (ML) have successfully provided automated solutions to numerous real-world problems. Healthcare is one of the most important research areas for ML researchers, with the aim of developing automated disease prediction systems. One of the disease detection problems that AI and ML researchers have focused on is dementia detection using ML methods. Numerous automated diagnostic systems based on ML techniques for early prediction of dementia have been proposed in the literature. Few systematic literature reviews (SLR) have been conducted for dementia prediction based on ML techniques in the past. However, these SLR focused on a single type of data modality for the detection of dementia. Hence, the purpose of this study is to conduct a comprehensive evaluation of ML-based automated diagnostic systems considering different types of data modalities such as images, clinical-features, and voice data. We collected the research articles from 2011 to 2022 using the keywords dementia, machine learning, feature selection, data modalities, and automated diagnostic systems. The selected articles were critically analyzed and discussed. It was observed that image data driven ML models yields promising results in terms of dementia prediction compared to other data modalities, i.e., clinical feature-based data and voice data. Furthermore, this SLR highlighted the limitations of the previously proposed automated methods for dementia and presented future directions to overcome these limitations.

The importance of a multidimensional approach to the preclinical study of major depressive disorder and apathy

Both the neuropsychiatric syndrome of apathy and major depressive disorder comprise a heterogenous cluster of symptoms which span multiple behavioural domains. Despite this heterogeneity, there is a tendency in the preclinical literature to conclude a MDD or apathy-like phenotype from a single dimensional behavioural task used in isolation, which may lead to inaccurate phenotypic interpretation. This is significant, as apathy and major depressive disorder are clinically distinct with different underlying mechanisms and treatment approaches. At the clinical level, apathy and major depressive disorder can be dissociated in the negative valence (loss) domain of the Research Domain Criteria. Symptoms of MDD in the negative valence (loss) domain can include an exaggerated response to emotionally salient stimuli and low mood, while in contrast apathy is characterised by an emotionally blunted state. In this article, we highlight how using a single dimensional approach can limit psychiatric model interpretation. We discuss how integrating behavioural findings from both the positive and negative (loss) valence domains of the Research Domain Criteria can benefit interpretation of findings. We focus particularly on behaviours relating to the negative valence (loss) domain, which may be used to distinguish between apathy and major depressive disorder at the preclinical level. Finally, we consider how future approaches using home cage monitoring may offer a new opportunity to detect distinct behavioural profiles and benefit the overall translatability of findings.

Automatic segmentation of white matter hyperintensities in routine clinical brain MRI by 2D VB-Net: A large-scale study

White matter hyperintensities (WMH) are imaging manifestations frequently observed in various neurological disorders, yet the clinical application of WMH quantification is limited. In this study, we designed a series of dedicated WMH labeling protocols and proposed a convolutional neural network named 2D VB-Net for the segmentation of WMH and other coexisting intracranial lesions based on a large dataset of 1,045 subjects across various demographics and multiple scanners using 2D thick-slice protocols that are more commonly applied in clinical practice. Using our labeling pipeline, the Dice consistency of the WMH regions manually depicted by two observers was 0.878, which formed a solid basis for the development and evaluation of the automatic segmentation system. The proposed algorithm outperformed other state-of-the-art methods (uResNet, 3D V-Net and Visual Geometry Group network) in the segmentation of WMH and other coexisting intracranial lesions and was well validated on datasets with thick-slice magnetic resonance (MR) images and the 2017 medical image computing and computer assisted intervention WMH Segmentation Challenge dataset (with thin-slice MR images), all showing excellent effectiveness. Furthermore, our method can subclassify WMH to display the WMH distributions and is very lightweight. Additionally, in terms of correlation to visual rating scores, our algorithm showed excellent consistency with the manual delineations and was overall better than those from other competing methods. In conclusion, we developed an automatic WMH quantification framework for multiple application scenarios, exhibiting a promising future in clinical practice.

Neuropsychiatric Symptoms as Predictor of Poor Clinical Outcome in Patients With Vascular Cognitive Impairment

OBJECTIVE

Examine the association between neuropsychiatric symptoms (NPS) and clinical outcome in memory clinic patients with vascular brain injury.

DESIGN/SETTING

TRACE-VCI prospective memory clinic cohort with follow-up (2.1 ± 0.5 years).

PARTICIPANTS

Five hundred and seventy-five memory clinic patients with vascular brain injury on MRI (i.e. possible Vascular Cognitive Impairment [VCI]). Severity of cognitive impairment ranged from no objective cognitive impairment to mild cognitive impairment (MCI) and dementia.

MEASUREMENTS

We used Neuropsychiatric Inventory (total score and score on hyperactive, psychotic, affective, and apathetic behavior domains) to measure NPS. We assessed the association between NPS and institutionalization, mortality and cognitive deterioration (increase ≥0.5 on Clinical Dementia Rating scale) with Cox proportional hazards models and logistic regression analyses.

RESULTS

NPS were present in 89% of all patients, most commonly in the hyperactive and apathetic behavior domain. Across the whole cohort, affective behavior was associated with institutionalization (HR: 1.98 [1.01-3.87]), mainly driven by the dementia subgroup (HR: 2.06 [1.00-4.21]). Apathetic behavior was associated with mortality and cognitive deterioration (HR: 2.07 [1.10-3.90],OR: 1.67 [1.12-2.49], respectively), mainly driven by the MCI subgroup (HR: 4.93 [1.07-22.86],OR: 3.25 [1.46-7.24], respectively). Conversely, hyperactive behavior was related to lower mortality (HR: 0.54 [0.29-0.98]), again particularly driven by the MCI subgroup (HR:0.17 [0.04-0.75]). Psychotic behavior was associated with cognitive deterioration in patients with no objective cognitive impairment (OR: 3.10 [1.09-8.80]) and with institutionalization in MCI (HR: 12.45 [1.28-121.14]).

CONCLUSION

NPS are common and have prognostic value in memory clinic patients with possible VCI. This prognostic value depends on the severity of cognitive impairment.

Long-term neuropsychiatric symptoms in spontaneous intracerebral haemorrhage survivors

OBJECTIVE

Neuropsychiatric (NP) symptoms are prominent features of cognitive decline, but they have been understudied in patients with spontaneous intracerebral haemorrhage (ICH). In ICH survivors, we aimed at assessing NP symptoms prevalence and profiles, and their influence on long-term outcomes.

METHODS

We analysed data from consecutive 6-month ICH survivors enrolled in the Prognosis of Intracerebral Haemorrhage study. We performed NP evaluation using the Neuropsychiatric Inventory Questionnaire. Patients underwent long-term clinical follow-up after ICH (median follow-up time 7.2 years, IQR 4.8-8.2).

RESULTS

Out of 560 patients with ICH, 265 survived at 6 months. NP evaluation 6 months after ICH was feasible in 202 patients. NP symptoms were present in 112 patients (55%), and in 36 out of 48 patients (75%) with post-ICH dementia. Affective symptoms were present in 77 patients (38%), followed by vegetative symptoms (52 patients, 26%) and hyperactivity (47 patients, 23%). Apathy and hyperactivity were associated with post-ICH dementia and cerebral amyloid angiopathy MRI profile (all p<0.05). Apathy and hyperactivity prevailing over affective symptoms at 6-month follow-up were associated with higher risks of developing new-onset dementia (HR 5.40; 95% CI 2.27 to 12.84), while presence or severity of NP symptoms were not.

CONCLUSION

NP symptoms were present in more than half of 6-month ICH survivors, with higher prevalence and severity in patients with post-ICH dementia. Distinctive NP profile might be associated to cognitive status and inform on long-term dementia risk.

Plasma Total Tau and Neurobehavioral Symptoms of Cognitive Decline in Cognitively Normal Older Adults

Depression and related neurobehavioral symptoms are common features of Alzheimer’s disease and other dementias. The presence of these potentially modifiable neurobehavioral symptoms in cognitively intact older adults may represent an early indication of pathophysiological processes in the brain. Tau pathology is a key feature of a number of dementias. A number of studies have found an association between tau and neurobehavioral symptoms. The current study investigated the relationship of a blood-based biomarker of tau and symptoms of depression, anxiety, worry, and sleep disturbances in 538 community based, cognitively normal older adults. Logistic regression revealed no significant relationship between plasma total tau and any measures of neurobehavioral symptoms. To assess the impact of level of tau on these relationships, participants were divided into those in the highest quintile of tau and those in the lower four quintiles. Regression analyses showed a significant relationship between level of plasma total tau and measures of depression, apathy, anxiety, worry and sleep. The presence of higher levels of plasma tau and elevated neurobehavioral symptoms may be an early indicator of cognitive decline and prodromal Alzheimer’s disease. Longitudinal research is needed to evaluate the impact of these factors on the development of dementia and may suggest areas for early intervention.

Evidence and implications of abnormal predictive coding in dementia

The diversity of cognitive deficits and neuropathological processes associated with dementias has encouraged divergence in pathophysiological explanations of disease. Here, we review an alternative framework that emphasizes convergent critical features of cognitive pathophysiology. Rather than the loss of ‘memory centres’ or ‘language centres’, or singular neurotransmitter systems, cognitive deficits are interpreted in terms of aberrant predictive coding in hierarchical neural networks. This builds on advances in normative accounts of brain function, specifically the Bayesian integration of beliefs and sensory evidence in which hierarchical predictions and prediction errors underlie memory, perception, speech and behaviour. We describe how analogous impairments in predictive coding in parallel neurocognitive systems can generate diverse clinical phenomena, including the characteristics of dementias. The review presents evidence from behavioural and neurophysiological studies of perception, language, memory and decision-making. The reformulation of cognitive deficits in terms of predictive coding has several advantages. It brings diverse clinical phenomena into a common framework; it aligns cognitive and movement disorders; and it makes specific predictions on cognitive physiology that support translational and experimental medicine studies. The insights into complex human cognitive disorders from the predictive coding framework may therefore also inform future therapeutic strategies.

Individual markers of cerebral small vessel disease and domain-specific quality of life deficits

BACKGROUND

Cerebral small vessel disease (SVD) leads to reduced quality of life (QOL), but the mechanisms underlying this relationship remain unknown. This study investigated multivariate relationships between radiological markers of SVD and domain-specific QOL deficits, as well as potential mediators, in patients with SVD.

METHODS

Clinical and neuroimaging measures were obtained from a pooled sample of 174 SVD patients from the St. George's Cognition and Neuroimaging in Stroke and PRESsure in established cERebral small VEssel disease studies. Lacunes, white matter hyperintensities, and microbleeds were defined as radiological markers of SVD and delineated using MRI. QOL was assessed using the Stroke-Specific Quality of Life Scale. Multivariate linear regression was used to determine whether SVD markers were associated with domain-specific QOL deficits. Significant associations were further investigated using mediation analysis to examine whether functional disability or cognition was potential mediators.

RESULTS

Multivariate regression analyses revealed that lacunes were associated with total QOL score (β = -8.22, p = .02), as well as reductions in mobility (β = -1.41, p = .008) and language-related subdomains (β = -0.69, p = .033). White matter hyperintensities and microbleeds showed univariate correlations with QOL, but these became nonsignificant during multivariate analyses. Mediation analyses revealed that functional disability, defined as reduced activities of daily living, and executive function, partially mediated the relationship between lacunes and total QOL, as well as mobility-related QOL, but not language-related QOL.

CONCLUSIONS

Lacunar infarcts have the most detrimental effect on QOL in SVD patients, particularly in the mobility and language-related subdomains. These effects may be partially explained by a reduction in activities of daily living. These results may inform targeted interventions to improve QOL in patients with SVD.

Grasping Social Apathy: The Role of Reach-To-Grasp Action Kinematics for the Assessment of Social Apathy in Mild Neurocognitive Disorders

BACKGROUND

Social apathy, a reduction in initiative in proposing or engaging in social activities or interactions, is common in mild neurocognitive disorders (MND). Current apathy assessment relies on self-reports or clinical scales, but growing attention is devoted to defining more objective, measurable and non-invasive apathy proxies.

OBJECTIVE

In the present study we investigated the interest of recording action kinematics in a social reach-to-grasp task for the assessment of social apathy.

METHODS

Thirty participants took part in the study: 11 healthy controls (HC; 6 females, mean age = 68.3±10.5 years) and 19 subjects with MND (13 females, mean age = 75.7±6.3 years). Based on the Diagnostic Criteria for Apathy, MND subjects were classified as socially apathetic (A-MND, N = 9) versus non-apathetic (NA-MND, N = 10). SensRing, a ring-shaped wearable sensor, was placed on their index finger, and subjects were asked to reach and grasp a can to place it into a cup (individual condition) and pass it to a partner (social condition).

RESULTS

In the reach-to-grasp phase of the action, HC and NA-MND showed different acceleration and velocity profiles in the social versus individual condition. No differences were found for A-MND.

CONCLUSION

Previous studies showed the interest of recording patients' level of weekly motor activity for apathy assessment. Here we showed that a 10-min reach-to-grasp task may provide information to differentiate socially apathetic and non-apathetic subjects with MND, thus providing a tool easily usable in the clinical practice. Future studies with a bigger sample are needed to better characterize these findings.

Specific Dimensions of Depression Have Different Associations With Cognitive Decline in Older Adults With Type 2 Diabetes

OBJECTIVE

Depression is highly frequent in older adults with type 2 diabetes and is associated with cognitive impairment, yet little is known about how various depression dimensions differentially affect cognition. We investigated longitudinal associations of specific depression dimensions with cognitive decline.

RESEARCH DESIGN AND METHODS

Participants (N = 1,002) were from the Israel Diabetes and Cognitive Decline study, were ≥65 years of age, had type 2 diabetes, and were not experiencing dementia at baseline. Participants underwent a comprehensive neuropsychological battery at baseline and every 18 months thereafter, including domains of episodic memory, attention/working memory, semantic categorization/language, and executive function, and Z-scores of each domain were averaged and further normalized to calculate global cognition. Depression items from the 15-item Geriatric Depression Scale were measured at each visit and subcategorized into five dimensions: dysphoric mood, withdrawal-apathy-vigor (entitled apathy), anxiety, hopelessness, and memory complaint. Random coefficients models examined the association of depression dimensions with baseline and longitudinal cognitive functioning, adjusting for sociodemographics and baseline characteristics, including cardiovascular risk factors, physical activity, and use of diabetes medications.

RESULTS

In the fully adjusted model at baseline, all dimensions of depression, except for anxiety, were associated with some aspect of cognition (P values from 0.01 to <0.001). Longitudinally, greater apathy scores were associated with faster decline in executive function (P = 0.004), a result that withstood adjustment for multiple comparisons. Associations of other depression dimensions with cognitive decline were not significant (P > 0.01).

CONCLUSIONS

Apathy was associated with a faster cognitive decline in executive function. These findings highlight the heterogeneity of depression as a clinical construct rather than as a single entity and point to apathy as a specific risk factor for cognitive decline among older adults with type 2 diabetes.

Apathy after stroke: Diagnosis, mechanisms, consequences, and treatment

Apathy is a reduction in goal-directed activity in the cognitive, behavioral, emotional, or social domains of a patient’s life and occurs in one out of three patients after stroke. Despite this, apathy is clinically under-recognized and poorly understood. This overview provides a contemporary introduction to apathy in stroke for researchers and practitioners, covering topics including diagnosis, neurobiological mechanisms, associated consequences, and potential treatments for apathy. Apathy is often misdiagnosed as other post-stroke conditions such as depression. Accurate differential diagnosis of apathy, which manifests as reductions in initiative, and depression, which manifests as negative emotionality, is important as it informs prognosis. Research on the neurobiology of apathy suggests that there are few consistent associations between stroke lesion location and the development of apathy. These may be resolved by adopting a network neuroscience approach, which models apathy as a pathology arising from structural or functional damage to brain networks underlying motivated behavior. Importantly, networks can be affected by physiological changes related to stroke, including the acute infarct but also diaschisis and neurodegeneration. Aside from neurobiological changes, apathy is also associated with other negative outcome measures such as functional disability, cognitive impairment, and emotional distress, suggesting that apathy is indicative of a worse prognosis following stroke. Unfortunately, high-quality trials aimed at treating apathy are scarce. Antidepressants may have limited effects on apathy. Acetylcholine and dopamine pharmacotherapy, behavioral interventions, and transcranial magnetic stimulation may be more promising avenues for treatment.

Theoretical Analysis of the Apathy Diagnostical Measurement

The article lays out a theoretical analysis of the problem with diagnosing apathy in today's research. Apathy is a state characterized by a simultaneous decrease in the behavioral, cognitive and emotional concomitants of goal-directed behavior due to loss of motivation [15]. Behavioral changes lie in a declining everyday problem-solving effectiveness at home or work. Cognitive changes result in reduced cognitive functioning and a lack of plans and life strategies. Emotional changes manifest in a decrease in affective response to events that previously elicited either a positive or negative emotional response. Diagnostic criteria, or the 'gold standard' for apathy, identify behavioral, cognitive, emotional, and social symptoms of apathy that cause clinically significant disorders in personal, social, professional, or other important areas of life. The differential diagnosis of apathy involves its clinical distinction from syndromes such as delirium, dementia, depression, abulia, akinesia, and demoralization. The review can be useful for psychiatrists, psychologists, social workers and all practitioners who interact with people at risk of developing apathetic states.

Cognitive Reserve, Leisure Activity, and Neuropsychological Profile in the Early Stage of Cognitive Decline

In older adults with normal cognition, cognitive reserve (CR) is known to be associated with the neuropsychological profile. We investigated the association between comprehensive CR and detailed neuropsychological profile in the early stage of cognitive decline. Fifty-five participants with mild cognitive impairment or subjective cognitive decline completed the cognitive reserve index questionnaire (CRIq) that yielded total, education, working activity, and leisure time scores (CRI-Total, CRI-Education, CRI-Working activity, and CRI-Leisure time, respectively). Mini-mental state examination (MMSE) and detailed neuropsychological evaluation were performed. Psychiatric symptom scales were applied to measure depression, apathy, positive or negative affect, and quality of life. Correlation and linear regression analyses of the variables were performed. The effect of CR-Education, CRI-Working activity, and CRI-Leisure time on the composite cognitive score was determined using a multivariable regression model. We observed that for CRI-Total (B = 3.00, p = 0.005), CRI-Education (B = 3.39, p = 0.002), and CRI-Leisure time (B = 2.56, p = 0.015), CR correlated with MMSE scores, while only CRI-Leisure time associated with the naming ability (B = 2.20, p = 0.033) in the detailed neuropsychological test results of the participants. Multivariable regression model also indicated that among CRI subscores, CRI-Leisure time directly affects the composite cognitive score (β = 0.32, p = 0.011). We found that in the early stage of cognitive decline in older adults, comprehensive CR was associated with global cognition, and only leisure activity was identified to be associated with the detailed neuropsychological profile including naming ability. These results may imply the positive effect of leisure activity on cognitive function in the early stages of cognitive decline.