Neuroanatomical and neurocognitive correlates of delusion in Alzheimer's disease and mild cognitive impairment.

BACKGROUND: Neuropsychiatric symptoms and delusions are highly prevalent among people with dementia. However, multiple roots of neurobiological bases and shared neural basis of delusion and cognitive function remain to be characterized. By utilizing a fine-grained multivariable approach, we investigated distinct neuroanatomical correlates of delusion symptoms across a large population of dementing illnesses. METHODS: In this study, 750 older adults with mild cognitive impairment and Alzheimer's disease completed brain structural imaging and neuropsychological assessment. We utilized principal component analysis followed by varimax rotation to identify the distinct multivariate correlates of cortical thinning patterns. Five of the cognitive domains were assessed whether the general cognitive abilities mediate the association between cortical thickness and delusion. RESULTS: The result showed that distributed thickness patterns of temporal and ventral insular cortex (component 2), inferior and lateral prefrontal cortex (component 1), and somatosensory-visual cortex (component 5) showed negative correlations with delusions. Subsequent mediation analysis showed that component 1 and 2, which comprises inferior frontal, anterior insula, and superior temporal regional thickness accounted for delusion largely through lower cognitive functions. Specifically, executive control function assessed with the Trail Making Test mediated the relationship between two cortical thickness patterns and delusions. DISCUSSION: Our findings suggest that multiple distinct subsets of brain regions underlie the delusions among older adults with cognitive impairment. Moreover, a neural loss may affect the occurrence of delusion in dementia largely due to impaired general cognitive abilities.

Facial Expressions Track Depressive Symptoms in Old Age.

Facial expressions play a crucial role in the diagnosis of mental illnesses characterized by mood changes. The Facial Action Coding System (FACS) is a comprehensive framework that systematically categorizes and captures even subtle changes in facial appearance, enabling the examination of emotional expressions. In this study, we investigated the association between facial expressions and depressive symptoms in a sample of 59 older adults without cognitive impairment. Utilizing the FACS and the Korean version of the Beck Depression Inventory-II, we analyzed both "posed" and "spontaneous" facial expressions across six basic emotions: happiness, sadness, fear, anger, surprise, and disgust. Through principal component analysis, we summarized 17 action units across these emotion conditions. Subsequently, multiple regression analyses were performed to identify specific facial expression features that explain depressive symptoms. Our findings revealed several distinct features of posed and spontaneous facial expressions. Specifically, among older adults with higher depressive symptoms, a posed face exhibited a downward and inward pull at the corner of the mouth, indicative of sadness. In contrast, a spontaneous face displayed raised and narrowed inner brows, which was associated with more severe depressive symptoms in older adults. These findings suggest that facial expressions can provide valuable insights into assessing depressive symptoms in older adults.

Social Network Characteristics Predict Loneliness in Older Adults.

INTRODUCTION: Social isolation is detrimental to late-life health outcomes. Although objective social isolation is a major source of perceived loneliness, how different layers of social disconnection systematically constitute the subjective experience of loneliness remains unclear. METHODS: This study focused on older adults who participated in the Korean Social Life, Health, and Aging Project (KSHAP) (n = 1,724; mean age = 72.91 years) and examined how the proximal and distal characteristics of social networks predict loneliness using a hierarchical linear regression model. The study also investigated whether the major loss of social roles (marital and working status) influences perceived loneliness through the proximal and distal aspects of social networks by cross-sectional mediation analysis. RESULTS: This study found that the proximal (subjective number of connections) and distal (brokerage and embeddedness) aspects of social networks additively explained the frequency of loneliness. Moreover, the loss of late-life social roles (marital and working status) was related to an increase in loneliness, where the distal characteristic of social networks mediated this relationship. DISCUSSION/CONCLUSION: The results of this study suggest that the proximal and the distal characteristic of social networks is a social determinant predicting loneliness in late life. Besides, the loss of bridging and cohesive position among community networks may be a critical pathway to psychosocial transition after marital and working status changes.

Distributed functional connectivity predicts neuropsychological test performance among older adults.

Neuropsychological test is an essential tool in assessing cognitive and functional changes associated with late-life neurocognitive disorders. Despite the utility of the neuropsychological test, the brain-wide neural basis of the test performance remains unclear. Using the predictive modeling approach, we aimed to identify the optimal combination of functional connectivities that predicts neuropsychological test scores of novel individuals. Resting-state functional connectivity and neuropsychological tests included in the OASIS-3 dataset (n = 428) were used to train the predictive models, and the identified models were iteratively applied to the holdout internal test set (n = 216) and external test set (KSHAP, n = 151). We found that the connectivity-based predicted score tracked the actual behavioral test scores (r = 0.08-0.44). The predictive models utilizing most of the connectivity features showed better accuracy than those composed of focal connectivity features, suggesting that its neural basis is largely distributed across multiple brain systems. The discriminant and clinical validity of the predictive models were further assessed. Our results suggest that late-life neuropsychological test performance can be formally characterized with distributed connectome-based predictive models, and further translational evidence is needed when developing theoretically valid and clinically incremental predictive models.

Association between Loneliness and Memory Function through White Matter Hyperintensities in Older Adults: The Moderating Role of Gender.

Loneliness has an important impact on memory function in late life. However, the neural mechanism by which loneliness detrimentally influences memory function remains elusive. Furthermore, it remains unclear whether the association between loneliness and memory function varies by gender. The current study aimed to investigate the neural mechanism underlying the association between loneliness and episodic memory function and explore whether it varies with gender among cognitively normal older adults. A total of 173 community-dwelling adults aged 60 years or older from the Korean Social Life, Health, and Aging Project (KSHAP) study (mean age = 71.87) underwent an assessment of loneliness, neuropsychological testing, and structural magnetic resonance imaging. The association between loneliness and episodic memory function was mediated by the volume of white matter hyperintensities (WMHs), but not by hippocampal or gray matter volumes. In addition, the association between loneliness and memory function through WMHs was significantly moderated by gender; specifically, the indirect effect was significant among men but not among women. The study suggests that WMHs may be a potential neurological mechanism that causes late-life memory dysfunction associated with loneliness in older men. The findings underscore the need for gender-specific interventions to mitigate memory impairment associated with late-life loneliness, with significant public health implications.

Brain connectivity during social exclusion differs depending on the closeness within a triad among older adults living in a village.

Social exclusion occurs in various types of social relationships, from anonymous others to close friends. However, the role that social relationships play in social exclusion is less well known because most paradigms investigating social exclusion have been done in laboratory contexts, without considering the features of individuals' real-world social relationships. Here, we addressed this gap by examining how pre-existing social relationships with rejecters may influence the brain response of individuals experiencing social exclusion. Eighty-eight older adults living in a rural village visited the laboratory with two other participants living in the same village and played Cyberball in an Magnetic Resonance Imaging scanner. Utilizing whole-brain connectome-based predictive modeling, we analyzed functional connectivity (FC) data obtained during the social exclusion task. First, we found that the level of self-reported distress during social exclusion was significantly related to sparsity, i.e. lack of closeness, within a triad. Furthermore, the sparsity was significantly predicted by the FC model, demonstrating that a sparse triadic relationship was associated with stronger connectivity patterns in brain regions previously implicated in social pain and mentalizing during Cyberball. These findings extend our understanding of how real-world social intimacy and relationships with excluders affect neural and emotional responses to social exclusion.

Lower cognitive function attenuates the convergence between self-ratings and observer ratings of depressive symptoms in late-life cognitive impairment.

OBJECTIVES: Assessment of depressive symptoms in older adults is challenging especially in the presence of risks in cognitive impairment. We aimed to examine whether the convergence between two measures of depressive symptoms (self-report and observer ratings) is affected by varying levels of cognitive function in older adults. METHODS: Self-reported scale of depression, informant-based rating of affective symptoms, and global cognitive function were assessed in 2533 older adults with no impairment, mild cognitive impairment, and Alzheimer's disease. The strength of rank-order correlation between the Geriatric Depression Scale (GDS) and behavioral ratings of the Neuropsychiatric Inventory (NPI) was examined as the metric of convergent validity. RESULTS: The results showed that the strength of convergence between the two measurements gradually decreased as a function of lowered cognitive function. Overall tendency showed that diagnoses of cognitive impairment and lower levels of cognitive function were associated with lower correspondence between the two depression measurements. The loss of convergent validity is especially evident in the behavioral symptom of apathy. CONCLUSIONS: Utilizing self-report scales of depression in older adults requires a cautious approach even with minimal or mild levels of cognitive impairment.

Erratum: A Comparison Between the Performances of Verbal and Nonverbal Fluency Tests in Discriminating Between Mild Cognitive Impairments and Alzheimer's Disease Patients and Their Brain Morphological Correlates.

[This corrects the article on p. 17 in vol. 21, PMID: 35154337.].

Psychological well-being and salivary markers of inflammation: The moderating effect of age.

Increasing evidence suggests a significant impact of higher psychological well-being (PWB) on health outcomes; however, such associations have been studied exclusively in middle-aged to older adults. This study examined the aging effect on PWB measures as well as the moderating effect of age on the link between PWB and inflammation, using salivary markers by comparing the younger adults (n = 127; Mage = 22.98 years) versus older adults (n = 75; Mage = 75.60 years). Older adults showed significantly lower levels of PWB, particularly regarding purpose in life and personal growth. Moreover, higher purpose in life was associated with lower salivary IL-1ß and IL-6 (b = 0.83, p < .001; b = 0.81, p < .01) only in the older adult group but not in younger adults. These findings highlight the potential buffering effect of the sense of living well on physiological pathways in later life.

Distinct neuroanatomical correlates of interference-related verbal episodic memory test in healthy older adults.

Verbal learning test can include a trial of interference process that intrude initial learning and impose additional cognitive stress. However, it has been unclear whether the multiple memory processes underly different brain structural bases. We measured performances of word retrieval that represents distinct memory processes (initial learning, interference, and retention) and regional gray matter morphology from 230 cognitively unimpaired older adults. We identified three distinct multivariate pattern modes using canonical correlation analysis that map correspondence between memory and brain morphometry. The first mode comprised weights highly loaded on temporal lobe and overall performances. The second mode reflected subcortical volumes and initial learning performances. The third mode comprised thickness in the lateral prefrontal and parietal cortex and captured an ability to resist retroactive interference effect. While overall test performance reflected the temporal lobe and whole-gray matter volume, the interim trial of interference signifies neural correlates extending to subcortical and frontoparietal regions.

Utility of Machine Learning Approach with Neuropsychological Tests in Predicting Functional Impairment of Alzheimer's Disease.

BACKGROUND: In assessing the levels of clinical impairment in dementia, a summary index of neuropsychological batteries has been widely used in describing the overall functional status. OBJECTIVE: It remains unexamined how complex patterns of the test performances can be utilized to have specific predictive meaning when the machine learning approach is applied. METHODS: In this study, the neuropsychological battery (CERAD-K) and assessment of functioning level (Clinical Dementia Rating scale and Instrumental Activities of Daily Living) were administered to 2,642 older adults with no impairment (n = 285), mild cognitive impairment (n = 1,057), and Alzheimer's disease (n = 1,300). Predictive accuracy on functional impairment level with the linear models of the single total score or multiple subtest scores (Model 1, 2) and support vector regression with low or high complexity (Model 3, 4) were compared across different sample sizes. RESULTS: The linear models (Model 1, 2) showed superior performance with relatively smaller sample size, while nonlinear models with low and high complexity (Model 3, 4) showed an improved accuracy with a larger dataset. Unlike linear models, the nonlinear models showed a gradual increase in the predictive accuracy with a larger sample size (n > 500), especially when the model training is allowed to exploit complex patterns of the dataset. CONCLUSION: Our finding suggests that nonlinear models can predict levels of functional impairment with a sufficient dataset. The summary index of the neuropsychological battery can be augmented for specific purposes, especially in estimating the functional status of dementia.

Clinical and biological subtypes of late-life depression.

BACKGROUND: Late-life depression (LDD) results from multiple psychosocial and neurobiological changes occurring in later life. The current study investigated how patterns of clinical symptoms and brain structural features are classified into LDD subtypes. METHOD: Self-report scale of depression, behavioral rating of affective symptoms, and brain structural imaging of white matter change and cortical thickness were assessed in 541 older adults with no cognitive impairment or mild cognitive impairment. Latent profile analysis was used to identify distinct subtypes of depression. RESULTS: The latent profile analysis identified four classes with mild to severe depressive symptoms and two classes with minimal symptoms. While the classes primarily differed in the overall severity, the combinatory patterns of clinical symptoms and neuropathological signature distinguished the classes with similar severity. The classes were distinguished in terms of whether or not neurodegenerative risk accompanied the corresponding depressive symptoms. The presence of the negative self-scheme and cortical thinning pattern notably characterized the subtypes of LDD. LIMITATIONS: The underlying etiologies of the biological subtypes are still speculative, and the current study lacks clinical history that differentiates late- and early-onset depression. CONCLUSIONS: Our finding provides insight in identifying heterogeneities of depressive disorder in later life and suggests that self-report and behavioral symptom profile in combination with white matter lesion and cortical thickness effectively characterizes distinct subtypes of LDD.

A Comparison Between the Performances of Verbal and Nonverbal Fluency Tests in Discriminating Between Mild Cognitive Impairments and Alzheimer's Disease Patients and Their Brain Morphological Correlates.

BACKGROUND AND PURPOSE: Verbal and nonverbal fluency tests are the conventional methods for examining executive function in the elderly population. However, differences in impairments result in fluency tests in patients with mild cognitive impairments (MCIs) and Alzheimer's disease (AD) and in neural correlates underlying the tests still necessitate concrete evidence. METHODS: We compared the test performances in 27 normal controls, 28 patients with MCI, and 20 with AD, and investigated morphological changes in association with the test performances using structural magnetic imaging. RESULTS: Patients with AD performed poorly across all the fluency tests, and a receiver operating characteristics curve analysis revealed that only category fluency test discriminated all the 3 groups. Association, category, and design fluency tests involved temporal and frontal regions, while letter fluency involved the cerebellum and caudate. CONCLUSIONS: Category fluency is a reliable measure for screening patients with AD and MCI, and this efficacy might be related to morphological correlates that underlie semantic and executive processing.

Brain Structural Alterations, Diabetes Biomarkers, and Cognitive Performance in Older Adults With Dysglycemia.

Despite the high risk of dementia in older adults with type 2 diabetes, the neuroanatomical correlates of cognitive dysfunction that are particularly affected by diabetes are not well characterized. This study is aimed to examine the structural brain alterations in dysglycemic older adults. Using voxel-based morphometric and tract-based spatial statistics, we examined changes in gray matter volume, white matter volume, and microstructural integrity in older adults with prediabetes and diabetes. We also assessed the correlation of these structural changes with diabetes biomarkers and cognitive performance. A total of 74 non-demented older adults (normal, n = 14; prediabetes, n = 37; and diabetes, n = 23) participated in this study and underwent structural and diffusion magnetic resonance imaging (MRI) scans and neuropsychological tests. Subjects with diabetes showed reduced volume of cerebellar gray matter and frontal white matter and diffuse white matter dysintegrity, while those with prediabetes only showed reduced volume of insular gray matter. Atrophic changes in the cerebellum and frontal lobe and frontal white matter dysintegrity were correlated with chronic hyperglycemia and insulin resistance and worse performance in verbal memory recognition and executive function tests. Our findings suggest that chronic hyperglycemia and insulin resistance may alter brain structures forming the fronto-cerebellar network, which may cause cognitive dysfunction in older adults.

Social Network Position Moderates the Relationship between Late-life Depressive Symptoms and Memory Differently in Men and Women.

Late-life depression has been considered to be associated with memory deficits and hippocampal volume reduction. Considering that not all depression patients undergo the same amount of cognitive impairment or regional brain volume loss, moderating factors such as complex mental activity and social activity have been examined to assess whether these factors attenuate the detrimental impact of depressive symptoms on cognitive function and regional brain volume. However, the premise that a cognitively stimulating experience may modify the association between depressive symptoms and memory or hippocampal volume has not been investigated using social network data, which would reflect individuals' concrete characteristic of everyday social activity. In a social network, a brokerage position which connects two otherwise unconnected others demands mental and physical efforts. Using complete social network data in an entire village in South Korea, we examined whether opportunities for brokerage in social networks alter the negative association between depressive symptoms and episodic memory function or hippocampal volume in older adults. Initially, 125 participants were included in the analysis involving episodic memory function. Then, of which 65 participants completed the MRI scan, and were included in the subsequent analysis containing the hippocampal volume. Furthermore, we investigated the gender-specific effect of brokerage based on the previously reported gender difference in the effect of social networks. We found a gender-specific moderating effect of brokerage. For men, a large opportunity for brokerage weakened the negative association between depressive symptoms and memory performance and left hippocampal volume. In contrast, women showed that a large opportunity for brokerage was not beneficial for assuaging the impact of depressive symptoms on memory performance and hippocampal volume. In women, the opportunity for brokerage was positively associated with the detrimental impact of depressive symptoms on memory performance and hippocampal volume. Our findings suggest that occupying a bridging position in a social network may minimize the impact of depressive symptoms on memory function and hippocampal volume among older men, whereas the opposite holds true for older women.

Feeling How Old I Am: Subjective Age Is Associated With Estimated Brain Age.

While the aging process is a universal phenomenon, people perceive and experience one's aging considerably differently. Subjective age (SA), referring to how individuals experience themselves as younger or older than their actual age, has been highlighted as an important predictor of late-life health outcomes. However, it is unclear whether and how SA is associated with the neurobiological process of aging. In this study, 68 healthy older adults underwent a SA survey and magnetic resonance imaging (MRI) scans. T1-weighted brain images of open-access datasets were utilized to construct a model for age prediction. We utilized both voxel-based morphometry (VBM) and age-prediction modeling techniques to explore whether the three groups of SA (i.e., feels younger, same, or older than actual age) differed in their regional gray matter (GM) volumes, and predicted brain age. The results showed that elderly individuals who perceived themselves as younger than their real age showed not only larger GM volume in the inferior frontal gyrus and the superior temporal gyrus, but also younger predicted brain age. Our findings suggest that subjective experience of aging is closely related to the process of brain aging and underscores the neurobiological mechanisms of SA as an important marker of late-life neurocognitive health.