Normal Cognition Research Articles

SUBJECTIVE COGNITIVE DECLINE MODERATES THE ASSOCIATION BETWEEN AGE AND MEMORY DECLINE IN MIDLIFE

Abstract Subjective cognitive decline (SCD) represents self-perceived worsening of memory and thinking abilities, in the absence of objective cognitive impairment, and serves as a prognostic marker of Alzheimer’s disease (AD). However, no study to date has investigated whether SCD moderates the relationship between aging and memory before older ages. We tested the hypothesis that SCD interacts with age to predict memory performance in midlife. A subset of 123 cognitively unimpaired, middle-aged adults (Mage=56.6±6.44 years; 87% females) from an ongoing clinical trial (NIH R01AG058919) were included for analyses. Multiple linear regression models tested the effects of age and SCD in predicting performance of mnemonic discrimination, auditory-verbal memory, visuospatial memory, paired associative memory, and verbal logical memory, while controlling relevant covariates (e.g., education, sex, and APOE ε4). Based on the optimal cutoff of the Everyday Cognition Scale, 28.2% of the sample were considered to have SCD and 71.8% perceived themselves to have normal cognition. After covariate adjustments, there were significant main and interaction effects of SCD and age on mnemonic discrimination performance on the Mnemonic Similarity Task (MST) but not on other memory outcomes. The negative relationship between age and mnemonic discrimination was evident in middle-aged adults who self-report cognitive concerns but not in those without such concerns. Since mnemonic discrimination is highly sensitive to hippocampal function, these findings support the utility of the MST to detect age-related hippocampal changes and ensuing memory declines in midlife as well as the importance of early interventions among middle-aged adults with SCD to prevent AD.

THE EARLY LIFE CONTEXTS OF THE HEALTH AND RETIREMENT STUDY HCAP SAMPLE: NEW INSIGHTS INTO DEMENTIA RISK FACTORS

Abstract There’s increasing interest in identifying potentially modifiable early-life socioenvironmental factors associated with late-life cognitive decline and dementia. To date, much research points to the importance of the number of years spent in education and age. We sought to extend evidence for potential modifiable targets by examining life history data available to date for women and men in the 2016 HRS-HCAP sample (N = 2645; Mean Age = 76; 61% women). The life history data were drawn from three HRS public cross-wave files: the 2015-2017 Life History Mail Surveys, the 1992-2018 Childhood Family and Childhood Health file, and the 1992-2020 Geographical Mobility File. Among the early factors examined were the US Census region of birth and school location at age 10; childhood physical and mental health conditions; childhood family SES; early learning and sensory/motor problems, early life activity engagement (cognitive, physical, social), college majors, and post-education work. The HRS-HCAP algorithm classifications (Dementia, MCI, vs Normal Cognition) served as outcomes. In addition to quantity of education and age/cohort, significant effects (all ps < .001) were revealed for childhood geographical locations, childhood mental health, and early-life access to and engagement in enriching activities. Over time, whereas the impact of changes such as increased access to post-secondary education and enriching high school activities are observed, other modifiable factors emerge. Tracking the impacts on cognitive aging of historical changes and disparities in the life course contexts of people in the HRS-HCAP subsample opens a new window into relevant social-environmental factors to target for intervention

PREVALENCE OF METABOLIC COMORBIDITIES AMONG COGNITIVELY NORMAL AND IMPAIRED WHITE AND AFRICAN AMERICANS

Abstract Assessing comorbidities associated with a MCI diagnosis is crucial for diagnostic accuracy and for understanding the role of comorbidities in cognitive decline. In this study of amnestic (aMCI) and non-amnestic (naMCI) MCI participants and persons with normal cognition (CN), we compared the prevalence of three primary comorbidities: Hypertension (HTN), Hyperlipidemia (HLD), and Diabetes Mellitus (DM) across African American and White populations using Chi-squares. Participant data (N = 9,342, 17% African American) were available through the National Alzheimer’s Coordinating Center and included: CN (n = 5,963; MOCA mean=27), aMCI (2,694; MOCA=22), and naMCI (685; MOCA=24) with diagnosis and data per their first Uniform Data Set (Version 3) visit. Significant differences in the distribution of HTN, HLD, and DM were found among the diagnostic groups for the total cohort and racial groups, separately; however, diagnostic differences across races were not always consistent. The relative rates of DM and HLD across the diagnostic groups for both races were generally similar, though higher percentages were seen in African Americans (25% of African Americans, 10% of Whites). As for HTN (52% of African Americans, 39% of Whites), however, the distributions differ across the diagnostic groups and race (%yes for diagnosis; White Americans: CN 35%, aMCI 47%, naMCI 44%; African Americans: CN 66%, aMCI 70%, naMCI 79%, p< 0.001). These findings highlight the importance of considering the contributions of both race and diagnosis when evaluating the role of comorbid factors and metabolic disorders in NC and MCI groups, in particular when considering blood pressure-related measures.

DESIGNING COLLABORATIVE AUGMENTED REALITY ACTIVITIES WITH OLDER ADULTS IN LONG TERM CARE

Abstract Loneliness is common among older adults in long term care (LTC) settings. Interactive communication technologies hold great promise in reducing loneliness but require design and evaluation studies. As part of a larger study on use of head mounted display augmented reality (HMD-AR) to connect older LTC adults with family members, we conducted a participatory design study to a) identify and design HMD-AR multi-user activities and b) address barriers found with LTC residents when interacting with HMD-AR. Results: Laboratory testing was conducted with 23 older adults with normal cognition (ages 65 to 93, 6 men) and field testing with iterative feedback cycles with 8 older adults with impaired mobility and cognition (ages 54 to 87, 2 men, 4 with stroke) that resulted in prototype development and testing of three activities: playing checkers, decorating a fireplace, and eating a meal. Challenges successfully addressed through technological innovations included: 1) enhancing perceptions and ease of interacting with photorealistic avatars, 2) providing various techniques to allow older adults to view and move AR objects despite cognitive and functional impairments (e.g., visual-perceptual impairments; limited dexterity), 3) using visual aids and voice commands, 4) developing visual adaptations for central vision and color detection impairments, and 5) creating tutorials and help guides for learnability and remembrance. Sessions lasted for 30 minutes and no adverse effects were noted with prolonged or repeated HMD-AR use. All enjoyed the HMD-AR activities. Conclusion: HMD-AR can be successfully adapted for use by older adults with multiple cognitive and physical impairments.

LINKING PLASMA PROTEOMICS TO BRAIN ACCELERATED/RESILIENT AGING IN THE ATHEROSCLEROSIS RISK IN COMMUNITY STUDY

Abstract Machine learning models are increasingly being used to estimate ‘brain age’ from neuroimaging data. The gap between chronological age and the estimated brain age (BAG) is potentially a measure of accelerated/resilient brain aging, and we estimated BAG based on an elastic net regression approach. Here, we report associations between this brain age measure and plasma protein levels (measured using an aptamer-based proteomic platform) in the Atherosclerosis Risk in Communities (ARIC) Study to determine whether BAG was associated with proteins linked to biologic aging. We used brain MRI scans from 1507 ARIC visit 5 participants: 938 were Cognitively Normal (CN), 495 had mild cognitive impairment (MCI) and 74 had dementia. The proteomic dataset contains 4877 plasma proteins in these same individuals. We fitted univariate linear regression models adjusting for age, race, smoking, education, sex, diabetes, hypertension and intra-cranial volume. A Bonferroni correction was applied to account for multiple testing to maintain an analysis-wise α=0.05. In total 31 proteins were significantly associated with BAG. Among these SEVP1, GDF-15, pleiotrophin, MMP7, Natriuretic-peptides and Hsp70 were found to be associated with accelerated BAG, whereas EGF-receptor, mast/stem-cell-growth-factor-receptor (KIT), Coagulation-factor-VII and cGMP-dependent-protein-kinase-1 were associated to resilient BAG. The analysis based only on CN participants produced 3 significant proteins: retinoblastoma-2 and SEVP1, which were associated with accelerated BAG and Coagulation-factor-VII, which was associated to resilient BAG. These results suggest circulating proteins implicated in biological aging, cellular senescence, angiogenesis and coagulation are associated with a neuroimaging measure of accelerated brain aging.

DEMENTIA AND MILD COGNITIVE IMPAIRMENT: PREVALENCE, CONVERSION RATES, AND LONGEVITY BETWEEN AGES 70 AND 95

Abstract This study describes the prevalence and conversion rates of Mild Cognitive Impairment (MCI) and dementia between age 70-95, and the association between cognitive status and mortality. The Jerusalem Longitudinal Study (1990-2023) prospectively follows a representative community-dwelling cohort born 1920-21, assessed at home visit during 1990,1998, 2005, 2010, 2015 at ages 70, 78, 85, 90, and 95 (n=437, 806, 1170, 584, 468) respectively. Comprehensive assessment included Mini Mental State Examination (MMSE), defining normal cognition (29-30/30), MCI (24-28/30) and dementia (≤23/30). Mortality data were collected from the Ministry of Interior. Cox proportional hazards ratios (HR) were determined, adjusting for gender, education, self-rated health, physical activity, BADL status, diabetes, hypertension, ischemic heart disease. At ages 70, 78, 85, 85, 90, and 95 the prevalence of MCI was 13.5%, 21.5%, 38.7%, 37.0%, and 50%; prevalence of dementia was 3.2%, 4.2%, 24.3%, 31.3%, 35.7%. Between age 70-78, 78-85, 85-90, 90-95, conversion rates from MCI back to normal were 74.2%, 27.4%, 18.2%, 7.3%; MCI declining to dementia were 6.5%, 29.2%, 37.0%, 50.9%; MCI remaining MCI were 19.4%, 43.4%, 44.8%, 41.8%. Dementia was significantly associated with increased mortality throughout the entire study period: at age 70-78 Hazards Ratio=4.36 (CI 95%: 2.09-9.10), age 90-95 HR=1.5 (CI 95%: 1.01-2.21). In contrast, MCI was not associated with increased mortality, apart from at age 85: HR=1.38 (CI 95%: 1.04-1.82). Our findings show that conversion rates from MCI to dementia are age-dependent, with less than half of MCI subjects progressing to dementia. Unlike dementia, MCI was largely unassociated with mortality.

FREE-LIVING HEART RATE VARIABILITY/PHYSICAL ACTIVITY AND COGNITIVE FUNCTION AND DEMENTIA IN ARIC

Abstract Low heart rate variability (HRV) and physical activity (PA) are associated with cognitive dysfunction in clinical settings. Yet, associations with these measures among older adults in the free-living environment remain unexplored. We hypothesize higher free-living HRV and PA are associated with higher cognitive test scores and less likelihood of mild cognitive impairment (MCI)/dementia. This study includes 1,590 ARIC participants aged 72-94 years who wore the Zio XT Patch for 14-days to simultaneously capture ECG and accelerometry, from which we derived HRV as the standard deviation (SDNN) or root mean squared successive difference (rMSSD) of normal RR intervals and PA as total mean amplitude deviation (TMAD; higher values represent more movement). Linear or ordinal regression models were fitted to estimate cross-sectional associations between log transformed HRV or PA with latent-variable derived global and domain-specific cognitive factor scores or adjudicated MCI/dementia, respectively. Participants were on average 79 years, 57% female, and 32% Black. There were no significant associations between either HRV measure and cognition. After adjusting for demographic and medical covariates, 1-unit higher in log TMAD was associated with a 0.30-point higher global factor score (95% CI: 0.16-0.44), 0.38-point higher executive function factor score (95% CI: 0.22-0.53), 62% lower odds of MCI (95% CI: 0.22-0.67) and 75% lower odds of dementia compared to normal cognition (95% CI: 0.08-0.74). In summary, free-living PA, but not HRV of RR intervals, is associated with cognitive and dementia status. Further investigation of other objective HRV measures and directionality of associations between PA and cognition is needed.

Liver Transplantation for Zellweger Syndrome.

Zellweger syndrome or cerebrohepatorenal syndrome is a rare, multisystem disorder occurring due to defect in metabolic pathway within the peroxisomes. Cirrhosis with portal hypertension is an important presentation of these patients. Given its progressive, multisystem nature, the role of liver transplantation (LT) in Zellweger syndrome remains undefined and controversial. An 11-y-old boy diagnosed with Zellweger syndrome presented to theauthors with decompensated cirrhosis along with bilateral proptosis. After a meticulous evaluation, he was offered an ABO incompatible liver transplantation with hismother being the donor. He had an uneventful post operative period. After a follow up of 24 mo, he has normal graft function,normal cognition along with resolution of proptosis. Therefore, in a group of carefully selected patients with Zellweger syndrome, a liver transplantation can be offered successfully with an excellent prognosis.

Association between dynapenia and cognitive decline in community-dwelling older Japanese adults: The IRIDE Cohort Study.

Muscle mass and strength correlate with cognitive function; however, it remains unclear whether dynapenia (i.e., muscle weakness with preserved muscle mass) is relevant. This study aimed to explore whether dynapenia is associated with global cognitive function in community-dwelling older Japanese adults. This cross-sectional study used data from the Integrated Research Initiative for Living Well with Dementia Cohort Study, which pooled data from five community-based geriatric cohorts. Dynapenia was defined as muscle weakness without muscle mass loss according to the Asian Working Group for Sarcopenia criteria. Cognitive function was assessed using the Mini-Mental State Examination (MMSE). An ordered logistic regression analysis was conducted with dynapenia as the exposure and with cognitive decline stages, defined as an MMSE score of 27-30 for normal cognition, 24-26 for possible cognitive decline, and <24 for cognitive decline, as the outcome, stratified by sex and adjusted for age, muscle mass, education, alcohol consumption, smoking habits, living alone, and non-communicable diseases. We analyzed data for 3338 participants (2162 female) with preserved muscle mass. Of these, 449 (13.5%) had dynapenia, and 79 (2.4%) exhibited cognitive decline. Multivariate odds ratios (95% confidence interval) for cognitive decline among those with dynapenia, compared with those without dynapenia, were 1.51 (1.02-2.24) for males and 2.08 (1.51-2.86) for females. Muscle weakness is associated with cognitive decline, even in individuals with preserved muscle mass. Further studies are needed to better understand the association between muscle weakness and cognitive decline over time in order to develop dementia prevention strategies for those with dynapenia. Geriatr Gerontol Int 2024; 24: 123-129.

Longitudinal trajectories of cognitive reserve in hypometabolic subtypes of Alzheimer's disease

Previous studies have demonstrated resilience to AD-related neuropathology in a form of cognitive reserve (CR). In this study we investigated a relationship between CR and hypometabolic subtypes of AD, specifically the typical and the limbic-predominant subtypes. We analyzed data from 59 Aβ-positive cognitively normal (CN), 221 prodromal Alzheimer’s disease (AD) and 174 AD dementia participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) from ADNI and ADNIGO/2 phases. For replication, we analyzed data from 5 Aβ-positive CN, 89 prodromal AD and 43 AD dementia participants from ADNI3. CR was estimated as standardized residuals in a model predicting cognition from temporoparietal grey matter volumes and covariates. Higher CR estimates predicted slower cognitive decline. Typical and limbic-predominant hypometabolic subtypes demonstrated similar baseline CR, but the results suggested a faster decline of CR in the typical subtype. These findings support the relationship between subtypes and CR, specifically longitudinal trajectories of CR. Results also underline the importance of longitudinal analyses in research on CR.

Aggregation Dynamics Characteristics of Seven Different Aβ Oligomeric Isoforms-Dependence on the Interfacial Interaction.

The aggregation of β-amyloid (Aβ) peptides has been confirmed to be associated with the onset of Alzheimer's disease (AD). Among the three phases of Aβ aggregation, the lag phase has been considered to be the best time for early Aβ pathological deposition clinical intervention and prevention for potential patients with normal cognition. Aβ peptide exists in various lengths in vivo, and Aβ oligomer in the early lag phase is neurotoxic but polymorphous and metastable, depending on Aβ length (isoform), molecular weight, and specific phase, and therefore hardly characterized experimentally. To cope with the problem, molecular dynamics simulation was used to investigate the aggregation process of five monomers for each of the seven common Aβ isoforms during the lag phase. Results showed that Aβ(1-40) and Aβ(1-38) monomers aggregated faster than their truncated analogues Aβ(4-40) and Aβ(4-38), respectively. However, the aggregation rate of Aβ(1-42) was slower than that of its truncated analogues Aβ(4-42) rather than that of Aβpe(3-42). More importantly, Aβ(1-38) is first predicted as more likely to form stable hexamer than the remaining five Aβ isoforms, as Aβ(1-42) does. It is hydrophobic interaction mainly (>50%) from the interfacial β1 and β2 regions of two reactants, pentamer and monomer, aggregated by Aβ(1-38)/Aβ(1-42) rather than by other Aβ isoforms, that drives the hexamer stably as a result of the formation of the effective hydrophobic collapse. This paper provides new insights into the aggregation characteristics of Aβ with different lengths and the conditions necessary for Aβ to form oligomers with a high molecular weight in the early lag phase, revealing the dependence of Aβ hexamer formation on the specific interfacial interaction.

Serum proinsulin levels as peripheral blood biomarkers in patients with cognitive impairment

Insulin has long been associated with dementia. Insulin affecting the clearance of amyloid-β peptide and phosphorylation of tau in the CNS. Proinsulin is a precursor of insulin and its elevated serum levels are associated with peripheral insulin resistance that may reduce brain insulin levels. Our study aimed to assess differences in serum proinsulin levels between normal and cognitive impairment groups. Prospective recruitment of elderly participants was initiated from October 2019 to September 2023. Patients were divided into “cognitive impairment” and “normal cognition” group. All participants had blood drawn and serum proinsulin was measured at baseline and 12 months. Neurocognitive testing was performed every 6 months. A total of 121 participants were recruited. Seventy-seven were in the normal cognition group and 44 in the cognitive impairment group. The glycemic control and prevalence of diabetes type 2 was similar between groups. Baseline serum proinsulin levels were higher in the cognitively impaired group compared to the normal group at baseline (p = 0.019) and correlated with worse cognitive scores. We identified cognitive status, age, and BMI as potential factors associated with variations in baseline proinsulin levels. Given the complex interplay between insulin and dementia pathogenesis, serum biomarkers related to insulin metabolism may exhibit abnormalities in cognitive impaired patients. Here we present the proinsulin levels in individuals with normal cognitive function versus those with cognitive impairment and found a significant difference. This observation may help identifying non-diabetic patients suitable for treatment with novel AD drugs that related to insulin pathway.

Whole Brain and Corpus Callosum Fractional Anisotropy Differences in Patients with Cognitive Impairment.

Diffusion tensor imaging (DTI) is an MRI analysis method that could help assess cognitive impairment (CI) in the ageing population more accurately. In this research, we evaluated fractional anisotropy (FA) of whole brain (WB) and corpus callosum (CC) in patients with normal cognition (NC), mild cognitive impairment (MCI), and moderate/severe cognitive impairment (SCI). In total, 41 participants were included in a cross-sectional study and divided into groups based on Montreal Cognitive Assessment (MoCA) scores (NC group, nine participants, MCI group, sixteen participants, and SCI group, sixteen participants). All participants underwent an MRI examination that included a DTI sequence. FA values between the groups were assessed by analysing FA value and age normative percentile. We did not find statistically significant differences between the groups when analysing CC FA values. Both approaches showed statistically significant differences in WB FA values between the MCI-SCI and MCI-NC groups, where the MCI group participants showed the highest mean FA and highest mean FA normative percentile results in WB.

Predicting Amyloid-β Positivity in Alzheimer’s Disease: Comprehensive Analysis of Feature Selection and Machine Learning Models for Accurate Identification

To accurately identify individuals at risk of Alzheimer’s disease (AD), it is crucial to develop precise tools for predicting amyloid-β (Aβ) positivity in the brain. We used data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) to analyze 1,377 human subjects. These participants were divided into five groups: cognitive normal (CN), subjective memory complaints (SMC), early mild cognitive impairment (EMCI), late mild cognitive impairment (LMCI), and confirmed AD. Each group was further divided into ten subgroups based on sex, resulting in a comprehensive analysis. The dataset was used to create and evaluate the performance of 15 machine learning (ML) models. A set of 17 potential predictors was generated by combining variables from different categories, including six demographic factors (such as age), ten measurements (such as ADAS13), and APOE4 status. Through ML-based predictive modeling, several cognitive assessment measures, including ADAS13, demonstrate significant importance in multiple ML models. The highest accuracies in the 10 subgroups were 0.875, 0.892, 0.778, 0.850, 0.771, 0.739, 0.781, 0.791, 0.879, and 0.903, respectively. The collection of ML models consists of practical and valuable risk feature scores that can significantly enhance the identification of individuals who are likely to test positive for Aβ.

Gray-white matter boundary Z-score and volume as imaging biomarkers of Alzheimer's disease.

Alzheimer's disease (AD) presents typically gray matter atrophy and white matter abnormalities in neuroimaging, suggesting that the gray-white matter boundary could be altered in individuals with AD. The purpose of this study was to explore differences of gray-white matter boundary Z-score (gwBZ) and its tissue volume (gwBTV) between patients with AD, amnestic mild cognitive impairment (MCI), and cognitively normal (CN) elderly participants. Three-dimensional T1-weight images of a total of 227 participants were prospectively obtained from our institute from 2006 to 2022 to map gwBZ and gwBTV on images. Statistical analyses of gwBZ and gwBTV were performed to compare the three groups (AD, MCI, CN), to assess their correlations with age and Korean version of the Mini-Mental State Examination (K-MMSE), and to evaluate their effects on AD classification in the hippocampus. This study included 62 CN participants (71.8 ± 4.8 years, 20 males, 42 females), 72 MCI participants (72.6 ± 5.1 years, 23 males, 49 females), and 93 AD participants (73.6 ± 7.7 years, 22 males, 71 females). The AD group had lower gwBZ and gwBTV than CN and MCI groups. K-MMSE showed positive correlations with gwBZ and gwBTV whereas age showed negative correlations with gwBZ and gwBTV. The combination of gwBZ or gwBTV with K-MMSE had a high accuracy in classifying AD from CN in the hippocampus with an area under curve (AUC) value of 0.972 for both. gwBZ and gwBTV were reduced in AD. They were correlated with cognitive function and age. Moreover, gwBZ or gwBTV combined with K-MMSE had a high accuracy in differentiating AD from CN in the hippocampus. These findings suggest that evaluating gwBZ and gwBTV in AD brain could be a useful tool for monitoring AD progression and diagnosis.

Neuroimaging and Neuropsychological Performance in Parkinson's Disease Patients with Normal Cognition: A Systematic Review

Introduction: Cognitive decline is one of Parkinson's disease's (PD) non-motor symptoms that is most frequently observed. Patients with PD exhibit quick cognitive decline in a variety of cognitive domains, particularly in the areas of executive functions, attention, language, memory, and visuospatial abilities. The scope of PD patients with normal cognition (PD-NC) and its relationship to specific regions of the brain as shown by neuroimaging, have not received much attention in the literature.&#x0D; Objective: This review was to summarise the existing literature that explored cognitive performance in PD-NC using different neuroimaging techniques.&#x0D; Methods: A comprehensive search was conducted on PubMed and Web of Science databases. This review focused on papers that investigated neuroimaging and neuropsychological performance in patients with PD. A total of 17 articles have met the criteria.&#x0D; Results: The findings of this review were that executive functions appear to be the most critical cognitive domain to be damaged in PD-NC. Global cognitive ability was found to have insignificant decline overall between PD-NC and healthy controls (HC). Attention and executive functions were associated with the prefrontal cortex. Memory was mainly associated with hippocampal atrophy. Language was associated with cerebrospinal fluid and grey matter. Visuospatial ability was associated with the anterior cingulate cortex.&#x0D; Conclusion: This review illustrated that PD-NC seemed to experience different cognitive patterns and neuroanatomical changes compared with HC. These results suggested that PD-NC may develop specific cognitive impairments associated with specific brain regions. Therefore, it indicated that PD-NC may need to have specific treatments tailored to their needs.

Factors associated with reduced sleep among spouses and caregivers of older adults with varying levels of cognitive decline.

Caregivers of persons with cognitive decline (PWCD) are at increased risk of poor sleep quantity and quality. It is unclear whether this is due to factors in the caregiver versus in the PWCD. This secondary data analysis using Aging, Demographics, and Memory Study data from the Health Retirement Study examined factors contributing to reduced sleep/rest among spouses and caregivers of older adults with varying levels of cognitive decline (cognitively normal (CN), cognitive impairment but not dementia (CIND), or dementia). In our preliminary analysis, among N = 218 spouses (not necessarily caregivers) (mean age (SD) = 73.77 (7.30); 70.64% female) of older adults with varying levels of cognitive decline, regression revealed that frequency of sleep complaints was lowest among spouses with CN partners, second highest with CIND partners, and highest with dementia-partners, X2 = 26.810, P = 0.002. among n = 136 caregivers of PWCD (mean age (SD) = 59.27 (13.97); 74.26% female; 22.79% spouses), we analyzed whether caregiver reduced sleep/rest was predicted by PWCD factors (i.e., frequent nighttime waking, dementia severity) and/or caregiver factors (i.e., depression symptoms, caregiver role overload). Regression revealed that caregiver depression symptoms (d = 0.62) and role overload (d = 0.88), but not PWCD factors, were associated with reduced caregiver sleep/rest after adjusting for demographic factors, caregiving frequency, and shared-dwelling status (overall model: X2 = 31.876, P = 0.002). Exploratory analyses revealed that a caregiver was 7.901 times more likely (95% CI: 0.99-63.15) to endorse experiencing reduced sleep/rest if back-up care was not available (P = 0.023). Findings highlight that the frequency of reported sleep problems among spouses increases in a stepwise fashion when partners have dementia versus CIND versus CN. The results also emphasise that caregiver mental health and burden are strongly associated with caregiver sleep disturbances and thus may be targets of intervention for caregiver sleep problems.

Subjective cognitive complaints in patients with progressive supranuclear palsy.

Subjective cognitive complaints (SCC) refer to self-reported cognitive decline that may or may not be reflected in objective neuropsychological evaluations. Such SCC are prevalent in neurodegenerative diseases, including Parkinson's disease (PD), but the prevalence and clinical features in patients with progressive supranuclear palsy (PSP) have not been investigated. We recruited 83 PSP patients without dementia and investigated their SCC using a semi-structured interview. Comprehensive neuropsychological test results and patient clinical features were compared according to presence of SCC and underlying cognitive state. Among the 83 patients, 16 had normal cognition (NC), 67 had mild cognitive impairment (MCI), and 36 (43.4%) reported SCC. Among NC patients, 37.5% (6/16) had SCC, while 44.8% (30/67) of MCI patients reported SCC. There were no differences between the neuropsychological test results or demographic and clinical characteristics of PSP patients with or without SCC in the NC group. The demographic and clinical characteristics of the MCI+SCC (MCI with SCC)and MCI-SCC (MCI without SCC) groups were comparable, but the MCI+SCC group had significantly worse neuropsychological scores than the MCI-SCC group, particularly in tests assessing attention, language, visual memory, and fronto-executive function domains. While SCC are commonly reported by PSP patients, patients with PSP and MCI+SCC had worse cognitive function than those who did not report SCC. These findings suggest that SCC in PSP patients with MCI could be a worsening sign of cognitive function. Therefore, it is crucial for physicians to assess SCC in PSP patients and to provide timely diagnosis and management of cognitive decline.

Detection of Cognitive Impairment From eSAGE Metadata Using Machine Learning.

Using the metadata collected in the digital version of the Self-Administered Gerocognitive Examination (eSAGE), we aim to improve the prediction of mild cognitive impairment (MCI) and dementia (DM) by applying machine learning methods. A total of 66 patients had a diagnosis of normal cognition (NC), MCI, or DM, and eSAGE scores and metadata were used. eSAGE scores and metadata were obtained. Each eSAGE question was scored and behavioral features (metadata) such as the time spent on each test page, drawing speed, and average stroke length were extracted for each patient. Logistic regression (LR) and gradient boosting models were trained using these features to detect cognitive impairment (CI). Performance was evaluated using 10-fold cross-validation, with accuracy, precision, recall, F1 score, and receiver operating characteristic area under the curve (AUC) score as evaluation metrics. LR with feature selection achieved an AUC of 89.51%, a recall of 87.56%, and an F1 of 85.07% using both behavioral and scoring. LR using scores and metadata also achieved an AUC of 84.00% in detecting MCI from NC, and an AUC of 98.12% in detecting DM from NC. Average stroke length was particularly useful for prediction and when combined with 4 other scoring features, LR achieved an even better AUC of 92.06% in detecting CI. The study shows that eSAGE scores and metadata are predictive of CI. eSAGE scores and metadata are predictive of CI. With machine learning methods, the metadata could be combined with scores to enable more accurate detection of CI.

White matter hyperintensities in cholinergic pathways correlates of cognitive impairment in moyamoya disease.

To investigate the effect of cholinergic pathways damage caused by white matter hyperintensities (WMHs) on cognitive function in moyamoya disease (MMD). We included 62 patients with MMD from a prospectively enrolled cohort. We evaluated the burden of cholinergic pathways damage caused by WMHs using the Cholinergic Pathways Hyperintensities Scale (CHIPS). Cognitive function was evaluated with the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Cognitive impairment was determined according to the cut-off of MMSE and education. Multivariate linear and logistic regression models were used to analyze whether CHIPS was independently associated with cognition. Receiver operating characteristic curve analysis was performed to identify the ability of CHIPS in discriminating cognitive impairment and normal cognition. CHIPS was associated with both MMSE and MoCA (β = - 0.601 and β = - 0.672, both p < 0.001). After correcting age, sex, education, volumes of limbic areas, and other factors, CHIPS remained to be independently associated with both MMSE and MoCA (β = - 0.388 and β = - 0.334, both p < 0.001). In the logistic regression, only CHIPS was associated with cognitive impairment (odds ratio = 1.431, 95% confidence interval = 1.103 to 1.856, p = 0.007). The optimal cut-off of CHIPS score was 10, yielding a sensitivity of 87.5% and a specificity of 78.3% in identifying MMD patients with cognitive impairment. The damage of cholinergic pathways caused by WMHs plays an independent effect on cognition and CHIPS could be a useful method in identifying MMD patients likely to be cognitive impairment. This study shows that Cholinergic Pathways Hyperintensities Scale (CHIPS) could be a simple and reliable method in identifying cognitive impairment for patients with moyamoya disease. CHIPS could be helpful in clinical practice, such as guiding treatment decisions and predicting outcome. • Cholinergic Pathways Hyperintensities Scale was significantly associated with cognitive screening tests in patients with moyamoya disease. • Cholinergic Pathways Hyperintensities Scale plays an independent effect on cognitive impairment in patients with moyamoya disease. • Cholinergic Pathways Hyperintensities Scale shows higher accuracy than education, volumes of limbic areas, and sex in identifying cognitive impairment in moyamoya disease.