White matter microstructural integrity as a key to effective propagation of gamma entrainment in humans.

Gamma entrainment through sensory stimulation has the potential to reduce the pathology of Alzheimer's disease in mouse models. However, clinical trials in Alzheimer's disease (AD) patients have yielded inconsistent results, necessitating further investigation. This single-center pre-post intervention study aims to explore the influence of white matter microstructural integrity on gamma rhythm propagation from the visual cortex to AD-affected regions in 31 cognitively normal volunteers aged ≥ 65. Gamma rhythm propagation induced by optimal FLS was measured. Diffusion tensor imaging was employed to assess the integrity of white matter tracts of interest. After excluding 5 participants with a deficit in steady-state visually evoked potentials, 26 participants were included in the final analysis. In the linear regression analyses, gamma entrainment was identified as a significant predictor of gamma propagation (p < 0.001). Furthermore, the study identified white matter microstructural integrity as a significant predictor of gamma propagation by flickering light stimulation (p < 0.05), which was specific to tracts that connect occipital and temporal or frontal regions. These findings indicate that, despite robust entrainment of gamma rhythms in the visual cortex, their propagation to other regions may be impaired if the microstructural integrity of the white matter tracts connecting the visual cortex to other areas is compromised. Consequently, our findings have expanded our understanding of the prerequisites for effective gamma entrainment and suggest that future clinical trials utilizing visual stimulation for gamma entrainment should consider white matter tract microstructural integrity for candidate selection and outcome analysis.

Construction and validation of a brain magnetic resonance imaging template for normal older Koreans.

BACKGROUND: Spatial normalization to a standardized brain template is a crucial step in magnetic resonance imaging (MRI) studies. Brain templates made from sufficient sample size have low brain variability, improving the accuracy of spatial normalization. Using population-specific template improves accuracy of spatial normalization because brain morphology varies according to ethnicity and age. METHODS: We constructed a brain template of normal Korean elderly (KNE200) using MRI scans 100 male and 100 female aged over 60 years old with normal cognition. We compared the deformation after spatial normalization of the KNE200 template to that of the KNE96, constructed from 96 cognitively normal elderly Koreans and to that of the brain template (OCF), constructed from 434 non-demented older Caucasians to examine the effect of sample size and ethnicity on the accuracy of brain template, respectively. We spatially normalized the MRI scans of elderly Koreans and quantified the amount of deformations associated with spatial normalization using the magnitude of displacement and volumetric changes of voxels. RESULTS: The KNE200 yielded significantly less displacement and volumetric change in the parahippocampal gyrus, medial and posterior orbital gyrus, fusiform gyrus, gyrus rectus, cerebellum and vermis than the KNE96. The KNE200 also yielded much less displacement in the cerebellum, vermis, hippocampus, parahippocampal gyrus and thalamus and much less volumetric change in the cerebellum, vermis, hippocampus and parahippocampal gyrus than the OCF. CONCLUSION: KNE200 had the better accuracy than the KNE96 due to the larger sample size and was far accurate than the template constructed from elderly Caucasians in elderly Koreans.

The influence of n-3 polyunsaturated fatty acids on cognitive function in individuals without dementia: a systematic review and dose-response meta-analysis.

BACKGROUND: Omega-3 polyunsaturated fatty acids (n-3 PUFA) have been suggested as a cognitive enhancing agent, though their effect is doubtful. We aimed to examine the effect of n-3 PUFA on the cognitive function of middle-aged or older adults without dementia. METHODS: We reviewed randomized controlled trials of individuals aged 40 years or older. We systematically searched PubMed/MEDLINE, EMBASE, CINAHL, PsycINFO, and Cochrane Library databases. We used the restricted cubic splines model for non-linear dose-response meta-analysis in terms of the standardized mean difference with 95% confidence intervals. RESULTS: The current meta-analysis on 24 studies (n 9660; follow-up 3 to 36 months) found that the beneficial effect on executive function demonstrates an upward trend within the initial 12 months of intervention. This effect is prominently observed with a daily intake surpassing 500 mg of n-3 PUFA and up to 420 mg of eicosapentaenoic acid (EPA). Furthermore, these trends exhibit heightened significance in regions where the levels of blood docosahexaenoic acid (DHA) + EPA are not very low. CONCLUSIONS: Supplementation of n-3 PUFA may confer potential benefits to executive function among the middle-aged and elderly demographic, particularly in individuals whose dietary DHA + EPA level is not substantially diminished.

A Preliminary Study on the Potential Protective Role of the Antioxidative Stress Markers of Cognitive Impairment: Glutathione and Glutathione Reductase.

Objective: : To investigate the relationship between reduced glutathione (GSH), a key molecule of the antioxidant defense system in the blood, and glutathione reductase (GR), which reduces oxidized glutathione (glutathione disulfide [GSSG]) to GSH and maintains the redox balance, with the prevalence of Alzheimer's dementia and cognitive decline. Methods: : In all, 20 participants with Alzheimer's dementia who completed the third follow-up clinical evaluation over 6 years were selected, and 20 participants with normal cognition were selected after age and sex matching. The GSH and GR concentrations were the independent variables. Clinical diagnosis and neurocognitive test scores were the dependent variables indicating cognitive status. Results: : The higher the level of GR, the greater the possibility of having normal cognition than of developing Alzheimer's dementia. Additionally, the higher the level of GR, the higher the neurocognitive test scores. However, this association was not significant for GSH. After 6 years, the conversion rate from normal cognition to cognitive impairment was significantly higher in the lower 50th percentile of the GR group than in the upper 50th percentile. Conclusion: : The higher the GR, the lower the prevalence of Alzheimer's dementia and incidence of cognitive impairment and the higher the cognitive test scores. Therefore, GR is a potential protective biomarker against Alzheimer's dementia and cognitive decline.

What is the impact of one's chronic illness on his or her spouse's future chronic illness: a community-based prospective cohort study.

BACKGROUND: Integrating a joint approach to chronic disease management within the context of a couple has immense potential as a valuable strategy for both prevention and treatment. Although spousal concordance has been reported in specific chronic illnesses, the impact they cumulatively exert on a spouse in a longitudinal setting has not been investigated. We aimed to determine whether one's cumulative illness burden has a longitudinal impact on that of their spouse. METHODS: Data was acquired from a community-based prospective cohort that included Koreans aged 60 years and over, randomly sampled from 13 districts nationwide. Data from the baseline assessment (conducted from November 2010 to October 2012) up to the 8-year follow-up assessment was analyzed from October 2021 to November 2022. At the last assessment, partners of the index participants were invited, and we included 814 couples in the analysis after excluding 51 with incomplete variables. Chronic illness burden of the participants was measured by the Cumulative Illness Rating Scale (CIRS). Multivariable linear regression and causal mediation analysis were used to examine the longitudinal effects of index chronic illness burden at baseline and its change during follow-up on future index and spouse CIRS scores. RESULTS: Index participants were divided based on baseline CIRS scores (CIRS < 6 points, n = 555, mean [SD] age 66.3 [4.79] years, 43% women; CIRS ≥ 6 points, n = 259, mean [SD] age 67.7 [4.76] years, 36% women). The baseline index CIRS scores and change in index CIRS scores during follow-up were associated with the spouse CIRS scores (ß = 0.154 [SE: 0.039], p < 0.001 for baseline index CIRS; ß = 0.126 [SE: 0.041], p = 0.002 for change in index CIRS) at the 8-year follow-up assessment. Subgroup analysis found similar results only in the high CIRS group. The baseline index CIRS scores and change in index CIRS scores during follow-up had both direct and indirect effects on the spouse CIRS scores at the 8-year follow-up assessment. CONCLUSIONS: The severity and course of one's chronic illnesses had a significant effect on their spouse's future chronic illness particularly when it was severe. Management strategies for chronic diseases that are centered on couples may be more effective.

The impact of the COVID-19 pandemic on depression in community-dwelling older adults: a prospective cohort study.

BACKGROUND: There are growing concerns about the impact of the COVID-19 pandemic on the mental health of older adults. We examined the effect of the pandemic on the risk of depression in older adults. METHODS: We analyzed data from the prospective cohort study of Korean older adults, which has been followed every 2 years. Among the 2308 participants who completed both the third and the fourth follow-up assessments, 58.4% completed their fourth follow-up before the outbreak of COVID-19 and the rest completed it during the pandemic. We conducted face-to-face diagnostic interviews using Mini International Neuropsychiatric Interview and used Geriatric Depression Scale. We performed generalized estimating equations and logistic regression analyses. RESULTS: The COVID-19 pandemic was associated with increased depressive symptoms in older adults [b (standard error) = 0.42 (0.20), p = 0.040] and a doubling of the risk for incident depressive disorder even in euthymic older adults without a history of depression (odds ratio = 2.44, 95% confidence interval 1.18-5.02, p = 0.016). Less social activities, which was associated with the risk of depressive disorder before the pandemic, was not associated with the risk of depressive disorder during the pandemic. However, less family gatherings, which was not associated with the risk of depressive disorder before the pandemic, was associated with the doubled risk of depressive disorder during the pandemic. CONCLUSIONS: The COVID-19 pandemic significantly influences the risk of late-life depression in the community. Older adults with a lack of family gatherings may be particularly vulnerable.

Development of a Gait Feature-Based Model for Classifying Cognitive Disorders Using a Single Wearable Inertial Sensor.

BACKGROUND AND OBJECTIVES: Gait changes are potential markers of cognitive disorders (CDs). We developed a model for classifying older adults with CD from those with normal cognition using gait speed and variability captured from a wearable inertial sensor and compared its diagnostic performance for CD with that of the model using the Mini-Mental State Examination (MMSE). METHODS: We enrolled community-dwelling older adults with normal gait from the Korean Longitudinal Study on Cognitive Aging and Dementia and measured their gait features using a wearable inertial sensor placed at the center of body mass while they walked on a 14-m long walkway thrice at comfortable paces. We randomly split our entire dataset into the development (80%) and validation (20%) datasets. We developed a model for classifying CD using logistic regression analysis from the development dataset and validated it in the validation dataset. In both datasets, we compared the diagnostic performance of the model with that using the MMSE. We estimated optimal cutoff score of our model using receiver operator characteristic analysis. RESULTS: In total, 595 participants were enrolled, of which 101 of them experienced CD. Our model included both gait speed and temporal gait variability and exhibited good diagnostic performance for classifying CD from normal cognition in both the development (area under the receiver operator characteristic curve [AUC] = 0.788, 95% CI 0.748-0.823, p < 0.001) and validation datasets (AUC = 0.811, 95% CI 0.729-0.877, p < 0.001). Our model showed comparable diagnostic performance for CD with that of the model using the MMSE in both the development (difference in AUC = 0.026, standard error [SE] = 0.043, z statistic = 0.610, p = 0.542) and validation datasets (difference in AUC = 0.070, SE = 0.073, z statistic = 0.956, p = 0.330). The optimal cutoff score of the gait-based model was >-1.56. DISCUSSION: Our gait-based model using a wearable inertial sensor may be a promising diagnostic marker of CD in older adults. CLASSIFICATION OF EVIDENCE: This study provides Class III evidence that gait analysis can accurately distinguish older adults with CDs from healthy controls.

Parental history of dementia and the risk of dementia: A cross-sectional analysis of a global collaborative study.

BACKGROUND: Parental history of dementia appears to increase the risk of dementia, but there have been inconsistent results. We aimed to investigate whether the association between parental history of dementia and the risk of dementia are different by dementia subtypes and sex of parent and offspring. METHODS: For this cross-sectional study, we harmonized and pooled data for 17,194 older adults from nine population-based cohorts of eight countries. These studies conducted face-to-face diagnostic interviews, physical and neurological examinations, and neuropsychological assessments to diagnose dementia. We investigated the associations of maternal and paternal history of dementia with the risk of dementia and its subtypes in offspring. RESULTS: The mean age of the participants was 72.8 ± 7.9 years and 59.2% were female. Parental history of dementia was associated with higher risk of dementia (odds ratio [OR] = 1.47, 95% confidence interval [CI] = 1.15-1.86) and Alzheimer's disease (AD) (OR = 1.72, 95% CI = 1.31-2.26), but not with the risk of non-AD. This was largely driven by maternal history of dementia, which was associated with the risk of dementia (OR = 1.51, 95% CI = 1.15-1.97) and AD (OR = 1.80, 95% CI = 1.33-2.43) whereas paternal history of dementia was not. These results remained significant when males and females were analyzed separately (OR = 2.14, 95% CI = 1.28-3.55 in males; OR = 1.68, 95% CI = 1.16-2.44 for females). CONCLUSIONS: Maternal history of dementia was associated with the risk of dementia and AD in both males and females. Maternal history of dementia may be a useful marker for identifying individuals at higher risk of AD and stratifying the risk for AD in clinical trials.

Shared Risk Factors for Depressive Disorder Among Older Adult Couples in Korea.

Importance: Although couples may share many risk factors for depressive disorders in their lifetime, whether these factors mediate the shared risk of depressive disorders has rarely been investigated. Objectives: To identify the shared risk factors for depressive disorder in couples and investigate their mediating roles in the shared risk of depressive disorders among older adult couples. Design, Setting, and Participants: This nationwide, multicenter, community-based cohort study assessed 956 older adults from the Korean Longitudinal Study on Cognitive Aging and Dementia (KLOSCAD) and a cohort of their spouses (KLOSCAD-S) between January 1, 2019, to February 28, 2021. Exposures: Depressive disorders of the KLOSCAD participants. Main Outcomes and Measures: The mediating roles of shared factors in couples on the association between one spouse's depressive disorder and the other's risk of depressive disorders was examined using structural equation modeling. Results: A total of 956 KLOSCAD participants (385 women [40.3%] and 571 men [59.7%]; mean [SD] age, 75.1 [5.0] years) and their spouses (571 women [59.7%] and 385 men [40.3%]; mean [SD] age, 73.9 [6.1] years) were included. The depressive disorders of the KLOSCAD participants were associated with an almost 4-fold higher risk of depressive disorders in their spouses in the KLOSCAD-S cohort (odds ratio, 3.89; 95% CI, 2.06-7.19; P < .001). Social-emotional support mediated the association between depressive disorders in the KLOSCAD participants and their spouses' risk of depressive disorders by itself (ß = 0.012; 95% CI, 0.001-0.024; P = .04; mediation proportion [MP] = 6.1%) and through chronic illness burden (ß = 0.003; 95% CI, 0.000-0.006; P = .04; MP = 1.5%). Chronic medical illness burden (ß = 0.025; 95% CI, 0.001-0.050; P = .04; MP = 12.6%) and presence of a cognitive disorder (ß = 0.027; 95% CI, 0.003-0.051; P = .03; MP = 13.6%) mediated the association. Conclusions and Relevance: The risk factors shared by older adult couples may mediate approximately one-third of the spousal risk of depressive disorders. Identification of and intervention in the shared risk factors of depression among older adult couples may reduce the risk of depressive disorders in the spouses of older adults with depression.

Evidence of risky driving in Korean older adults: A longitudinal cohort.

OBJECTIVES: The aim of this study was to determine the differences in the risk factors for dangerous driving between older adults with normal cognition and those with cognitive impairment. DESIGN: The driving risk questionnaire (DRQ) that was applied to a community-dwelling older adult cohort and 2 years of accident/violation records from the National Police Agency were analyzed. We conducted regression analyses with the presence or absence of risky driving based on records (accidents + violations) 2 years before and after evaluation as a dependent variable and dichotomized scores of each risky driving factor as independent variables. RESULTS: According to four identified factors-crash history, safety concern, reduced mileage, and aggressive driving-significant associations were found between risky driving over the past 2 years and crash history and for aggressive driving in the normal cognition group. In the cognitive impairment group, only crash history was significantly associated, although safety concerns showed a trend toward significance. CONCLUSIONS: In this study, it was suggested that the factors of DRQ have a significant association with actual risky driving. Our results are expected to contribute to establishing the evidence for evaluating and predicting risky driving and advising whether to continue driving in clinics.

A Case-Control Clinical Trial on a Deep Learning-Based Classification System for Diagnosis of Amyloid-Positive Alzheimer's Disease.

OBJECTIVE: A deep learning-based classification system (DLCS) which uses structural brain magnetic resonance imaging (MRI) to diagnose Alzheimer's disease (AD) was developed in a previous recent study. Here, we evaluate its performance by conducting a single-center, case-control clinical trial. METHODS: We retrospectively collected T1-weighted brain MRI scans of subjects who had an accompanying measure of amyloid-beta (Aß) positivity based on a 18F-florbetaben positron emission tomography scan. The dataset included 188 Aß-positive patients with mild cognitive impairment or dementia due to AD, and 162 Aß-negative controls with normal cognition. We calculated the sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUC) of the DLCS in the classification of Aß-positive AD patients from Aß-negative controls. RESULTS: The DLCS showed excellent performance, with sensitivity, specificity, positive predictive value, negative predictive value, and AUC of 85.6% (95% confidence interval [CI], 79.8-90.0), 90.1% (95% CI, 84.5-94.2), 91.0% (95% CI, 86.3-94.1), 84.4% (95% CI, 79.2-88.5), and 0.937 (95% CI, 0.911-0.963), respectively. CONCLUSION: The DLCS shows promise in clinical settings where it could be routinely applied to MRI scans regardless of original scan purpose to improve the early detection of AD.

Clinical Data Interchange Standards in Clinical Trials on Alzheimer's Disease.

OBJECTIVE: The Clinical Data Interchange Standards Consortium (CDISC) proposed outcome measures for clinical trials on Alzheimer's disease (AD) in the Therapeutic Area User Guide for AD (TAUG-AD). To investigate how well the clinical trials on AD registered in the ClinicalTrials.gov complied with the recommendations on outcome measures by the CDISC. METHODS: We compared the outcome measures proposed in the TAUG-AD version 2.0.1 with those employed in the protocols of clinical trials on AD registered in ClinicalTrials.gov. RESULTS: We analyzed 101 outcome measures from 305 protocols. The TAUG-AD listed ten scales for outcome measures of clinical trials on AD. The scales for cognition, activities of daily living, behavioral and psychological symptoms of dementia, and global severity listed in TAUG-AD were most frequently employed in the clinical trials on AD. However, TAUG-AD did not include any scale on quality of life. Also, several scales such as Montreal Cognitive Assessment, Alzheimer's Disease Cooperative Study-Activities of Daily Living, and Cohen- Mansfield Agitation Inventory not listed in the TAUG-AD were commonly employed in the clinical trials on AD and changed over time. CONCLUSION: To properly standardize the data from clinical trials on AD, the gap between the TAUG-AD and the measures employed in real-world clinical trials should be filled.

Deep learning-based diagnosis of Alzheimer's disease using brain magnetic resonance images: an empirical study.

The limited accessibility of medical specialists for Alzheimer's disease (AD) can make obtaining an accurate diagnosis in a timely manner challenging and may influence prognosis. We investigated whether VUNO Med-DeepBrain AD (DBAD) using a deep learning algorithm can be employed as a decision support service for the diagnosis of AD. This study included 98 elderly participants aged 60 years or older who visited the Seoul Asan Medical Center and the Korea Veterans Health Service. We administered a standard diagnostic assessment for diagnosing AD. DBAD and three panels of medical experts (ME) diagnosed participants with normal cognition (NC) or AD using T1-weighted magnetic resonance imaging. The accuracy (87.1% for DBAD and 84.3% for ME), sensitivity (93.3% for DBAD and 80.0% for ME), and specificity (85.5% for DBAD and 85.5% for ME) of both DBAD and ME for diagnosing AD were comparable; however, DBAD showed a higher trend in every analysis than ME diagnosis. DBAD may support the clinical decisions of physicians who are not specialized in AD; this may enhance the accessibility of AD diagnosis and treatment.

Development of a gait speed estimation model for healthy older adults using a single inertial measurement unit.

Although gait speed changes are associated with various geriatric conditions, standard gait analysis systems, such as laboratory-based motion capture systems or instrumented walkways, are too expensive, spatially limited, and difficult to access. A wearable inertia sensor is cheap and easy to access; however, its accuracy in estimating gait speed is limited. In this study, we developed a model for accurately estimating the gait speed of healthy older adults using the data captured by an inertia sensor placed at their center of body mass (CoM). We enrolled 759 healthy older adults from two population-based cohort studies and asked them to walk on a 14 m long walkway thrice at comfortable paces with an inertia sensor attached to their CoM. In the middle of the walkway, we placed GAITRite™ to obtain the gold standard of gait speed. We then divided the participants into three subgroups using the normalized step length and developed a linear regression model for estimating the gold standard gait speed using age, foot length, and the features obtained from an inertia sensor, including cadence, vertical height displacement, yaw angle, and role angle of CoM. Our model exhibited excellent accuracy in estimating the gold standard gait speed (mean absolute error = 3.74%; root mean square error = 5.30 cm/s; intraclass correlation coefficient = 0.954). Our model may contribute to the early detection and monitoring of gait disorders and other geriatric conditions by making gait assessment easier, cheaper, and more ambulatory while remaining as accurate as other standard gait analysis systems.

Optimal flickering light stimulation for entraining gamma rhythms in older adults.

With aging, optimal parameters of flickering light stimulation (FLS) for gamma entrainment may change in the eyes and brain. We investigated the optimal FLS parameters for gamma entrainment in 35 cognitively normal old adults by comparing event-related synchronization (ERS) and spectral Granger causality (sGC) of entrained gamma rhythms between different luminance intensities, colors, and flickering frequencies of FLSs. ERS entrained by 700 cd/m2 FLS and 32 Hz or 34 Hz FLSs was stronger than that entrained by 400 cd/m2 at Pz (p < 0.01) and 38 Hz or 40 Hz FLSs, respectively, at both Pz (p < 0.05) and Fz (p < 0.01). Parieto-occipital-to-frontotemporal connectivities of gamma rhythm entrained by 700 cd/m2 FLS and 32 Hz or 34 Hz FLSs were also stronger than those entrained by 400 cd/m2 at Pz (p < 0.01) and 38 Hz or 40 Hz FLSs, respectively (p < 0.001). ERS and parieto-occipital-to-frontotemporal connectivities of entrained gamma rhythms did not show significant difference between white and red lights. Adverse effects were comparable between different parameters. In older adults, 700 cd/m2 FLS at 32 Hz or 34 Hz can entrain a strong gamma rhythm in the whole brain with tolerable adverse effects.

Altered resting state brain metabolic connectivity in dementia with Lewy bodies.

Although dementia with Lewy bodies (DLB) have Parkinsonism in common with Parkinson's disease (PD) or PD dementia (PDD), they have different neuropathologies that underlie Parkinsonism. Altered brain functional connectivity that may correspond to neuropathology has been reported in PD while never been studied in DLB. To identify the characteristic brain connectivity of Parkinsonism in DLB, we compared the resting state metabolic connectivity in striato-thalamo-cortical (STC) circuit, nigrostriatal pathway, and cerebello-thalamo-cortical motor (CTC) circuit in 27 patients with drug-naïve DLB and 27 age- and sex-matched normal controls using 18F-fluoro-2-deoxyglucose PET. We derived 118 regions of interest using the Automated Anatomical Labeling templates and the Wake Forest University Pick-Atlas. We applied the sparse inverse covariance estimation method to construct the metabolic connectivity matrix. Patients with DLB, with or without Parkinsonism, showed lower inter-regional connectivity between the areas included in the STC circuit (motor cortex-striatum, midbrain-striatum, striatum-globus pallidus, and globus pallidus-thalamus) than the controls. DLB patients with Parkinsonism showed less reduced inter-regional connectivity between the midbrain and the striatum than those without Parkinsonism, and higher inter-regional connectivity between the areas included in the CTC circuit (motor cortex-pons, pons-cerebellum, and cerebellum-thalamus) than those without Parkinsonism and the controls. The resting state metabolic connectivity in the STC circuit may be reduced in DLB. In DLB with Parkinsonism, the CTC circuit and the nigrostriatal pathway may be activated to mitigate Parkinsonism. This difference in the brain connectivity may be a candidate biomarker for differentiating DLB from PD or PDD.

Association of Low Emotional and Tangible Support With Risk of Dementia Among Adults 60 Years and Older in South Korea.

Importance: The association between social support and dementia risk has been debated. Most previous prospective studies have not differentiated the subtypes of social support. Objective: To examine whether the association between social support and risk of dementia differs by subtype of social support and by sex. Design, Setting, and Participants: This nationwide prospective cohort study included randomly sampled South Korean adults 60 years or older. The study was launched November 1, 2010, with follow-up every 2 years until November 30, 2020. The 5852 participants who completed the assessment for social support and were not diagnosed as having dementia, severe psychiatric disorders including major depressive disorder, or major neurological disorders at the baseline assessment were included in the analysis. Exposures: Geriatric psychiatrists administered the structured diagnostic interviews and physical examinations to every participant based on the Korean version of the Consortium to Establish a Registry for Alzheimer Disease (CERAD-K) Assessment Packet Clinical Assessment Battery. Main Outcomes and Measures: Baseline levels of emotional and tangible support using the Medical Outcomes Survey Social Support Survey. Results: Among the 5852 participants (mean [SD] age, 69.8 [6.6] years; 3315 women [56.6%]; mean [SD] follow-up duration, 5.9 [2.4] years), 237 (4.0%) had incident all-cause dementia and 160 (2.7%) had incident Alzheimer disease (AD) subtype of dementia. Compared with women who reported having emotional support, those with low emotional support had almost a 2-fold higher incidence of all-cause dementia (18.4 [95% CI, 13.6-23.2] vs 10.7 [95% CI, 9.0-12.5] per 1000 person-years) and AD (14.4 [95% CI, 10.2-18.6] vs 7.8 [95% CI, 6.3-9.3] per 1000 person-years). Adjusted Cox proportional hazard analysis revealed that low emotional support was associated with increased risk of all-cause dementia (hazard ratio, 1.61 [95% CI, 1.10-2.36]; P = .02) and AD (hazard ratio, 1.66 [95% CI, 1.07-2.57]; P = .02) only in women. Low tangible support was not associated with a risk of all-cause dementia or AD regardless of sex. Conclusions and Relevance: The findings of this cohort study suggest that older women with low emotional support constitute a population at risk for dementia. The level of emotional support should be included in risk assessments of dementia.

Association Between Retinal Layer Thickness and Cognitive Decline in Older Adults.

Importance: Retinal layer thickness is hypothesized to be related to cognitive function in patients with mild cognitive impairment (MCI) and Alzheimer disease (AD). However, longitudinal cohort studies of the healthy older population are scarce. Objective: To investigate the association between retinal layer thickness and cognitive impairment and future cognitive decline in a community-based population cohort. Design, Setting, and Participants: A total of 430 randomly sampled community-dwelling Korean individuals 60 years or older participated in the baseline assessment (mean [SD], 76.3 [6.6] years) 215 of whom completed a mean (SD) of 5.4 (0.6) years (range, 4.1-6.2 years) of follow-up. Using spectral-domain optical coherence tomography, the study team assessed the thickness of 6 retinal layers in the macular region, the peripapillary retinal nerve fiber layers (RNFLs), and the subfoveal choroid at baseline. Exposures: Age, sex, education, diabetes, hypertension, and apolipoprotein E4 gene status. Main Outcomes and Measures: Retinal layer thickness and cognitive function test scores were analyzed. Results: This study included 430 participants (female, 208 [48.6%]). Baseline macular RNFL thickness was associated with baseline Consortium to Establish a Registry for Alzheimer's Disease (CERAD) score (coefficient [ß] = 0.077; 95% CI, 0.054-0.100; P = .04 for total macular area) and Mini-Mental State Examination (MMSE) score (coefficient [ß] = 0.082; 95% CI, 0.063-0.101; P = .03 for total macular area). A thinner baseline total macular RNFL thickness (lowest quartile, <231 µm) was associated with a larger decline in the CERAD and MMSE scores during the follow-up period (P = .003 and P = .01, respectively). Furthermore, participants with baseline total macular RNFL thickness below the lowest quartile cutoff value presented a greater decline in cognitive scores and a higher prevalence of cognitive impairment and Alzheimer disease than those with RNFL thickness above the lowest quartile cutoff value. Conclusions and Relevance: In this study, macular RNFL thickness could be used as a prognostic biomarker of long-term cognitive decline in adults 60 years or older. However, to confirm these results, further large-scale population-based studies should be performed.

Association between serum free hemoglobin level and cerebral white matter hyperintensity volume in older adults.

The association between serum free hemoglobin (sfHb) level and white matter hyperintensity (WMH) volume is controversial. This study is to examine this association considering nonlinearity, sex dimorphism, and WMH type. We enrolled 704 older adults among the participants of the Korean Longitudinal Study on Cognitive Aging and Dementia and visitors to the Dementia Clinic of Seoul National University Bundang Hospital. We measured sfHb level in the venous blood and WMH volume (VWMH) using fluid-attenuated inversion recovery magnetic resonance images. The association between sfHb level and periventricular VWMH was linear in men (linear regression; ß = - 0.18, p = 0.006) and U-shaped in women (restricted cubic spline; F = 6.82, p < 0.001). sfHb level was not associated with deep VWMH in either sex. These findings were also observed in participants without anemia. To conclude, sfHb level is associated with periventricular VWMH in older adults of both sexes. Maintaining an optimal sfHb level may contribute to the prevention of WMH.

Long-Term Cognitive Decline After Stroke: An Individual Participant Data Meta-Analysis.

BACKGROUND: Poststroke cognitive impairment is common, but the trajectory and magnitude of cognitive decline after stroke is unclear. We examined the course and determinants of cognitive change after stroke using individual participant data from the Stroke and Cognition Consortium. METHODS: Nine longitudinal hospital-based cohorts from 7 countries were included. Neuropsychological test scores and normative data were used to calculate standardized scores for global cognition and 5 cognitive domains. One-step individual participant data meta-analysis was used to examine the rate of change in cognitive function and risk factors for cognitive decline after stroke. Stroke-free controls were included to examine rate differences. Based on the literature and our own data that showed short-term improvement in cognitive function after stroke, key analyses were restricted to the period beginning 1-year poststroke to focus on its long-term effects. RESULTS: A total of 1488 patients (mean age, 66.3 years; SD, 11.1; 98% ischemic stroke) were followed for a median of 2.68 years (25th-75th percentile: 1.21-4.14 years). After an initial period of improvement through up to 1-year poststroke, decline was seen in global cognition and all domains except executive function after adjusting for age, sex, education, vascular risk factors, and stroke characteristics (-0.053 SD/year [95% CI, -0.073 to -0.033]; P<0.001 for global cognition). Recurrent stroke and older age were associated with faster decline. Decline was significantly faster in patients with stroke compared with controls (difference=-0.078 SD/year [95% CI, -0.11 to -0.045]; P<0.001 for global cognition in a subgroup analysis). CONCLUSIONS: Patients with stroke experience cognitive decline that is faster than that of stroke-free controls from 1 to 3 years after onset. An increased rate of decline is associated with older age and recurrent stroke.