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BackgroundParticipant eligibility for the A4 Study was determined by amyloid PET imaging. Given the disadvantages of amyloid PET imaging in accessibility and cost, blood-based biomarkers may serve as a sufficient biomarker and more cost-effective screening tool for patient enrollment into preclinical AD trials.ObjectiveTo determine if a blood-based screening test can adequately identify amyloid burden in participants screened into a preclinical AD trial.MethodsIn this cross-sectional study, 224 participants from the A4 Study received an amyloid PET scan (18Florbetapir) within 90 days of blood sample collection. Blood samples from all study participants were processed within 2 h after phlebotomy. Plasma amyloid measures were quantified by Shimazdu and C2 N Diagnostics using mass spectrometry-based platforms. A corresponding subset of blood samples (n = 100) was processed within 24 h after phlebotomy and analyzed by C2 N.ResultsPlasma Aβ42/Aβ40 demonstrated the highest association for Aβ accumulation in the brain with an AUC 0.76 (95%CI = 0.69, 0.82) at C2 N and 0.80 (95%CI = 0.75, 0.86) at Shimadzu. Blood samples processed to plasma within 2 h after phlebotomy provided a better prediction of amyloid PET status than blood samples processed within 24 h (AUC 0.80 versus 0.64; p

Aim: 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. Methods: 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. Results: 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. Conclusions: 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. [ABSTRACT FROM AUTHOR]

Introduction: We examined the relationship between previous fluctuations in Mini-Mental State Examination (MMSE) scores, future changes in MMSE scores, and attrition from follow-up surveys, which helps in a more comprehensive interpretation of repeatedly collected MMSE scores. Methods: This 4-year longitudinal study included 2,073 community-dwelling older adults aged ≥65 years in Japan. The MMSE was administered at baseline (T0), 2 years (T1), and 4 years (T2) follow-up. We performed multinomial logistic regression analysis with the dependent variable, indicating the change in MMSE score from T1 to T2 (categorized as increase, no change [reference category], and decrease) and attrition at T2. The independent variables included the change in MMSE scores from T0 to T1 and MMSE scores at T0 and T1. Results: The mean MMSE score was 29 across the three time points. A one-point decrease in MMSE score from T0 to T1 was associated with 79% (95% confidence interval: 1.62, 1.97) higher odds of an increase in MMSE score from T1 to T2 and 28% (1.17, 1.40) higher odds of attrition at T2. A one-point decrement in the MMSE score at T0 and T1 was also associated with an increase in the MMSE score from T1 to T2 and attrition at T2. Conclusion: Focusing on cognitive fluctuation for 2 years, rather than cognitive function at a point in time, would have no remarkable advantage when focusing on future cognitive function and attrition. Our results emphasize the need for further studies to identify factors that distinguish between those who continue to attend follow-up surveys and show improvements in cognitive test scores and those who drop out. [ABSTRACT FROM AUTHOR]

Background: With increasingly aging societies, a comprehensive strategy for dementia research is important. The Organized Registration for the Assessment of dementia by the Nationwide General consortium toward Effective treatment (ORANGE) Registry is the first longitudinal multicenter prospective trial-ready cohort in Japan.Objective: To establish a large cohort for use in clinical trials and research in Japan.Methods: This registry, based on communities, hospitals, and nursing homes, covers three dementia stages (preclinical, mild cognitive impairment [MCI], and advanced dementia), and includes more than 30 hospitals. We analyzed enrollment and 1-year follow-up data for disease progression.Results: There were 1450 registered patients (649 men, 801 women; mean age, 77.92±6.70 years; mean Mini-Mental State Examination [MMSE] score, 25.19±2.76). The conversion rates from MCI to dementia and MCI to normal were 14.3% and 1.1%, respectively. High Clinical Dementia Rating score (odds ratio [OR] = 11.085, 95% confidence interval [CI]:1.619-75.913, p = 0.014), low MMSE score (OR = 0.835, 95% CI: 0.761-0.917, p < 0.001), high Geriatric Depression Scale score (OR = 1.093, 95% CI: 1.005-1.189, p = 0.038), and low body mass index (OR = 0.895, 95% CI: 0.829-0.967, p = 0.005) at enrollment were significant factors for conversion.Conclusion: The ORANGE MCI Registry is an established registry that facilitates creation of trial-ready cohorts to accelerate promotion of clinical trials with low reversion rates as it originates from a hospital. One-year follow-up analysis suggested assessing various factors for conversion risk. Further analyses will be possible in future with registry expansion. We will continue to refine this registry, including how it can be used more efficiently. [ABSTRACT FROM AUTHOR]

The article discusses the importance of early identification of prefrailty and frailty in older adults within the community, emphasizing collaboration among healthcare professionals for proactive frailty interventions. It introduces the Prefrailty scale for Appearance Observation by Nurses (PAON) as a simple yet effective tool for identifying prefrailty through clinical observations by nurses, highlighting its potential to improve early detection and intervention strategies for frailty.

Background: Previous studies have demonstrated associations between gut microbiota, microbial metabolites, and cognitive decline. However, relationships between these factors and lipopolysaccharides (LPS; molecules of the outer membrane of gram-negative bacteria) remain controversial.Objective: To evaluate associations between plasma LPS, gut microbiota, and cognitive function.Methods: We performed a cross-sectional sub-analysis of data of 127 participants (women: 58%, mean age: 76 years) from our prospective cohort study regarding the relationship between gut microbiota and cognitive function. We enrolled patients who visited our memory clinic and assessed demographics, dementia-related risk factors, cognitive function, brain imaging, gut microbiomes, and microbial metabolites. We evaluated relationships between cognitive decline and plasma LPS using multivariable logistic regression analyses.Results: Plasma LPS concentration increased with increasing degree of cognitive decline and total cerebral small vessel disease (SVD) score (Kruskal-Wallis test; p = 0.016 and 0.007, respectively). Participants with high plasma LPS concentrations tended to have lower concentrations of gut microbial metabolites, such as lactic acid and acetic acid, and were less likely to consume fish and shellfish (44.7% versus 69.6%, p = 0.027) than those with low plasma LPS concentrations. Multivariable analyses revealed that plasma LPS concentration was independently associated with the presence of mild cognitive impairment in participants without dementia (odds ratio: 2.09, 95% confidence interval: 1.14-3.84, p = 0.007).Conclusion: In this preliminary study, plasma LPS concentration was associated with both cognitive decline and cerebral SVD and significantly correlated with beneficial gut microbial metabolites. Plasma LPS may be a risk factor for cognitive decline. [ABSTRACT FROM AUTHOR]

Background: Previous studies have demonstrated associations between gut microbiota, microbial metabolites, and cognitive decline. However, relationships between these factors and neurofilament light chain (NfL; a disease-nonspecific biomarker of neural damage) remain controversial.Objective: To evaluate the associations between plasma NfL, gut microbiota, and cognitive function.Methods: We performed a cross-sectional sub-analysis of data from our prospective cohort study that was designed to investigate the relationship between gut microbiota and cognitive function. Patients who visited our memory clinic were enrolled and demographics, dementia-related risk factors, cognitive function, brain imaging, gut microbiomes, and microbial metabolites were assessed. We evaluated the relationships between the gut microbiome, microbial metabolites, and plasma NfL. Moreover, the relationships between plasma NfL and cognitive function were assessed using multivariable logistic regression analyses.Results: We analyzed 128 participants (women: 59%, mean age: 74 years). Participants with high (above the median) plasma NfL concentrations tended to be older, women, and hypertensive and have a history of stroke, chronic kidney disease, and dementia. Plasma NfL was also associated with cerebral small vessel disease. However, plasma NfL levels were not significantly correlated with gut microbial metabolites. Multivariable analyses revealed that a higher plasma NfL concentration was independently associated with the presence of dementia (odds ratio: 9.94, 95% confidence interval: 2.75-48.2, p < 0.001).Conclusion: High plasma NfL concentration was independently associated with the presence of dementia as previously reported. However, plasma NfL levels were not significantly correlated with gut microbial metabolites in this preliminary study. [ABSTRACT FROM AUTHOR]

Aim: Community settings often need simple screening, rather than detailed tests, to identify cognitive impairment. This study aimed to develop models to screen older adults with cognitive impairment. Methods: This study used data from the Integrated Research Initiative for Living Well with Dementia Cohort Study and included 5830 older adults. Individuals were considered cognitively impaired if their Mini‐Mental State Examination score was less than 24. Three screening models were developed: the simple model (age, sex, and education), the base model comprising 13 candidate variables available in the questionnaire, and the enhanced model, where grip strength and gait speed were added to the base model. We performed binary logistic regression analysis with stepwise backward elimination (P < 0.1 for retention in the model) to develop each model. Then, we calculated integer scores from coefficients to develop score‐based models. The area under the receiver operating characteristic curve (AUC) was used to evaluate discrimination. Results: Participants with cognitive impairment accounted for 4.0% (n = 233) of the total. The score‐based simple model comprised three variables (AUC = 0.72, sensitivity: 72%, specificity: 61%). The score‐based base model included nine variables (AUC = 0.76, sensitivity: 70%, specificity: 67%). The score‐based enhanced model comprised eight variables, including grip strength and gait speed (AUC = 0.79, sensitivity: 73%, specificity: 70%). Conclusions: This study developed three screening models with acceptable discriminant validity for cognitive impairment. These models comprised simple questionnaire‐based items and common physical performance measurements. These models could enable screening of older adults suspected of cognitive impairment without the need to conduct cognitive tests in community settings. Geriatr Gerontol Int 2022; 22: 292–297. [ABSTRACT FROM AUTHOR]

The article explores the need for cognitive assessments in Community General Support Centers (CGSCs) among older adults and the rarity of standardized cognitive evaluation. Topics include cognitive assessment needs, methods used, and identified barriers, emphasizing the applicability of a screening model for dementia. .

The article discusses behavioral and psychological symptoms of dementia (BPSD), a short-form version of the Japanese version of the Dementia, Behavior Disturbance Scale (DBD13) to assess the effect of some long-term care insurance services. Topics discussed include mild cognitive disorder or dementia according to the ICD-10 Classification of Mental and Behavioral Disorders; internal consistency of the DBD5; and rehabilitation in residential facilities and daycare services.

Background: Living alone has been associated with cognitive impairment; however, findings have been inconsistent. Social isolation among older adults who live alone may contribute to cognitive impairment. This study was carried out to examine the association of social isolation and living alone with cognitive impairment in community-dwelling older adults., Methods: In this cross-sectional study, data from the Integrated Research Initiative for Living Well with Dementia Cohort Study, which comprises pooled data from five community-based geriatric cohorts, was used. Social isolation was defined as infrequent interactions with others. Participants were categorized into four groups based on their social isolation and living alone statuses. Cognitive function was assessed using the Mini-Mental State Examination, with a score <24 indicating cognitive impairment. The association between social isolation combined with living alone and cognitive impairment was analyzed using logistic regression., Results: Of the 4362 participants included in the analysis (mean age 75.6 years, 44.3 % male), 11 % had cognitive impairment. Regardless of living alone, social isolation was associated with cognitive impairment (no social isolation x not living alone: reference, social isolation x not living alone; odds ratio (OR): 1.74, 95 % confidence interval (CI): 1.29-2.33, social isolation x living alone; OR: 2.10, 95 % CI: 1.46-3.01)., Conclusions: Social isolation is associated with cognitive impairment; however, living alone is not intrinsically associated with cognitive impairment in older adults. Healthcare providers must focus on social interactions to prevent cognitive impairment in older adults rather than simply focusing on living arrangements., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Objective: To develop a combined index using cognitive function and instrumental activities of daily living (IADL) to discriminate between Clinical Dementia Rating (CDR) scores of 0.5 and 1 in the clinical setting, and to investigate its optimal cutoff values and internal and external validities., Methods: We included outpatients aged 65-89 years with CDR scores of 0.5 or 1. The optimal cutoff values and internal validity were verified using Japanese memory clinic-based datasets between September 2010 and October 2021 [National Center for Geriatrics and Gerontology (NCGG) datasets]. Cognitive function and IADL were assessed using the Mini-Mental State Examination (MMSE) and Lawton Index (LI), respectively. The optimal cutoff values were defined using the Youden Index. To verify internal validity, sensitivity and specificity were calculated using stratified 5-fold cross-validation. To verify external validity, sensitivity and specificity of the optimal cutoff values were assessed in the Organized Registration for the Assessment of dementia on Nationwide General consortium toward Effective treatment (ORANGE) Registry dataset between July 2015 and March 2022, which has multicenter clinical data., Results: A total of 800 (mean age, 77.53 years; men, 50.1%) and 1494 (mean age, 77.97 years; men, 43.3%) participants comprised the NCGG and ORANGE Registry datasets, respectively. The optimum cutoff values for men and women were determined as MMSE < 25 and LI < 5 and MMSE < 25 and LI < 8, respectively; such a combined index showed good discriminative performance in internal (sensitivity/specificity: men, 92.50/73.52; women, 88.57/65.65) and external validities (men, 81.43/77.62; women, 77.64/74.67)., Conclusion: The index developed is useful in discriminating between CDR scores of 0.5 and 1 and should be applicable to various settings, such as memory clinics and clinical research., (© Copyright 2024 Physicians Postgraduate Press, Inc.)

Importance: Blood-based tests for brain amyloid-β (Aβ) pathology are needed for widespread implementation of Alzheimer disease (AD) biomarkers in clinical care and to facilitate patient screening and monitoring of treatment responses in clinical trials., Objective: To compare the performance of plasma Aβ42/40 measured using 8 different Aβ assays when detecting abnormal brain Aβ status in patients with early AD., Design, Setting, and Participants: This study included 182 cognitively unimpaired participants and 104 patients with mild cognitive impairment from the BioFINDER cohort who were enrolled at 3 different hospitals in Sweden and underwent Aβ positron emission tomography (PET) imaging and cerebrospinal fluid (CSF) and plasma collection from 2010 to 2014. Plasma Aβ42/40 was measured using an immunoprecipitation-coupled mass spectrometry developed at Washington University (IP-MS-WashU), antibody-free liquid chromatography MS developed by Araclon (LC-MS-Arc), and immunoassays from Roche Diagnostics (IA-Elc); Euroimmun (IA-EI); and Amsterdam University Medical Center, ADx Neurosciences, and Quanterix (IA-N4PE). Plasma Aβ42/40 was also measured using an IP-MS-based method from Shimadzu in 200 participants (IP-MS-Shim) and an IP-MS-based method from the University of Gothenburg (IP-MS-UGOT) and another immunoassay from Quanterix (IA-Quan) among 227 participants. For validation, 122 participants (51 cognitively normal, 51 with mild cognitive impairment, and 20 with AD dementia) were included from the Alzheimer Disease Neuroimaging Initiative who underwent Aβ-PET and plasma Aβ assessments using IP-MS-WashU, IP-MS-Shim, IP-MS-UGOT, IA-Elc, IA-N4PE, and IA-Quan assays., Main Outcomes and Measures: Discriminative accuracy of plasma Aβ42/40 quantified using 8 different assays for abnormal CSF Aβ42/40 and Aβ-PET status., Results: A total of 408 participants were included in this study. In the BioFINDER cohort, the mean (SD) age was 71.6 (5.6) years and 49.3% of the cohort were women. When identifying participants with abnormal CSF Aβ42/40 in the whole cohort, plasma IP-MS-WashU Aβ42/40 showed significantly higher accuracy (area under the receiver operating characteristic curve [AUC], 0.86; 95% CI, 0.81-0.90) than LC-MS-Arc Aβ42/40, IA-Elc Aβ42/40, IA-EI Aβ42/40, and IA-N4PE Aβ42/40 (AUC range, 0.69-0.78; P < .05). Plasma IP-MS-WashU Aβ42/40 performed significantly better than IP-MS-UGOT Aβ42/40 and IA-Quan Aβ42/40 (AUC, 0.84 vs 0.68 and 0.64, respectively; P < .001), while there was no difference in the AUCs between IP-MS-WashU Aβ42/40 and IP-MS-Shim Aβ42/40 (0.87 vs 0.83; P = .16) in the 2 subcohorts where these biomarkers were available. The results were similar when using Aβ-PET as outcome. Plasma IPMS-WashU Aβ42/40 and IPMS-Shim Aβ42/40 showed highest coefficients for correlations with CSF Aβ42/40 (r range, 0.56-0.65). The BioFINDER results were replicated in the Alzheimer Disease Neuroimaging Initiative cohort (mean [SD] age, 72.4 [5.4] years; 43.4% women), where the IP-MS-WashU assay performed significantly better than the IP-MS-UGOT, IA-Elc, IA-N4PE, and IA-Quan assays but not the IP-MS-Shim assay., Conclusions and Relevance: The results from 2 independent cohorts indicate that certain MS-based methods performed better than most of the immunoassays for plasma Aβ42/40 when detecting brain Aβ pathology.