A Combined Index Using the Mini-Mental State Examination and Lawton Index to Discriminate Between Clinical Dementia Rating Scores of 0.5 and 1: A Development and Validation Study.

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.

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

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.

Subjective Cognitive Decline and Frailty Trajectories and Influencing Factors in Japanese Community-Dwelling Older Adults: A Longitudinal Study.

We studied frailty and subjective cognitive decline (SCD) trajectories in older Japanese adults and evaluated the influence of various factors on these trajectories. We analyzed data from 1157 non-demented adults aged 70 and above from 2013 to 2019. Frailty was assessed using the self-administered Kihon Checklist (KCL), a Japanese frailty index. SCD was evaluated using the questionnaire of the Subjective Memory Complaints scale. Through group-based joint trajectory models, we discerned three frailty trajectories: non-progressive (n = 775), moderate progressive (n = 312), and rapid progressive (n = 70); and three SCD trajectories: non-progressive (n = 302), moderate progressive (n = 625), and rapid progressive (n = 230). Individuals in the rapid progressive SCD trajectory had a 32.2% probability of also being in the rapid progressive frailty trajectory. In contrast, those in the non-progressive SCD trajectory had zero probability of being in the rapid progressive frailty trajectory. Both the rapid progressive frailty and SCD groups combined had a higher incidence of depressive symptoms and slow gait speed. Our results have found that frailty and SCD share a similar trajectory in Japanese older adults. Additionally, rapid progressive frailty and SCD were associated with the highest risk of depressive symptoms and slow gait speed. Thus, interventions targeting both frailty and cognitive decline should prioritize mental health enhancement and gait speed improvement.

Fluctuations in Cognitive Test Scores and Loss to Follow-Up in Community-Dwelling Older Adults: The IRIDE Cohort Study.

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.

Association of functional and cognitive impairment severity with discharge to long-term care facilities in older patients admitted to a general acute care hospital from home.

BACKGROUND: The early recognition of hospitalized patients at risk of being discharged to long-term care facilities (LTCFs) may help to identify those who require transitional care programs and interventions that support discharge to home. We examined the association of functional and cognitive impairment severity with discharge to LTCFs among older hospitalized patients. METHODS: In this retrospective cohort study, we used an administrative claims database linked with geriatric assessment data from a general acute care hospital in Japan. We analyzed patients aged ≥65 years discharged between July 2016 and December 2018. The severity of functional and cognitive impairments was assessed using the Dementia Assessment Sheet for Community-based Integrated Care System 8-items (DASC-8) scale. Based on their DASC-8 scores, patients were designated as Category I (no impairment), Category Ⅱ (mild impairment), or Category III (moderate/severe impairment). We conducted logistic regression analyses to examine the association between the severity of impairments and discharge to LTCFs after adjusting for patient-level factors. RESULTS: We analyzed 9,060 patients (mean age: 79.4 years). Among the 112 patients (1.2%) discharged to LTCFs, 62.3%, 18.6%, and 19.2% fell under Category I, Category Ⅱ, and Category III, respectively. Category II was not significantly associated with discharge to LTCFs. However, Category III had a significantly higher odds of discharge to LTCFs than Category I (Adjusted odds ratio: 2.812, 95% confidence interval: 1.452-5.449). CONCLUSION: Patients identified as Category III by the DASC-8 on admission may benefit from enhanced transitional care and interventions that promote discharge to home.

All-Cause Readmission or Potentially Avoidable Readmission: Which Is More Predictable Using Frailty, Comorbidities, and ADL?

Background and Objectives: Readmission-related health care reforms have shifted their focus from all-cause readmissions (ACR) to potentially avoidable readmissions (PAR). However, little is known about the utility of analytic tools from administrative data in predicting PAR. This study determined whether 30-day ACR or 30-day PAR is more predictable using tools that assess frailty, comorbidities, and activities of daily living (ADL) from administrative data. Research Design and Methods: This retrospective cohort study was conducted at a large general acute care hospital in Tokyo, Japan. We analyzed patients aged ≥70 years who had been admitted to and discharged from the subject hospital between July 2016 and February 2021. Using administrative data, we assessed each patient's Hospital Frailty Risk Score, Charlson Comorbidity Index, and Barthel Index on admission. To determine the influence of each tool on readmission predictions, we constructed logistic regression models with different combinations of independent variables for predicting unplanned ACR and PAR within 30 days of discharge. Results: Among 16 313 study patients, 4.1% experienced 30-day ACR and 1.8% experienced 30-day PAR. The full model (including sex, age, annual household income, frailty, comorbidities, and ADL as independent variables) for 30-day PAR showed better discrimination (C-statistic: 0.79, 95% confidence interval: 0.77-0.82) than the full model for 30-day ACR (0.73, 0.71-0.75). The other prediction models for 30-day PAR also had consistently better discrimination than their corresponding models for 30-day ACR. Discussion and Implications: PAR is more predictable than ACR when using tools that assess frailty, comorbidities, and ADL from administrative data. Our PAR prediction model may contribute to the accurate identification of at-risk patients in clinical settings who would benefit from transitional care interventions.

Age- and sex-specific associations between sarcopenia severity and poor cognitive function among community-dwelling older adults in Japan: The IRIDE Cohort Study.

Introduction: This study examined whether the association between sarcopenia severity and cognitive function differed according to sex and age in community-dwelling older adults in Japan. Methods: This is a cross-sectional study of older adults (age ≥ 65 years) consisting of five regional cohorts integrated as the Integrated Research Initiative for Living Well with Dementia (IRIDE) Cohort Study. Sarcopenia severity was determined based on the Asian Working Group for Sarcopenia 2019, which assessed grip strength, walking speed, and skeletal muscle mass index. Poor cognitive function was defined as a Mini-Mental State Examination score of ≤ 23. Odds ratios (ORs) and 95% confidence intervals (CIs) for poor cognitive function were calculated by sex and age group (65-74 and ≥75 years) using binomial logistic regression models, which were adjusted for age, educational attainment, history of non-communicable diseases, smoking and drinking habits, living alone, frequency of going outdoors, exercise habits, and depressive symptom. Results: Of the 8,180 participants, 6,426 (1,157 men aged 65-74 and 1,063 men aged 75 or older; 2,281 women aged 65-74 and 1,925 women aged 75 or older) were analyzed. The prevalence ratio of sarcopenia and severe sarcopenia were 309 (13.9%) and 92 (4.1%) among men and 559 (13.3%) and 166 (3.7%) among women, respectively. A total of 127 (5.8%) men and 161 (3.9%) women had a poor cognitive function. Setting non-sarcopenia as a reference, the adjusted ORs (95% CI) of poor cognitive function were 2.20 (1.54, 3.15) for sarcopenia and 3.56 (2.20, 5.71) for severe sarcopenia. A similar trend was observed in analyses stratified by sex and age, with linear associations (P for trend <0.05) in both categories. Furthermore, there was a significant interaction (P < 0.05) between sex and sarcopenia severity, indicating a stronger linear association of sarcopenia severity with poor cognitive function in women compared with men. Discussion and conclusion: Sarcopenia severity was linearly associated with poor cognitive function in adults aged ≥ 65 years, with a stronger association in women compared with men.

Evaluation of Blood-Based Plasma Biomarkers as Potential Markers of Amyloid Burden in Preclinical Alzheimer's Disease.

BACKGROUND: Participant 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. OBJECTIVE: To determine if a blood-based screening test can adequately identify amyloid burden in participants screened into a preclinical AD trial. METHODS: In 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. RESULTS: Plasma Aß42/Aß40 demonstrated the highest association for Aß 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 < 0.001). Age, sex, and APOE ɛ4 carrier status did not the diagnostic performance of plasma Aß42/Aß40 to predict amyloid PET positivity in A4 Study participants. CONCLUSION: Plasma Aß42/Aß40 may serve as a potential biomarker for predicting elevated amyloid in the brain. Utilizing blood testing over PET imaging may improve screening efficiency into clinical trials.

Organized Registration for the Assessment of Dementia by the Nationwide General Consortium Toward Effective Treatment (ORANGE) Registry: Current Status and Perspectives of Mild Cognitive Impairment.

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.

Older adults with a higher frailty index tend to have electrolyte imbalances.

OBJECTIVES: Frailty is a state of increased vulnerability to poor resolution of homeostasis after a stressor. We hypothesized that frail older adults would tend to have electrolyte imbalances because they should have many stressors together with fragile physiological systems. In this study, we aimed to determine whether older adults with higher Frailty Index scores have electrolyte imbalances and to establish which domains of the Frailty Index are correlated with electrolyte imbalances. DESIGN: A cross-sectional study. SETTING AND PARTICIPANTS: A total of 4204 older adults aged 70 years or over who visited the Japanese National Center for Geriatrics and Gerontology. METHODS: We calculated the 50-item Frailty Index with the following domains: comorbidities, cognitive function and mood, basic and instrumental activities of daily living, physical function, nutrition, and fall risks from physical weakness and comorbidities. Participants were categorized into four groups: a non-frail group (Frailty Index ≤0.2), mildly frail group (0.20 < Frailty Index ≤0.3), moderately frail group (0.3 < Frailty Index ≤0.4), and severely frail group (0.4 < Frailty Index). Their serum sodium, potassium, calcium, and phosphorus concentrations were measured. A multiple regression model was used to explore the relationship of electrolyte imbalances with the Frailty Index and to determine which frailty domains are correlated with electrolyte imbalances. RESULTS: Compared with the non-frail group, the mildly and moderately frail groups tended to have hypernatremia and hypophosphatemia, whereas the severely frail group tended to have dysnatremia, hypokalemia, and hypophosphatemia. The estimated odds ratios increased by 15%-52% for each electrolyte imbalance as the Frailty Index increased by 0.1. The Frailty Index domains of cognitive function, activities of daily living, and nutrition were correlated with more than three kinds of electrolyte imbalances, the domains of physical function and fall risks from physical weakness were correlated with three kinds of electrolyte imbalances, and the domains of comorbidities and fall risks from comorbidities were correlated with two kinds of electrolyte imbalances. CONCLUSIONS: Older adults with higher Frailty Index scores tend to have electrolyte imbalances.

Relationship Between Plasma Lipopolysaccharides, Gut Microbiota, and Dementia: A Cross-Sectional Study.

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.

Relationship Between Plasma Neurofilament Light Chain, Gut Microbiota, and Dementia: A Cross-Sectional Study.

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.

Simple screening models for cognitive impairment in community settings: The IRIDE Cohort Study.

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.

Relationship between the Japanese-style diet, gut microbiota, and dementia: A cross-sectional study.

OBJECTIVE: Previous studies have shown associations between the gut microbiota, microbial metabolites, and cognitive decline. However, the effect of the dietary composition on such associations has not been fully investigated. The aims of this study were to evaluate the relationships between adherence to a Japanese-style diet, the gut microbiota, and cognitive decline. Furthermore, we aimed to evaluate the three forms of the Japanese diet index (JDI; the conventional [JDI9], updated [JDI12], and a newly modified JDI) to determine which would show the closest relationships with cognition and the gut microbiota. METHODS: We performed a cross-sectional subanalysis of data from a prospective hospital-based cohort study. We assessed the patients' demographic characteristics, dietary composition, risk factors, cognitive function, brain imaging, gut microbiome, and microbial metabolites. On the basis of previous studies, a nine-component traditional JDI (JDI9), a 12-component modern JDI (JDI12), and a 12-component revised JDI (rJDI12), were defined. We evaluated the relationships between the JDI scores, cognitive function, and the gut microbiome and microbial metabolites using multivariable logistic regression analyses. RESULTS: We analyzed data from 85 eligible participants (61% women; mean age: 74.6 ± 7.4 y). Compared with participants who had dementia, those without dementia were more likely to consume foods in the JDI12, including fish and shellfish (64.5 versus 39.1%, P = 0.048), mushrooms (61.3 versus 30.4%, P = 0.015), soybeans and soybean-derived foods (62.9 versus 30.4%, P = 0.013), and coffee (71 versus 43.5%, P = 0.024). There were non-significant trends toward lower fecal concentrations of gut microbial metabolites in participants with a more traditional Japanese diet. Participants with dementia had lower JDI scores than those without dementia (dementia versus non-dementia, median JDI9 score: 5 versus 7, P = 0.049; JDI12: 7 versus 8, P = 0.017; and rJDI12: 7 versus 9, P = 0.006, respectively). CONCLUSIONS: Adherence to a traditional Japanese diet was found to be inversely associated with cognitive decline and tended to be associated with lower concentrations of gut microbial metabolites.

Head-to-Head Comparison of 8 Plasma Amyloid-ß 42/40 Assays in Alzheimer Disease.

Importance: Blood-based tests for brain amyloid-ß (Aß) 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 Aß42/40 measured using 8 different Aß assays when detecting abnormal brain Aß 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 Aß positron emission tomography (PET) imaging and cerebrospinal fluid (CSF) and plasma collection from 2010 to 2014. Plasma Aß42/40 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 Aß42/40 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 Aß-PET and plasma Aß 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 Aß42/40 quantified using 8 different assays for abnormal CSF Aß42/40 and Aß-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 Aß42/40 in the whole cohort, plasma IP-MS-WashU Aß42/40 showed significantly higher accuracy (area under the receiver operating characteristic curve [AUC], 0.86; 95% CI, 0.81-0.90) than LC-MS-Arc Aß42/40, IA-Elc Aß42/40, IA-EI Aß42/40, and IA-N4PE Aß42/40 (AUC range, 0.69-0.78; P < .05). Plasma IP-MS-WashU Aß42/40 performed significantly better than IP-MS-UGOT Aß42/40 and IA-Quan Aß42/40 (AUC, 0.84 vs 0.68 and 0.64, respectively; P < .001), while there was no difference in the AUCs between IP-MS-WashU Aß42/40 and IP-MS-Shim Aß42/40 (0.87 vs 0.83; P = .16) in the 2 subcohorts where these biomarkers were available. The results were similar when using Aß-PET as outcome. Plasma IPMS-WashU Aß42/40 and IPMS-Shim Aß42/40 showed highest coefficients for correlations with CSF Aß42/40 (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 Aß42/40 when detecting brain Aß pathology.