skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


This content will become publicly available on December 1, 2025

Title: Association of amyloid and cardiovascular risk with cognition: Findings from KBASE
Abstract BACKGROUNDLimited research has explored the effect of cardiovascular risk and amyloid interplay on cognitive decline in East Asians. METHODSVascular burden was quantified using Framingham's General Cardiovascular Risk Score (FRS) in 526 Korean Brain Aging Study (KBASE) participants. Cognitive differences in groups stratified by FRS and amyloid positivity were assessed at baseline and longitudinally. RESULTSBaseline analyses revealed that amyloid‐negative (Aβ–) cognitively normal (CN) individuals with high FRS had lower cognition compared to Aβ– CN individuals with low FRS (p < 0.0001). Longitudinally, amyloid pathology predominantly drove cognitive decline, while FRS alone had negligible effects on cognition in CN and mild cognitive impairment (MCI) groups. CONCLUSIONOur findings indicate that managing vascular risk may be crucial in preserving cognition in Aβ– individuals early on and before the clinical manifestation of dementia. Within the CN and MCI groups, irrespective of FRS status, amyloid‐positive individuals had worse cognitive performance than Aβ– individuals. HighlightsVascular risk significantly affects cognition in amyloid‐negative older Koreans.Amyloid‐negative CN older adults with high vascular risk had lower baseline cognition.Amyloid pathology drives cognitive decline in CN and MCI, regardless of vascular risk.The study underscores the impact of vascular health on the AD disease spectrum.  more » « less
Award ID(s):
2514834 2145314
PAR ID:
10623938
Author(s) / Creator(s):
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more » ; ; ; ; ; ; ; « less
Corporate Creator(s):
Publisher / Repository:
Alzheimer's & Dementia
Date Published:
Journal Name:
Alzheimer's & Dementia
Volume:
20
Issue:
12
ISSN:
1552-5260
Page Range / eLocation ID:
8527 to 8540
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; ; ; ; ; ; ; et al (, Alzheimer's & Dementia)
    Abstract INTRODUCTIONAlzheimer's disease (AD) initiates years prior to symptoms, underscoring the importance of early detection. While amyloid accumulation starts early, individuals with substantial amyloid burden may remain cognitively normal, implying that amyloid alone is not sufficient for early risk assessment. METHODSGiven the genetic susceptibility of AD, a multi‐factorial pseudotime approach was proposed to integrate amyloid imaging and genotype data for estimating a risk score. Validation involved association with cognitive decline and survival analysis across risk‐stratified groups, focusing on patients with mild cognitive impairment (MCI). RESULTSOur risk score outperformed amyloid composite standardized uptake value ratio in correlation with cognitive scores. MCI subjects with lower pseudotime risk score showed substantial delayed onset of AD and slower cognitive decline. Moreover, pseudotime risk score demonstrated strong capability in risk stratification within traditionally defined subgroups such as early MCI, apolipoprotein E (APOE) ε4+ MCI,APOEε4– MCI, and amyloid+ MCI. DISCUSSIONOur risk score holds great potential to improve the precision of early risk assessment. HighlightsAccurate early risk assessment is critical for the success of clinical trials.A new risk score was built from integrating amyloid imaging and genetic data.Our risk score demonstrated improved capability in early risk stratification. 
    more » « less
  2. ; ; ; ; ; ; ; (, Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring)
    Abstract INTRODUCTIONIdentifying mild cognitive impairment (MCI) patients at risk for dementia could facilitate early interventions. Using electronic health records (EHRs), we developed a model to predict MCI to all‐cause dementia (ACD) conversion at 5 years. METHODSCox proportional hazards model was used to identify predictors of ACD conversion from EHR data in veterans with MCI. Model performance (area under the receiver operating characteristic curve [AUC] and Brier score) was evaluated on a held‐out data subset. RESULTSOf 59,782 MCI patients, 15,420 (25.8%) converted to ACD. The model had good discriminative performance (AUC 0.73 [95% confidence interval (CI) 0.72–0.74]), and calibration (Brier score 0.18 [95% CI 0.17–0.18]). Age, stroke, cerebrovascular disease, myocardial infarction, hypertension, and diabetes were risk factors, while body mass index, alcohol abuse, and sleep apnea were protective factors. DISCUSSIONEHR‐based prediction model had good performance in identifying 5‐year MCI to ACD conversion and has potential to assist triaging of at‐risk patients. HighlightsOf 59,782 veterans with mild cognitive impairment (MCI), 15,420 (25.8%) converted to all‐cause dementia within 5 years.Electronic health record prediction models demonstrated good performance (area under the receiver operating characteristic curve 0.73; Brier 0.18).Age and vascular‐related morbidities were predictors of dementia conversion.Synthetic data was comparable to real data in modeling MCI to dementia conversion. Key PointsAn electronic health record–based model using demographic and co‐morbidity data had good performance in identifying veterans who convert from mild cognitive impairment (MCI) to all‐cause dementia (ACD) within 5 years.Increased age, stroke, cerebrovascular disease, myocardial infarction, hypertension, and diabetes were risk factors for 5‐year conversion from MCI to ACD.High body mass index, alcohol abuse, and sleep apnea were protective factors for 5‐year conversion from MCI to ACD.Models using synthetic data, analogs of real patient data that retain the distribution, density, and covariance between variables of real patient data but are not attributable to any specific patient, performed just as well as models using real patient data. This could have significant implications in facilitating widely distributed computing of health‐care data with minimized patient privacy concern that could accelerate scientific discoveries. 
    more » « less
  3. ; ; ; ; ; ; ; ; ; ; et al (, Frontiers in Aging Neuroscience)
    IntroductionThis study investigated the role of proactive semantic interference (frPSI) in predicting the progression of amnestic Mild Cognitive Impairment (aMCI) to dementia, taking into account various cognitive and biological factors. MethodsThe research involved 89 older adults with aMCI who underwent baseline assessments, including amyloid PET and MRI scans, and were followed longitudinally over a period ranging from 12 to 55 months (average 26.05 months). ResultsThe findings revealed that more than 30% of the participants diagnosed with aMCI progressed to dementia during the observation period. Using Cox Proportional Hazards modeling and adjusting for demographic factors, global cognitive function, hippocampal volume, and amyloid positivity, two distinct aspects of frPSI were identified as significant predictors of a faster decline to dementia. These aspects were fewer correct responses on a frPSI trial and a higher number of semantic intrusion errors on the same trial, with 29.5% and 31.6 % increases in the likelihood of more rapid progression to dementia, respectively. DiscussionThese findings after adjustment for demographic and biological markers of Alzheimer’s Disease, suggest that assessing frPSI may offer valuable insights into the risk of dementia progression in individuals with aMCI. 
    more » « less
  4. ; ; ; ; ; ; ; ; ; ; et al (, Applied Neuropsychology: Adult)
    Objective: The interaction of ethnicity, progression of cognitive impairment, and neuroimaging biomarkers of Alzheimer’s Disease remains unclear. We investigated the stability in cognitive status classification (cognitively normal [CN] and mild cognitive impairment [MCI]) of 209 participants (124 Hispanics/Latinos and 85 European Americans). Methods: Biomarkers (structural MRI and amyloid PET scans) were compared between Hispanic/Latino and European American individuals who presented a change in cognitive diagnosis during the second or third follow-up and those who remained stable over time. Results: There were no significant differences in biomarkers between ethnic groups in any of the diagnostic categories. The frequency of CN and MCI participants who were progressors (progressed to a more severe cognitive diagnosis at follow-up) and non-progressors (either stable through follow-ups or unstable [progressed but later reverted to a diagnosis of CN]) did not significantly differ across ethnic groups. Progressors had greater atrophy in the hippocampus (HP) and entorhinal cortex (ERC) at baseline compared to unstable non-progressors (reverters) for both ethnic groups, and more significant ERC atrophy was observed among progressors of the Hispanic/Latino group. For European Americans diagnosed with MCI, there were 60% more progressors than reverters (reverted from MCI to CN), while among Hispanics/Latinos with MCI, there were 7% more reverters than progressors. Binomial logistic regressions predicting progression, including brain biomarkers, MMSE, and ethnicity, demonstrated that only MMSE was a predictor for CN participants at baseline. However, for MCI participants at baseline, HP atrophy, ERC atrophy, and MMSE predicted progression. 
    more » « less
  5. ; ; ; ; ; ; ; ; ; ; et al (, Frontiers in Neurology)
    BackgroundSemantic intrusion errors (SIEs) are associated with mild cognitive impairment (MCI) due to Alzheimer's disease (AD). It is unknown whether accounting for maximum learning capacity still leads to an increase in SIEs when elevated plasma p-tau217, a biological indicator of underlying AD, is present. MethodsOne hundred fifty-eight older adult participants completed the Loewenstein-Acevedo Scales for Semantic Interference and Learning (LASSI-L), a sensitive cognitive challenge test designed to elicit SIEs. Of these, 108 were clinically diagnosed with amnestic MCI (aMCI). Fifty-eight individuals met or exceeded a plasma p-tau217positivity of >0.55 pg/ml, while 50 individuals scored below this threshold. ResultsAfter adjusting for demographic covariates and maximum learning capacity, the aMCI p-tau217+ group evidenced more SIEs compared to aMCI p-tau217- on the first (list B1;p= 0.035) and second trials of the competing list (list B2;p= 0.006). Biological predictors such asApoEε4 status, higher p-tau217, and older age were predictors of an elevated number of SIEs [list B2:F(3,104) = 10.92;p= 0.001;R= 0.489)]. ConclusionsUnlike previous studies that used amyloid PET or other plasma biomarkers, individuals with aMCI p-tau217+ evidenced more SIEs, even after adjusting for their initial learning capacity, a covariate that has not been studied previously. These findings support that SIEs are more prevalent in the presence of underlying AD pathology and occur independent of learning deficits. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email