Cognitively Normal Participants Research Articles

Comparison between morphometry and radiomics: detecting normal brain aging based on grey matter.

Voxel-based morphometry (VBM), surface-based morphometry (SBM), and radiomics are widely used in the field of neuroimage analysis, while it is still unclear that the performance comparison between traditional morphometry and emerging radiomics methods in diagnosing brain aging. In this study, we aimed to develop a VBM-SBM model and a radiomics model for brain aging based on cognitively normal (CN) individuals and compare their performance to explore both methods' strengths, weaknesses, and relationships. 967 CN participants were included in this study. Subjects were classified into the middle-aged group (n = 302) and the old-aged group (n = 665) according to the age of 66. The data of 360 subjects from the Alzheimer's Disease Neuroimaging Initiative were used for training and internal test of the VBM-SBM and radiomics models, and the data of 607 subjects from the Australian Imaging, Biomarker and Lifestyle, the National Alzheimer's Coordinating Center, and the Parkinson's Progression Markers Initiative databases were used for the external tests. Logistics regression participated in the construction of both models. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were used to evaluate the two model performances. The DeLong test was used to compare the differences in AUCs between models. The Spearman correlation analysis was used to observe the correlations between age, VBM-SBM parameters, and radiomics features. The AUCs of the VBM-SBM model and radiomics model were 0.697 and 0.778 in the training set (p = 0.018), 0.640 and 0.789 in the internal test set (p = 0.007), 0.736 and 0.737 in the AIBL test set (p = 0.972), 0.746 and 0.838 in the NACC test set (p < 0.001), and 0.701 and 0.830 in the PPMI test set (p = 0.036). Weak correlations were observed between VBM-SBM parameters and radiomics features (p < 0.05). The radiomics model achieved better performance than the VBM-SBM model. Radiomics provides a good option for researchers who prioritize performance and generalization, whereas VBM-SBM is more suitable for those who emphasize interpretability and clinical practice.

Greater white matter degeneration and lower structural connectivity in non-amnestic vs. amnestic Alzheimer's disease.

Multimodal evidence indicates Alzheimer's disease (AD) is characterized by early white matter (WM) changes that precede overt cognitive impairment. WM changes have overwhelmingly been investigated in typical, amnestic mild cognitive impairment and AD; fewer studies have addressed WM change in atypical, non-amnestic syndromes. We hypothesized each non-amnestic AD syndrome would exhibit WM differences from amnestic and other non-amnestic syndromes. Participants included 45 cognitively normal (CN) individuals; 41 amnestic AD patients; and 67 patients with non-amnestic AD syndromes including logopenic-variant primary progressive aphasia (lvPPA, n = 32), posterior cortical atrophy (PCA, n = 17), behavioral variant AD (bvAD, n = 10), and corticobasal syndrome (CBS, n = 8). All had T1-weighted MRI and 30-direction diffusion-weighted imaging (DWI). We performed whole-brain deterministic tractography between 148 cortical and subcortical regions; connection strength was quantified by tractwise mean generalized fractional anisotropy. Regression models assessed effects of group and phenotype as well as associations with grey matter volume. Topological analyses assessed differences in persistent homology (numbers of graph components and cycles). Additionally, we tested associations of topological metrics with global cognition, disease duration, and DWI microstructural metrics. Both amnestic and non-amnestic patients exhibited lower WM connection strength than CN participants in corpus callosum, cingulum, and inferior and superior longitudinal fasciculi. Overall, non-amnestic patients had more WM disease than amnestic patients. LvPPA patients had left-lateralized WM degeneration; PCA patients had reductions in connections to bilateral posterior parietal, occipital, and temporal areas. Topological analysis showed the non-amnestic but not the amnestic group had more connected components than controls, indicating persistently lower connectivity. Longer disease duration and cognitive impairment were associated with more connected components and fewer cycles in individuals' brain graphs. We have previously reported syndromic differences in GM degeneration and tau accumulation between AD syndromes; here we find corresponding differences in WM tracts connecting syndrome-specific epicenters. Determining the reasons for selective WM degeneration in non-amnestic AD is a research priority that will require integration of knowledge from neuroimaging, biomarker, autopsy, and functional genetic studies. Furthermore, longitudinal studies to determine the chronology of WM vs. GM degeneration will be key to assessing evidence for WM-mediated tau spread.

Increased extra-neurite conductivity of brain in patients with Alzheimer's disease: A pilot study

The objectives of this study were to investigate how the extra-neurite conductivity (EC) and intra-neurite conductivity (IC) were reflected in Alzheimer's disease (AD) patients compared with old cognitively normal (CN) people and patients with amnestic mild cognitive impairment (MCI) and to evaluate the association between those conductivity values and cognitive decline. To do this, high-frequency conductivity (HFC) at the Larmor frequency was obtained using MRI-based electrical property tomography (MREPT) and was decomposed into EC and IC using information of multi-shell multi-gradient direction diffusion tensor images. This prospective single-center study included 20 patients with mild or moderate AD, 25 patients with amnestic MCI, and 21 old CN participants. After decomposing EC and IC from HFC for all participants, we performed voxel-based and regions-of-interest analyses to compare conductivity between the three participant groups and to evaluate the association with either age or the Mini-Mental State Examination (MMSE) scores. We found increased EC in AD compared to CN and MCI. EC was significantly negatively associated with MMSE scores in the insula, and middle temporal gyrus. EC might be used as an imaging biomarker for helping to monitor cognitive function.

Brain 11β-Hydroxysteroid Dehydrogenase Type 1 Occupancy by Xanamem™ Assessed by PET in Alzheimer's Disease and Cognitively Normal Individuals.

11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) regulates intracellular cortisol and its inhibition by the small molecule inhibitor, Xanamem™, may provide a disease-modifying strategy for Alzheimer's disease (AD). Animal models suggest a range of 30-60% enzyme inhibition may suffice to provide neuroprotection. To determine the regional brain occupancy of 11β-HSD1 by Xanamem™ in cognitively normal participants (CN) and mild cognitive impairment (MCI)/mild AD patients to investigate potential dosing ranges for future efficacy studies. Seventeen MCI/AD and 23 CN were included. Regional brain time-activity curves (TAC), standardized uptake values (SUV40-60) and volume of distribution (VT) from Logan plot with image derived input function from 11C-TARACT positron emission tomography (PET) were used to assess the degree of 11β-HSD1 occupancy by increasing doses of Xanamem™ (5 mg, 10 mg, 20 mg or 30 mg daily for 7 days). All measures showed high 11β-HSD1 occupancy with Xanamem to similar degree in CN and MCI/AD. The dose-response relationship was relatively flat above 5 mg. Respective median (interquartile range [Q1-Q3]) 11β-HSD1 occupancy in the MCI/AD and CN groups after treatment with 10 mg Xanamem were 80% [79-81%] and 75% [71-76%] in the neocortex, 69% [64-70%] and 61% [52-63%] in the medial temporal lobe, 80% [79-80%] and 73% [68-73%] in the basal ganglia, and 71% [67-75%] and 66% [62-68%] in the cerebellum. TAC, SUV40-60, and VT measures indicate Xanamem achieves high target occupancy levels with near saturation at 10 mg daily. These data support exploration of doses of≤10 mg daily in future clinical studies.

Interest in genetic susceptibility testing and disclosure of AD dementia risk in cognitively normal adults: a survey study

BackgroundApolipoprotein-E (APOE) genetic testing for Alzheimer’s disease is becoming more important as clinical trials are increasingly targeting individuals carrying APOE-ε4 alleles. Little is known about the interest in finding out one’s genetic risk for Alzheimer’s disease in the general population. Our objective was to examine this in a sample of cognitively normal (CN) adults within a population-based online research registry with the goal to implement APOE-ε4 status for trial recruitment.MethodsAn online survey was completed by 442 CN participants between the age of 49 and 75 years (56% female) from the Dutch Brain Research Registry. The survey assessed interest in participation in research into, and disclosure of, genetic risk for dementia. The survey assessed interest in participation in research into, and disclosure of, genetic risk for dementia and knowing their genetic risk in different hypothetical risk scenarios (10%, 30%, and 50% genetic risk for dementia at age 85, corresponding to APOEε2/ε2 or ε2/ε3, APOEε3/ε4 or ε2ε4, and APOE-ε4/ε4 genotypes). Cochran’s Q and post hoc McNemar tests were used to analyse differences in frequencies across scenarios.ResultsMost participants were interested in participating in research into and disclosure of their genetic risk (81%). The most reported reason was to contribute to scientific research (94%). Interest was higher in males, whilst lower-educated participants were more often undecided. When provided with different risk scenarios, interest in knowing their risk was somewhat higher in the scenarios with higher risk, i.e. in the 50% (79%) compared to the 10% scenario (73%;χ2(2) = 7.98; p = .005). Most individuals expected they would share their genetic risk with close relatives (77–89%), would participate in medication trials (79–88%), and would make long-term arrangements, e.g. retirement, health care, will (69–82%), with larger proportions for scenarios with higher hypothetical genetic risk.ConclusionsOur findings indicate that the vast majority of CN adults participating in a research registry expresses interest in AD genetic risk research and disclosure. Interest in genetic risk disclosure is higher in scenarios corresponding to the APOE-ε4 genotype. This suggests APOE-ε4 screening within an online research registry is potentially a well-received method to accelerate inclusion for trials.

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

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

PLASMA BDNF/IRISIN RATIO ASSOCIATES WITH COGNITIVE FUNCTION IN OLDER ADULTS

Abstract Objectives To examine whether plasma biomarkers brain-derived neurotrophic factor (BDNF), irisin, clusterin and BDNF/irisin ratio (BIR) could differentiate people with mild cognitive impairment (MCI) from cognitively normal (CN) individuals, and to explore their relations with cognitive performance. Methods We included 124 participants with MCI and 126 CN participants from a community-based aged and cognitive health cohort. Plasma BDNF, irisin and clusterin were measured, and BIR was calculated. Global cognition was evaluated with Montreal Cognitive Assessment. T-tests, logistic regressions, and linear regressions were used to explore the relations between plasma biomarkers and cognitive function. Results The plasma levels of irisin, but not BDNF, was significantly different between MCI and CN groups. Higher irisin concentration was associated with increased probability for MCI (OR: 1.06, p = 0.004) after adjusting for covariates. By contrast, BDNF, but not irisin, was linearly correlated with cognitive performance (β = 0.14, p = 0.033). BIR values were positively correlated with cognitive performance (β= 0.14, p = 0.036), and significant differences on BIR values existed between MCI and CN groups. The MCI risk decreased by 53% (OR=0.47, p = 0.043) with each unit increase in BIR values after adjusting for covariates. Plasma BDNF and irisin concentrations increased with aging, whereas BIR values remained stable across the ages. No significant results of clusterin were observed in the above analyses. Conclusion Plasma BIR is a potentially reliable indicator which not only reflects the odds of the presence of MCI but also directly associates with cognitive performance in the aged population.

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

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

Unpuzzling the relationship between hypertension, stroke, and Alzheimer’s disease – an observation from the Australian Imaging Biomarkers and Lifestyle Study

AbstractBackgroundAlzheimer’s disease (AD), hypertension and stroke are common diseases in elderly people, but whether they are intrinsically linked with each other remains uncertain. The aim of this study was to investigate the risks of people who have hypertension and stroke to develop mild cognitive impairment (MCI) and AD, and if hypertension and stroke are risk factors for AD.MethodThe longitudinal data was retrieved from the Australian Imaging Biomarkers and Lifestyle Study (AIBL). The prevalence of hypertension and stroke was compared between cognitively normal (CN) participants, participants who were CN but subsequently diagnosed with MCI/AD during the study (refer to as participants exhibited cognitive decline), and participants with AD confirmed at recruitment.ResultThe prevalence of hypertension (odds ratio [OR] = 1.37, 95% confidence interval [CI] = 1.05 ‐ 1.77, p = 0.018) was significantly higher in participants exhibited cognitive decline than CN participants. Interestingly, the prevalence of hypertension (OR = 0.88, 95% CI = 0.70 ‐ 1.11, p = 0.287) was comparable between CN and AD participants. This observation suggested that hypertension is a risk factor for the progression of cognitive decline. The prevalence of stroke was significantly higher in participants exhibited cognitive decline (OR = 2.04, 95% CI = 1.10 ‐ 3.79, p = 0.024) and AD participants (OR = 3.43, 95% CI = 2.09 – 5.64, p&lt;0.001) than CN participants. This observation suggested that stroke is a risk factor for the progression of cognitive decline and AD.ConclusionThis preliminary study demonstrated that hypertension and stroke are risk factors for the progression of cognitive decline, and stroke is a risk factor for AD. Given the elevated risk in cognitive decline, the cognitive function of elderly people with hypertension or history of stroke should be monitored for timely detection of MCI and AD.

BrainChart cortical thickness centile scores: a generalizable tool to detect age‐inappropriate cortical neurodegeneration in Alzheimer’s disease

AbstractBackgroundIdentifying age‐inappropriate cortical neurodegeneration on structural MRI is a key component of Alzheimer’s disease (AD) assessment. However, widely available reference standards that enable objective interpretation are lacking. BrainChart (www.BrainChart.io; https://github.com/BrainChart/Lifespan) calculates age and sex adjusted centile scores for structural MRI metrics using normative data from 101,457 participants across the lifecourse and can be applied across different datasets. We applied this approach to regional cortical thickness estimates and explored its utility in identifying patients with AD associated neurodegeneration.MethodsCross‐sectional BrainChart cortical thickness centile scores were calculated for 241 individuals with pathologically confirmed AD (median scan time prior to death 5.8 years), as well as 1432 cognitively normal participants (CN) from the NACC dataset. Area under the receiver operating characteristic curve (AUC) analyses were performed to identify the cortical regions that best identified patients with pathologically confirmed AD. This approach was then applied to 305 participants from the ADNI‐3 cohort, all of whom underwent clinical amyloid (florbetapir) PET and tau (flortaucipir) PET within 6 months of structural MRI (CN = 185; Mild Cognitive Impairment (MCI) = 95); AD = 26).ResultsThe top ten performing regions for differentiating pathologically confirmed AD from CN in the NACC dataset were entorhinal, middle temporal, inferior parietal, isthmus cingulate, fusiform, supramarginal, inferior temporal, superior temporal, precuneus and temporal pole. AUCs ranged from 0.72 – 0.77 (figure 1 and table 1). Combining these ten regions into a single model significantly improved diagnostic separability (AUC = 0.81, figure 1). Optimal cut‐points for individual regions ranged from the 25th centile to the 35th centile, with sensitivities ranging from 57.7% to 68.9%, and specificities ranging from 72.6% to 80.9%. Using progressively lower centile scores increased specificity but decreased sensitivity (table 1).In ADNI‐3 participants, a combined model of the same ten regions derived from the NACC dataset was able to discriminate amyloid and tau pet positive AD patients from amyloid and tau negative CN (AUC = 0.98), as well as amyloid and tau positive MCI patients from amyloid and tau negative CN (AUC = 0.85) (figure 2).ConclusionBrainChart age and sex adjusted cortical thickness centile scores, derived from an extensive normative dataset, represent a generalizable method for objectively identifying cortical neurodegeneration in AD.

BrainChart cortical thickness centile scores: a generalizable tool to detect age‐inappropriate cortical neurodegeneration in Alzheimer’s disease

AbstractBackgroundIdentifying age‐inappropriate cortical neurodegeneration on structural MRI is a key component of Alzheimer’s disease (AD) assessment. However, widely available reference standards that enable objective interpretation are lacking. BrainChart (www.BrainChart.io; https://github.com/BrainChart/Lifespan) calculates age and sex adjusted centile scores for structural MRI metrics using normative data from 101,457 participants across the lifecourse and can be applied across different datasets. We applied this approach to regional cortical thickness estimates and explored its utility in identifying patients with AD associated neurodegeneration.MethodCross‐sectional BrainChart cortical thickness centile scores were calculated for 241 individuals with pathologically confirmed AD (median scan time prior to death 5.8 years), as well as 1432 cognitively normal participants (CN) from the NACC dataset. Area under the receiver operating characteristic curve (AUC) analyses were performed to identify the cortical regions that best identified patients with pathologically confirmed AD. This approach was then applied to 305 participants from the ADNI‐3 cohort, all of whom underwent clinical amyloid (florbetapir) PET and tau (flortaucipir) PET within 6 months of structural MRI (CN = 185; Mild Cognitive Impairment (MCI) = 95); AD = 26).ResultThe top ten performing regions for differentiating pathologically confirmed AD from CN in the NACC dataset were entorhinal, middle temporal, inferior parietal, isthmus cingulate, fusiform, supramarginal, inferior temporal, superior temporal, precuneus and temporal pole. AUCs ranged from 0.72 – 0.77 (figure 1 and table 1). Combining these ten regions into a single model significantly improved diagnostic separability (AUC = 0.81, figure 1). Optimal cut‐points for individual regions ranged from the 25th centile to the 35th centile, with sensitivities ranging from 57.7% to 68.9%, and specificities ranging from 72.6% to 80.9%. Using progressively lower centile scores increased specificity but decreased sensitivity (table 1). In ADNI‐3 participants, a combined model of the same ten regions derived from the NACC dataset was able to discriminate amyloid and tau pet positive AD patients from amyloid and tau negative CN (AUC = 0.98), as well as amyloid and tau positive MCI patients from amyloid and tau negative CN (AUC = 0.85) (figure 2).ConclusionBrainChart age and sex adjusted cortical thickness centile scores, derived from an extensive normative dataset, represent a generalizable method for objectively identifying cortical neurodegeneration in AD.

Machine learning composite of remote cognitive tests for screening of preclinical AD cohorts

AbstractBackgroundComputerized cognitive tests are critical in the screening of preclinical Alzheimer’s Disease (AD) given their ability to be conducted remotely at low cost. Here, we explore whether machine‐learning derived composites of remote cognitive tests can improve sensitivity when detecting brain amyloid (Aβ) accumulation in cognitively normal (CN) cohorts than traditional pen‐and‐paper alternatives.MethodBased on the CogState Brief Battery tests in CN individuals from the A4 dataset (n = 4230, Aβ‐ = 3094), we construct a data‐driven composite, denoted the Remote Empirical Cognitive composite for Alzheimer’s Disease (RECAD), designed to be sensitive to Aβ‐PET positivity. Specifically, the composite uses a random feature elimination logistic regression to identify a subset of predictive tests. We construct and evaluate the model using 10 repeat, 5‐fold cross‐validation in the A4 baseline data. We conduct temporal validation with the A4 second visit and external validation using CN participants from the ADNI (n = 389, Aβ‐ = 143), comparing against the pen‐and‐paper‐based PACC composite and previous computerized composites CBB and C3.ResultRECAD includes three accuracy scores (Identification, One‐Back and One‐card) and one reaction time (Detection). In cross‐validation in the A4 baseline, RECAD show a significantly higher ability to discriminate Aβ status [mean Cohen’s d = 0.26] than PACC [mean d = 0.25, t‐test p&lt;0.001] and computerized composites CBB [median d = 0.13, p&lt;0.001] and C3 [mean d = 0.18, p&lt;0.001]. RECAD significantly improves beyond C3 in the A4 second visit (z‐test p&lt;0.001). Moreover, these trends are replicated in the ADNI at baseline (RECAD d = 0.215, PACC d = 0.061) and 24 months (RECAD d = 0.295, PACC d = ‐0.026) but the small sample and effect size limits our ability to demonstrate statistical significance.ConclusionRECAD, as a machine‐learning derived composite of remotely conducted cognitive tests, shows a comparable or better sensitivity to the established pen‐and‐paper composite test when screening for Aβ+ among CN cohorts. While effect sizes are small, conducting such remote tests repeatedly may be a useful pre‐screening for downstream biofluid evaluation.

CSF synapse marker changes in predementia Alzheimer´s Disease: AMPA receptor modulators NPTX2 and NPTXR mediate cognition within A/T/N stages

AbstractBackgroundSynapse pathology has been linked to excitotoxicity and glutamate receptor dysregulation (such as AMPAR) in Alzheimer´s Disease (AD) progression. Of the core cerebrospinal fluid (CSF) AD biomarkers for amyloid, tau pathology and neurodegeneration (A/T/N), T/N status is proposed to reflect levels of neuronal plasticity, but fluid biomarkers for precision interventions in subgroups with increased excitotoxicity are lacking. Herein, we assess group differences of 19 CSF synapse markers including the AMPAR‐modulating NPTX, in both cognitively normal (CN) and Mild Cognitive Impairment (MCI) with either A+/T‐/N‐ and A+/T or N+ (A+/T/N+) as compared to CN A‐/T‐/N‐ and assess relationships with verbal memory recall and hippocampal volume.MethodsA/T/N was determined using the CSF Aβ42/40 ratio, p‐tau181 and total‐tau in predementia AD cases (n = 194) and CN participants with normal AD biomarkers (n = 145) in the Dementia Disease Initiation cohort. CSF synapse marker concentrations were determined using mass‐spectrometry (table 1) and ELISA for GAP‐43. Adjusted for age and sex, we compared marker concentrations between CN cases (A+/T‐/N‐ n = 20; A+/T/N+ n = 40) and MCI cases (A+/T‐/N‐ n = 25;A+/T/N+ n = 109) with CN A‐/T‐/N‐ (n = 145) as the reference group. Associations to verbal memory recall and brain imaging were performed in the total sample and respective A/T/N groups adjusted for covariates. Results p&lt;.01 were considered significant.ResultsTop markers based on between‐group results are reported (Table 1 &amp; figure 1‐2 for all markers). Compared to CN A‐/T‐/N‐, 14‐3‐3 ζ/δ concentrations were higher in all A+/T/N+ groups (p&lt;.001), but unaltered in A+/T‐/N‐ groups. In A+/T‐/N‐, NPTX2 concentrations were lower in MCI (p&lt;.001) but not in CN. In A+/T/N+, NPTX2 was higher in CN (p&lt;.001) but not in MCI. 14‐3‐3 ζ/δ was associated with worse memory in the total sample (p&lt;.001) but not in the A+ groups. Lower NPTX2 was associated with worse memory in the total sample (p&lt;.001) and in both A+ groups (p&lt;.01; p&lt;001). Neither 14‐3‐3 ζ/δ nor NPTX2 were significantly associated with hippocampal volume (figure 2).ConclusionOverall, increased 14‐3‐3 ζ/δ was most closely associated with worse memory recall. Lower NPTX2 was linked to poorer cognitive status within A+ groups, suggesting links to AMPAR dysregulation and excitotoxicity.

Effects of apolipoprotein E2 and E4 on brain microstructure in cognitively intact and mildly impaired older adults: Modification by sex and age

AbstractBackgroundAPOE4 is the strongest single genetic risk factor for sporadic Alzheimer’s disease (AD), whereas APOE2 confers protection against AD. However, effects of APOE on neurodegeneration in cognitively intact individuals, and how these associations differ from those presenting with mild cognitive impairments, are unclear. Furthermore, few studies have evaluated whether effects of APOE on early neurodegenerative changes are modified by other AD risk factors including age and sex.MethodSubjects included older adult participants (77±7 years; 57% women) of the Rancho Bernardo Study of Health Aging and the University of California San Diego Alzheimer’s Disease Research Center, including 192 cognitively normal (CN) individuals and 33 with mild cognitive impairment (CI). Participants completed a multi‐shell diffusion MRI scan and restriction spectrum imaging (RSI) metrics were computed in white matter, gray matter, and subcortical regions of interest. Participants were classified as APOE4‐carriers (33%), APOE2‐carriers (10%), and APOE3 homozygotes (57%). Linear regressions, adjusting for age, sex, and scanner, were conducted among CN to assess associations between APOE and RSI measures, as well as interactions of APOE with sex, and with linear or squared age. Regressions across all subjects examined interactions between APOE4 and cognitive status.ResultAmong CN participants, entorhinal cortex neurite density was lower for APOE4‐carriers than non‐carriers, whereas entorhinal restricted isotropic diffusion decreased with age among APOE4 non‐carriers but not among carriers. Entorhinal cortex hindered diffusion was lower for APOE2‐carriers than non‐carriers among women only. Age more strongly correlated with white matter and subcortical microstructure among APOE2 non‐carriers than among APOE2 carriers. Across the full sample, associations between cognitive status and microstructure were modified by APOE4, with greater differences between CN and CI for APOE4‐carriers in medial temporal regions, but stronger differences for APOE4 non‐carriers in the striatum.ConclusionThe entorhinal cortex may be an early target of neurodegenerative changes associated with APOE4 preceding cognitive decline, whereas APOE2 may protect against entorhinal microstructural injury, particularly among women. APOE modifies patterns of microstructural abnormalities associated with aging and cognitive impairment, which may support the development of biomarkers differentially indicative of cytoarchitectural changes occurring with normal brain aging, APOE‐dependent pathways, and non‐AD etiologies.

Performance of complex daily tasks and cerebrospinal fluid biomarkers of Alzheimer disease

AbstractBackgroundThe preclinical stage of Alzheimer disease (AD) is a clinically silent period that is detectable through neuroimaging and biofluid biomarkers of amyloid, tau, and neurodegeneration. We evaluated whether performance on cognitively‐focused complex daily tasks is associated with cerebrospinal fluid (CSF) biomarkers of brain amyloidosis or tau pathology in cognitively normal (CN) older adults.MethodIn this cross‐sectional analysis of an ongoing longitudinal cohort study, CN older adults performed three cognitively‐focused complex tasks of daily living (shopping, checkbook balancing, and medication management) from the Performance Assessment of Self‐Care Skills (PASS) in their home. PASS tasks were scored for independence (cues required to complete task) and adequacy of performance (quality and process, efficiency, redundant actions). Participants also had a CSF sample obtained within two years of completing the PASS. CSF amyloid (Aβ42, Aβ40) and CSF tau phosphorylated at position 181 (p‐tau181) were measured with Lumipulse immunoassays. Nonparametric partial correlations were used to examine the associations between task performance and biomarkers of AD (CSF Aβ42/Aβ40 and CSF p‐tau181), controlling for age, gender, and level of education.Result122 CN participants (mean age 74.4 years, 53% female, 88% white) were included. After controlling for age, gender, and years of education, worse performance on complex daily tasks was associated with lower CSF Aβ42/Aβ40 (more cues required: Spearman rho = ‐0.213, p = 0.03), and there was a trend towards lower adequacy (rho = 0.161, p = 0.08). There were no significant associations with CSF p‐tau181.ConclusionThis study suggests that worse performance on complex daily tasks in CN older adults may be associated with greater amyloid burden. These findings could lead to a better understanding of functional changes that may be associated with amyloidosis prior to the onset of noticeable memory symptoms in AD or related dementias.

Mapping High‐Frequency Conductivity Using MRI in the Brains of Alzheimer’s Disease Patients

AbstractBackgroundPrevious studies reported increased concentrations of metallic ions and imbalanced Na+ and K+ ions in patients with Alzheimer’s disease (AD) and the increased mobility of protons by microstructural disruptions in AD. The purposes of this study were: 1)to apply a high‐frequency conductivity (HFC) mapping technique using a clinical 3T MRI system and 2)to compare HFC values among participant groups.MethodThis prospective study included 74 participants (23 AD patients, 27 amnestic mild cognitive impairment (MCI) patients, and 24 cognitively normal (CN) elderly people) to explore the clinical application of HFC mapping in the brain. For the brain MREPT images, a multi‐echo turbo spin‐echo pulse sequence was used. A homemade software was used to map the HFC at the Larmor frequency of 128 MHz at 3T. We performed statistical analyses to 1) compare HFC maps between the three participant groups and 2) to evaluate the association of HFC maps with Mini‐Mental State Examination (MMSE) scores.ResultThe HFC value was higher in the AD group than in the CN and MCI groups. MMSE scores were negatively associated with HFC values, but age was positively associated with HFC values. The HFC value in the insula has a high area under the ROC curve (AUC) value to differentiate AD patients from the CN participants (Sensitivity (SE) = 82, Specificity (SP) = 97, AUC = 0.902, p &lt; 0.0001), better than GMV in hippocampus (SE = 79, SP = 83, AUC = 0.880, p &lt; 0.0001).ConclusionHFC values were significantly increased in the AD group compared to the CN group and increased with age and disease severity. HFC values of the insula along with the GMV of the hippocampus can be used as an imaging biomarker to improve the differentiation of AD from CN.

The utility of neuropsychological process scores in verbal recall and verbal fluency in persons with or at risk for dementia: Data from COMPASS‐ND

AbstractBackgroundSubjective cognitive decline (SCD) is considered a risk state for decline to mild cognitive impairment (MCI) or dementia due to Alzheimer’s disease (AD). By definition, individuals with SCD report concerns about changes in cognitive function but perform within normal limits on formal testing. This study examined whether neuropsychology process scores on tests of auditory learning and memory (the Rey Auditory Verbal Learning Test, RAVLT) and semantic and phonemic oral fluency were able to distinguish subtle difficulties in cognition, over and above total scores.MethodWe used data from the Comprehensive Assessment of Neurodegeneration and Dementia (COMPASS‐ND) study to examine performance in 60 cognitively normal (CN) older adults with no cognitive complaints (mean age = 69 years; mean education = 16 years), 55 participants with SCD (age = 70; education = 17), 102 with MCI (age = 72; education = 16), and 47 with AD (age = 75; education = 15). Participants were matched on age and education, except for AD participants who were older. Age and education were co‐variates in all analyses. For the RAVLT, we examined delayed recall total scores, and process measures of primacy and recency recall on the second learning trial. For fluency, we examined total scores, and process measures of clustering, switching, word frequency, and age of acquisition.ResultRAVLT: An item position by group interaction revealed that primacy scores better distinguished all participant groups (CU&gt;SCD&gt;MCI&gt;AD) than delayed recall (CU = SCD = MCI&gt;AD). The left subiculum hippocampal subfield volume was positively associated with primacy scores in the MCI group, controlling for intracranial volume and age. Oral fluency: Both phonemic and semantic total scores discriminated CN, MCI, and AD participants in a stepwise manner; there was a non‐significant trend for SCD participants to perform more poorly than CN. Process scores did not provide additional discrimination.ConclusionThese findings indicate that primacy scores for episodic recall are sensitive to subtle memory deficits in SCD and may reflect hippocampal atrophy, supporting the clinical use of using serial position effects in the assessment of MCI and SCD.Learning Objective(s): Participants will learn about more detailed scoring methods for common neuropsychological tests, their sensitivity to subtle cognitive deficits in SCD, and their relationship with neuroanatomical structures.

High expression of Alzheimer’s disease‐related metabolic brain pattern is predictive of conversion to mild cognitive impairment or dementia and faster cognitive decline

AbstractBackgroundAlzheimer’s disease‐related pattern (ADRP) is a metabolic brain biomarker of Alzheimer’s disease (AD), which was previously identified and validated. Its utility for differential diagnosis is known. Here, we aimed to explore its predictive value for conversion from cognitively normal (CN) to mild cognitive impairment (MCI), from MCI to dementia and for the rate of cognitive decline.MethodsWe analysed 609 participants followed for up to 15 years and their FDG PET scans from ADNI database (CN = 133, MCI = 352, dementia due to AD = 124) and 56 participants from University Medical centre Ljubljana (MCI = 22, AD = 34). ADRP expression was calculated from pre‐processed FDG PET scans. CN and MCI participants were stratified according to their conversion status and cerebrospinal fluid biomarkers. Amyloid positivity (A+) was defined as Aβ42 &lt; 880 pg/mL and tau positivity (T+) as pTau &gt; 21.8 pg/mL. AD patients were stratified into slow (&lt; 2 points/per year decline on mini mental state examination (MMSE)) and fast (&gt; 2 points/per year decline on MMSE) progressors.ResultsA+T+ cCN had higher baseline ADRP expression than A–T– (p&lt;0.001), A+T– (p = 0.003) and A+T+ (p = 0.01) stable CN corrected for age, while the groups did not differ in gender, education or baseline MMSE scores. A+T+ cMCI had higher baseline ADRP expression than A–T– (p&lt;0.001), A+T– (p = 0.001) and A+T+ (p&lt;0.001) stable MCI, corrected for baseline age and MMSE. A+T– stable MCI had higher baseline ADRP expression than A–T– stable MCI (p = 0.02). ADRP was a predictor of conversion to dementia in survival analysis (HR = 4.5[2.4‐8.7]). Similarly, in the UMCL dataset A+T+ cMCI had higher baseline ADRP expression than A–T– stable MCI (p = 0.03). Fast progressing AD patients had higher baseline ADRP expression than slowly progressing AD patients (p&lt;0.001). Similarly, in the UMCL dataset fast progressing AD patients had higher baseline ADRP expression than slowly progressing AD patients (p = 0.02). In neither dataset, AD groups differed in age, sex or baseline MMSE scores.ConclusionADRP expression levels can be used to predict conversion from CN to MCI and from MCI to dementia in A+T+ individuals. AD patients with high ADRP expression are at an elevated risk for faster progression of cognitive decline.

Impact of White Matter Hyperintensities on domain‐specific cognition in Southeast Asians

AbstractBackgroundDementia affects 55 million people worldwide, with 60% of the burden in Asia. White Matter Hyperintensities (WMH) is a key marker of small vessel disease, with high prevalence in Asian populations with prodromal and clinical dementia. WMH is described as: Deep White Matter Hyperintensities (DWMH), Periventricular Hyperintensities (PVH) or Fazekas‐Total (DWMH and PVH).However, association between WMH topography and performance in specific cognitive domains remains unexplored. Thus, this study aims to characterise the impact of Fazekas‐Total, DWMH and PVH on different cognitive domains.Method304 participants (mean age 60.6, mean education years 14.2, mean Montreal Cognitive Assessment 25.99, 43.8% males) from Biomarkers and Cognition Study, Singapore (Dementia Research Centre (Singapore)) met the inclusion criteria.Eight domains of cognition were tested: global cognition, learning and memory, language, executive function, complex‐attention, perceptual‐motor, social‐cognition, and processing speed.Normality tests, correlation analysis and stepwise regression (with Benjamini and Hochberg False Discovery Rate correction) were performed to understand association between Fazekas‐Total, DWMH, PVH on domains of cognition tested, accounting for age, education, and gender.Two approaches were used for data analysis: (1) by grouping participants as Mild Cognitive Impairment (MCI), Subjective Cognitive Decline (SCD) and Cognitively Normal (CN) as per the National Institute on Aging‐Alzheimer’s Association (NIA‐AA) criteria and (2) by grouping participants’ WMH as confluent (DWMH ≥2 and PVH ≥3) and non‐confluent.ResultHigher Fazekas‐Total was associated with slower processing speed (p = 0.0255, R = ‐0.039) in prodromal participants (MCI and SCD). Higher PVH was associated with slower processing speed in MCI (p = 0.017, R = ‐0.32) and CN (p = 0.017, R = ‐0.663) participants. Higher PVH was significantly associated with poorer learning and memory (p = 0.045, R = ‐0.043) in SCD participants. Higher DWMH was significantly associated with poorer learning and memory (p = 0.017, R = ‐0.765) in CN participants.ConclusionThese results demonstrate differential association between PVH, DWMH and cognitive domains, thus the location of WMH determines the affected cognitive domains. Therefore, it is worthwhile to assess PVH and DWMH in clinical cognitive outcomes separately and to understand the upstream pathobiology of DWMH and PVH.Furthermore, higher Fazekas‐Total was strongly associated with slower processing speed in prodromal participants and could be a marker of cognitive decline.

High expression of Alzheimer’s disease‐related metabolic brain pattern is predictive of conversion to mild cognitive impairment or dementia and faster cognitive decline

AbstractBackgroundAlzheimer’s disease‐related pattern (ADRP) is a metabolic brain biomarker of Alzheimer’s disease (AD), which was previously identified and validated. Its utility for differential diagnosis is known. Here, we aimed to explore its predictive value for conversion from cognitively normal (CN) to mild cognitive impairment (MCI), from MCI to dementia and for the rate of cognitive decline.MethodWe analysed 609 participants followed for up to 15 years and their FDG PET scans from ADNI database (CN = 133, MCI = 352, dementia due to AD = 124) and 56 participants from University Medical centre Ljubljana (MCI = 22, AD = 34). ADRP expression was calculated from pre‐processed FDG PET scans. CN and MCI participants were stratified according to their conversion status and cerebrospinal fluid biomarkers. Amyloid positivity (A+) was defined as Aß42 &lt; 880 pg/mL and tau positivity (T+) as pTau &gt; 21.8 pg/mL. AD patients were stratified into slow (&lt; 2 points/per year decline on mini mental state examination (MMSE)) and fast (&gt; 2 points/per year decline on MMSE) progressors.ResultA+T+ cCN had higher baseline ADRP expression than A–T– (p&lt;0.001), A+T– (p = 0.003) and A+T+ (p = 0.01) stable CN corrected for age, while the groups did not differ in gender, education or baseline MMSE scores. A+T+ cMCI had higher baseline ADRP expression than A–T– (p&lt;0.001), A+T– (p = 0.001) and A+T+ (p&lt;0.001) stable MCI, corrected for baseline age and MMSE. A+T– stable MCI had higher baseline ADRP expression than A–T– stable MCI (p = 0.02). ADRP was a predictor of conversion to dementia in survival analysis (HR = 4.5[2.4‐8.7]). Similarly, in the UMCL dataset A+T+ cMCI had higher baseline ADRP expression than A–T– stable MCI (p = 0.03). Fast progressing AD patients had higher baseline ADRP expression than slowly progressing AD patients (p&lt;0.001). Similarly, in the UMCL dataset fast progressing AD patients had higher baseline ADRP expression than slowly progressing AD patients (p = 0.02). In neither dataset, AD groups differed in age, sex or baseline MMSE scores.ConclusionADRP expression levels can be used to predict conversion from CN to MCI and from MCI to dementia in A+T+ individuals. AD patients with high ADRP expression are at an elevated risk for faster progression of cognitive decline.