Synergistic effect of β-amyloid and neurodegeneration on cognitive decline in clinically normal individuals

Distinct Characteristics of Suspected Non-Alzheimer Pathophysiology in Relation to Cognitive Status and Cerebrovascular Burden

PURPOSE OF THE REPORT

This study investigated the prevalence and clinical characteristics of suspected non-Alzheimer disease pathophysiology (SNAP) across varying cognitive statuses and cerebral small vessel disease (CSVD) burden.

PATIENTS AND METHODS

We included 1992 participants with cognitive status categorized as cognitively unimpaired, mild cognitive impairment, or dementia. β-amyloid (Aβ, A) positivity was assessed by Aβ PET, and neurodegeneration (N) positivity was determined through hippocampal volume. Participants were further divided by the presence or absence of severe CSVD. The clinical and imaging characteristics of A-N+ (SNAP) group were compared with those of the A-N- and A+N+ groups.

RESULTS

SNAP participants were older and had more vascular risk factors compared with A-N- and A+N+ in the CSVD(-) cohort. SNAP and A+N+ showed similar cortical thinning. At the dementia stage, SNAP had a cognitive trajectory similar to A+N+ in the CSVD(-) cohort. However, SNAP exhibited less cognitive decline than A+N+ in the CSVD(+) cohort.

CONCLUSIONS

SNAP is characterized by distinct clinical and imaging characteristics; however, it does not necessarily indicate a benign prognosis, particularly at the dementia stage. These findings highlight the need to assess SNAP in relation to the cognitive stage and CSVD presence to better understand its progression and guide interventions.

The effect of Alzheimer's disease genetic factors on limbic white matter microstructure

INTRODUCTION

White matter (WM) microstructure is essential for brain function but deteriorates with age and in neurodegenerative conditions such as Alzheimer's disease (AD). Diffusion MRI, enhanced by advanced bi-tensor models accounting for free water (FW), enables in vivo quantification of WM microstructural differences.

METHODS

To evaluate how AD genetic risk factors affect limbic WM microstructure - crucial for memory and early impacted in disease - we conducted linear regression analyses in a cohort of 2,614 non-Hispanic White aging adults (aged 50.12 to 100.85 years). The study evaluated 36 AD risk variants across 26 genes, the association between AD polygenic scores (PGSs) and WM metrics, and interactions with cognitive status.

RESULTS

AD PGSs, variants in TMEM106B, PTK2B, WNT3, and apolipoprotein E (APOE), and interactions involving MS4A6A were significantly linked to WM microstructure.

DISCUSSION

These findings implicate AD-related genetic factors related to neurodevelopment (WNT3), lipid metabolism (APOE), and inflammation (TMEM106B, PTK2B, MS4A6A) that contribute to alternations in WM microstructure in older adults.

HIGHLIGHTS

AD risk variants in TMEM106B, PTK2B, WNT3, and APOE genes showed distinct associations with limbic FW-corrected WM microstructure metrics. Interaction effects were observed between MS4A6A variants and cognitive status. PGS for AD was associated with higher FW content in the limbic system.

Decreased practice effects in cognitively unimpaired amyloid betapositive individuals: a multicenter, longitudinal, cohort study

INTRODUCTION

We aimed to determine whether cognitively unimpaired (CU) amyloid- beta-positive (Aβ+) individuals display decreased practice effects on serial neuropsychological testing.

METHODS

We included 209 CU participants from three research centers, 157 Aβ- controls and 52 Aβ+ individuals. Participants underwent neuropsychological assessment at baseline and annually during a 2-year follow-up. We used linear mixed-effects models to analyze cognitive change over time between the two groups, including time from baseline, amyloid status, their interaction, age, sex, and years of education as fixed effects and the intercept and time as random effects.

RESULTS

The Aβ+ group showed reduced practice effects in verbal learning (β = -1.14, SE = 0.40, p = 0.0046) and memory function (β = -0.56, SE = 0.19, p = 0.0035), as well as in language tasks (β = -0.59, SE = 0.19, p = 0.0027).

DISCUSSION

Individuals with normal cognition who are in the Alzheimer's continuum show decreased practice effects over annual neuropsychological testing. Our findings could have implications for the design and interpretation of primary prevention trials.

HIGHLIGHTS

This was a multicenter study on practice effects in asymptomatic Aβ+ individuals. We used LME models to analyze cognitive trajectories across multiple domains. Practice-effects reductions might be an indicator of subtle cognitive decline. Implications on clinical and research settings within the AD field are discussed.

Using remote, digital, multi-day testing to characterize long-term forgetting in cognitively unimpaired older adults

INTRODUCTION

Accelerated long-term forgetting (LTF) might be an early marker of subtle memory changes in older adults at risk for Alzheimer's disease (AD). We leveraged remote, multi-day digital testing to characterize LTF in older adults and investigated its association with initial learning and AD imaging biomarkers.

METHODS

One hundred four cognitively unimpaired older adults completed a face-name memory task for seven consecutive days and were asked to recognize face-name pairs 1 week later. LTF was computed as the number of correctly identified stimuli divided by a participant's maximum performance during learning.

RESULTS

Better learning was associated with less LTF (β = 0.52, 95% confidence interval [CI]:0.34-0.71, p < 0.001). Accelerated LTF was associated with cortical thinning in AD-signature regions (β = 0.33, 95% CI: 0.13-0.52, p = 0.001), but associations with regional tau were more subtle.

DISCUSSION

Remote, multi-day testing may facilitate the assessment of LTF as an early cognitive marker of preclinical AD, but further replication is needed.

HIGHLIGHTS

Using digital, remote assessments, we evaluated long-term forgetting in cognitively unimpaired older adults. We found a potential association between long-term forgetting and tau in Alzheimer's disease (AD)-related regions. Assessing long-term forgetting may facilitate early detection of AD-related cognitive decline.

Influence of Different Diagnostic Criteria on Alzheimer Disease Clinical Research

BACKGROUND AND OBJECTIVES

Updates in Alzheimer disease (AD) diagnostic guidelines by the National Institute on Aging-Alzheimer's Association (NIA-AA) and the International Working Group (IWG) over the past 11 years may affect clinical diagnoses. We assessed how these guidelines affect clinical AD diagnosis in a cohort of cognitively unimpaired (CU) and cognitively impaired (CI) individuals.

METHODS

We applied clinical and biomarker data in algorithms to classify individuals from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort according to the following diagnostic guidelines for AD: 2011 NIA-AA, 2016 IWG-2, 2018 NIA-AA, and 2021 IWG-3, assigning the following generic diagnostic labels: (1) not AD (nAD), (2) increased risk of developing AD (irAD), and (3) AD. Diagnostic labels were compared according to their frequency, convergence across guidelines, biomarker profiles, and prognostic value. We also evaluated the diagnostic discordance among the criteria.

RESULTS

A total of 1,195 individuals (mean age 73.2 ± 7.2 years, mean education 16.1 ± 2.7, 44.0% female) presented different repartitions of diagnostic labels according to the 2011 NIA-AA (nAD = 37.8%, irAD = 23.0%, AD = 39.2%), 2016 IWG-2 (nAD = 37.7%, irAD = 28.7%, AD = 33.6%), 2018 NIA-AA (nAD = 40.7%, irAD = 9.3%, AD = 50.0%), and 2021 IWG-3 (nAD = 51.2%, irAD = 8.4%, AD = 48.3%) frameworks. Discordant diagnoses across all guidelines were found in 512 participants (42.8%) (138 [91.4%] occurring in only β-amyloid [CU 65.4%, CI 34.6%] and 191 [78.6%] in only tau-positive [CU 71.7%, CI 28.3%] individuals). Differences in predicting cognitive impairment between nAD and irAD groups were observed with the 2011 NIA-AA (hazard ratio [HR] 2.21, 95% CI 1.34-3.65, p = 0.002), 2016 IWG-2 (HR 2.81, 95% CI 1.59-4.96, p < 0.000), and 2021 IWG-3 (HR 3.61, 95% CI 2.09-6.23, p < 0.000), but not with 2018 NIA-AA (HR 1.69, 95% CI 0.87-3.28, p = 0.115).

DISCUSSION

Over 42% of the studied population presented discordant diagnoses when using the different examined AD criteria, mostly in individuals with a single positive biomarker. Except for 2018 NIA-AA, all guidelines identified asymptomatic individuals at risk of cognitive impairment. Our findings highlight important differences between the guidelines, emphasizing the necessity for updated criteria with enhanced staging metrics, considering clinical, research, therapeutic, and trial design aspects.

Free-water: A promising structural biomarker for cognitive decline in aging and mild cognitive impairment

Diffusion MRI derived free-water (FW) metrics show promise in predicting cognitive impairment and decline in aging and Alzheimer's disease (AD). FW is sensitive to subtle changes in brain microstructure, so it is possible these measures may be more sensitive than traditional structural neuroimaging biomarkers. In this study, we examined the associations among FW metrics (measured in the hippocampus and two AD signature meta-ROIs) with cognitive performance, and compared FW findings to those from more traditional neuroimaging biomarkers of AD. We leveraged data from a longitudinal cohort (nparticipants = 296, nobservations = 870, age at baseline: 73 ± 7 years, 40% mild cognitive impairment [MCI]) of older adults who underwent serial neuropsychological assessment (episodic memory, information processing speed, executive function, language, and visuospatial skills) and brain MRI over a maximum of four time points, including baseline (n = 284), 18-month (n = 246), 3-year (n = 215), and 5-year (n = 125) visits. The mean follow-up period was 2.8 ± 1.3 years. Structural MRI was used to quantify hippocampal volume, in addition to Schwarz and McEvoy AD Signatures. FW and FW-corrected fractional anisotropy (FAFWcorr) were quantified in the hippocampus (hippocampal FW) and the AD signature areas (SchwarzFW, McEvoyFW) from diffusion-weighted (dMRI) images using bi-tensor modeling (FW elimination and mapping method). Linear regression assessed the association of each biomarker with baseline cognitive performance. Additionally, linear mixed-effects regression assessed the association between baseline biomarker values and longitudinal cognitive performance. A subsequent competitive model analysis was conducted on both baseline and longitudinal data to determine how much additional variance in cognitive performance was explained by each biomarker compared to the covariate only model, which included age, sex, race/ethnicity, apolipoprotein-ε4 status, cognitive status, and modified Framingham Stroke Risk Profile scores. All analyses were corrected for multiple comparisons using an FDR procedure. Cross-sectional results indicate that hippocampal volume, hippocampal FW, Schwarz and McEvoy AD Signatures, and the SchwarzFW and McEvoyFW metrics are all significantly associated with memory performance. Baseline competitive model analyses showed that the McEvoy AD Signature and SchwarzFW explain the most unique variance beyond covariates for memory (ΔRadj 2 = 3.47 ± 1.65%) and executive function (ΔRadj 2 = 2.43 ± 1.63%), respectively. Longitudinal models revealed that hippocampal FW explained substantial unique variance for memory performance (ΔRadj 2 = 8.13 ± 1.25%), and outperformed all other biomarkers examined in predicting memory decline (pFDR = 1.95 x 10-11). This study shows that hippocampal FW is a sensitive biomarker for cognitive impairment and decline, and provides strong evidence for further exploration of this measure in aging and AD.

Change in Depressive Symptoms and Longitudinal Regional Amyloid Accumulation in Unimpaired Older Adults

Importance

Depressive symptoms in older adults may be a harbinger of Alzheimer disease (AD), even in preclinical stages. It is unclear whether worsening depressive symptoms are manifestations of regional distributions of core AD pathology (amyloid) and whether cognitive changes affect this relationship.

Objective

To evaluate whether increasing depressive symptoms are associated with amyloid accumulation in brain regions important for emotional regulation and whether those associations vary by cognitive performance.

Design, Setting, and Participants

Participants from the Harvard Aging Brain Study, a longitudinal cohort study, underwent annual assessments of depressive symptoms and cognition alongside cortical amyloid positron emission tomography (PET) imaging at baseline and every 2 to 3 years thereafter (mean [SD] follow-up, 8.6 [2.2] years). Data collection was conducted from September 2010 to October 2022 in a convenience sample of community-dwelling older adults who were cognitively unimpaired with, at most, mild baseline depression. Data were analyzed from October 2022 to December 2023.

Main Outcomes and Measures

Depression (Geriatric Depression Scale [GDS]-30-item), cognition (Preclinical Alzheimer Cognitive Composite-5 [PACC]), and a continuous measure of cerebral amyloid (Pittsburgh compound B [PiB] PET) examined in a priori-defined regions (medial orbitofrontal cortex [mOFC], lateral orbitofrontal cortex, middle frontal cortex [MFC], superior frontal cortex, anterior cingulate cortex, isthmus cingulate cortex [IC], posterior cingulate cortex, and amygdala). Associations between longitudinal GDS scores, regional amyloid slopes, and PACC slopes were assessed using linear mixed-effects models.

Results

In this sample of 154 individuals (94 [61%] female; mean [SD] age, 72.6 [6.4] years; mean (SD) education, 15.9 [3.1] years), increasing PiB slopes in the bilateral mOFC, IC, and MFC were associated with increasing GDS scores (mOFC: β = 11.07 [95% CI, 5.26-16.87]; t = 3.74 [SE, 2.96]; P = .004; IC: β = 12.83 [95% CI, 5.68-19.98]; t = 3.51 [SE, 3.65]; P = .004; MFC: β = 9.22 [95% CI, 2.25-16.20]; t = 2.59 [SE, 3.56]; P = .03). Even with PACC slope as an additional covariate, associations remained significant in these regions.

Conclusions and Relevance

In this cohort study of cognitively unimpaired older adults with, at most, mild baseline depressive symptoms, greater depressive symptoms over time were associated with amyloid accumulation in regions associated with emotional control. Furthermore, these associations persisted in most regions independent of cognitive changes. These results shed light on the neurobiology of depressive symptoms in older individuals and underscore the importance of monitoring for elevated mood symptoms early in AD.

Spatial extent as a sensitive amyloid-PET metric in preclinical Alzheimer's disease

INTRODUCTION

Spatial extent-based measures of how far amyloid beta (Aβ) has spread throughout the neocortex may be more sensitive than traditional Aβ-positron emission tomography (PET) measures of Aβ level for detecting early Aβ deposits in preclinical Alzheimer's disease (AD) and improve understanding of Aβ's association with tau proliferation and cognitive decline.

METHODS

Pittsburgh Compound-B (PIB)-PET scans from 261 cognitively unimpaired older adults from the Harvard Aging Brain Study were used to measure Aβ level (LVL; neocortical PIB DVR) and spatial extent (EXT), calculated as the proportion of the neocortex that is PIB+.

RESULTS

EXT enabled earlier detection of Aβ deposits longitudinally confirmed to reach a traditional LVL-based threshold for Aβ+ within 5 years. EXT improved prediction of cognitive decline (Preclinical Alzheimer Cognitive Composite) and tau proliferation (flortaucipir-PET) over LVL.

DISCUSSION

These findings indicate EXT may be more sensitive to Aβ's role in preclinical AD than level and improve targeting of individuals for AD prevention trials.

HIGHLIGHTS

Aβ spatial extent (EXT) was measured as the percentage of the neocortex with elevated Pittsburgh Compound-B. Aβ EXT improved detection of Aβ below traditional PET thresholds. Early regional Aβ deposits were spatially heterogeneous. Cognition and tau were more closely tied to Aβ EXT than Aβ level. Neocortical tau onset aligned with reaching widespread neocortical Aβ.

Vascular contributions to cognitive decline: Beyond amyloid and tau in the Harvard Aging Brain Study

In addition to amyloid and tau pathology, elevated systemic vascular risk, white matter injury, and reduced cerebral blood flow contribute to late-life cognitive decline. Given the strong collinearity among these parameters, we proposed a framework to extract the independent latent features underlying cognitive decline using the Harvard Aging Brain Study (N = 166 cognitively unimpaired older adults at baseline). We used the following measures from the baseline visit: cortical amyloid, inferior temporal cortex tau, relative cerebral blood flow, white matter hyperintensities, peak width of skeletonized mean diffusivity, and Framingham Heart Study cardiovascular disease risk. We used exploratory factor analysis to extract orthogonal factors from these variables and their interactions. These factors were used in a regression model to explain longitudinal Preclinical Alzheimer Cognitive Composite-5 (PACC) decline (follow-up = 8.5 ±2.7 years). We next examined whether gray matter volume atrophy acts as a mediator of factors and PACC decline. Latent factors of systemic vascular risk, white matter injury, and relative cerebral blood flow independently explain cognitive decline beyond amyloid and tau. Gray matter volume atrophy mediates these associations with the strongest effect on white matter injury. These results suggest that systemic vascular risk contributes to cognitive decline beyond current markers of cerebrovascular injury, amyloid, and tau.

Identifying longitudinal cognitive resilience from cross-sectional amyloid, tau, and neurodegeneration

BACKGROUND

Leveraging Alzheimer's disease (AD) imaging biomarkers and longitudinal cognitive data may allow us to establish evidence of cognitive resilience (CR) to AD pathology in-vivo. Here, we applied latent class mixture modeling, adjusting for sex, baseline age, and neuroimaging biomarkers of amyloid, tau and neurodegeneration, to a sample of cognitively unimpaired older adults to identify longitudinal trajectories of CR.

METHODS

We identified 200 Harvard Aging Brain Study (HABS) participants (mean age = 71.89 years, SD = 9.41 years, 59% women) who were cognitively unimpaired at baseline with 2 or more timepoints of cognitive assessment following a single amyloid-PET, tau-PET and structural MRI. We examined latent class mixture models with longitudinal cognition as the dependent variable and time from baseline, baseline age, sex, neocortical Aβ, entorhinal tau, and adjusted hippocampal volume as independent variables. We then examined group differences in CR-related factors across the identified subgroups from a favored model. Finally, we applied our favored model to a dataset from the Alzheimer's Disease Neuroimaging Initiative (ADNI; n = 160, mean age = 73.9 years, SD = 7.6 years, 60% women).

RESULTS

The favored model identified 3 latent subgroups, which we labelled as Normal (71% of HABS sample), Resilient (22.5%) and Declining (6.5%) subgroups. The Resilient subgroup exhibited higher baseline cognitive performance and a stable cognitive slope. They were differentiated from other groups by higher levels of verbal intelligence and past cognitive activity. In ADNI, this model identified a larger Normal subgroup (88.1%), a smaller Resilient subgroup (6.3%) and a Declining group (5.6%) with a lower cognitive baseline.

CONCLUSION

These findings demonstrate the value of data-driven approaches to identify longitudinal CR groups in preclinical AD. With such an approach, we identified a CR subgroup who reflected expected characteristics based on previous literature, higher levels of verbal intelligence and past cognitive activity.

Trajectories of amyloid beta accumulation - Unveiling the relationship with APOE genotype and cognitive decline

Amyloid beta (Aβ) follows a sigmoidal time function with varying accumulation rates. We studied how the position on this function, reflected by different Aβ accumulation phases, influences APOE ɛ4's association with Aβ and cognitive decline in 503 participants without dementia using Aβ-PET imaging over 5.3-years. First, Aβ load and accumulation were analyzed irrespective of phases using linear mixed regression. Generally, ɛ4 carriers displayed a higher Aβ load. Moreover, Aβ normal (Aβ-) ɛ4 carriers demonstrated higher accumulation. Next, we categorized accumulation phases as "decrease", "stable", or "increase" based on trajectory shapes. After excluding the Aβ-/decrease participants from the initial regression, the difference in accumulation attributable to genotype among Aβ- individuals was no longer significant. Further analysis revealed that in increase phases, Aβ accumulation was higher among noncarriers, indicating a genotype-related timeline shift. Finally, cognitive decline was analyzed across phases and was already evident in the Aβ-/increase phase. Our results encourage early interventions for ɛ4 carriers and imply that monitoring accumulating Aβ- individuals might help identify those at risk for cognitive decline.

Exploration of neuroanatomical characteristics to differentiate prodromal Alzheimer's disease from cognitively unimpaired amyloid-positive individuals

Differentiating clinical stages based solely on positive findings from amyloid PET is challenging. We aimed to investigate the neuroanatomical characteristics at the whole-brain level that differentiate prodromal Alzheimer's disease (AD) from cognitively unimpaired amyloid-positive individuals (CU A+) in relation to amyloid deposition and regional atrophy. We included 45 CU A+ participants and 135 participants with amyloid-positive prodromal AD matched 1:3 by age, sex, and education. All participants underwent 18F-florbetaben positron emission tomography and 3D structural T1-weighted magnetic resonance imaging. We compared the standardized uptake value ratios (SUVRs) and volumes in 80 regions of interest (ROIs) between CU A+ and prodromal AD groups using independent t-tests, and employed the least absolute selection and shrinkage operator (LASSO) logistic regression model to identify ROIs associated with prodromal AD in relation to amyloid deposition, regional atrophy, and their interaction. After applying False Discovery Rate correction at < 0.1, there were no differences in global and regional SUVR between CU A+ and prodromal AD groups. Regional volume differences between the two groups were observed in the amygdala, hippocampus, entorhinal cortex, insula, parahippocampal gyrus, and inferior temporal and parietal cortices. LASSO logistic regression model showed significant associations between prodromal AD and atrophy in the entorhinal cortex, inferior parietal cortex, both amygdalae, and left hippocampus. The mean SUVR in the right superior parietal cortex (beta coefficient = 0.0172) and its interaction with the regional volume (0.0672) were also selected in the LASSO model. The mean SUVR in the right superior parietal cortex was associated with an increased likelihood of prodromal AD (Odds ratio [OR] 1.602, p = 0.014), particularly in participants with lower regional volume (OR 3.389, p < 0.001). Only regional volume differences, not amyloid deposition, were observed between CU A+ and prodromal AD. The reduced volume in the superior parietal cortex may play a significant role in the progression to prodromal AD through its interaction with amyloid deposition in that region.

The use of individual-based FDG-PET volume of interest in predicting conversion from mild cognitive impairment to dementia

BACKGROUND

Based on a longitudinal cohort design, the aim of this study was to investigate whether individual-based 18F fluorodeoxyglucose positron emission tomography (18F-FDG-PET) regional signals can predict dementia conversion in patients with mild cognitive impairment (MCI).

METHODS

We included 44 MCI converters (MCI-C), 38 non-converters (MCI-NC), 42 patients with Alzheimer's disease with dementia, and 40 cognitively normal controls. Data from annual cognitive measurements, 3D T1 magnetic resonance imaging (MRI) scans, and 18F-FDG-PET scans were used for outcome analysis. An individual-based FDG-PET approach was applied using seven volumes of interest (VOIs), Z transformed using a normal FDG-PET template. Hypometabolism was defined as a Z score < -2 of regional standard uptake value ratio. For the longitudinal cognitive test scores, generalized estimating equations were used. A linear mixed-effects model was used to compare the temporal impact of cortical hypometabolism and cortical thickness degeneration.

RESULTS

The clinical follow-up period was 6.6 ± 3.8 years (range 3.1 to 16.0 years). The trend of cognitive decline could differentiate MCI-C from MCI-NC after 3 years of follow-up. In the baseline 18F-FDG-PET scan of the patients with MCI, medial temporal lobe (MTL; 94.7% sensitivity, 80.5% specificity) and posterior cingulate cortex (PCC; 89.5% sensitivity, 73.1% specificity) hypometabolism predicted conversion with high accuracy. 18F-FDG-PET hypometabolism preceded dementia conversion at an interval of 3.70 ± 1.68 years and was earlier than volumetric changes, with the exception of the MTL.

CONCLUSIONS

Our finding supports the use of individual-based 18F-FDG-PET analysis to predict MCI conversion to dementia. Reduced FDG-PET metabolism in the MTL and PCC were strongly associated with future cognitive decline in the MCI-C group. Changes in 18F-FDG-PET occurred 1 to 8 years prior to conversion to dementia. Progressive hypometabolism in the PCC, precuneus and lateral temporal lobe, but not MTL, preceded MRI findings at the MCI stage.

Contribution of Global Amyloid-PET Imaging for Predicting Future Cognition in the MEMENTO Cohort

BACKGROUND AND OBJECTIVES

Global amyloid-PET is associated with cognition and cognitive decline, but most research on this association does not account for past cognitive information. We assessed the prognostic benefit of amyloid-PET measures for future cognition when prior cognitive assessments are available, evaluating the added value of amyloid measures beyond information on multiple past cognitive assessments.

METHODS

The French MEMENTO cohort (a cohort of outpatients from French research memory centers to improve knowledge on Alzheimer disease and related disorders) includes older outpatients with incipient cognitive changes, but no dementia diagnosis at inclusion. Global amyloid burden was assessed using positron emission tomography (amyloid-PET) for a subset of participants; semiannual cognitive testing was subsequently performed. We predicted mini-mental state examination (MMSE) scores using demographic characteristics (age, sex, marital status, and education) alone or in combination with information on prior cognitive measures. The added value of amyloid burden as a predictor in these models was evaluated with percent reduction of the mean squared error (MSE). All models were conducted separately for evaluating the added value of dichotomous amyloid positivity status compared with a continuous amyloid-standardized uptake-value ratio.

RESULTS

Our analytic sample comprised 510 individuals who underwent amyloid-PET scans with at least 4 MMSE assessments. The mean age at the PET scan was 71.6 (standard deviation 7.4) years; 60.7% were female. The median follow-up was 4.6 years (interquartile range: 0.9 years). Adding amyloid burden when adjusting for only demographic characteristics reduced the MSE of predictions by 5.08% (95% CI 0.97%-10.86%) and 12.64% (95% CI 3.35%-25.28%) for binary and continuous amyloid, respectively. If the model included 1 past MMSE measure, the MSE improvement was 3.51% (95% CI 1.01%-7.28%) when adding binary amyloid and 8.83% (95% CI 2.63%-16.37%) when adding continuous amyloid. Improvements in model fit were smaller with the addition of amyloid burden when more than 1 past cognitive assessment was included. For all models incorporating past cognitive assessments, differences in predictions amounted to a fraction of 1 MMSE point on average.

DISCUSSION

In a clinical setting, global amyloid burden did not appreciably improve cognitive predictions when past cognitive assessments were available.

TRIAL REGISTRATION INFORMATION

ClinicalTrials.gov Identifier: NCT02164643.

Early Detection of Amyloid-Related Changes in Memory among Cognitively Unimpaired Older Adults with Daily Digital Testing

OBJECTIVE

This study was undertaken to determine whether assessing learning over days reveals Alzheimer disease (AD) biomarker-related declines in memory consolidation that are otherwise undetectable with single time point assessments.

METHODS

Thirty-six (21.9%) cognitively unimpaired older adults (aged 60-91 years) were classified with elevated β-amyloid (Aβ+) and 128 (78%) were Aβ- using positron emission tomography with 11C Pittsburgh compound B. Participants completed the multiday Boston Remote Assessment for Neurocognitive Health (BRANCH) for 12 min/day on personal devices (ie, smartphones, laptops), which captures the trajectory of daily learning of the same content on 3 repeated tests (Digit Signs, Groceries-Prices, Face-Name). Learning is computed as a composite of accuracy across all 3 measures. Participants also completed standard in-clinic cognitive tests as part of the Preclinical Alzheimer's Cognitive Composite (PACC-5), with 123 participants undergoing PACC-5 follow-up after 1.07 (standard deviation = 0.25) years.

RESULTS

At the cross-section, there were no statistically significant differences in performance between Aβ+/- participants on any standard in-clinic cognitive tests (eg, PACC-5) or on day 1 of multiday BRANCH. Aβ+ participants exhibited diminished 7-day learning curves on multiday BRANCH after 4 days of testing relative to Aβ- participants (Cohen d = 0.49, 95% confidence interval = 0.10-0.87). Diminished learning curves were associated with greater annual PACC-5 decline (r = 0.54, p < 0.001).

INTERPRETATION

Very early Aβ-related memory declines can be revealed by assessing learning over days, suggesting that failures in memory consolidation predate other conventional amnestic deficits in AD. Repeated digital memory assessments, increasingly feasible and uniquely able to assess memory consolidation over short time periods, have the potential to be transformative for detecting the earliest cognitive changes in preclinical AD. ANN NEUROL 2024;95:507-517.

Disease trajectories in older adults with non-AD pathologic change and comparison with Alzheimer's disease pathophysiology: A longitudinal study

Based on the 'AT(N)' system, individuals with normal amyloid biomarkers but abnormal tauopathy or neurodegeneration biomarkers are classified as non-Alzheimer's disease (AD) pathologic change. This study aimed to assess the long-term clinical and cognitive trajectories of individuals with non-AD pathologic change among older adults without dementia, comparing them to those with normal AD biomarkers and AD pathophysiology. Analyzing Alzheimer's Disease Neuroimaging Initiative data, we evaluated clinical outcomes and conversion risk longitudinally using mixed effects models and multivariate Cox proportional hazard models. We found that compared to individuals with A-T-N-, those with abnormal tauopathy or neurodegeneration biomarkers (A-T + N-, A-T-N + , and A-T + N + ) had a faster rate of cognitive decline and disease progression. Individuals with A-T + N + had a faster rate of decline than those with A-T + N-. Additionally, in individuals with the same baseline tauopathy and neurodegeneration biomarker status, the presence of baseline amyloid could accelerate cognitive decline and clinical progression. These findings provide a foundation for future studies on non-AD pathologic change and its comparison with AD pathophysiology.

A Closer Look at Practice Effects in Mild Cognitive Impairment and Alzheimer's Disease

Practice effects have become a potentially important variable regarding the diagnosis, prognosis, and treatment recommendations in mild cognitive impairment (MCI) and Alzheimer's disease (AD). However, the understanding of these short-term changes in test scores remains unclear. The current observational study sought to examine variables that influence the magnitude of short-term practice effects in MCI and AD, including demographic information, cognitive performance, daily functioning, and medical comorbidities. One hundred sixty-six older adults classified as cognitively intact, amnestic MCI, or mild AD were tested twice across 1 week with a brief battery of neuropsychological tests. Correlational and regression analyses examined the relationship of practice effects with demographic and clinical variables. Results indicated that practice effects were minimally related to demographic variables and medical comorbidities, but they were significantly related to cognitive variables, depressive symptoms, and daily functioning. These findings expand our understanding of practice effects in MCI and AD, and they may allow a better appreciation of how they could affect clinical care and research.

Estimating Dementia Onset: AT(N) Profiles and Predictive Modeling in Mild Cognitive Impairment Patients

BACKGROUND

Mild Cognitive Impairment (MCI) usually precedes the symptomatic phase of dementia and constitutes a window of opportunities for preventive therapies.

OBJECTIVES

The objective of this study was to predict the time an MCI patient has left to reach dementia and obtain the most likely natural history in the progression of MCI towards dementia.

METHODS

This study was conducted on 633 MCI patients and 145 subjects with dementia through 4726 visits over 15 years from Alzheimer Disease Neuroimaging Initiative (ADNI) cohort. A combination of data from AT(N) profiles at baseline and longitudinal predictive modeling was applied. A data-driven approach was proposed for categorical diagnosis prediction and timeline estimation of cognitive decline progression, which combined supervised and unsupervised learning techniques.

RESULTS

A reduced vector of only neuropsychological measures was selected for training the models. At baseline, this approach had high performance in detecting subjects at high risk of converting from MCI to dementia in the coming years. Furthermore, a Disease Progression Model (DPM) was built and also verified using three metrics. As a result of the DPM focused on the studied population, it was inferred that amyloid pathology (A+) appears about 7 years before dementia, and tau pathology (T+) and neurodegeneration (N+) occur almost simultaneously, between 3 and 4 years before dementia. In addition, MCI-A+ subjects were shown to progress more rapidly to dementia compared to MCI-A- subjects.

CONCLUSION

Based on proposed natural histories and cross-sectional and longitudinal analysis of AD markers, the results indicated that only a single cerebrospinal fluid sample is necessary during the prodromal phase of AD. Prediction from MCI into dementia and its timeline can be achieved exclusively through neuropsychological measures.

Mayo Normative Studies: Amyloid and Neurodegeneration Negative Normative Data for the Auditory Verbal Learning Test and Sex-Specific Sensitivity to Mild Cognitive Impairment/Dementia

Background

Conventional normative samples include individuals with undetected Alzheimer's disease neuropathology, lowering test sensitivity for cognitive impairment.

Objective

We developed Mayo Normative Studies (MNS) norms limited to individuals without elevated amyloid or neurodegeneration (A-N-) for Rey's Auditory Verbal Learning Test (AVLT). We compared these MNS A-N- norms in female, male, and total samples to conventional MNS norms with varying levels of demographic adjustments.

Methods

The A-N- sample included 1,059 Mayo Clinic Study of Aging cognitively unimpaired (CU) participants living in Olmsted County, MN, who are predominantly non-Hispanic White. Using a regression-based approach correcting for age, sex, and education, we derived fully-adjusted T-score formulas for AVLT variables. We validated these A-N- norms in two independent samples of CU (n = 261) and mild cognitive impairment (MCI)/dementia participants (n = 392) > 55 years of age.

Results

Variability associated with age decreased by almost half in the A-N- norm sample relative to the conventional norm sample. Fully-adjusted MNS A-N- norms showed approximately 7- 9% higher sensitivity to MCI/dementia compared to fully-adjusted MNS conventional norms for trials 1- 5 total and sum of trials. Among women, sensitivity to MCI/dementia increased with each normative data refinement. In contrast, age-adjusted conventional MNS norms showed greatest sensitivity to MCI/dementia in men.

Conclusions

A-N- norms show some benefits over conventional normative approaches to MCI/dementia sensitivity, especially for women. We recommend using these MNS A-N- norms alongside MNS conventional norms. Future work is needed to determine if normative samples that are not well characterized clinically show greater benefit from biomarker-refined approaches.

Interaction Between Arteriosclerosis and Amyloid-β on Cognitive Function

BACKGROUND

Dementia is a multifactorial disease, with Alzheimer's disease (AD) and vascular pathology often co-occurring in many individuals with dementia. Yet, the interplay between AD and vascular pathology in cognitive decline is largely undetermined.

OBJECTIVE

The aim of the present study was to examine the joint effect of arteriosclerosis and AD pathology on cognition in the general population without dementia.

METHODS

We determined the interaction between blood-based AD biomarkers and CT-defined arteriosclerosis on cognition in 2,229 dementia-free participants of the population-based Rotterdam Study (mean age: 68.9 years, 52% women) cross-sectionally.

RESULTS

Amyloid-β (Aβ)42 and arterial calcification were associated with cognitive performance. After further adjustment for confounders in a model that combined all biomarkers, only arterial calcification remained independently associated with cognition. There was a significant interaction between arterial calcification and Aβ42 and between arterial calcification and the ratio of Aβ42/40. Yet, estimates attenuated, and interactions were no longer statistically significant after adjustment for cardio metabolic risk factors.

CONCLUSIONS

Arteriosclerosis and AD display additive interaction-effects on cognition in the general population, that are due in part to cardio metabolic risk factors. These findings suggest that joint assessment of arteriosclerosis and AD pathology is important for understanding of disease etiology in individuals with cognitive impairment.

Sex and APOE ε4 carrier effects on atrophy, amyloid PET, and tau PET burden in early-onset Alzheimer's disease

INTRODUCTION

We used sex and apolipoprotein E ε4 (APOE ε4) carrier status as predictors of pathologic burden in early-onset Alzheimer's disease (EOAD).

METHODS

We included baseline data from 77 cognitively normal (CN), 230 EOAD, and 70 EO non-Alzheimer's disease (EOnonAD) participants from the Longitudinal Early-Onset Alzheimer's Disease Study (LEADS). We stratified each diagnostic group by males and females, then further subdivided each sex by APOE ε4 carrier status and compared imaging biomarkers in each stratification. Voxel-wise multiple linear regressions yielded statistical brain maps of gray matter density, amyloid, and tau PET burden.

RESULTS

EOAD females had greater amyloid and tau PET burdens than males. EOAD female APOE ε4 non-carriers had greater amyloid PET burdens and greater gray matter atrophy than female ε4 carriers. EOnonAD female ε4 non-carriers also had greater gray matter atrophy than female ε4 carriers.

DISCUSSION

The effects of sex and APOE ε4 must be considered when studying these populations.

HIGHLIGHTS

Novel analysis examining the effects of biological sex and apolipoprotein E ε4 (APOE ε4) carrier status on neuroimaging biomarkers among early-onset Alzheimer's disease (EOAD), early-onset non-AD (EOnonAD), and cognitively normal (CN) participants. Female sex is associated with greater pathology burden in the EOAD cohort compared to male sex. The effect of APOE ε4 carrier status on pathology burden was the most impactful in females across all cohorts.

Real-world prediction of preclinical Alzheimer's disease with a deep generative model

Amyloid positivity is an early indicator of Alzheimer's disease and is necessary to determine the disease. In this study, a deep generative model is utilized to predict the amyloid positivity of cognitively normal individuals using proxy measures, such as structural MRI scans, demographic variables, and cognitive scores, instead of invasive direct measurements. Through its remarkable efficacy in handling imperfect datasets caused by missing data or labels, and imbalanced classes, the model outperforms previous studies and widely used machine learning approaches with an AUROC of 0.8609. Furthermore, this study illuminates the model's adaptability to diverse clinical scenarios, even when feature sets or diagnostic criteria differ from the training data. We identify the brain regions and variables that contribute most to classification, including the lateral occipital lobes, posterior temporal lobe, and APOE ϵ4 allele. Taking advantage of deep generative models, our approach can not only provide inexpensive, non-invasive, and accurate diagnostics for preclinical Alzheimer's disease, but also meet real-world requirements for clinical translation of a deep learning model, including transferability and interpretability.

Cortical microstructural changes predict tau accumulation and episodic memory decline in older adults harboring amyloid

INTRODUCTION

Non-invasive diffusion-weighted imaging (DWI) to assess brain microstructural changes via cortical mean diffusivity (cMD) has been shown to be cross-sectionally associated with tau in cognitively normal older adults, suggesting that it might be an early marker of neuronal injury. Here, we investigated how regional cortical microstructural changes measured by cMD are related to the longitudinal accumulation of regional tau as well as to episodic memory decline in cognitively normal individuals harboring amyloid pathology.

METHODS

122 cognitively normal participants from the Harvard Aging Brain Study underwent DWI, T1w-MRI, amyloid and tau PET imaging, and Logical Memory Delayed Recall (LMDR) assessments. We assessed whether the interaction of baseline amyloid status and cMD (in entorhinal and inferior-temporal cortices) was associated with longitudinal regional tau accumulation and with longitudinal LMDR using separate linear mixed-effects models.

RESULTS

We find a significant interaction effect of the amyloid status and baseline cMD in predicting longitudinal tau in the entorhinal cortex (p = 0.044) but not the inferior temporal lobe, such that greater baseline cMD values predicts the accumulation of entorhinal tau in amyloid-positive participants. Moreover, we find a significant interaction effect of the amyloid status and baseline cMD in the entorhinal cortex (but not inferior temporal cMD) in predicting longitudinal LMDR (p < 0.001), such that baseline entorhinal cMD predicts the episodic memory decline in amyloid-positive participants.

CONCLUSIONS

The combination of amyloidosis and elevated cMD in the entorhinal cortex may help identify individuals at short-term risk of tau accumulation and Alzheimer's Disease-related episodic memory decline, suggesting utility in clinical trials.

Association of Stages of Objective Memory Impairment With Incident Symptomatic Cognitive Impairment in Cognitively Normal Individuals

BACKGROUND AND OBJECTIVES

Increasing evidence indicates that a subset of cognitively normal individuals has subtle cognitive impairment at baseline. We sought to identify them using the Stages of Objective Memory Impairment (SOMI) system. Symptomatic cognitive impairment was operationalized by a Clinical Dementia Rating (CDR) ≥0.5. We hypothesized that incident impairment would be higher for participants with subtle retrieval impairment (SOMI-1), higher still for those with moderate retrieval impairment (SOMI-2), and highest for those with storage impairment (SOMI-3/4) after adjusting for demographics and APOE ε4 status. A secondary objective was to determine whether including biomarkers of β-amyloid, tau pathology, and neurodegeneration in the models affect prediction. We hypothesized that even after adjusting for in vivo biomarkers, SOMI would remain a significant predictor of time to incident symptomatic cognitive impairment.

METHODS

Among 969 cognitively normal participants, defined by a CDR = 0, from the Knight Alzheimer Disease Research Center, SOMI stage was determined from their baseline Free and Cued Selective Reminding Test scores, 555 had CSF and structural MRI measures and comprised the biomarker subgroup, and 144 of them were amyloid positive. Cox proportional hazards models tested associations of SOMI stages at baseline and biomarkers with time to incident cognitive impairment defined as the transition to CDR ≥0.5.

RESULTS

Among all participants, the mean age was 69.35 years, 59.6% were female, and mean follow-up was 6.36 years. Participants in SOMI-1-4 had elevated hazard ratios for the transition from normal to impaired cognition in comparison with those who were SOMI-0 (no memory impairment). Individuals in SOMI-1 (mildly impaired retrieval) and SOMI-2 (moderately impaired retrieval) were at nearly double the risk of clinical progression compared with persons with no memory problems. When memory storage impairment emerges (SOMI-3/4), the hazard ratio for clinical progression increased approximately 3 times. SOMI stage remained an independent predictor of incident cognitive impairment after adjusting for all biomarkers.

DISCUSSION

SOMI predicts the transition from normal cognition to incident symptomatic cognitive impairment (CDR ≥0.5). The results support the use of SOMI to identify those cognitively normal participants most likely to develop incident cognitive impairment who can then be referred for biomarker screening.

Detection and treatment of Alzheimer's disease in its preclinical stage

Longitudinal multimodal biomarker studies reveal that the continuum of Alzheimer's disease (AD) includes a long latent phase, referred to as preclinical AD, which precedes the onset of symptoms by decades. Treatment during the preclinical AD phase offers an optimal opportunity for slowing the progression of disease. However, trial design in this population is complex. In this Review, we discuss the recent advances in accurate plasma measurements, new recruitment approaches, sensitive cognitive instruments and self-reported outcomes that have facilitated the successful launch of multiple phase 3 trials for preclinical AD. The recent success of anti-amyloid immunotherapy trials in symptomatic AD has increased the enthusiasm for testing this strategy at the earliest feasible stage. We provide an outlook for standard screening of amyloid accumulation at the preclinical stage in clinically normal individuals, during which effective therapy to delay or prevent cognitive decline can be initiated.

Harmonizing the preclinical Alzheimer cognitive composite for multicohort studies

OBJECTIVES

Studies are increasingly examining research questions across multiple cohorts using data from the preclinical Alzheimer cognitive composite (PACC). Our objective was to use modern psychometric approaches to develop a harmonized PACC.

METHOD

We used longitudinal data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), Harvard Aging Brain Study (HABS), and Australian Imaging, Biomarker and Lifestyle Study of Ageing (AIBL) cohorts (n = 2,712). We further demonstrated our method with the Anti-Amyloid Treatment of Asymptomatic Alzheimer's Disease (A4) Study prerandomized data (n = 4,492). For the harmonization method, we used confirmatory factor analysis (CFA) on the final visit of the longitudinal cohorts to determine parameters to generate latent PACC (lPACC) scores. Overlapping tests across studies were set as "anchors" that tied cohorts together, while parameters from unique tests were freely estimated. We performed validation analyses to assess the performance of lPACC versus the common standardized PACC (zPACC).

RESULTS

Baseline (BL) scores for the zPACC were centered on zero, by definition. The harmonized lPACC did not define a common mean of zero and demonstrated differences in baseline ability levels across the cohorts. Baseline lPACC slightly outperformed zPACC in the prediction of progression to dementia. Longitudinal change in the lPACC was more constrained and less variable relative to the zPACC. In combined-cohort analyses, longitudinal lPACC slightly outperformed longitudinal zPACC in its association with baseline β-amyloid status.

CONCLUSIONS

This study proposes procedures for harmonizing the PACC that make fewer strong assumptions than the zPACC, facilitating robust multicohort analyses. This implementation of item response theory lends itself to adapting across future cohorts with similar composites. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

An accurate fully automated panel of plasma biomarkers for Alzheimer's disease

INTRODUCTION

There is a great need for fully automated plasma assays that can measure amyloid beta (Aβ) pathology and predict future Alzheimer's disease (AD) dementia.

METHODS

Two cohorts (n = 920) were examined: Panel A+ (n = 32 cognitively unimpaired [CU], n = 106 mild cognitive impairment [MCI], and n = 89 AD) and BioFINDER-1 (n = 461 CU, n = 232 MCI). Plasma Aβ42/Aβ40, phosphorylated tau (p-tau)181, two p-tau217 variants, ApoE4 protein, neurofilament light, and GFAP were measured using Elecsys prototype immunoassays.

RESULTS

The best biomarker for discriminating Aβ-positive versus Aβ-negative participants was Aβ42/Aβ40 (are under the curve [AUC] 0.83-0.87). Combining Aβ42/Aβ40, p-tau181, and ApoE4 improved the AUCs significantly (0.90 to 0.93; P< 0.01). Adding additional biomarkers had marginal effects (ΔAUC ≤0.01). In BioFINDER, p-tau181, p-tau217, and ApoE4 predicted AD dementia within 6 years in CU (AUC 0.88) and p-tau181, p-tau217, and Aβ42/Aβ40 in MCI (AUC 0.87).

DISCUSSION

The high accuracies for Aβ pathology and future AD dementia using fully automated instruments are promising for implementing plasma biomarkers in clinical trials and clinical routine.

Disease trajectories in elders with suspected non-Alzheimer's pathophysiology and its comparison with Alzheimer's disease pathophysiology: a longitudinal study

Background

According to the new 'AT(N)' system, those with a normal amyloid biomarker but with abnormal tauopathy or biomarkers of neurodegeneration or neuronal injury, have been labeled suspected non-Alzheimer's pathophysiology (SNAP). We aimed to estimate the long-term clinical and cognitive trajectories of SNAP individuals in non-demented elders and its comparison with individual in the Alzheimer's disease (AD) pathophysiology using 'AT(N)' system.

Methods

We included individuals with available baseline cerebrospinal fluid (CSF) Aβ (A), CSF phosphorylated tau examination (T) and 18F-uorodeoxyglucose PET or volumetric magnetic resonance imaging (N) from the Alzheimer's Disease Neuroimaging Initiative database. Longitudinal change in clinical outcomes are assessed using linear mixed effects models. Conversion risk from cognitively normal (CN) to cognitively impairment, and conversion from mild cognitive impairment (MCI) to dementia are assessed using multivariate Cox proportional hazard models.

Results

Totally, 366 SNAP individuals were included (114 A-T-N-, 154 A-T + N-, 54 A-T-N + and 44 A-T + N+) of whom 178 were CN and 188 were MCI. Compared with A-T-N-, CN elders with A-T + N-, A-T-N + and A-T + N + had a faster rate of ADNI-MEM score decline. Moreover, CN older individuals with A-T + N + also had a faster rate of decline in ADNI-MEM score than those with A-T + N- individuals. MCI patients with A-T + N + had a faster rate of ADNI-MEM and ADNI-EF decline and hippocampal volume loss compared with A-T-N- and A-T + N- profiles. CN older individuals with A-T + N + had an increased risk of conversion to cognitive impairment (CDR-GS ≥ 0.5) compared with A-T + N- and A-T-N-. In MCI patients, A-T + N + also had an increased risk of conversion to dementia compared with A-T + N- and A-T-N-. Compared with A-T + N-, CN elders and MCI patients with A + T + N- and A + T + N + had a faster rate of ADNI-MEM score, ADNI-EF score decline, and hippocampal volume loss. CN individuals with A + T + N + had a faster rate of ADNI-EF score decline compare with A-T + N + individuals. Moreover, MCI patients with A + T + N + also had a faster rate of decline in ADNI-MEM score, ADNI-EF score and hippocampal volume loss than those with A-T + N + individuals.

Conclusions

The findings from clinical, imaging and biomarker studies on SNAP, and its comparison with AD pathophysiology offered an important foundation for future studies.

How can secondary dementia prevention trials of Alzheimer's disease be clinically meaningful?

After clinical trial failures in symptomatic Alzheimer's disease (AD), our field has moved to earlier intervention in cognitively normal individuals with biomarker evidence of AD. This offers potential for dementia prevention, but mainly low and variable rates of progression to AD dementia reduce the usefulness of trials' data in decision making by potential prescribers. With results from several Phase 3 secondary prevention studies anticipated within the next few years and the Food and Drug Administration's recent endorsement of amyloid beta as a surrogate outcome biomarker for AD clinical trials, it is time to question the clinical significance of changes in biomarkers, adequacy of current trial durations, and criteria for treatment success if cognitively unimpaired patients and their doctors are to meaningfully evaluate the potential value of new agents. We argue for a change of direction toward trial designs that can unambiguously inform clinical decision making about dementia risk and progression.

Association Between Dietary Habits in Midlife With Dementia Incidence Over a 20-Year Period

BACKGROUND AND OBJECTIVES

Dementia cases are expected to triple during the next 30 years, highlighting the importance of finding modifiable risk factors for dementia. The aim of this study was to investigate whether adherence to conventional dietary recommendations or to a modified Mediterranean diet are associated with a subsequent lower risk of developing all-cause dementia, Alzheimer disease (AD), vascular dementia (VaD), or with future accumulation of AD-related β-amyloid (Aβ) pathology.

METHODS

Baseline examination in the prospective Swedish population-based Malmö Diet and Cancer Study took place in 1991-1996 with a follow-up for incident dementia until 2014. Nondemented individuals born 1923-1950 and living in Malmö were invited to participate. Thirty thousand four hundred forty-six were recruited (41% of all eligible). Twenty-eight thousand twenty-five had dietary data and were included in this study. Dietary habits were assessed with a 7-day food diary, detailed food frequency questionnaire, and 1-hour interview. Main outcomes were incident all-cause dementia, AD, or VaD determined by memory clinic physicians. Secondary outcome was Aβ-accumulation measured using CSF Aβ42 (n = 738). Cox proportional hazard models were used to examine associations between diet and risk of developing dementia (adjusted for demographics, comorbidities, smoking, physical activity, and alcohol).

RESULTS

Sixty-one percent were women, and the mean (SD) age was 58.1 (7.6) years. One thousand nine hundred forty-three (6.9%) were diagnosed with dementia (median follow-up, 19.8 years). Individuals adhering to conventional dietary recommendations did not have lower risk of developing all-cause dementia (hazard ratio [HR] comparing worst with best adherence, 0.93, 95% CI 0.81-1.08), AD (HR 1.03, 0.85-1.23), or VaD (HR 0.93, 0.69-1.26). Neither did adherence to the modified Mediterranean diet lower the risk of developing all-cause dementia (HR 0.93 0.75-1.15), AD (HR 0.90, 0.68-1.19), or VaD (HR 1.00, 0.65-1.55). The results were similar when excluding participants developing dementia within 5 years or those with diabetes. No significant associations were found between diet and abnormal Aβ accumulation, conventional recommendations (OR 1.28, 0.74-2.24) or modified Mediterranean diet (OR 0.85, 0.39-1.84).

DISCUSSION

In this 20-year follow-up study, neither adherence to conventional dietary recommendations nor to modified Mediterranean diet were significantly associated with subsequent reduced risk for developing all-cause dementia, AD dementia, VaD, or AD pathology.

Associations of Stages of Objective Memory Impairment with Cerebrospinal Fluid and Neuroimaging Biomarkers of Alzheimer's Disease

OBJECTIVE

To investigate cerebrospinal fluid (CSF) and neuroimaging correlates of Stages of Objective Memory Impairment (SOMI) based on Free and Cued Selective Reminding Test (FCSRT) performance, and to evaluate the effect of APOE ε4 status on this relationship.

METHODS

Data from 586 cognitively unimpaired individuals who had FCSRT, CSF, and volumetric magnetic resonance imaging (MRI) measures available was used. We compared CSF measures of β-amyloid (Aβ42/Aβ40 ratio), phosphorylated tau (p-Tau181), total tau (t-Tau), hippocampal volume, and PIB-PET mean cortical binding potential with partial volume correction (MCBP) among SOMI groups in the whole sample and in subsamples stratified by APOE ε4 status.

RESULTS

Participants had a mean age of 67.4 (SD=9.1) years, had 16.1 (SD=2.6) years of education, 57.0% were female, and 33.8% were APOE ε4 positive. In the entire sample, there was no significant difference between SOMI stages in Aβ42/Aβ40 ratio, p-Tau181, t-Tau, or PIB-PET MCBP when adjusted for age, sex, and education. However, higher SOMI stages had smaller hippocampal volume (F=3.29, p=0.020). In the stratified sample based on APOE ε4 status, in APOE ε4 positive individuals, higher SOMI stages had higher p-Tau181 (F=2.94, p=0.034) higher t-Tau (F=3.41, p=0.019), and smaller hippocampal volume (F=5.78, p<0.001). There were no significant differences in CSF or imaging biomarkers between SOMI groups in the APOE ε4 negative subsample.

CONCLUSION

Cognitively normal older individuals with higher SOMI stages have higher in-vivo tau and neurodegenerative pathology only in APOE ε4 carriers. These original results indicate the potential usefulness of the SOMI staging system in assessing of tau and neurodegenerative pathology.

Repeatable battery for the assessment of neuropsychological status and its relationship to biomarkers of Alzheimer's disease

The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) has been associated with commonly used biomarkers of Alzheimer's disease (AD). However, prior studies have typically utilized small and poorly characterized samples, and they have not analyzed the subtests of the RBANS. The current study sought to expand on prior work by examining the relationship between the Indexes and subtest scores of the RBANS and three AD biomarkers: amyloid deposition via positron emission tomography, hippocampal volume via magnetic resonance imaging, and APOE ε4 status.

One-hundred twenty-one older adults across the AD continuum (intact, amnestic Mild Cognitive Impairment, mild AD), who were mostly Caucasian and well-educated, underwent assessment with the RBANS and collection of the three biomarkers.

Greater amyloid deposition was significantly related to lower scores on all five Indexes and the Total Scale score of the RBANS, as well as 11 of 12 subtests. For bilateral hippocampal volume, significant correlations were observed for 4 of the 5 Indexes, Total Scale score, and 9 of 12 subtests, with smaller hippocampi being related to lower RBANS scores. Participants with at least one APOE ε4 allele had significantly lower scores on 3 of the 5 Indexes, Total Scale score, and 8 of the 12 subtests.

In this sample of participants across the dementia spectrum, most RBANS Indexes and subtests showed relationships with the amyloid deposition, hippocampal volumes, and APOE status, with poorer performance on the RBANS being associated with biomarker positivity. Although memory scores on the RBANS have traditionally been linked to biomarkers in AD, other Index and subtest scores also hold promise as indicators of AD. Replication in a more diverse sample is needed.

Waning locus coeruleus integrity precedes cortical tau accrual in preclinical autosomal dominant Alzheimer's disease

INTRODUCTION

Autopsy studies recognize the locus coeruleus (LC) as one of the first sites accumulating tau in Alzheimer's disease (AD). Recent AD work related in vivo LC magnetic resonance imaging (MRI) integrity to tau and cognitive decline; however, relationships of LC integrity to age, tau, and cognition in autosomal dominant AD (ADAD) remain unexplored.

METHODS

We associated LC integrity (3T-MRI) with estimated years of onset, cortical amyloid beta, regional tau (positron emission tomography [PET]) and memory (Consortium to Establish a Registry for Alzheimer's Disease (CERAD) Word-List-Learning) among 27 carriers and 27 non-carriers of the presenilin-1 (PSEN1) E280A mutation. Longitudinal changes between LC integrity and tau were evaluated in 10 carriers.

RESULTS

LC integrity started to decline at age 32 in carriers, 12 years before clinical onset, and 20 years earlier than in sporadic AD. LC integrity was negatively associated with cortical tau, independent of amyloid beta, and predicted precuneus tau increases. LC integrity was positively associated with memory.

DISCUSSION

These findings support LC integrity as marker of disease progression in preclinical ADAD.

A 5-year community program in Singapore to prevent cognitive decline

INTRODUCTION

There is a scarcity of naturalistic follow-up studies on cognitive stimulating activities (CSAs), particularly in a real-world setting and over long-term. We thus investigated a pooled novel CSA intervention to prevent cognitive decline amongst community-dwelling older adults without dementia.

METHODS

Nested within a community-based longitudinal follow-up cohort study of community-dwelling and multi-ethnic older adults (N = 991), a subset of the cohort (n = 264) underwent four single-blinded randomized controlled trials involving four novel CSAs, including mindfulness, horticulture, art therapy, and choral singing. At the cohort's 5-year follow-up, we examined if involvements in the CSAs improved cognition, compared to controls (n = 727). The primary outcomes were changes in global cognition and specific cognitive domain scores measured by the mini-mental state examination (MMSE). Exploratory subgroup analyses stratified by baseline cognitive status and the number of CSAs were also conducted.

RESULTS

Compared to the control group, there was a small improvement in the CSA group on the total MMSE score (d = 0.108) and MMSE-immediate recall score (d = 0.199). Furthermore, subgroup analyses revealed medium effect sizes of improvements (d = 0.420) in cognitive domains in mild cognitive impairment (MCI) (vs. cognitively healthy) and those involved in two CSAs (vs. one CSA).

DISCUSSION

In summary, a CSA intervention improved cognition. MCI and those involved in two CSAs gained greater benefits from the CSAs. These sustained improvements in cognitive functions could have a significant impact on delaying or preventing dementia.

Distinct tau neuropathology and cellular profiles of an APOE3 Christchurch homozygote protected against autosomal dominant Alzheimer's dementia

We describe in vivo follow-up PET imaging and postmortem findings from an autosomal dominant Alzheimer's disease (ADAD) PSEN1 E280A carrier who was also homozygous for the APOE3 Christchurch (APOE3ch) variant and was protected against Alzheimer's symptoms for almost three decades beyond the expected age of onset. We identified a distinct anatomical pattern of tau pathology with atypical accumulation in vivo and unusual postmortem regional distribution characterized by sparing in the frontal cortex and severe pathology in the occipital cortex. The frontal cortex and the hippocampus, less affected than the occipital cortex by tau pathology, contained Related Orphan Receptor B (RORB) positive neurons, homeostatic astrocytes and higher APOE expression. The occipital cortex, the only cortical region showing cerebral amyloid angiopathy (CAA), exhibited a distinctive chronic inflammatory microglial profile and lower APOE expression. Thus, the Christchurch variant may impact the distribution of tau pathology, modulate age at onset, severity, progression, and clinical presentation of ADAD, suggesting possible therapeutic strategies.

Ketones: potential to achieve brain energy rescue and sustain cognitive health during ageing

Alzheimer’s disease (AD) is the most common major neurocognitive disorder of ageing. Although largely ignored until about a decade ago, accumulating evidence suggests that deteriorating brain energy metabolism plays a key role in the development and/or progression of AD-associated cognitive decline. Brain glucose hypometabolism is a well-established biomarker in AD but was mostly assumed to be a consequence of neuronal dysfunction and death. However, its presence in cognitively asymptomatic populations at higher risk of AD strongly suggests that it is actually a pre-symptomatic component in the development of AD. The question then arises as to whether progressive AD-related cognitive decline could be prevented or slowed down by correcting or bypassing this progressive ‘brain energy gap’. In this review, we provide an overview of research on brain glucose and ketone metabolism in AD and its prodromal condition – mild cognitive impairment (MCI) – to provide a clearer basis for proposing keto-therapeutics as a strategy for brain energy rescue in AD. We also discuss studies using ketogenic interventions and their impact on plasma ketone levels, brain energetics and cognitive performance in MCI and AD. Given that exercise has several overlapping metabolic effects with ketones, we propose that in combination these two approaches might be synergistic for brain health during ageing. As cause-and-effect relationships between the different hallmarks of AD are emerging, further research efforts should focus on optimising the efficacy, acceptability and accessibility of keto-therapeutics in AD and populations at risk of AD.

Validation of one-year reliable change in the RBANS for community-dwelling older adults with amnestic mild cognitive impairment

Objective: The current study sought to externally validate previously published standardized regression-based (SRB) equations for the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) Indexes administered twice over a one-year period. Method: Hammers and colleagues' SRB prediction equations were applied to two independent samples of community-dwelling older adults with amnestic Mild Cognitive Impairment (MCI), including those recruited from the community (n = 64) and those recruited from a memory disorders clinic (n = 58). Results: While Observed Baseline and Observed Follow-up performances were generally comparable for both MCI samples over one year, both samples possessed significantly lower Observed One-Year Follow-up scores than were predicted based on Hammers and colleagues' development sample across many RBANS Indexes. Relatedly, both amnestic MCI samples possessed a greater percentage of participants either "declining" or failing to exhibit a long-term practice effect over one year relative to expectation across most Indexes. Further, the clinic-recruited amnestic MCI sample displayed worse baseline performances, smaller long-term practice effects, and greater proportions of individual participants exhibiting a decline across one year relative to the community amnestic MCI sample. Conclusions: These findings validate Hammers and colleagues' SRB prediction equations by (1) indicating their ability to identify clinically meaningful change across RBANS Indexes in independent samples, and (2) discriminating rates of cognitive change among cognitively nuanced samples.

Measurement of neurodegeneration using a multivariate early frame amyloid PET classifier

Introduction

Amyloid measurement provides important confirmation of pathology for Alzheimer's disease (AD) clinical trials. However, many amyloid positive (Am+) early-stage subjects do not worsen clinically during a clinical trial, and a neurodegenerative measure predictive of decline could provide critical information. Studies have shown correspondence between perfusion measured by early amyloid frames post-tracer injection and fluorodeoxyglucose (FDG) positron emission tomography (PET), but with limitations in sensitivity. Multivariate machine learning approaches may offer a more sensitive means for detection of disease related changes as we have demonstrated with FDG.

Methods

Using summed dynamic florbetapir image frames acquired during the first 6 minutes post-injection for 107 Alzheimer's Disease Neuroimaging Initiative subjects, we applied optimized machine learning to develop and test image classifiers aimed at measuring AD progression. Early frame amyloid (EFA) classification was compared to that of an independently developed FDG PET AD progression classifier by scoring the FDG scans of the same subjects at the same time point. Score distributions and correlation with clinical endpoints were compared to those obtained from FDG. Region of interest measures were compared between EFA and FDG to further understand discrimination performance.

Results

The EFA classifier produced a primary pattern similar to that of the FDG classifier whose expression correlated highly with the FDG pattern (R-squared 0.71), discriminated cognitively normal (NL) amyloid negative (Am-) subjects from all Am+ groups, and that correlated in Am+ subjects with Mini-Mental State Examination, Clinical Dementia Rating Sum of Boxes, and Alzheimer's Disease Assessment Scale-13-item Cognitive subscale (R = 0.59, 0.63, 0.73) and with subsequent 24-month changes in these measures (R = 0.67, 0.73, 0.50).

Discussion

Our results support the ability to use EFA with a multivariate machine learning-derived classifier to obtain a sensitive measure of AD-related loss in neuronal function that correlates with FDG PET in preclinical and early prodromal stages as well as in late mild cognitive impairment and dementia.

Highlights

The summed initial post-injection minutes of florbetapir positron emission tomography  correlate with fluorodeoxyglucose.A machine learning classifier enabled sensitive detection of early prodromal Alzheimer's disease.Early frame amyloid (EFA) classifier scores correlate with subsequent change in Mini-Mental State Examination, Clinical Dementia Rating Sum of Boxes, and Alzheimer's Disease Assessment Scale-13-item Cognitive subscale.EFA classifier effect sizes and clinical prediction outperformed region of interest standardized uptake value ratio.EFA classification may aid in stratifying patients to assess treatment effect.

Physical activity is associated with increased resting-state functional connectivity in networks predictive of cognitive decline in clinically unimpaired older adults

Introduction

Physical activity (PA) promotes resilience with respect to cognitive decline, although the underlying mechanisms are not well understood. We examined the associations between objectively measured PA and resting-state functional connectivity magnetic resonance imaging (rs-fcMRI) across seven anatomically distributed neural networks.

Methods

rs-fcMRI, amyloid beta (Aβ) positron emission tomography (PET), PA (steps/day × 1 week), and longitudinal cognitive (Preclinical Alzheimer's Cognitive Composite) data from 167 cognitively unimpaired adults (ages 63 to 90) were used. We used linear and linear mixed-effects regression models to examine the associations between baseline PA and baseline network connectivity and between PA, network connectivity, and longitudinal cognitive performance.

Results

Higher PA was associated selectively with greater connectivity in three networks previously associated with cognitive decline (default, salience, left control). This association with network connectivity accounted for a modest portion of PA's effects on Aβ-related cognitive decline.

Discussion

Although other mechanisms are likely present, PA may promote resilience with respect to Aß-related cognitive decline, partly by increasing connectivity in a subset of cognitive networks.

Predictive Scale for Amyloid PET Positivity Based on Clinical and MRI Variables in Patients with Amnestic Mild Cognitive Impairment

The presence of amyloid-β (Aβ) deposition is considered important in patients with amnestic mild cognitive impairment (aMCI), since they can progress to Alzheimer’s disease dementia. Amyloid positron emission tomography (PET) has been used for detecting Aβ deposition, but its high cost is a significant barrier for clinical usage. Therefore, we aimed to develop a new predictive scale for amyloid PET positivity using easily accessible tools. Overall, 161 aMCI patients were recruited from six memory clinics and underwent neuropsychological tests, brain magnetic resonance imaging (MRI), apolipoprotein E (APOE) genotype testing, and amyloid PET. Among the potential predictors, verbal and visual memory tests, medial temporal lobe atrophy, APOE genotype, and age showed significant differences between the Aβ-positive and Aβ-negative groups and were combined to make a model for predicting amyloid PET positivity with the area under the curve (AUC) of 0.856. Based on the best model, we developed the new predictive scale comprising integers, which had an optimal cutoff score ≥ 3. The new predictive scale was validated in another cohort of 98 participants and showed a good performance with AUC of 0.835. This new predictive scale with accessible variables may be useful for predicting Aβ positivity in aMCI patients in clinical practice.

Differential Effects of APOE and Modifiable Risk Factors on Hippocampal Volume Loss and Memory Decline in Aβ- and Aβ+ Older Adults

BACKGROUND AND OBJECTIVES

This prospective study sought to determine the association of modifiable/nonmodifiable components included in the Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE) risk score with hippocampal volume (HV) loss and episodic memory (EM) decline in cognitively normal (CN) older adults classified as brain β-amyloid (Aβ) negative (Aβ-) or positive (Aβ+).

METHODS

Australian Imaging, Biomarkers and Lifestyle study participants (age 58-91 years) who completed ≥2 neuropsychological assessments and a brain Aβ PET scan (n = 592) were included in this study. We computed the CAIDE risk score (age, sex, APOE ε4 status, education, hypertension, body mass index [BMI], hypercholesterolemia, physical inactivity) and a modifiable CAIDE risk score (CAIDE-MR; education, hypertension, BMI, hypercholesterolemia, physical inactivity) for each participant. Aβ+ was classified using Centiloid >25. Linear mixed models assessed interactions between each CAIDE score, Aβ group, and time on HV loss and EM decline. Age, sex, and APOE ε4 were included as separate predictors in CAIDE-MR models to assess differential associations. Exploratory analyses examined relationships between individual modifiable risk factors and outcomes in Aβ- cognitively normal (CN) adults.

RESULTS

We observed a significant Aβ group × CAIDE × time interaction on HV loss (β [SE] = -0.04 [0.01]; p < 0.000) but not EM decline (β [SE] = -2.33 [9.96]; p = 0.98). Decomposition revealed a significant CAIDE × time interaction in Aβ+ participants only. When modifiable/nonmodifiable CAIDE components were considered separately, we observed a significant Aβ group × CAIDE-MR × time interaction on EM decline only (β [SE] = 3.03 [1.18]; p = 0.01). A significant CAIDE-MR score × time interaction was observed in Aβ- participants only. Significant interactions between APOE ε4 and age × time on HV loss and EM decline were observed in both groups. Exploratory analyses in Aβ- CN participants revealed a significant interaction between BMI × time on EM decline (β [SE] = -3.30 [1.43]; p = 0.02).

DISCUSSION

These results are consistent with studies showing that increasing age and APOE ε4 are associated with increased rates of HV loss and EM decline. In Aβ- CN adults, lower prevalence of modifiable cardiovascular risk factors was associated with less HV loss and EM decline over ∼10 years, suggesting interventions to reduce modifiable cardiovascular risk factors could be beneficial in this group.

Biomarkers and Tools for Predicting Alzheimer's Disease in the Preclinical Stage

Alzheimer's disease (AD) is the only leading cause of death for which no disease-modifying therapy is currently available. Over the past decade, a string of disappointing clinical trial results has forced us to shift our focus to the preclinical stage of AD, which represents the most promising therapeutic window. However, the accurate diagnosis of preclinical AD requires the presence of brain β- amyloid deposition determined by cerebrospinal fluid or amyloid-positron emission tomography, significantly limiting routine screening and diagnosis in non-tertiary hospital settings. Thus, an easily accessible marker or tool with high sensitivity and specificity is highly needed. Recently, it has been discovered that individuals in the late stage of preclinical AD may not be truly "asymptomatic" in that they may have already developed subtle or subjective cognitive decline. In addition, advances in bloodderived biomarker studies have also allowed the detection of pathologic changes in preclinical AD. Exosomes, as cell-to-cell communication messengers, can reflect the functional changes of their source cell. Methodological advances have made it possible to extract brain-derived exosomes from peripheral blood, making exosomes an emerging biomarker carrier and liquid biopsy tool for preclinical AD. The eye and its associated structures have rich sensory-motor innervation. In this regard, studies have indicated that they may also provide reliable markers. Here, our report covers the current state of knowledge of neuropsychological and eye tests as screening tools for preclinical AD and assesses the value of blood and brain-derived exosomes as carriers of biomarkers in conjunction with the current diagnostic paradigm.

Cerebrovascular disease in Suspected Non-Alzheimer's Pathophysiology and cognitive decline over time

BACKGROUND

The underlying cause of cognitive decline in individuals who are positive for biomarkers of neurodegeneration (N) but negative for biomarkers of amyloid-beta (A), designated as Suspected Non-Alzheimer's Pathophysiology (SNAP), remains unclear. We evaluate whether cerebrovascular disease (CeVD) is more prevalent in those with SNAP compared to A-N- and A+N+ individuals and whether CeVD is associated with cognitive decline over time in SNAP patients.

METHODS

A total of 216 individuals from a prospective memory clinic cohort [mean (SD) age, 72.7(7.3) years, 100 women (56.5%)] were included and were diagnosed as no cognitive impairment (NCI), cognitive impairment no dementia (CIND), Alzheimer's dementia (AD) or Vascular dementia (VaD). All individuals underwent clinical evaluation and neuropsychological assessment annually for up to 5 years. [¹¹ C]-PiB or [¹⁸ F]-Flutafuranol-PET imaging was performed to ascertain amyloid-beta status. MRI was performed to assess neurodegeneration as measured by medial temporal atrophy≥2, as well as significant CeVD (sCeVD) burden, defined by cortical infarct count≥1, Fazekas-score≥2, lacune count≥2 or cerebral microbleed count≥2.

RESULTS

Of the 216 individuals, 50(23.1%) A-N+ were (SNAP), 93(43.1%) A-N-, 36(16.7%) A+N- and 37(17.1%) A+N+. A+N+ individuals were significantly older, while A+N+ and SNAP individuals were more likely to have dementia. The SNAP group had a higher prevalence of sCeVD (90.0%) compared to A-N-. Moreover, SNAP individuals with sCeVD had significantly steeper decline in global cognition compared to A-N- over 5 years (P=0.042).

CONCLUSIONS

These findings suggest that CeVD is a contributing factor to cognitive decline in SNAP. Therefore, SNAP-individuals should be carefully assessed and treated for CeVD.

Cognitive decline, sensory impairment, and the use of audio-visual aids by long-term care facility residents

BACKGROUND

Hearing and vision impairments and the use of audio-visual aids are associated with cognitive decline in community-dwelling older people, but effects in long-term care facilities (LFCF) are unclear. We hypothesize that visual and hearing impairment are associated with cognitive decline and these relationships are mediated by using visual and hearing aids.

METHODS

Secondary data analysis of a longitudinal study was conducted in the 7 government-subsidized LTCF operated by one of the largest non-governmental organizations in Hong Kong using data between 2005 and 2016. Eligible residents were ≥ 60 years of age without severe cognitive impairment at baseline who had stayed in the facilities for more than 3 years. All variables were measured by using the Minimum Data Set-Resident Assessment Instrument Version 2.0, Hong Kong version. The outcome was cognitive decline. Predictors were visual and hearing impairments. Mediators were the use of visual and hearing aids. General linear models were employed to test the hypotheses.

RESULTS

Results for 2,233 residents were analyzed, with a mean age of 82.1 ± 8.2 years and a mean follow-up period of 4.4 ± 0.8 years. Results showed that those who had visual impairment (p = 0.004) and hearing impairments (p = 0.022) had a higher risk of cognitive decline. Using hearing aids (coefficient = 0.0186, p < 0.05) positively mediates the effect of hearing impairment on cognitive decline. Using visual aids (coefficient = -0.0881, p < 0.05) negatively mediates the effects of visual impairment on cognitive decline.

CONCLUSION

In LTCF, hearing and visual impairments are associated with a higher risk of cognitive decline. Hearing aids often-users were associated with a higher risk of cognitive decline. LTCF residents with visual impairment did not use visual aids. Use of visual aids demonstrated potential effects in slowing cognitive decline. A future study with a larger and more diverse sample with attention to quality of devices is proposed to confirm its effects.

Potential Applications of Artificial Intelligence in Clinical Trials for Alzheimer’s Disease

Clinical trials for Alzheimer’s disease (AD) face multiple challenges, such as the high screen failure rate and the even allocation of heterogeneous participants. Artificial intelligence (AI), which has become a potent tool of modern science with the expansion in the volume, variety, and velocity of biological data, offers promising potential to address these issues in AD clinical trials. In this review, we introduce the current status of AD clinical trials and the topic of machine learning. Then, a comprehensive review is focused on the potential applications of AI in the steps of AD clinical trials, including the prediction of protein and MRI AD biomarkers in the prescreening process during eligibility assessment and the likelihood stratification of AD subjects into rapid and slow progressors in randomization. Finally, this review provides challenges, developments, and the future outlook on the integration of AI into AD clinical trials.

EEG/ERP evidence of possible hyperexcitability in older adults with elevated beta-amyloid

BACKGROUND

Although growing evidence links beta-amyloid (Aβ) and neuronal hyperexcitability in preclinical mouse models of Alzheimer's disease (AD), a similar association in humans is yet to be established. The first aim of the study was to determine the association between elevated Aβ (Aβ+) and cognitive processes measured by the P3 event-related potential (ERP) in cognitively normal (CN) older adults. The second aim was to compare the event-related power between CNAβ+ and CNAβ-.

METHODS

Seventeen CNAβ+ participants (age: 73 ± 5, 11 females, Montreal Cognitive Assessment [MoCA] score 26 ± 2) and 17 CNAβ- participants group-matched for age, sex, and MOCA completed a working memory task (n-back with n = 0, 1, 2) test while wearing a 256-channel electro-encephalography net. P3 peak amplitude and latency of the target, nontarget and task difference effect (nontarget-target), and event-related power in the delta, theta, alpha, and beta bands, extracted from Fz, Cz, and Pz, were compared between groups using linear mixed models. P3 amplitude of the task difference effect at Fz and event-related power in the delta band were considered main outcomes. Correlations of mean Aβ standard uptake value ratios (SUVR) using positron emission tomography with P3 amplitude and latency of the task difference effect were analyzed using Pearson Correlation Coefficient r.

RESULTS

The P3 peak amplitude of the task difference effect at Fz was lower in the CNAβ+ group (P = 0.048). Similarly, power was lower in the delta band for nontargets at Fz in the CNAβ+ participants (P = 0.04). The CNAβ+ participants also demonstrated higher theta and alpha power in channels at Cz and Pz, but no changes in P3 ERP. Strong correlations were found between the mean Aβ SUVR and the latency of the 1-back (r =  - 0.69; P = 0.003) and 2-back (r =  - 0.69; P = 0.004) of the task difference effect at channel Fz in the CNAβ+ group.

CONCLUSIONS

Our data suggest that the elevated amyloid in cognitively normal older adults is associated with neuronal hyperexcitability. The decreased P3 task difference likely reflects early impairments in working memory processes. Further research is warranted to determine the validity of ERP in predicting clinical, neurobiological, and functional manifestations of AD.

CSF markers of AD-related pathology relate specifically to memory impairment in older people with HIV: a pilot study

Given the co-occurrence of memory impairment in HIV-associated neurocognitive disorders (HAND) and amnestic mild cognitive impairment/Alzheimer's disease (aMCI/AD), biomarkers are needed that can disentangle these conditions among people with HIV (PWH). We assessed whether cerebrospinal fluid (CSF) markers of AD could help in this effort by determining their relationship to learning and memory deficits versus cognitive deficits more characteristic of HAND than aMCI/AD (processing speed and complex visual/motor coordination) among 31 older PWH. CSF amyloid-β42 phosphorylated-tau, amyloid-β40/amyloid-β42 and phosphorylated-tau/amyloid-β42 ratio related to learning/memory performance but not HAND-related deficits, suggesting that these biomarkers may have utility in disentangling aMCI/AD from HAND.

Association of Depressive Symptoms and Cognition in Older Adults Without Dementia Across Different Biomarker Profiles

BACKGROUND

Depression is a late-life risk factor for cognitive decline. Evidence suggests an association between Alzheimer's disease (AD) associated pathologic changes and depressive symptoms.

OBJECTIVE

To investigate the influence of AT(N) biomarker profile (amyloid-β [A], p-tau [T], and neurodegeneration [N]) and gender on cross-sectional associations between subclinical depressive symptoms and cognitive function among older adults without dementia.

METHODS

Participants included 868 individuals without dementia from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Depressive symptoms were measured using the Geriatric Depression Scale (GDS). ADNI neuropsychological composite scores assessed memory and executive function (EF). PET, cerebrospinal fluid, and MRI modalities classified the study sample into biomarker profiles: normal biomarkers (A-T-N-), AD continuum (A+T±N±), and suspect non-AD pathology (SNAP; A-T±N-or A-T-N±). Multivariate regression models were used to investigate associations between GDS and cognitive domains.

RESULTS

GDS was negatively associated with memory (β= -0.156, p < 0.001) and EF (β= -0.147, p < 0.001) in the whole sample. When classified by biomarker profile, GDS was negatively associated with memory and EF in AD continuum (memory: β= -0.174, p < 0.001; EF: β= -0.129 p = 0.003) and SNAP (memory: β= -0.172, p = 0.005; EF: β= -0.197, p = 0.001) subgroups. When stratified by sex, GDS was negatively associated with memory (β= -0.227, p < 0.001) and EF (β= -0.205, p < 0.001) in men only.

CONCLUSION

The association between subclinical depressive symptoms and cognitive function is highly influenced by the AT(N) biomarker profile.

A deep learning toolbox for automatic segmentation of subcortical limbic structures from MRI images

A tool was developed to automatically segment several subcortical limbic structures (nucleus accumbens, basal forebrain, septal nuclei, hypothalamus without mammillary bodies, the mammillary bodies, and fornix) using only a T1-weighted MRI as input. This tool fills an unmet need as there are few, if any, publicly available tools to segment these clinically relevant structures. A U-Net with spatial, intensity, contrast, and noise augmentation was trained using 39 manually labeled MRI data sets. In general, the Dice scores, true positive rates, false discovery rates, and manual-automatic volume correlation were very good relative to comparable tools for other structures. A diverse data set of 698 subjects were segmented using the tool; evaluation of the resulting labelings showed that the tool failed in less than 1% of cases. Test-retest reliability of the tool was excellent. The automatically segmented volume of all structures except mammillary bodies showed effectiveness at detecting either clinical AD effects, age effects, or both. This tool will be publicly released with FreeSurfer (surfer.nmr.mgh.harvard.edu/fswiki/ScLimbic). Together with the other cortical and subcortical limbic segmentations, this tool will allow FreeSurfer to provide a comprehensive view of the limbic system in an automated way.