Amyloid-positive Mild Cognitive Impairment Research Articles

Comparison of plasma and neuroimaging biomarkers to predict cognitive decline in non-demented memory clinic patients.

Plasma biomarkers of Alzheimer's disease (AD) pathology, neurodegeneration, and neuroinflammation are ideally suited for secondary prevention programs in self-sufficient persons at-risk of dementia. Plasma biomarkers have been shown to be highly correlated with traditional imaging biomarkers. However, their comparative predictive value versus traditional AD biomarkers is still unclear in cognitively unimpaired (CU) subjects and with mild cognitive impairment (MCI). Plasma (Aβ42/40, p-tau181, p-tau231, NfL, and GFAP) and neuroimaging (hippocampal volume, centiloid of amyloid-PET, and tau-SUVR of tau-PET) biomarkers were assessed at baseline in 218 non-demented subjects (CU = 140; MCI = 78) from the Geneva Memory Center. Global cognition (MMSE) was evaluated at baseline and at follow-ups up to 5.7 years. We used linear mixed-effects models and Cox proportional-hazards regression to assess the association between biomarkers and cognitive decline. Lastly, sample size calculations using the linear mixed-effects models were performed on subjects positive for amyloid-PET combined with tau-PET and plasma biomarker positivity. Cognitive decline was significantly predicted in MCI by baseline plasma NfL (β=-0.55), GFAP (β=-0.36), hippocampal volume (β = 0.44), centiloid (β=-0.38), and tau-SUVR (β=-0.66) (all p < 0.05). Subgroup analysis with amyloid-positive MCI participants also showed that only NfL and GFAP were the only significant predictors of cognitive decline among plasma biomarkers. Overall, NfL and tau-SUVR showed the highest prognostic values (hazard ratios of 7.3 and 5.9). Lastly, we demonstrated that adding NfL to the inclusion criteria could reduce the sample sizes of future AD clinical trials by up to one-fourth in subjects with amyloid-PET positivity or by half in subjects with amyloid-PET and tau-PET positivity. Plasma NfL and GFAP predict cognitive decline in a similar manner to traditional imaging techniques in amyloid-positive MCI patients. Hence, even though they are non-specific biomarkers of AD, both can be implemented in memory clinic workups as important prognostic biomarkers. Likewise, future clinical trials might employ plasma biomarkers as additional inclusion criteria to stratify patients at higher risk of cognitive decline to reduce sample sizes and enhance effectiveness.

Multiomics Blood-Based Biomarkers Predict Alzheimer’s Predementia with High Specificity in a Multicentric Cohort Study

BackgroundThe primary criteria for diagnosing mild cognitive impairment (MCI) due to Alzheimer’s Disease (AD) or probable mild AD dementia rely partly on cognitive assessments and the presence of amyloid plaques. Although these criteria exhibit high sensitivity in predicting AD among cognitively impaired patients, their specificity remains limited. Notably, up to 25% of non-demented patients with amyloid plaques may be misdiagnosed with MCI due to AD, when in fact they suffer from a different brain disorder. The introduction of anti-amyloid antibodies complicates this scenario. Physicians must prioritize which amyloid-positive MCI patients receive these treatments, as not all are suitable candidates. Specifically those with non-AD amyloid pathologies are not primary targets for amyloid-modifying therapies. Consequently there is an escalating medical necessity for highly specific blood biomarkers that can accurately detect pre-dementia AD, thus optimizing amyloid antibody prescription.ObjectivesThe objective of this study was to evaluate a predictive model based on peripheral biomarkers to identify MCI and mild dementia patients who will develop AD dementia symptoms in cognitively impaired population with high specificity.DesignPeripheral biomarkers were identified in a gene transfer-based animal model of AD and then validated during a retrospective multi-center clinical study.SettingParticipants from 7 retrospective cohorts (US, EU and Australia).ParticipantsThis study followed 345 cognitively impaired individuals over up to 13 years, including 193 with MCI and 152 with mild dementia, starting from their initial visits. The final diagnoses, established during their last assessments, classified 249 participants as AD patients and 96 as having non-AD brain disorders, based on the specific diagnostic criteria for each disorder subtype. Amyloid status, assessed at baseline, was available for 82.9% of the participants, with 61.9% testing positive for amyloid. Both amyloid-positive and negative individuals were represented in each clinical group. Some of the AD patients had co-morbidities such as metabolic disorders, chronic diseases, or cardiovascular pathologies.MeasurementsWe developed targeted mass spectrometry assays for 81 blood-based biomarkers, encompassing 45 proteins and 36 metabolites previously identified in AAV-AD rats.MethodsWe analyzed blood samples from study participants for the 81 biomarkers. The B-HEALED test, a machine learning-based diagnostic tool, was developed to differentiate AD patients, including 123 with Prodromal AD and 126 with mild AD dementia, from 96 individuals with non-AD brain disorders. The model was trained using 70% of the data, selecting relevant biomarkers, calibrating the algorithm, and establishing cutoff values. The remaining 30% served as an external test dataset for blind validation of the predictive accuracy.ResultsIntegrating a combination of 19 blood biomarkers and participant age, the B-HEALED model successfully distinguished participants that will develop AD dementia symptoms (82 with Prodromal AD and 83 with AD dementia) from non-AD subjects (71 individuals) with a specificity of 93.0% and sensitivity of 65.4% (AUROC=81.9%, p<0.001) during internal validation. When the amyloid status (derived from CSF or PET scans) and the B-HEALED model were applied in association, with individuals being categorized as AD if they tested positive in both tests, we achieved 100% specificity and 52.8% sensitivity. This performance was consistent in blind external validation, underscoring the model’s reliability on independent datasets.ConclusionsThe B-HEALED test, utilizing multiomics blood-based biomarkers, demonstrates high predictive specificity in identifying AD patients within the cognitively impaired population, minimizing false positives. When used alongside amyloid screening, it effectively identifies a nearly pure prodromal AD cohort. These results bear significant implications for refining clinical trial inclusion criteria, facilitating drug development and validation, and accurately identifying patients who will benefit the most from disease-modifying AD treatments.

Health-related quality of life in subjective cognitive decline and mild cognitive impairment: a longitudinal cohort analysis

BackgroundHealth-related quality of life (HR-QoL) is an important outcome for patients and crucial for demonstrating the value of new treatments. Health utility estimates in subjective cognitive decline (SCD) and mild cognitive impairment (MCI) are limited, especially in biomarker-confirmed populations. Besides, little is known about the longitudinal HR-QoL trajectory. This study aims to provide health utility estimates for SCD and MCI and investigate the QoL trajectory along the disease continuum.MethodsLongitudinal data from 919 SCD and 1336 MCI patients from the MEMENTO cohort were included. SCD was defined as clinical dementia rating (CDR) = 0, and MCI as CDR = 0.5. HR-QoL was measured using the EQ-5D-3L patient-reported instrument. Linear mixed-effect models (LMM) were used to assess the longitudinal change in HR-QoL and identify predictors of these changes.ResultsBaseline health utilities were 0.84 ± 0.16 and 0.81 ± 0.18, and visual analogue scale (VAS) were 75.8 ± 14.82 and 70.26 ± 15.77 in SCD and MCI. In amyloid-confirmed cases, health utilities were 0.85 ± 0.14 and 0.86 ± 0.12 in amyloid-negative and amyloid-positive SCD, and 0.83 ± 0.17 and 0.84 ± 0.16 in amyloid-negative and amyloid-positive MCI. LMM revealed an annual decline in health utility of − 0.015 (SE = 0.006) and − 0.09 (SE = 0.04) in moderate and severe dementia (P < 0.05). There was a negative association between clinical stage and VAS where individuals with MCI, mild, moderate, and severe dementia were on average 1.695 (SE = 0.274), 4.401 (SE = 0.676), 4.999 (SE = 0.8), and 15.386 (SE = 3.142) VAS points lower than individuals with SCD (P < 0.001). Older age, female sex, higher body mass index, diabetes, cardiovascular history, depression, and functional impairment were associated with poor HR-QoL. Amyloid positivity was associated with an annual decline of − 0.011 (SE = 0.004, P < 0.05) health utility over time.ConclusionsHealth utility estimates from this study can be used in economic evaluations of interventions targeting SCD and MCI. Health utility declines over time in moderate and severe dementia, and VAS declines with advancing clinical stages. Amyloid-positive patients show a faster decline in health utility indicating the importance of considering biomarker status in HR-QoL assessments. Future research is needed to confirm the longitudinal relationship between amyloid status and HR-QoL and to examine the level at which depression and IADL contribute to HR-QoL decline in AD.

Longitudinal resting-state EEG in amyloid-positive patients along the Alzheimer’s disease continuum: considerations for clinical trials

BackgroundTo enable successful inclusion of electroencephalography (EEG) outcome measures in Alzheimer’s disease (AD) clinical trials, we retrospectively mapped the progression of resting-state EEG measures over time in amyloid-positive patients with mild cognitive impairment (MCI) or dementia due to AD.MethodsResting-state 21-channel EEG was recorded in 148 amyloid-positive AD patients (MCI, n = 88; dementia due to AD, n = 60). Two or more EEG recordings were available for all subjects. We computed whole-brain and regional relative power (i.e., theta (4-8 Hz), alpha1 (8-10 Hz), alpha2 (10-13 Hz), beta (13-30 Hz)), peak frequency, signal variability (i.e., theta permutation entropy), and functional connectivity values (i.e., alpha and beta corrected amplitude envelope correlation, theta phase lag index, weighted symbolic mutual information, inverted joint permutation entropy). Whole-group linear mixed effects models were used to model the development of EEG measures over time. Group-wise analysis was performed to investigate potential differences in change trajectories between the MCI and dementia subgroups. Finally, we estimated the minimum sample size required to detect different treatment effects (i.e., 50% less deterioration, stabilization, or 50% improvement) on the development of EEG measures over time, in hypothetical clinical trials of 1- or 2-year duration.ResultsWhole-group analysis revealed significant regional and global oscillatory slowing over time (i.e., increased relative theta power, decreased beta power), with strongest effects for temporal and parieto-occipital regions. Disease severity at baseline influenced the EEG measures’ rates of change, with fastest deterioration reported in MCI patients. Only AD dementia patients displayed a significant decrease of the parieto-occipital peak frequency and theta signal variability over time. We estimate that 2-year trials, focusing on amyloid-positive MCI patients, require 36 subjects per arm (2 arms, 1:1 randomization, 80% power) to detect a stabilizing treatment effect on temporal relative theta power.ConclusionsResting-state EEG measures could facilitate early detection of treatment effects on neuronal function in AD patients. Their sensitivity depends on the region-of-interest and disease severity of the study population. Conventional spectral measures, particularly recorded from temporal regions, present sensitive AD treatment monitoring markers.

Performance of a [18F]Flortaucipir PET Visual Read Method Across the Alzheimer Disease Continuum and in Dementia With Lewy Bodies.

Recently, the US Food and Drug Administration approved the tau-binding radiotracer [18F]flortaucipir and an accompanying visual read method to support the diagnostic process in cognitively impaired patients assessed for Alzheimer disease (AD). Studies evaluating this visual read method are limited. In this study, we evaluated the performance of the visual read method in participants along the AD continuum and dementia with Lewy bodies (DLB) by determining its reliability, accordance with semiquantitative analyses, and associations with clinically relevant variables. We included participants who underwent tau-PET at Amsterdam University Medical Center. A subset underwent follow-up tau-PET. Two trained nuclear medicine physicians visually assessed all scans. Inter-reader agreement was calculated using Cohen κ. To examine the concordance of visual read tau positivity with semiquantification, we defined standardized uptake value ratio (SUVr) positivity using different threshold approaches. To evaluate the prognostic value of tau-PET visual read, we performed linear mixed models with longitudinal Mini-Mental State Examination (MMSE). We included 263 participants (mean age 68.5 years, 45.6% female), including 147 cognitively unimpaired (CU) participants, 97 amyloid-positive participants with mild cognitive impairment or AD dementia (AD), and 19 participants with DLB. The visual read inter-reader agreement was excellent (κ = 0.95, CI 0.91-0.99). None of the amyloid-negative CU participants (0/92 [0%]) and 1 amyloid-negative participant with DLB (1/12 [8.3%]) were tau-positive. Among amyloid-positive participants, 13 CU participants (13/52 [25.0%]), 85 with AD (85/97 [87.6%]), and 3 with DLB (3/7 [42.9%]) were tau-positive. Two-year follow-up visual read status was identical to baseline. Tau-PET visual read corresponded strongly to SUVr status, with up to 90.4% concordance. Visual read tau positivity was associated with a decline on the MMSE in CU participants (β = -0.52, CI -0.74 to -0.30, p < 0.001) and participants with AD (β = -0.30, CI -0.58 to -0.02, p = 0.04). The excellent inter-reader agreement, strong correspondence with SUVr, and longitudinal stability indicate that the visual read method is reliable and robust, supporting clinical application. Furthermore, visual read tau positivity was associated with prospective cognitive decline, highlighting its additional prognostic potential. Future studies in unselected cohorts are needed for a better generalizability to the clinical population. This study provides Class II evidence that [18F]flortaucipir visual read accurately distinguishes patients with low tau-tracer binding from those with high tau-tracer binding and is associated with amyloid positivity and cognitive decline.

T cell exhaustion is associated with cognitive status and amyloid accumulation in Alzheimer’s disease

Studies over the last 100 years have suggested a link between inflammation, infectious disease, and Alzheimer’s Disease (AD). Understanding how the immune system changes during the development of AD may facilitate new treatments. Here, we studied an aging cohort who had been assessed for AD pathology with amyloid positron emission tomography and cognitive testing, and conducted high dimensional flow cytometry on peripheral blood mononuclear and cerebrospinal fluid cells. Participants were assigned a classification of being amyloid negative cognitively normal, amyloid positive cognitively normal (APCN), or amyloid positive mild cognitive impairment (APMCI), an early stage of AD. We observed major alterations in the peripheral innate immune system including increased myeloid and plasmacytoid dendritic cells in the blood of APMCI participants. When the adaptive immune system was examined, amyloid positive participants, regardless of cognitive status, had increased CD3+ T cells. Further analyses of CD4+ and CD8+ T cells revealed that APMCI participants had an increase in more differentiated phenotype T cells, such as effector memory and effector memory CD45RA expressing (TEMRA), compared to those with normal cognition. When T cell function was measured, we observed that T cells from APCN participants had increased IFNγ+GzB- producing cells compared to the other participants. In contrast, we demonstrate that APMCI participants had a major increase in T cells that lacked cytokine production following restimulation and expressed increased levels of PD-1 and Tox, suggesting these are exhausted cells. Rejuvenation of these cells may provide a potential treatment for AD.

Depression Is Associated with the Aberration of Resting State Default Mode Network Functional Connectivity in Patients with Amyloid-Positive Mild Cognitive Impairment.

Mild cognitive impairment (MCI) is an intermediate stage between normal aging and dementia, and a significant number of individuals with MCI progress to develop dementia. Depression is prevalent in MCI patients and has been found to influence the disease progression of MCI. The default mode network (DMN), a brain network associated with Alzheimer's disease (AD), and its functional connectivity might be a neurological mechanism linking depression and AD. However, the relationship between depression, DMN functional connectivity, and cerebral beta-amyloid (Aβ) pathology remains unclear. This study aimed to investigate DMN functional connectivity differences in Aβ-positive MCI patients with depression compared to those without depression. A total of 126 Aβ-positive MCI patients were included, with 66 having depression and 60 without depression. The results revealed increased functional connectivity in the anterior DMN in the depression group compared to the non-depression group. The functional connectivity of the anterior DMN positively correlated with depression severity but not with Aβ deposition. Our findings suggest that depression influences DMN functional connectivity in Aβ-positive MCI patients, and the depression-associated DMN functional connectivity aberrance might be an important neural mechanism linking depression, Aβ pathology, and disease progression in the trajectory of AD.

Disruption of early visual processing in amyloid-positive healthy individuals and mild cognitive impairment

BackgroundAmyloid deposition is a primary predictor of Alzheimer’s disease (AD) and related neurodegenerative disorders. Retinal changes involving the structure and function of the ganglion cell layer are increasingly documented in both established and prodromal AD. Visual event-related potentials (vERP) are sensitive to dysfunction in the magno- and parvocellular visual systems, which originate within the retinal ganglion cell layer. The present study evaluates vERP as a function of amyloid deposition in aging, and in mild cognitive impairment (MCI).MethodsvERP to stimulus-onset, motion-onset, and alpha-frequency steady-state (ssVEP) stimuli were obtained from 16 amyloid-positive and 41 amyloid-negative healthy elders and 15 MCI individuals and analyzed using time–frequency approaches. Social cognition was assessed in a subset of individuals using The Awareness of Social Inference Test (TASIT).ResultsNeurocognitively intact but amyloid-positive participants and MCI individuals showed significant deficits in stimulus-onset (theta) and motion-onset (delta) vERP generation relative to amyloid-negative participants (all p < .01). Across healthy elders, a composite index of these measures correlated highly (r = − .52, p < .001) with amyloid standardized uptake value ratios (SUVR) and TASIT performance. A composite index composed of vERP measures significant differentiated amyloid-positive and amyloid-negative groups with an overall classification accuracy of > 70%.DiscussionvERP may assist in the early detection of amyloid deposition among older individuals without observable neurocognitive impairments and in linking previously documented retinal deficits in both prodromal AD and MCI to behavioral impairments in social cognition.

New Therapeutics in Alzheimer’s Disease Longitudinal Cohort study (NTAD): study protocol

IntroductionWith the pressing need to develop treatments that slow or stop the progression of Alzheimer’s disease, new tools are needed to reduce clinical trial duration and validate new targets for...

Topographical differences in white matter hyperintensity burden and cognition in aging, MCI, and AD.

White matter hyperintensities (WMHs) are pathological changes that occur with increased age and are associated with cognitive decline. Most WMH research has not examined regional differences and focuses on a whole-brain approach. This study examined regional WMHs between normal controls (NCs), people with mild cognitive impairment (MCI), and Alzheimer's disease (AD). We also examined whether WMHs were associated with cognitive decline. Participants from the Alzheimer's Disease Neuroimaging Initiative were included if they had at least one WMH measurement and cognitive scores examining global cognition, executive functioning, and memory. Only amyloid-positive MCI and AD participants were included. A total of 1573 participants with 7381 timepoints over a maximum period of 13years were included. Linear mixed-effects models examined group differences in WMH burden and associations between WMH burden and cognition. People with MCI and AD had increased total and regional WMHs compared to NCs. An association between WMHs and cognition was observed for global cognition, executive functioning, and memory in NCs in all regions. A steeper decline (stronger association between WMH and cognition) was observed in MCI compared to NCs for all cognitive domains in all regions. A steeper decline was observed in AD compared to NCs for global cognition in only the temporal region. A strong association is observed between all cognitive domains of interest and WMH burden in healthy aging and MCI, while those with AD only had a few associations between WMH and global cognition. These findings suggest that the WMH burden is associated with changes in cognition in healthy aging and early cognitive decline.

A longitudinal study on quality of life along the spectrum of Alzheimer’s disease

BackgroundQuality of life (QoL) is an important outcome from the perspective of patients and their caregivers, in both dementia and pre-dementia stages. Yet, little is known about the long-term changes in QoL over time. We aimed to compare the trajectories of QoL between amyloid-positive and amyloid-negative SCD or MCI patients and to evaluate QoL trajectories along the Alzheimer’s disease (AD) continuum of cognitively normal to dementia.MethodsWe included longitudinal data of 447 subjective cognitive decline (SCD), 276 mild cognitive impairment (MCI), and 417 AD dementia patients from the Amsterdam Dementia Cohort. We compared QoL trajectories (EQ-5D and visual analog scale (VAS)) between (1) amyloid-positive and amyloid-negative SCD or MCI patients and (2) amyloid-positive SCD, MCI, and dementia patients with linear mixed-effect models. The models were adjusted for age, sex, Charlson Comorbidity Index (CCI), education, and EQ-5D scale (3 or 5 level).ResultsIn SCD, amyloid-positive participants had a higher VAS at baseline but showed a steeper decline over time in EQ-5D and VAS than amyloid-negative participants. Also, in MCI, amyloid-positive patients had higher QoL at baseline but subsequently showed a steeper decline in QoL over time compared to amyloid-negative patients. When we compared amyloid-positive patients along the Alzheimer continuum, we found no difference between SCD, MCI, or dementia in baseline QoL, but QoL decreased at a faster rate in the dementia stage compared with the of SCD and MCI stages.ConclusionsQoL decreased at a faster rate over time in amyloid-positive SCD or MCI patients than amyloid-negative patients. QoL decreases over time along the entire AD continuum of SCD, MCI and dementia, with the strongest decrease in dementia patients. Knowledge of QoL trajectories is essential for the future evaluation of treatments in AD.

The impact of subthreshold levels of amyloid deposition on conversion to dementia in patients with amyloid-negative amnestic mild cognitive impairment

BackgroundAbout 40–50% of patients with amnestic mild cognitive impairment (MCI) are found to have no significant Alzheimer’s pathology based on amyloid PET positivity. Notably, conversion to dementia in this population is known to occur much less often than in amyloid-positive MCI. However, the relationship between MCI and brain amyloid deposition remains largely unknown. Therefore, we investigated the influence of subthreshold levels of amyloid deposition on conversion to dementia in amnestic MCI patients with negative amyloid PET scans.MethodsThis study was a retrospective cohort study of patients with amyloid-negative amnestic MCI who visited the memory clinic of Asan Medical Center. All participants underwent detailed neuropsychological testing, brain magnetic resonance imaging, and [18F]-florbetaben (FBB) positron emission tomography scan (PET). Conversion to dementia was determined by a neurologist based on a clinical interview with a detailed neuropsychological test or a decline in the Korean version of the Mini-Mental State Examination score of more than 4 points per year combined with impaired activities of daily living. Regional cortical amyloid levels were calculated, and a receiver operating characteristic (ROC) curve for conversion to dementia was obtained. To increase the reliability of the results of the study, we analyzed the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset together.ResultsDuring the follow-up period, 36% (39/107) of patients converted to dementia from amnestic MCI. The dementia converter group displayed increased standardized uptake value ratio (SUVR) values of FBB on PET in the bilateral temporal, parietal, posterior cingulate, occipital, and left precuneus cortices as well as increased global SUVR. Among volume of interests, the left parietal SUVR predicted conversion to dementia with the highest accuracy in the ROC analysis (area under the curve [AUC] = 0.762, P < 0.001). The combination of precuneus, parietal cortex, and FBB composite SUVRs also showed a higher accuracy in predicting conversion to dementia than other models (AUC = 0.763). Of the results of ADNI data, the SUVR of the left precuneus SUVR showed the highest AUC (AUC = 0.596, P = 0.006).ConclusionOur findings suggest that subthreshold amyloid levels may contribute to conversion to dementia in patients with amyloid-negative amnestic MCI.

Disentangling Alzheimer's disease neurodegeneration from typical brain ageing using machine learning.

Neuroimaging biomarkers that distinguish between changes due to typical brain ageing and Alzheimer’s disease are valuable for determining how much each contributes to cognitive decline. Supervised machine learning models can derive multivariate patterns of brain change related to the two processes, including the Spatial Patterns of Atrophy for Recognition of Alzheimer’s Disease (SPARE-AD) and of Brain Aging (SPARE-BA) scores investigated herein. However, the substantial overlap between brain regions affected in the two processes confounds measuring them independently. We present a methodology, and associated results, towards disentangling the two.T1-weighted MRI scans of 4054 participants (48–95 years) with Alzheimer’s disease, mild cognitive impairment (MCI), or cognitively normal (CN) diagnoses from the Imaging-based coordinate SysTem for AGIng and NeurodeGenerative diseases (iSTAGING) consortium were analysed. Multiple sets of SPARE scores were investigated, in order to probe imaging signatures of certain clinically or molecularly defined sub-cohorts. First, a subset of clinical Alzheimer’s disease patients (n = 718) and age- and sex-matched CN adults (n = 718) were selected based purely on clinical diagnoses to train SPARE-BA1 (regression of age using CN individuals) and SPARE-AD1 (classification of CN versus Alzheimer’s disease) models. Second, analogous groups were selected based on clinical and molecular markers to train SPARE-BA2 and SPARE-AD2 models: amyloid-positive Alzheimer’s disease continuum group (n = 718; consisting of amyloid-positive Alzheimer’s disease, amyloid-positive MCI, amyloid- and tau-positive CN individuals) and amyloid-negative CN group (n = 718). Finally, the combined group of the Alzheimer’s disease continuum and amyloid-negative CN individuals was used to train SPARE-BA3 model, with the intention to estimate brain age regardless of Alzheimer’s disease-related brain changes.The disentangled SPARE models, SPARE-AD2 and SPARE-BA3, derived brain patterns that were more specific to the two types of brain changes. The correlation between the SPARE-BA Gap (SPARE-BA minus chronological age) and SPARE-AD was significantly reduced after the decoupling (r = 0.56–0.06). The correlation of disentangled SPARE-AD was non-inferior to amyloid- and tau-related measurements and to the number of APOE ε4 alleles but was lower to Alzheimer’s disease-related psychometric test scores, suggesting the contribution of advanced brain ageing to the latter. The disentangled SPARE-BA was consistently less correlated with Alzheimer’s disease-related clinical, molecular and genetic variables.By employing conservative molecular diagnoses and introducing Alzheimer’s disease continuum cases to the SPARE-BA model training, we achieved more dissociable neuroanatomical biomarkers of typical brain ageing and Alzheimer’s disease.

Development of prediction models for distinguishable cognitive trajectories in patients with amyloid positive mild cognitive impairment

The clinical outcomes of patients with amyloid beta-positive (Aβ+) mild cognitive impairment (MCI) are heterogeneous. We therefore developed prediction models for distinguishable cognitive trajectories in Aβ+ participants with MCI. We included 238 Aβ+ participants with MCI from the Alzheimer's Disease Neuroimaging Initiative to develop a group-based trajectory model and 63 Aβ+ participants with MCI from the Samsung Medical Center for external validation. Three distinguishable classes, slow decliners (18.5%), intermediate decliners (42.9%), and fast decliners (38.7%), were identified. Intermediate decliners were associated with older age, higher AV45 standardized uptake value ratios (SUVR) and lower fluorodeoxyglucose (FDG) SUVR than slow decliners. Fast decliners were associated with older age, presence of APOE ε4, higher AV45 SUVR and lower FDG SUVR than slow decliners. Prediction models of cognitive decline showed good discrimination and calibration capabilities in the development and validation data sets. Our analysis yields novel insights into the cognitive trajectories of Aβ+ patients with MCI, which will facilitate their effective stratification in Aβ-targeted clinical trials.

Differential levels of plasma biomarkers of neurodegeneration in Lewy body dementia, Alzheimer’s disease, frontotemporal dementia and progressive supranuclear palsy

ObjectivesThis longitudinal study compared emerging plasma biomarkers for neurodegenerative disease between controls, patients with Alzheimer’s disease (AD), Lewy body dementia (LBD), frontotemporal dementia (FTD) and progressive supranuclear palsy (PSP).MethodsPlasma phosphorylated...

Alpha power is associated with hippocampal volume in Alzheimer’s disease: A combined MEG and MRI study

AbstractBackground New Therapeutics in Alzheimer’s Disease (NTAD) is a multi‐centre, longitudinal study to develop reliable and sensitive biomarkers for patients in the early stage of Mild Cognitive Impairment (MCI) and Alzheimer’s Disease (AD). The hallmark of E/MEG abnormalities in AD patients is changes to the power and frequency of the alpha rhythm. Here, we explore spontaneous alpha oscillations in the NTAD cohort and how they relate to diagnostic condition (patient vs control), resting task (eyes open vs eyes closed) and hippocampal atrophy.MethodAt present, there has been MRI and E/MEG data collected on neurologically healthy controls (N=15; MMSE M=29.4±0.74) and amyloid positive MCI and AD patients (N=46; MMSE M=24.8±3.37). Resting‐state E/MEG recordings were obtained for two 5‐minute sessions; eyes opened and eyes closed. Average power and peak frequency were computed for each participant. A T1‐weighted MR scan was used to calculate hippocampal volume, whilst accounting for individual brain volume. Firstly, we compared the average power and peak frequency for patients and controls in both the eyes opened and eyes closed conditions. Secondly, we explored how alpha varies across these conditions and diagnoses and how these differences relate to hippocampal volume.ResultWe found that patients had lower peak frequency and power compared to controls. Specifically, there was a decreased power in eyes closed, and decreased frequency in eyes opened. These differences were also present in hippocampal volume as patients had significantly smaller hippocampi than controls, and this was correlated with decreased alpha peak frequency specifically in the eyes opened session (R2 = 0.172). These individual differences were further associated with MMSE scores.ConclusionThere are individual differences between alpha frequency and power between patients and controls. Alpha decreases with increasing cognitive impairment and is related to hippocampal volume. Whilst this is specific to eyes opened or eyes closed, results suggest that progressive atrophy of the hippocampus is associated with decreased alpha frequency. This confirms the clinical benefit of E/MEG measurements in dementia research and improve our understanding of the integration between structural and electrophysiological measures of synaptic dysfunction. Ongoing data analysis will be conducted to standardise these measures for future clinical trials.

Decreased Global EEG Synchronization in Amyloid Positive Mild Cognitive Impairment and Alzheimer's Disease Patients-Relationship to APOE ε4.

The apolipoprotein E (APOE) ε4 allele is a risk factor for Alzheimer’s disease (AD) that has been linked to changes in brain structure and function as well as to different biological subtypes of the disease. The present study aimed to investigate the association of APOE ε4 genotypes with brain functional impairment, as assessed by quantitative EEG (qEEG) in patients on the AD continuum. The study population included 101 amyloid positive patients diagnosed with mild cognitive impairment (MCI) (n = 50) and AD (n = 51) that underwent resting-state EEG recording and CSF Aβ42 analysis. In total, 31 patients were APOE ε4 non-carriers, 42 were carriers of one, and 28 were carriers of two APOE ε4 alleles. Quantitative EEG analysis included computation of the global field power (GFP) and global field synchronization (GFS) in conventional frequency bands. Amyloid positive patients who were carriers of APOE ε4 allele(s) had significantly higher GFP beta and significantly lower GFS in theta and beta bands compared to APOE ε4 non-carriers. Increased global EEG power in beta band in APOE ε4 carriers may represent a brain functional compensatory mechanism that offsets global EEG slowing in AD patients. Our findings suggest that decreased EEG measures of global synchronization in theta and beta bands reflect brain functional deficits related to the APOE ε4 genotype in patients that are on a biomarker-verified AD continuum.

Differences in structural and functional default mode network connectivity in amyloid positive mild cognitive impairment: a longitudinal study.

Default mode network (DMN) has emerged as a potential biomarker of Alzheimer's disease (AD); however, it is not clear whether it can differentiate amnestic mild cognitive impairment with altered amyloid (aMCI-Aβ +) who will evolve to AD. We evaluated if structural and functional connectivity (FC), hippocampal volumes (HV), and cerebrospinal fluid biomarkers (CSF-Aβ42, p-Tau, and t-Tau) can differentiate aMCI-Aβ + converters from non-converters. Forty-eight individuals (18 normal controls and 30 aMCI subjects in the AD continuum - with altered Aβ42 in the CSF) were followed up for an average of 13months. We used MultiAtlas, UF2C, and Freesurfer software to evaluate diffusion tensor imaging, FC, and HV, respectively, INNOTEST® kits to measure CSF proteins, and neuropsychological tests. Besides, we performed different MANOVAs with further univariate analyses to differentiate groups. During follow-up, 8/30 aMCI-Aβ + converted (26.6%) to AD dementia. There were no differences in multivariate analysis between groups in CSF biomarkers (p = 0.092) or at DMN functional connectivity (p = 0.814). aMCI-Aβ + converters had smaller right HV than controls (p = 0.013), and greater right cingulum parahippocampal bundle radial diffusivity than controls (p < 0.001) and non-converters (p = 0.036). In this exploratory study, structural, but not functional, DMN connectivity alterations may differentiate aMCI-Aβ + subjects who converted to AD dementia.

EEG-fMRI Signal Coupling Is Modulated in Subjects With Mild Cognitive Impairment and Amyloid Deposition.

Cognitive impairment indicates disturbed brain physiology which can be due to various mechanisms including Alzheimer's pathology. Combined functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) recordings (EEG-fMRI) can assess the interplay between complementary measures of brain activity and EEG changes to be localized to specific brain regions. We used a two-step approach, where we first examined changes related to a syndrome of mild cognitive impairment irrespective of pathology and then studied the specific impact of amyloid pathology. After detailed clinical and neuropsychological characterization as well as a positron emission tomography (PET) scans with the tracer 11-[C]-Pittsburgh Compound B to estimate cerebral amyloid deposition, 14 subjects with mild cognitive impairment (MCI) (mean age 75.6 SD: 8.9) according to standard criteria and 21 cognitively healthy controls (HCS) (mean age 71.8 SD: 4.2) were assessed with EEG-fMRI. Thalamo-cortical alpha-fMRI signal coupling was only observed in HCS. Additional EEG-fMRI signal coupling differences between HCS and MCI were observed in parts of the default mode network, salience network, fronto-parietal network, and thalamus. Individuals with significant cerebral amyloid deposition (amyloid-positive MCI and HCS combined compared to amyloid-negative HCS) displayed abnormal EEG-fMRI signal coupling in visual, fronto-parietal regions but also in the parahippocampus, brain stem, and cerebellum. This finding was paralleled by stronger absolute fMRI signal in the parahippocampus and weaker absolute fMRI signal in the inferior frontal gyrus in amyloid-positive subjects. We conclude that the thalamocortical coupling in the alpha band in HCS more closely reflects previous findings observed in younger adults, while in MCI there is a clearly aberrant coupling in several networks dominated by an anticorrelation in the posterior cingulate cortex. While these findings may broadly indicate physiological changes in MCI, amyloid pathology was specifically associated with abnormal fMRI signal responses and disrupted coupling between brain oscillations and fMRI signal responses, which especially involve core regions of memory: the hippocampus, para-hippocampus, and lateral prefrontal cortex.

Correlation between depressive symptom and executive function decline in amyloid positive mild cognitive impairment

AbstractBackground VDepression is a risk factor of Alzheimer’s disease dementia. We aimed to explore the correlation between depressive symptom and neuropsychological test results in mild cognitive impairment by amyloid positivity.MethodSixty‐eight individuals with MCI were recruited. All participants received a Clinical Dementia Rating score of 0.5 and met the Petersen’s criteria. Comprehensive neuropsychological assessment was performed using the SNSB II. The [18F]Florbetaben PET and MRI scans were performed. T1‐weighted MR 3D volumes were acquired for co‐registration with PET. All participants underwent Geriatric depression scale (GDS). Participants were classified as amyloid positive when the mean cortical SUVR was 1.20 and over. Correlation analyses between GDS score and each neuropsychological test standard score (z‐score based on age‐, education‐, and gender specific normative information) were performed.ResultSignificant negative correlation between GDS score and Rey Complex Figure Test Copy z score was found in all MCI participants (r = ‐0.299, p = 0.013). For amyloid positive MCI group (n = 30), we found GDS scores were significantly correlated with Rey Complex Figure Test Copy z score (r = ‐0.364, p = 0.048) and Trail Making Test A z score (r = ‐0.473, p = 0.008). However, for amyloid negative MCI group (n = 39), there was no significant correlation.ConclusionOur results suggest that amyloid positive MCI patients have significant correlation between depressive symptoms and executive function decline.