Change in Cerebrospinal Fluid Tau Microtubule Binding Region Detects Symptom Onset, Cognitive Decline, Tangles, and Atrophy in Dominantly Inherited Alzheimer's Disease.

OBJECTIVE: Identifying cerebrospinal fluid measures of the microtubule binding region of tau (MTBR-tau) species that reflect tau aggregation could provide fluid biomarkers that track Alzheimer's disease related neurofibrillary tau pathological changes. We examined the cerebrospinal fluid (CSF) MTBR-tau species in dominantly inherited Alzheimer's disease (DIAD) mutation carriers to assess the association with Alzheimer's disease (AD) biomarkers and clinical symptoms. METHODS: Cross-sectional and longitudinal CSF from 229 DIAD mutation carriers and 130 mutation non-carriers had sequential characterization of N-terminal/mid-domain phosphorylated tau (p-tau) followed by MTBR-tau species and tau positron emission tomography (tau PET), other soluble tau and amyloid biomarkers, comprehensive clinical and cognitive assessments, and brain magnetic resonance imaging of atrophy. RESULTS: CSF MTBR-tau species located within the putative "border" region and one species corresponding to the "core" region of aggregates in neurofibrillary tangles (NFTs) increased during the presymptomatic stage and decreased during the symptomatic stage. The "border" MTBR-tau species were associated with amyloid pathology and CSF p-tau; whereas the "core" MTBR-tau species were associated stronger with tau PET and CSF measures of neurodegeneration. The ratio of the border to the core species provided a continuous measure of increasing amounts that tracked clinical progression and NFTs. INTERPRETATION: Changes in CSF soluble MTBR-tau species preceded the onset of dementia, tau tangle increase, and atrophy in DIAD. The ratio of 4R-specific MTBR-tau (border) to the NFT (core) MTBR-tau species corresponds to the pathology of NFTs in DIAD and change with disease progression. The dynamics between different MTBR-tau species in the CSF may serve as a marker of tau-related disease progression and target engagement of anti-tau therapeutics. ANN NEUROL 2023;93:1158-1172.

α-Synuclein seed amplification assay detects Lewy body co-pathology in autosomal dominant Alzheimer's disease late in the disease course and dependent on Lewy pathology burden.

INTRODUCTION: Amyloid beta and tau pathology are the hallmarks of sporadic Alzheimer's disease (AD) and autosomal dominant AD (ADAD). However, Lewy body pathology (LBP) is found in ≈ 50% of AD and ADAD brains. METHODS: Using an α-synuclein seed amplification assay (SAA) in cerebrospinal fluid (CSF) from asymptomatic (n = 26) and symptomatic (n = 27) ADAD mutation carriers, including 12 with known neuropathology, we investigated the timing of occurrence and prevalence of SAA positive reactivity in ADAD in vivo. RESULTS: No asymptomatic participant and only 11% (3/27) of the symptomatic patients tested SAA positive. Neuropathology revealed LBP in 10/12 cases, primarily affecting the amygdala or the olfactory areas. In the latter group, only the individual with diffuse LBP reaching the neocortex showed α-synuclein seeding activity in CSF in vivo. DISCUSSION: Results suggest that in ADAD LBP occurs later than AD pathology and often as amygdala- or olfactory-predominant LBP, for which CSF α-synuclein SAA has low sensitivity. HIGHLIGHTS: Cerebrospinal fluid (CSF) real-time quaking-induced conversion (RT-QuIC) detects misfolded α-synuclein in ≈ 10% of symptomatic autosomal dominant Alzheimer's disease (ADAD) patients. CSF RT-QuIC does not detect α-synuclein seeding activity in asymptomatic mutation carriers. Lewy body pathology (LBP) in ADAD mainly occurs as olfactory only or amygdala-predominant variants. LBP develops late in the disease course in ADAD. CSF α-synuclein RT-QuIC has low sensitivity for focal, low-burden LBP.

Translational profiling of hypocretin neurons identifies candidate molecules for sleep regulation.

Hypocretin (orexin; Hcrt)-containing neurons of the hypothalamus are essential for the normal regulation of sleep and wake behaviors and have been implicated in feeding, anxiety, depression, and reward. The absence of these neurons causes narcolepsy in humans and model organisms. However, little is known about the molecular phenotype of these cells; previous attempts at comprehensive profiling had only limited sensitivity or were inaccurate. We generated a Hcrt translating ribosome affinity purification (bacTRAP) line for comprehensive translational profiling of all ribosome-bound transcripts in these neurons in vivo. From this profile, we identified >6000 transcripts detectably expressed above background and 188 transcripts that are highly enriched in these neurons, including all known markers of the cells. Blinded analysis of in situ hybridization databases suggests that ~60% of these are expressed in a Hcrt marker-like pattern. Fifteen of these were confirmed with double labeling and microscopy, including the transcription factor Lhx9. Ablation of this gene results in a >30% loss specifically of Hcrt neurons, without a general disruption of hypothalamic development. Polysomnography and activity monitoring revealed a profound hypersomnolence in these mice. These data provide an in-depth and accurate profile of Hcrt neuron gene expression and suggest that Lhx9 may be important for specification or survival of a subset of these cells.

The clinical feasibility of deep learning-based classification of amyloid PET images in visually equivocal cases.

PURPOSE: Although most deep learning (DL) studies have reported excellent classification accuracy, these studies usually target typical Alzheimer's disease (AD) and normal cognition (NC) for which conventional visual assessment performs well. A clinically relevant issue is the selection of high-risk subjects who need active surveillance among equivocal cases. We validated the clinical feasibility of DL compared with visual rating or quantitative measurement for assessing the diagnosis and prognosis of subjects with equivocal amyloid scans. METHODS: 18F-florbetaben scans of 430 cases (85 NC, 233 mild cognitive impairment, and 112 AD) were assessed through visual rating-based, quantification-based, and DL-based methods. DL was trained using 280 two-dimensional PET images (80%) and tested by randomly assigning the remaining (70 cases, 20%) cases and a clinical validation set of 54 equivocal cases. In the equivocal cases, we assessed the agreement among the visual rating, quantification, and DL and compared the clinical outcome according to each modality-based amyloid status. RESULTS: The visual reading was positive in 175 cases, equivocal in 54 cases, and negative in 201 cases. The composite SUVR cutoff value was 1.32 (AUC 0.99). The subject-level performance of DL using the test set was 100%. Among the 54 equivocal cases, 37 cases were classified as positive (Eq(deep+)) by DL, 40 cases were classified by a second-round visual assessment, and 40 cases were classified by quantification. The DL- and quantification-based classifications showed good agreement (83%, κ = 0.59). The composite SUVRs differed between Eq(deep+) (1.47 [0.13]) and Eq(deep-) (1.29 [0.10]; P < 0.001). DL, but not the visual rating, showed a significant difference in the Mini-Mental Status Examination score change during the follow-up between Eq(deep+) (- 4.21 [0.57]) and Eq(deep-) (- 1.74 [0.76]; P = 0.023) (mean duration, 1.76 years). CONCLUSIONS: In visually equivocal scans, DL was more related to quantification than to visual assessment, and the negative cases selected by DL showed no decline in cognitive outcome. DL is useful for clinical diagnosis and prognosis assessment in subjects with visually equivocal amyloid scans.

Comparison of Amyloid ß and Tau Spread Models in Alzheimer's Disease.

Tau and amyloid ß (Aß), 2 key pathogenic proteins in Alzheimer's disease (AD), reportedly spread throughout the brain as the disease progresses. Models of how these pathogenic proteins spread from affected to unaffected areas had been proposed based on the observation that these proteins could transmit to other regions either through neural fibers (transneuronal spread model) or through extracellular space (local spread model). In this study, we modeled the spread of tau and Aß using a graph theoretical approach based on resting-state functional magnetic resonance imaging. We tested whether these models predict the distribution of tau and Aß in the brains of AD spectrum patients. To assess the models' performance, we calculated spatial correlation between the model-predicted map and the actual map from tau and amyloid positron emission tomography. The transneuronal spread model predicted the distribution of tau and Aß deposition with significantly higher accuracy than the local spread model. Compared with tau, the local spread model also predicted a comparable portion of Aß deposition. These findings provide evidence of transneuronal spread of AD pathogenic proteins in a large-scale brain network and furthermore suggest different contributions of spread models for tau and Aß in AD.

Neural substrates of cognitive reserve in Alzheimer's disease spectrum and normal aging.

The concept of cognitive reserve (CR) originated from discrepancies between the degree of brain pathology and the severity of clinical manifestations. CR has been characterized through CR proxies, such as education and occupation complexity; however, such approaches have inherent limitations. Although several methods have been developed to overcome these limitations, they fail to reflect the entire Alzheimer's disease (AD) pathology. Meanwhile, graph theory analysis, one of most powerful and flexible approaches, have established remarkable network properties of the brain. The functional and structural brain networks are damaged in neurodegenerative diseases. Therefore, network analysis has been applied to clarify the characteristics of the disease or give insight. Here, using multimodal neuroimaging, we propose an intuitive model to estimate CR based on its original definition, and explore the neural substrates of CR from the perspective of networks and functional connectivity. A total of 87 subjects (21 AD, 32 mild cognitive impairment, and 34 normal aging) underwent tau and amyloid PET, 3D T1-weighted MR, and resting-state fMRI. We hypothesized CR as a residual of actual cognitive performance and expected performance to be related to quantitative factors, such as AD pathology, demographics, and a genetic factor. Then, we correlated this marker using education and occupation complexity as conventional CR proxies. We validated this marker by testing whether it would modulate the effect of brain pathology on memory function. To examine the neural substrates associated with CR, we performed graph analysis to investigate the association between the CR marker and network measures at different granularities in total subjects, AD spectrum and normal aging, respectively. The CR marker from our model was well associated with education and occupation complexity. More directly, the CR marker was revealed to modify the relationship between brain pathology and memory function among AD spectrum. The CR marker was correlated with the global efficiency of the entire network, nodal clustering coefficient, and local efficiency of the right middle-temporal pole. In connectivity analysis, one cluster of edges centered on right middle-temporal pole was significantly correlated with the CR marker. In subgroup analysis, the network measures of right middle-temporal pole still correlated with the CR marker among AD spectrum. However, right precentral gyrus was revealed to be associated with the CR marker in normal aging. This study demonstrates that our intuitive model using multimodal neuroimaging and network perspective adequately and comprehensively captures CR. From a network perspective, CR is associated with the capacity to process information efficiently in the brain. The right middle-temporal pole was revealed to be a pivotal neural substrate of CR in AD spectrum. These findings foster understanding of AD and will be useful to help identify individuals with vulnerability or resistance to AD pathology, and characterize patients for intervention or drug trials.

Differences in gray and white matter 18F-THK5351 uptake between behavioral-variant frontotemporal dementia and other dementias.

PURPOSE: We investigated the regional distribution of 18F-THK5351 uptake in gray (GM) and white matter (WM) in patients with behavioral-variant frontotemporal dementia (bvFTD) and compared it with that in patients with Alzheimer's disease (AD) or semantic dementia (SD). METHODS: 18F-THK-5351 positron emission tomography (PET), 18F-florbetaben PET, magnetic resonance imaging, and neuropsychological testing were performed in 103 subjects including 30, 24, 9, and 8 patients with mild cognitive impairment, AD, bvFTD, and SD, respectively, and 32 normal subjects. Standardized uptake value ratios (SUVRs) of 18F-THK-5351 PET images were measured from six GM and WM regions using cerebellar GM as reference. GM and WM SUVRs and WM/GM ratios, the relationship between GM SUVR and WM/GM ratio, and correlation between SUVR and cognitive function were compared. RESULTS: In AD, both parietal GM (p < 0.001) and WM (p < 0.001) SUVRs were higher than in bvFTD. In AD and SD, the WM/GM ratio decreased as the GM SUVR increased, regardless of lobar region. In AD, memory function correlated with parietal GM (ρ = -0.74, p < 0.001) and WM (ρ = -0.53, p < 0.001) SUVR. In SD, language function correlated with temporal GM SUVR (ρ = -0.69, p = 0.006). The frontal WM SUVR was higher in bvFTD than in AD (p = 0.003) or SD (p = 0.017). The frontal WM/GM ratio was higher in bvFTD than in AD (p < 0.001). In bvFTD, the WM/GM ratio increased more prominently than the GM SUVR only in the frontal lobe (R2 = 0.026). In bvFTD, executive function correlated with frontal WM SUVR (ρ = -0.64, p = 0.014). CONCLUSIONS: Frontal WM 18F-THK5351 uptake was higher in bvFTD than in other dementias. The increase in frontal WM uptake was greater than the increase in GM uptake and correlated with executive function. This suggests that frontal lobe WM 18F-THK5351 uptake reflects neuropathological differences between bvFTD and other dementias.

Brain-State Extraction Algorithm Based on the State Transition (BEST): A Dynamic Functional Brain Network Analysis in fMRI Study.

Spatial pattern of the brain network changes dynamically. This change is closely linked to the brain-state transition, which vary depending on a dynamic stream of thoughts. To date, many dynamic methods have been developed for decoding brain-states. However, most of them only consider changes over time, not the brain-state transition itself. Here, we propose a novel dynamic functional connectivity analysis method, brain-state extraction algorithm based on state transition (BEST), which constructs connectivity matrices from the duration of brain-states and decodes the proper number of brain-states in a data-driven way. To set the duration of each brain-state, we detected brain-state transition time-points using spatial standard deviation of the brain activity pattern that changes over time. Furthermore, we also used Bayesian information criterion to the clustering method to estimate and extract the number of brain-states. Through validations, it was proved that BEST could find brain-state transition time-points and could estimate the proper number of brain-states without any a priori knowledge. It has also shown that BEST can be applied to resting state fMRI data and provide stable and consistent results.

Normalization of cortical thickness measurements across different T1 magnetic resonance imaging protocols by novel W-Score standardization.

BACKGROUND: The use of different 3D T1-weighted magnetic resonance (T1 MR) imaging protocols induces image incompatibility across multicenter studies, negating the many advantages of multicenter studies. A few methods have been developed to address this problem, but significant image incompatibility still remains. Thus, we developed a novel and convenient method to improve image compatibility. METHODS: W-score standardization creates quality reference values by using a healthy group to obtain normalized disease values. We developed a protocol-specific w-score standardization to control the protocol effect, which is applied to each protocol separately. We used three data sets. In dataset 1, brain T1 MR images of normal controls (NC) and patients with Alzheimer's disease (AD) from two centers, acquired with different T1 MR protocols, were used (Protocol 1 and 2, n = 45/group). In dataset 2, data from six subjects, who underwent MRI with two different protocols (Protocol 1 and 2), were used with different repetition times, echo times, and slice thicknesses. In dataset 3, T1 MR images from a large number of healthy normal controls (Protocol 1: n = 148, Protocol 2: n = 343) were collected for w-score standardization. The protocol effect and disease effect on subjects' cortical thickness were analyzed before and after the application of protocol-specific w-score standardization. RESULTS: As expected, different protocols resulted in differing cortical thickness measurements in both NC and AD subjects. Different measurements were obtained for the same subject when imaged with different protocols. Multivariate pattern difference between measurements was observed between the protocols. Classification accuracy between two protocols was nearly 90%. After applying protocol-specific w-score standardization, the differences between the protocols substantially decreased. Most importantly, protocol-specific w-score standardization reduced both univariate and multivariate differences in the images while maintaining the AD disease effect. Compared to conventional regression methods, our method showed the best performance for in terms of controlling the protocol effect while preserving disease information. CONCLUSIONS: Protocol-specific w-score standardization effectively resolved the concerns of conventional regression methods. It showed the best performance for improving the compatibility of a T1 MR post-processed feature, cortical thickness.

White Matter Changes May Precede Gray Matter Loss in Elderly with Subjective Memory Impairment.

BACKGROUND/AIMS: A limited number of studies addressed MRI-based neurodegenerative changes in subjective memory impairment (SMI). We investigated changes in white matter (WM) microstructures as well as gray matter (GM) macrostructures in subjects with SMI of high and low risk for progression. METHODS: A modeling scale (score range, 0-6) developed for prediction of SMI progression was used to divide SMI subjects (n = 46) into two groups: a high risk of progression (score ≥3; n = 19) and a low risk of progression (score ≤2; n = 27). Cross-sectional comparisons were performed using a region-of-interest-based diffusion tensor imaging (DTI) analysis, cortical thickness analysis, and hippocampal volumetry. RESULTS: The high-risk group had more microstructural disruption shown by lower fractional anisotropy in the hippocampus, parahippocampal gyrus, supramarginal gyrus, and parts of frontotemporal lobes. On the other hand, GM macrostructural changes did not differ between the groups and were not associated with modeling scale scores. CONCLUSION: SMI subjects with a high risk of progression had more WM microstructural disruption than those with a low risk, and the changes were not explained by GM atrophy. Our findings suggest that the degree of microstructural alterations in SMI may be distinctive according to the risk factors and may precede GM atrophy.

A potential association between COVID-19 vaccination and development of alzheimer's disease.

BACKGROUND: The challenges of the COVID-19 pandemic extend to concerns about vaccine side effects, particularly potential links to neurodegenerative diseases such as Alzheimer's disease (AD). AIM: This study investigates the association between COVID-19 vaccination and the onset of AD and its prodromal state, mild cognitive impairment (MCI). DESIGN: A nationwide, retrospective cohort study leveraging data from the Korean National Health Insurance Service was conducted. METHODS: The study, conducted in Seoul, South Korea, analyzed data from a random 50% sample of city residents aged 65 and above, totaling 558,017 individuals. Participants were divided into vaccinated and unvaccinated groups, with vaccinations including mRNA and cDNA vaccines. The study focused on AD and MCI incidences post-vaccination, identified via ICD-10 codes, using multivariable logistic and Cox regression analyses. Patients with vascular dementia or Parkinson's disease served as controls. RESULTS: Findings showed an increased incidence of MCI and AD in vaccinated individuals, particularly those receiving mRNA vaccines, within three months post-vaccination. The mRNA vaccine group exhibited a significantly higher incidence of AD (Odds Ratio [OR]: 1.225; 95% Confidence Interval [CI]: 1.025-1.464; p = 0.026) and MCI (OR: 2.377; CI: 1.845-3.064; p < 0.001) compared to the unvaccinated group. No significant relationship was found with vascular dementia or Parkinson's disease. CONCLUSIONS: Preliminary evidence suggests a potential link between COVID-19 vaccination, particularly mRNA vaccines, and increased incidences of AD and MCI. This underscores the need for further research to elucidate the relationship between vaccine-induced immune responses and neurodegenerative processes, advocating for continuous monitoring and investigation into the vaccines' long-term neurological impacts.

One-Year Longitudinal Changes in Tau Accumulation on [18F]PI-2620 PET in the Alzheimer Spectrum.

We investigated the longitudinal changes in cortical tau accumulation and their association with cognitive decline in patients in the Alzheimer disease (AD) continuum using 2-(2-([18F]fluoro)pyridin-4-yl)-9H-pyrrolo[2,3-b:4,5c']dipyridine ([18F]PI-2620) PET. Methods: We prospectively enrolled 52 participants (age, 69.7 ± 8.4 y; 18 men and 34 women): 7 with normal cognition, 28 with mild cognitive impairment, and 17 with AD. They all completed the [18F]PI-2620 and [18F]florbetaben PET, MRI, and neuropsychologic tests at baseline and, excepting the [18F]florbetaben PET, at the 1-y follow-up. Amyloid-ß (Aß) PET images were visually scored as positive (+) or negative (-). Patients on the AD continuum, including Aß+ mild cognitive impairment and AD, were classified into early-onset (EO+) (<65 y old) or late-onset (LO+) (≥65 y old) groups. [18F]PI-2620 PET SUV ratios (SUVRs) were determined by calculating the cerebral-to-inferior cerebellar ratio. Cortical volumes were calculated using 3-dimensional T1-weighted MRI. The correlation between tau accumulation progression and cognitive decline was also investigated. Results: The global [18F]PI-2620 PET SUVRs were 1.04 ± 0.07 in 15 Aß- patients, 1.18 ± 0.21 in 20 LO+ patients (age, 76.7 ± 3.8 y), and 1.54 ± 0.38 in 17 EO+ patients (age, 63.4 ± 5.4 y; P < 0.001) at baseline. The global SUVR increased over 1 y by 0.05 ± 0.07 (3.90%) and 0.13 ± 0.22 (8.41%) in the LO+ and EO+ groups, respectively, whereas in the Aß- groups, it remained unchanged. The EO+ group showed higher global and regional tau deposition than did the Aß- and LO+ groups (P < 0.05 for each) and rapid accumulation in Braak stage V (0.15 ± 0.25; 9.10% ± 12.27%; P = 0.016 and 0.008), Braak stage VI (0.08 ± 0.12; 7.16% ± 10.06%; P < 0.006 and 0.005), and global SUVR (P = 0.013) compared with the Aß- group. In the EO+ group, the changes in SUVR in Braak stages II-VI were strongly correlated with the baseline and changes in verbal memory (P < 0.03). The LO+ group showed higher tau accumulation in Braak stage I-IV areas than did the Aß- group (P < 0.001 for each). In the LO+ group, the change in SUVR in Braak stages III and IV moderately correlated with the change in attention (P < 0.05), and the change in SUVR in Braak stages V and VI moderately correlated with the change in visuospatial function (P < 0.005). Conclusion: These findings suggest that [18F]PI-2620 PET can be a biomarker to provide regional and chronologic information about tau pathology in the AD continuum.

Comparison of tau spread in people with Down syndrome versus autosomal-dominant Alzheimer's disease: a cross-sectional study.

BACKGROUND: In people with genetic forms of Alzheimer's disease, such as in Down syndrome and autosomal-dominant Alzheimer's disease, pathological changes specific to Alzheimer's disease (ie, accumulation of amyloid and tau) occur in the brain at a young age, when comorbidities related to ageing are not present. Studies including these cohorts could, therefore, improve our understanding of the early pathogenesis of Alzheimer's disease and be useful when designing preventive interventions targeted at disease pathology or when planning clinical trials. We compared the magnitude, spatial extent, and temporal ordering of tau spread in people with Down syndrome and autosomal-dominant Alzheimer's disease. METHODS: In this cross-sectional observational study, we included participants (aged ≥25 years) from two cohort studies. First, we collected data from the Dominantly Inherited Alzheimer's Network studies (DIAN-OBS and DIAN-TU), which include carriers of autosomal-dominant Alzheimer's disease genetic mutations and non-carrier familial controls recruited in Australia, Europe, and the USA between 2008 and 2022. Second, we collected data from the Alzheimer Biomarkers Consortium-Down Syndrome study, which includes people with Down syndrome and sibling controls recruited from the UK and USA between 2015 and 2021. Controls from the two studies were combined into a single group of familial controls. All participants had completed structural MRI and tau PET (18F-flortaucipir) imaging. We applied Gaussian mixture modelling to identify regions of high tau PET burden and regions with the earliest changes in tau binding for each cohort separately. We estimated regional tau PET burden as a function of cortical amyloid burden for both cohorts. Finally, we compared the temporal pattern of tau PET burden relative to that of amyloid. FINDINGS: We included 137 people with Down syndrome (mean age 38·5 years [SD 8·2], 74 [54%] male, and 63 [46%] female), 49 individuals with autosomal-dominant Alzheimer's disease (mean age 43·9 years [11·2], 22 [45%] male, and 27 [55%] female), and 85 familial controls, pooled from across both studies (mean age 41·5 years [12·1], 28 [33%] male, and 57 [67%] female), who satisfied the PET quality-control procedure for tau-PET imaging processing. 134 (98%) people with Down syndrome, 44 (90%) with autosomal-dominant Alzheimer's disease, and 77 (91%) controls also completed an amyloid PET scan within 3 years of tau PET imaging. Spatially, tau PET burden was observed most frequently in subcortical and medial temporal regions in people with Down syndrome, and within the medial temporal lobe in people with autosomal-dominant Alzheimer's disease. Across the brain, people with Down syndrome had greater concentrations of tau for a given level of amyloid compared with people with autosomal-dominant Alzheimer's disease. Temporally, increases in tau were more strongly associated with increases in amyloid for people with Down syndrome compared with autosomal-dominant Alzheimer's disease. INTERPRETATION: Although the general progression of amyloid followed by tau is similar for people Down syndrome and people with autosomal-dominant Alzheimer's disease, we found subtle differences in the spatial distribution, timing, and magnitude of the tau burden between these two cohorts. These differences might have important implications; differences in the temporal pattern of tau accumulation might influence the timing of drug administration in clinical trials, whereas differences in the spatial pattern and magnitude of tau burden might affect disease progression. FUNDING: None.

Cerebellar atrophy in patients with subcortical-type vascular cognitive impairment.

Recent studies suggest that the role of the cerebellum extends into cognitive regulation and that subcortical vascular dementia (SVaD) can result in cerebellar atrophy. However, there has been no evaluation of the cerebellar volume in the preclinical stage of SVaD. We aimed to compare cerebellar volume among patients with amnestic mild cognitive impairment (aMCI) and subcortical vascular mild cognitive impairment (svMCI) and evaluate which factors could have contributed to the cerebellar volume. Participants were composed of 355 patients with aMCI, svMCI, Alzheimer's disease (AD), and SVaD. Cerebellar volumes were measured using automated methods. A direct comparison of the cerebellar volume in SVaD and AD groups showed that the SVaD group had a statistically smaller cerebellar volume than the AD group. Additionally, the svMCI group had a smaller cerebellar volume than the aMCI group, with the number of lacunes (especially in the supratentorial regions) being associated with cerebellar volume. Cerebellar volumes were associated with some neuropsychological tests, digit span backward and ideomotor apraxia. These findings suggest that cerebellar atrophy may be useful in differentiating subtypes of dementia and the cerebellum plays a potential role in cognition.

Do radiomics or diffusion-tensor images provide additional information to predict brain amyloid-beta positivity?

The aim of the present study was to predict amyloid-beta positivity using a conventional T1-weighted image, radiomics, and a diffusion-tensor image obtained by magnetic resonance imaging (MRI). We included 186 patients with mild cognitive impairment (MCI) who underwent Florbetaben positron emission tomography (PET), MRI (three-dimensional T1-weighted and diffusion-tensor images), and neuropsychological tests at the Asan Medical Center. We developed a stepwise machine learning algorithm using demographics, T1 MRI features (volume, cortical thickness and radiomics), and diffusion-tensor image to distinguish amyloid-beta positivity on Florbetaben PET. We compared the performance of each algorithm based on the MRI features used. The study population included 72 patients with MCI in the amyloid-beta-negative group and 114 patients with MCI in the amyloid-beta-positive group. The machine learning algorithm using T1 volume performed better than that using only clinical information (mean area under the curve [AUC]: 0.73 vs. 0.69, p < 0.001). The machine learning algorithm using T1 volume showed better performance than that using cortical thickness (mean AUC: 0.73 vs. 0.68, p < 0.001) or texture (mean AUC: 0.73 vs. 0.71, p = 0.002). The performance of the machine learning algorithm using fractional anisotropy in addition to T1 volume was not better than that using T1 volume alone (mean AUC: 0.73 vs. 0.73, p = 0.60). Among MRI features, T1 volume was the best predictor of amyloid PET positivity. Radiomics or diffusion-tensor images did not provide additional benefits.

Cardiovascular risk factors cause cortical thinning in cognitively impaired patients: relationships among cardiovascular risk factors, white matter hyperintensities, and cortical atrophy.

Cardiovascular risk factors are associated with cognitive impairments. However, the effects of cardiovascular risk factors on the topography of cortical thinning have not yet been studied in patients with mild cognitive impairment (MCI) or dementia. Thus, we aimed to evaluate the topography of cortical thinning related to cardiovascular risk factors and the relationships among cardiovascular risk factors, white matter hyperintensities (WMH), and cortical atrophy. Participants included 226 patients with Alzheimer disease or subcortical vascular dementia and 135 patients with amnestic MCI or subcortical vascular MCI. We automatically measured the volume of WMH and cortical thickness. Hypertension was associated with cortical thinning in the frontal and perisylvian regions, and cortical thinning related to diabetes mellitus (DM) occurred in the frontal region. In path analyses, hypertension accounted for 0.04 of the frontal thinning with the mediation of WMH and 0.16 without the mediation of WMH. In case of DM, it accounted for 0.02 of the frontal thinning with the mediation of WMH and 0.13 without the mediation of WMH. Hypertension and DM predominantly affected frontal thinning both with and without the mediation of WMH, where the effects without the mediation of WMH were greater than those with the mediation of WMH.

Patterns of Focal Amyloid Deposition Using 18F-Florbetaben PET in Patients with Cognitive Impairment.

Accumulation of aggregated amyloid-ß (Aß) in the brain is considered the first pathological event within the pathogenesis of Alzheimer's disease (AD). It is difficult to accurately identify the initial brain regions of Aß accumulation due to the time-lag between the start of the pathophysiology and symptom onset. However, focal regional amyloid uptake on amyloid PET scans may provide insights into this. Hence, we aimed to evaluate the topographic distribution of amyloid deposition in patients with cognitive impairment and to identify the starting order of amyloid accumulation in the brain using conditional probability. We enrolled 58 patients composed of 9 normal cognition (NC), 32 mild cognitive impairment (MCI), and 17 dementia showing focal regional amyloid deposition corresponding to a brain amyloid plaque load (BAPL) score of 2 among those who visited the Memory Clinic of Asan Medical Center and underwent an 18F-florbetaben PET scan (March 2013 to April 2019). Regions of interest (ROI) included the frontal, parietal, lateral temporal, and occipital cortices, the posterior cingulate/precuneus, and the striatum. The most frequent occurrence of Aß deposition was in the posterior cingulate/precuneus (n = 41, 68.3%). The second most frequent site was the lateral temporal cortex (n = 24, 40.0%), followed by the lateral parietal cortex (n = 21, 35.6%) and other lesions, such as the frontal and occipital cortices. The striatum was the least frequently affected. Our study found that the posterior cingulate/precuneus and the lateral temporal and parietal cortices may be the earliest areas to be affected by Aß accumulation. Longitudinal follow-up of focal brain amyloid deposition may help elucidate the evolutionary pattern of Aß accumulation in the brain of people with AD continuum.

Regional Comparison of Imaging Biomarkers in the Striatum between Early- and Late-onset Alzheimer's Disease.

Striatal changes in the pathogenesis of Alzheimer's disease (AD) is not fully understood yet. We compared structural and functional image differences in the striatum between patients with early onset AD (EOAD) and late onset AD (LOAD) to investigate whether EOAD harbors autosomal dominant AD like imaging findings. The clinical, neuropsychological and neuroimaging biomarkers of 77 probable AD patients and 107 elderly subjects with normal cognition (NC) from the Alzheimer's Disease Neuroimaging Initiative (ADNI)-2 dataset were analyzed. Enrolled each subject completed a 3-Tesla MRI, baseline 18F-FDG-PET, and baseline 18F-AV-45 (Florbetapir) amyloid PET studies. AD patients were divided into two groups based on the onset age of clinical symptoms (EOAD <65 yrs; LOAD ≥65 yrs). A standardized uptake value ratio of the striatum and subcortical structures was obtained from both amyloid and FDG-PET scans. Structural MR imaging analysis was conducted using a parametric boundary description protocol, SPHARM-PDM. Of the 77 AD patients, 18 were EOAD and 59 were LOAD. Except for age of symptom onset, there were no statistically significant differences between the groups in demographics and detailed neuropsychological test results. 18F-AV-45 amyloid PET showed marked ß-amyloid accumulation in the bilateral caudate nucleus and left pallidum in the EOAD group. Intriguingly, the caudate nucleus and putamen showed maintained glucose metabolism in the EOAD group compared to the LOAD group. Our image findings in the striatum of EOAD patients suggest that sporadic EOAD may share some pathophysiological changes noted in autosomal dominant AD.

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

BACKGROUND: About 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. METHODS: This 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. RESULTS: During 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). CONCLUSION: Our findings suggest that subthreshold amyloid levels may contribute to conversion to dementia in patients with amyloid-negative amnestic MCI.

[18F]THK-5351 PET Patterns in Patients With Alzheimer's Disease and Negative Amyloid PET Findings.

BACKGROUND AND PURPOSE: Alzheimer's disease (AD) does not always mean amyloid positivity. [18F]THK-5351 has been shown to be able to detect reactive astrogliosis as well as tau accompanied by neurodegenerative changes. We evaluated the [18F]THK-5351 retention patterns in positron-emission tomography (PET) and the clinical characteristics of patients clinically diagnosed with AD dementia who had negative amyloid PET findings. METHODS: We performed 3.0-T magnetic resonance imaging, [18F]THK-5351 PET, and amyloid PET in 164 patients with AD dementia. Amyloid PET was visually scored as positive or negative. [18F]THK-5351 PET were visually classified as having an intratemporal or extratemporal spread pattern. RESULTS: The 164 patients included 23 (14.0%) who were amyloid-negative (age 74.9±8.3 years, mean±standard deviation; 9 males, 14 females). Amyloid-negative patients were older, had a higher prevalence of diabetes mellitus, and had better visuospatial and memory functions. The frequency of the apolipoprotein E ε4 allele was higher and the hippocampal volume was smaller in amyloid-positive patients. [18F]THK-5351 uptake patterns of the amyloid-negative patients were classified into intratemporal spread (n=10) and extratemporal spread (n=13). Neuropsychological test results did not differ significantly between these two groups. The standardized uptake value ratio of [18F]THK-5351 was higher in the extratemporal spread group (2.01±0.26 vs. 1.61±0.15, p=0.001). After 1 year, Mini Mental State Examination (MMSE) scores decreased significantly in the extratemporal spread group (-3.5±3.2, p=0.006) but not in the intratemporal spread group (-0.5±2.8, p=0.916). The diagnosis remained as AD (n=5, 50%) or changed to other diagnoses (n=5, 50%) in the intratemporal group, whereas it remained as AD (n=8, 61.5%) or changed to frontotemporal dementia (n=4, 30.8%) and other diagnoses (n=1, 7.7%) in the extratemporal spread group. CONCLUSIONS: Approximately 70% of the patients with amyloid-negative AD showed abnormal [18F]THK-5351 retention. MMSE scores deteriorated rapidly in the patients with an extratemporal spread pattern.