[¹⁸F]THK5351 PET Imaging in Patients with Mild Cognitive Impairment

Distinct effects of cholesterol profile components on amyloid and vascular burdens

BACKGROUND

Cholesterol plays important roles in β-amyloid (Aβ) metabolism and atherosclerosis. However, the relationships of plasma cholesterol levels with Aβ and cerebral small vessel disease (CSVD) burdens are not fully understood in Asians. Herein, we investigated the relationships between plasma cholesterol profile components and Aβ and CSVD burdens in a large, non-demented Korean cohort.

METHODS

We enrolled 1,175 non-demented participants (456 with unimpaired cognition [CU] and 719 with mild cognitive impairment [MCI]) aged ≥ 45 years who underwent Aβ PET at the Samsung Medical Center in Korea. We performed linear regression analyses with each cholesterol (low-density lipoprotein cholesterol [LDL-c], high-density lipoprotein cholesterol [HDL-c], and triglyceride) level as a predictor and each image marker (Aβ uptake on PET, white matter hyperintensity [WMH] volume, and hippocampal volume) as an outcome after controlling for potential confounders.

RESULTS

Increased LDL-c levels (β = 0.014 to 0.115, p = 0.013) were associated with greater Aβ uptake, independent of the APOE e4 allele genotype and lipid-lowering medication. Decreased HDL-c levels (β =  - 0.133 to - 0.006, p = 0.032) were predictive of higher WMH volumes. Increased LDL-c levels were also associated with decreased hippocampal volume (direct effect β =  - 0.053, p = 0.040), which was partially mediated by Aβ uptake (indirect effect β =  - 0.018, p = 0.006).

CONCLUSIONS

Our findings highlight that increased LDL-c and decreased HDL-c levels are important risk factors for Aβ and CSVD burdens, respectively. Furthermore, considering that plasma cholesterol profile components are potentially modified by diet, exercise, and pharmacological agents, our results provide evidence that regulating LDL-c and HDL-c levels is a potential strategy to prevent dementia.

Effect of Tablet-based Cognitive Intervention on Cognition in Patients With Mild Cognitive Impairment: A Pilot Study

Background and Purpose

Growing evidence has shown that cognitive interventions can mitigate cognitive decline in patients with mild cognitive impairment (MCI). However, most previous cognitive interventions have been group-based programs. Due to their intrinsic limitations, group-based programs are not widely used in clinical practice. Therefore, we have developed a tablet-based cognitive intervention program. This preliminary study investigated the feasibility and effects of a 12-week structured tablet-based program on cognitive function in patients with MCI.

Methods

We performed a single-arm study on 24 patients with MCI. The participants underwent a tablet-based cognitive intervention program 5 times a week over a 12-week period. The primary outcome was changes in cognitive function, measured using the Korean version of the Consortium to Establish a Registry for Alzheimer's Disease Assessment Packet (CERAD-K). Outcomes were evaluated at baseline, within two weeks of the last program (post-intervention), and at the six-month follow-up session.

Results

The completion rate of the tablet-based program was 83.3% in patients with MCI. The program improved cognitive function based on the CERAD-K total score (p=0.026), which was maintained for at least three months (p=0.004). There was also an improvement in the depression scale score (p=0.002), which persisted for three months (p=0.027).

Conclusions

Our 12-week structured tablet-based program is feasible for patients with MCI. Furthermore, although further studies with a double-arm design are required, the program appears to be an effective strategy to prevent cognitive decline in patients with MCI.

Preclinical Evaluation of Novel PET Probes for Dementia

The development of novel PET imaging agents that selectively bind specific dementia-related targets can contribute significantly to accurate, differential and early diagnosis of dementia causing diseases and support the development of therapeutic agents. Consequently, in recent years there has been a growing body of literature describing the development and evaluation of potential new promising PET tracers for dementia. This review article provides a comprehensive overview of novel dementia PET probes under development, classified by their target, and pinpoints their preclinical evaluation pathway, typically involving in silico, in vitro and ex/in vivo evaluation. Specific target-associated challenges and pitfalls, requiring extensive and well-designed preclinical experimental evaluation assays to enable successful clinical translation and avoid shortcomings observed for previously developed 'well-established' dementia PET tracers are highlighted in this review.

Evaluation of advanced, pathophysiologic new targets for imaging of CNS

The inadequate information about the in vivo pathological, physiological, and neurological impairments, as well as the absence of in vivo tools for assessing brain penetrance and the efficiency of newly designed drugs, has hampered the development of new techniques for the treatment for variety of new central nervous system (CNS) diseases. The searching sites such as Science Direct and PubMed were used to find out the numerous distinct tracers across 16 CNS targets including tau, synaptic vesicle glycoprotein, the adenosine 2A receptor, the phosphodiesterase enzyme PDE10A, and the purinoceptor, among others. Among the most encouraging are [¹⁸ F]FIMX for mGluR imaging, [¹¹ C]Martinostat for Histone deacetylase, [¹⁸ F]MNI-444 for adenosine 2A imaging, [¹¹ C]ER176 for translocator protein, and [¹⁸ F]MK-6240 for tau imaging. We also reviewed the findings for each tracer's features and potential for application in CNS pathophysiology and therapeutic evaluation investigations, including target specificity, binding efficacy, and pharmacokinetic factors. This review aims to present a current evaluation of modern positron emission tomography tracers for CNS targets, with a focus on recent advances for targets that have newly emerged for imaging in humans.

Association of Enlarged Perivascular Spaces With Amyloid Burden and Cognitive Decline in Alzheimer Disease Continuum

BACKGROUND AND OBJECTIVES

To investigate the effects of enlarged perivascular space (EPVS) on amyloid burden and cognitive function in Alzheimer disease (AD) continuum.

METHODS

We retrospectively reviewed 208 patients with AD across the cognitive continuum (preclinical, prodromal, and AD dementia) who showed amyloid deposition on 18F-florbetaben PET scans and 82 healthy controls. EPVSs were counted for each patient in the basal ganglia (BG), centrum semiovale (CSO), and hippocampus (HP) on axial T2-weighted images. Patients were then classified according to the number of EPVSs into the EPVS+ (>10 EPVSs) and EPVS- (0-10 EPVSs) groups for the BG and CSO, respectively. In terms of HP-EPVS, equal or more than 7 EPVSs on bilateral hemisphere were regarded as the presence of HP-EPVS. After adjusting for markers of small vessel disease (SVD), multiple linear regression analyses were performed to determine the intergroup differences in global and regional amyloid deposition and cognitive function at the time of diagnosis of AD continuum. A linear mixed model was used to assess the effects of EPVSs on the longitudinal changes in the Mini-Mental State Examination (MMSE) scores.

RESULTS

Amyloid burden at the time of diagnosis of AD continuum was not associated with the degree of BG-, CSO-, or HP-EPVS. BG-EPVS affected language and frontal/executive function via SVD markers, and HP-EPVS was associated with general cognition via SVD markers. However, CSO-EPVS was not associated with baseline cognition. A higher number of CSO-EPVS was significantly associated with a more rapid decline in MMSE scores (β = -0.58, standard error = 0.23, p = 0.011) independent of the amyloid burden. In terms of BG and HP, there was no difference between the EPVS+ and EPVS- groups in the rate of longitudinal decreases in MMSE scores.

DISCUSSION

Our findings suggest that BG-, CSO-, and HP-EPVS are not associated with baseline β-amyloid burden or cognitive function independently of SVD at the diagnosis of AD continuum. However, CSO-EPVS appears to be associated with the progression of cognitive decline in an amyloid-independent manner. Further studies are needed to investigate whether CSO-EPVS is a potential therapeutic target in patients with AD continuum.

Gender-specific relationship between thigh muscle and fat mass and brain amyloid-β positivity

BACKGROUND

The relationship of specific body composition in the thighs and brain amyloid-beta (Aβ) deposition remained unclear, although there were growing evidence that higher muscle and fat mass in thighs had a protective effect against cardiometabolic syndromes. To determine whether muscle mass and fat mass in the thighs affected amyloid-beta (Aβ) positivity differently in relation to gender, we investigated the association of muscle mass and fat mass with Aβ positivity using positron emission tomography (PET) in individuals without dementia.

METHODS

We recruited 240 participants (134 [55.8%] males, 106 [44.2%] females) without dementia ≥45 years of age who underwent Aβ PET, bioelectrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DEXA) scans of the hip in the health promotion center at Samsung Medical Center in Seoul, Korea. Lower extremity skeletal muscle mass index (LASMI) was measured using BIA, and gluteofemoral fat percentage (GFFP) was estimated using DEXA scans of the hip. We investigated the associations of LASMI and GFFP with Aβ positivity using logistic regression analyses after controlling for age, APOE4 genotype, and cognitive stage.

RESULTS

Higher muscle mass in the thighs, measured as LASMI (odds ratio [OR]=0.27, 95% confidence interval [CI] 0.08 to 0.84, p=0.031) was associated with a lesser risk of Aβ positivity in only females. Higher fat mass in the thighs, measured as GFFP (OR=0.84, 95% CI 0.73 to 0.95, p=0.008) was associated with a lesser risk of Aβ positivity in only males. However, the association between LAMSI (p for interaction= 0.810), GFFP (p for interaction= 0.075) and Aβ positivity did not significantly differ by gender. Furthermore, LAMSI only negatively correlated with centiloid (CL) values in females (r=-0.205, p=0.037), and GFFP only negatively correlated with CL values only in males (r=-0.253, p=0.004).

CONCLUSIONS

Our findings highlight the importance of recognizing that gender differences exist with respect to the specific body composition to potentially protect against Aβ deposition. Therefore, our results may help in designing gender-specific strategies for controlling body composition to prevent Aβ deposition.

Independent effect of body mass index variation on amyloid-β positivity

Objectives

The relationship of body mass index (BMI) changes and variability with amyloid-β (Aβ) deposition remained unclear, although there were growing evidence that BMI is associated with the risk of developing cognitive impairment or AD dementia. To determine whether BMI changes and BMI variability affected Aβ positivity, we investigated the association of BMI changes and BMI variability with Aβ positivity, as assessed by PET in a non-demented population.

Methods

We retrospectively recruited 1,035 non-demented participants ≥50 years of age who underwent Aβ PET and had at least three BMI measurements in the memory clinic at Samsung Medical Center. To investigate the association between BMI change and variability with Aβ deposition, we performed multivariable logistic regression. Further distinctive underlying features of BMI subgroups were examined by employing a cluster analysis model.

Results

Decreased (odds ratio [OR] = 1.68, 95% confidence interval [CI] 1.16–2.42) or increased BMI (OR = 1.60, 95% CI 1.11–2.32) was associated with a greater risk of Aβ positivity after controlling for age, sex, APOE e4 genotype, years of education, hypertension, diabetes, baseline BMI, and BMI variability. A greater BMI variability (OR = 1.73, 95% CI 1.07–2.80) was associated with a greater risk of Aβ positivity after controlling for age, sex, APOE e4 genotype, years of education, hypertension, diabetes, baseline BMI, and BMI change. We also identified BMI subgroups showing a greater risk of Aβ positivity.

Conclusion

Our findings suggest that participants with BMI change, especially those with greater BMI variability, are more vulnerable to Aβ deposition regardless of baseline BMI. Furthermore, our results may contribute to the design of strategies to prevent Aβ deposition with respect to weight control.

Age-related increase of monoamine oxidase B in amyloid-negative cognitively unimpaired elderly subjects

OBJECTIVE

Monoamine oxidase B (MAO-B) is highly abundant in reactive astrocytes and upregulated in neuroinflammatory processes. However, the age-related change of MAO-B in amyloid-negative cognitively unimpaired elderly subjects has not yet been sufficiently evaluated on positron emission tomography (PET). ¹⁸F-THK5351 is a radiotracer with high affinity to MAO-B, which may potentially serve as an imaging biomarker for detecting neuroinflammation. The purpose of this study was to investigate the age-related topographic change of ¹⁸F-THK5351 PET in amyloid-negative cognitively unimpaired elderly subjects.

METHODS

The age-related change of ¹⁸F-THK5351 retention was evaluated on the visual analysis, voxel and region of interest (ROI)-based analyses using Statistical Parametric Mapping and PETSurfer tool of FreeSurfer in 31 amyloid-negative cognitively unimpaired elderly subjects.

RESULTS

On visual inspection, elderly groups showed the spread of ¹⁸F-THK5351 accumulation from the medial to inferolateral temporal and basal frontal lobes, and cingulate gyrus. Additionally, voxel- and ROI-based analysis demonstrated the correlation between ¹⁸F-THK5351 accumulation and participants' age, especially in the inferior temporal lobes.

CONCLUSIONS

This study demonstrated age-dependent increase of ¹⁸F-THK5351 retention in amyloid-negative cognitively unimpaired subjects, which suggests an increase in MAO-B positive reactive astrocytes with aging.

[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.

Differential and subtype-specific neuroimaging abnormalities in amnestic and nonamnestic mild cognitive impairment: A systematic review and meta-analysis

While mild cognitive impairment (MCI) has been classified into amnestic MCI (aMCI) and nonamnestic MCI (naMCI), the neuropathological bases of these two subtypes remain elusive. Here, we performed a systematic review and meta-analysis to determine the subtype specificity of neuroimaging abnormalities in MCI and to identify neural features that may differ between aMCI and naMCI. We synthesized 50 studies that used common neuroimaging modalities, including magnetic resonance imaging and positron emission tomography, to compare brain atrophy, white matter abnormalities, cortical thinning, cerebral hypometabolism, amyloid/tau deposition, or other features among aMCI, naMCI, and normal cognition. Compared with normal cognition, aMCI shows diverse neuroimaging abnormalities of large effect sizes. In contrast, naMCI exhibits restricted abnormalities of small effect sizes. Some features, including medial temporal lobe atrophy and white matter abnormalities, are shared by the two MCI subtypes. Overall, brain abnormalities are worse, if not similar, in aMCI than in naMCI. The only neuroimaging abnormality specific to aMCI is increased amyloid burden; no feature specific to naMCI was found. Taken together, our findings have elucidated the neuropathological changes that occur in aMCI and naMCI. Clarifying the neuroimaging profiles of aMCI and naMCI can improve the early identification, differentiation, and intervention of prodromal dementia.

Harmonization of Multicenter Cortical Thickness Data by Linear Mixed Effect Model

Objective

Analyzing neuroimages being useful method in the field of neuroscience and neurology and solving the incompatibilities across protocols and vendors have become a major problem. We referred to this incompatibility as "center effects," and in this study, we attempted to correct such center effects of cortical feature obtained from multicenter magnetic resonance images (MRIs).

Methods

For MRI of a total of 4,321 multicenter subjects, the harmonized w-score was calculated by correcting biological covariates such as age, sex, years of education, and intercranial volume (ICV) as fixed effects and center information as a random effect. Afterward, we performed classification tasks using principal component analysis (PCA) and linear discriminant analysis (LDA) to check whether the center effect was successfully corrected from the harmonized w-score.

Results

First, an experiment was conducted to predict the dataset origin of a random subject sampled from two different datasets, and it was confirmed that the prediction accuracy of linear mixed effect (LME) model-based w-score was significantly closer to the baseline than that of raw cortical thickness. As a second experiment, we classified the data of the normal and patient groups of each dataset, and LME model-based w-score, which is biological-feature-corrected values, showed higher classification accuracy than the raw cortical thickness data. Afterward, to verify the compatibility of the dataset used for LME model training and the dataset that is not, intraobject comparison and w-score RMSE calculation process were performed.

Conclusion

Through comparison between the LME model-based w-score and existing methods and several classification tasks, we showed that the LME model-based w-score sufficiently corrects the center effects while preserving the disease effects from the dataset. We also showed that the preserved disease effects have a match with well-known disease atrophy patterns such as Alzheimer's disease or Parkinson's disease. Finally, through intrasubject comparison, we found that the difference between centers decreases in the LME model-based w-score compared with the raw cortical thickness and thus showed that our model well-harmonizes the data that are not used for the model training.

Differentiating amnestic from non-amnestic mild cognitive impairment subtypes using graph theoretical measures of electroencephalography

The purpose of this study was to explore different patterns of functional networks between amnestic mild cognitive impairment (aMCI) and non-aMCI (naMCI) using electroencephalography (EEG) graph theoretical analysis. The data of 197 drug-naïve individuals who complained cognitive impairment were reviewed. Resting-state EEG data was acquired. Graph analyses were performed and compared between aMCI and naMCI, as well as between early and late aMCI. Correlation analyses were conducted between the graph measures and neuropsychological test results. Machine learning algorithms were applied to determine whether the EEG graph measures could be used to distinguish aMCI from naMCI. Compared to naMCI, aMCI showed higher modularity in the beta band and lower radius in the gamma band. Modularity was negatively correlated with scores on the semantic fluency test, and the radius in the gamma band was positively correlated with visual memory, phonemic, and semantic fluency tests. The naïve Bayes algorithm classified aMCI and naMCI with 89% accuracy. Late aMCI showed inefficient and segregated network properties compared to early aMCI. Graph measures could differentiate aMCI from naMCI, suggesting that these measures might be considered as predictive markers for progression to Alzheimer’s dementia in patients with MCI.

Longitudinal Assessment of Tau-Associated Pathology by 18F-THK5351 PET Imaging: A Histological, Biochemical, and Behavioral Study

Several common and debilitating neurodegenerative disorders are characterized by the intracellular accumulation of neurofibrillary tangles (NFTs), which are composed of hyperphosphorylated tau protein. In Alzheimer's disease (AD), NFTs are accompanied by extracellular amyloid-beta (Aβ), but primary tauopathy disorders are marked by the accumulation of tau protein alone, including forms of frontotemporal dementia (FTD), corticobasal degeneration (CBD), and progressive supranuclear palsy (PSP), among others. ¹⁸F-THK5351 has been reported to bind pathological tau as well as associated reactive astrogliosis. The goal of this study was to validate the ability of the PET tracer ¹⁸F-THK5351 to detect early changes in tau-related pathology and its relation to other pathological hallmarks. We demonstrated elevated in vivo ¹⁸F-THK5351 PET signaling over time in transgenic P301S tau mice from 8 months that had a positive correlation with histological and biochemical tau changes, as well as motor, memory, and learning impairment. This study indicates that ¹⁸F-THK5351 may help fill a critical need to develop PET imaging tracers that detect aberrant tau aggregation and related neuropathology in order to diagnose the onset of tauopathies, gain insights into their underlying pathophysiologies, and to have a reliable biomarker to follow during treatment trials.

Alzheimer disease

Alzheimer disease (AD) is biologically defined by the presence of β-amyloid-containing plaques and tau-containing neurofibrillary tangles. AD is a genetic and sporadic neurodegenerative disease that causes an amnestic cognitive impairment in its prototypical presentation and non-amnestic cognitive impairment in its less common variants. AD is a common cause of cognitive impairment acquired in midlife and late-life but its clinical impact is modified by other neurodegenerative and cerebrovascular conditions. This Primer conceives of AD biology as the brain disorder that results from a complex interplay of loss of synaptic homeostasis and dysfunction in the highly interrelated endosomal/lysosomal clearance pathways in which the precursors, aggregated species and post-translationally modified products of Aβ and tau play important roles. Therapeutic endeavours are still struggling to find targets within this framework that substantially change the clinical course in persons with AD.

Identification of Heterogeneous Subtypes of Mild Cognitive Impairment Using Cluster Analyses Based on PET Imaging of Tau and Astrogliosis

Background: Mild cognitive impairment (MCI) is a condition with diverse causes and clinical outcomes that can be categorized into subtypes. [¹⁸F]THK5351 has been known to detect reactive astrogliosis as well as tau which is accompanied by neurodegenerative changes. Here, we identified heterogeneous groups of MCI patients using THK retention patterns and a graph theory approach, allowing for the comparison of risk of progression to dementia in these MCI subgroups.

Methods: Ninety-seven participants including 60 MCI patients and individuals with normal cognition (NC, n = 37) were included and undertook 3T MRI, [¹⁸F]THK5351 PET, and detailed neuropsychological tests. [¹⁸F]Flutemetamol PET was also performed in 62 participants. We calculated similarities between MCI patients using their regional standardized uptake value ratio of THK retention in 75 ROIs, and clustered subjects with similar retention patterns using the Louvain method based on the modularity of the graph. The clusters of patients identified were compared with an age-matched control group using a general linear model. Dementia conversion was evaluated after a median follow-up duration of 34.6 months.

Results: MCI patients were categorized into four groups according to their THK retention patterns: (1) limbic type; (2) diffuse type; (3) sparse type; and (4) AD type (retention pattern as in AD). Subjects of the limbic type were characterized by older age, small hippocampal volumes, and reduced verbal memory and frontal/executive functions. Patients of the diffuse type had relatively large vascular burden, reduced memory capacity and some frontal/executive functions. Co-morbidity and mortality were more frequent in this subgroup. Subjects of the sparse type were younger and declined only in terms of visual memory and attention. No individuals in this subgroup converted to dementia. Patients in the AD type group exhibited the poorest cognitive function. They also had the smallest hippocampal volumes and the highest risk of progression to dementia (90.9%).

Conclusion: Using cluster analyses with [¹⁸F]THK5351 retention patterns, it is possible to identify clinically-distinct subgroups of MCI patients and those at greater risk of progression to dementia.