Conversion of amyloid positive and negative MCI to AD over 3 years: an 11C-PIB PET study

Deep learning model for individualized trajectory prediction of clinical outcomes in mild cognitive impairment

Objectives

Accurately predicting when patients with mild cognitive impairment (MCI) will progress to dementia is a formidable challenge. This work aims to develop a predictive deep learning model to accurately predict future cognitive decline and magnetic resonance imaging (MRI) marker changes over time at the individual level for patients with MCI.

Methods

We recruited 657 amnestic patients with MCI from the Samsung Medical Center who underwent cognitive tests, brain MRI scans, and amyloid-β (Aβ) positron emission tomography (PET) scans. We devised a novel deep learning architecture by leveraging an attention mechanism in a recurrent neural network. We trained a predictive model by inputting age, gender, education, apolipoprotein E genotype, neuropsychological test scores, and brain MRI and amyloid PET features. Cognitive outcomes and MRI features of an MCI subject were predicted using the proposed network.

Results

The proposed predictive model demonstrated good prediction performance (AUC = 0.814 ± 0.035) in five-fold cross-validation, along with reliable prediction in cognitive decline and MRI markers over time. Faster cognitive decline and brain atrophy in larger regions were forecasted in patients with Aβ (+) than with Aβ (-).

Conclusion

The proposed method provides effective and accurate means for predicting the progression of individuals within a specific period. This model could assist clinicians in identifying subjects at a higher risk of rapid cognitive decline by predicting future cognitive decline and MRI marker changes over time for patients with MCI. Future studies should validate and refine the proposed predictive model further to improve clinical decision-making.

Predicting amyloid-PET and clinical conversion in apolipoprotein E ε3/ε3 non-demented individuals with multidimensional factors

The apolipoprotein E (APOE) ε4 is a well-established risk factor of amyloid-β (Aβ) in Alzheimer's disease (AD). However, because of the high prevalence of APOE ε3, there may be a large number of people with APOE ε3/ε3 who are non-demented and have Aβ pathology. There are limited studies on assessing Aβ status and clinical conversion in the APOE ε3/ε3 non-demented population. Two hundred and ninety-three non-demented individuals with APOE ε3/ε3 from ADNI database were divided into Aβ-positron emission tomography (Aβ-PET) positivity (+) and Aβ-PET negativity (-) groups using cut-off value of >1.11. Stepwise regression searched for a single or multidimensional clinical variables for predicting Aβ-PET (+), and the receiver operating characteristic curve (ROC) assessed the accuracy of the predictive models. The Cox regression model explored the risk factors associated with clinical conversion to mild cognitive impairment (MCI) or AD. The results showed that the combination of sex, education, ventricle and white matter hyperintensity (WMH) volume can accurately predict Aβ-PET status in cognitively normal (CN), and the combination of everyday cognition study partner total (EcogSPTotal) score, age, plasma p-tau 181 and WMH can accurately predict Aβ-PET status in MCI individuals. EcogSPTotal score were independent predictors of clinical conversion to MCI or AD. The findings may provide a non-invasive and effective tool to improve the efficiency of screening Aβ-PET (+), accelerate and reduce costs of AD trial recruitment in future secondary prevention trials or help to select patients at high risk of disease progression in clinical trials.

Clinical and Neuroimaging Predictors of Alzheimer's Dementia Conversion in Patients with Mild Cognitive Impairment Using Amyloid Positron Emission Tomography by Quantitative Analysis over 2 Years

Patients with mild cognitive impairment (MCI) have a relatively high risk of developing Alzheimer's dementia (AD), so early identification of the risk for AD conversion can lessen the socioeconomic burden. In this study, 18F-Florapronol, newly developed in Korea, was used for qualitative and quantitative analyses to assess amyloid positivity. We also investigated the clinical predictors of the progression from MCI to dementia over 2 years. From December 2019 to December 2022, 50 patients with MCI were recruited at a single center, and 34 patients were included finally. Based on visual analysis, 13 (38.2%) of 34 participants were amyloid-positive, and 12 (35.3%) were positive by quantitative analysis. Moreover, 6 of 34 participants (17.6%) converted to dementia after a 2-year follow-up (p = 0.173). Among the 15 participants who were positive for amyloid in the posterior cingulate region, 5 (33.3%) patients developed dementia (p = 0.066). The Clinical Dementia Rating-Sum of Boxes (CDR-SOB) at baseline was significantly associated with AD conversion in multivariate Cox regression analyses (p = 0.043). In conclusion, these results suggest that amyloid positivity in the posterior cingulate region and higher CDR-SOB scores at baseline can be useful predictors of AD conversion in patients with MCI.

Risk of conversion to mild cognitive impairment or dementia among subjects with amyloid and tau pathology: a systematic review and meta-analysis

BACKGROUND

Measurement of beta-amyloid (Aβ) and phosphorylated tau (p-tau) levels offers the potential for early detection of neurocognitive impairment. Still, the probability of developing a clinical syndrome in the presence of these protein changes (A+ and T+) remains unclear. By performing a systematic review and meta-analysis, we investigated the risk of mild cognitive impairment (MCI) or dementia in the non-demented population with A+ and A- alone and in combination with T+ and T- as confirmed by PET or cerebrospinal fluid examination.

METHODS

A systematic search of prospective and retrospective studies investigating the association of Aβ and p-tau with cognitive decline was performed in three databases (MEDLINE via PubMed, EMBASE, and CENTRAL) on January 9, 2024. The risk of bias was assessed using the Cochrane QUIPS tool. Odds ratios (OR) and Hazard Ratios (HR) were pooled using a random-effects model. The effect of neurodegeneration was not studied due to its non-specific nature.

RESULTS

A total of 18,162 records were found, and at the end of the selection process, data from 36 cohorts were pooled (n= 7,793). Compared to the unexposed group, the odds ratio (OR) for conversion to dementia in A+ MCI patients was 5.18 [95% CI 3.93; 6.81]. In A+ CU subjects, the OR for conversion to MCI or dementia was 5.79 [95% CI 2.88; 11.64]. Cerebrospinal fluid Aβ42 or Aβ42/40 analysis and amyloid PET imaging showed consistent results. The OR for conversion in A+T+ MCI subjects (11.60 [95% CI 7.96; 16.91]) was significantly higher than in A+T- subjects (2.73 [95% CI 1.65; 4.52]). The OR for A-T+ MCI subjects was non-significant (1.47 [95% CI 0.55; 3.92]). CU subjects with A+T+ status had a significantly higher OR for conversion (13.46 [95% CI 3.69; 49.11]) than A+T- subjects (2.04 [95% CI 0.70; 5.97]). Meta-regression showed that the ORs for Aβ exposure decreased with age in MCI. (beta = -0.04 [95% CI -0.03 to -0.083]).

CONCLUSIONS

Identifying Aβ-positive individuals, irrespective of the measurement technique employed (CSF or PET), enables the detection of the most at-risk population before disease onset, or at least at a mild stage. The inclusion of tau status in addition to Aβ, especially in A+T+ cases, further refines the risk assessment. Notably, the higher odds ratio associated with Aβ decreases with age.

TRIAL REGISTRATION

The study was registered in PROSPERO (ID: CRD42021288100).

The plasma derived exosomal miRNA-483-5p/502-5p serve as potential MCI biomarkers in aging

Alzheimer's disease (AD) is the leading cause of dementia and is rapidly becoming one of the most costly, fatal diseases, which is typically discovered in the late stage of molecular pathology, at which point medication intervention is irreversible. As a result, there is an urgent need for a low-cost, least-invasive way of screening cognitive impairment, with the goal of identifying persons at risk of AD. Mild cognitive impairment (MCI) has been described as a transitional state between normal cognitive aging and AD. Early detection and timely tracking of MCI can to some extent prevent the progression towards AD. We found a population in Northwestern China has a comparatively high prevalence of MCI. Continued education, consistent exercise, and a secure financial situation can all help older people maintain cognitive function. Due to the critical role of circulating microRNAs in intercellular signaling and the perturbations thereof, their investigation has assumed paramount significance in elucidating various pathological conditions. Numerous investigations have substantiated the significance of circulating miRNAs specifically in MCI. Here, we evaluated miR-483-5p (Area Under the Curve (AUC) is 0.901, sensitivity 79.2 % and specificity 100 %) and miR-502-5p (AUC is 0.872, sensitivity 79.2 % and specificity 83.3 %), which were derived from plasma exosomes and maintained at high levels in elderly people with MCI, could be employed as promising noninvasive biomarkers.

Modified RCTU Score: A Semi-Quantitative, Visual Tool for Predicting Alzheimer's Conversion from aMCI

This research evaluated the modified RCTU score, derived from amyloid PET scans, for predicting the progression from amnestic Mild Cognitive Impairment (aMCI) to Alzheimer's Disease (AD). aMCI patients underwent baseline evaluations, including amyloid PET. AD conversion was identified through neuropsychological tests after observation. The RCTU was modified by segmenting frontal, parietal, and temporal lobes into left and right, resulting in seven areas. Scores from both modified and conventional RCTU were analyzed and compared. Among 45 patients, 12 progressed to AD (over 17.8 ± 6.8 months). AD converters showed higher scores in modified RCTU scores. Modified RCTU score had strong correlations with amyloid SUVR (r > 0.7). Modified RCTU sum score was the significant covariate of AD conversion. Modified RCTU could determine the asymmetry of amyloid deposits. We demonstrated that symmetric deposits of amyloid showed a higher risk for AD conversion when analyzed using modified RCTU. The modified RCTU score is a promising method for predicting AD conversion, correlating strongly with amyloid SUVR.

Heart rate variability and risk of agitation in Alzheimer's disease: the Atherosclerosis Risk in Communities Study

Agitation in Alzheimer's disease is common and may be related to impaired emotion regulation capacity. Heart rate variability, a proposed index of autonomic and emotion regulation neural network integrity, could be associated with agitation propensity in Alzheimer's disease. We used the Atherosclerosis Risk in Communities Study cohort data, collected over seven visits spanning over two decades, to investigate whether heart rate variability (change) was associated with agitation risk in individuals clinically diagnosed with dementia due to Alzheimer's disease. Agitation (absence/presence) at Visit 5, the primary outcome, was based on the Neuropsychiatric Inventory agitation/aggression subscale, or a composite score comprising the total number of agitation/aggression, irritability, disinhibition and aberrant motor behaviour subscales present. Visit 1-5 heart rate variability measures were the log-transformed root mean square of successive differences in R-R intervals and standard deviation of normal-to-normal R-R intervals obtained from resting, supine, standard 12-lead ECGs. To aid interpretability, heart rate variability data were scaled such that model outputs were expressed for each 0.05 log-unit change in heart rate variability (which approximated to the observed difference in heart rate variability with every 5 years of age). Among 456 participants who had dementia, 120 were clinically classified to have dementia solely attributable to Alzheimer's disease. This group showed a positive relationship between heart rate variability and agitation risk in regression models, which was strongest for measures of (potentially vagally mediated) heart rate variability change over the preceding two decades. Here, a 0.05 log-unit of heart rate variability change was associated with an up to 10-fold increase in the odds of agitation and around a half-unit increase in the composite agitation score. Associations persisted after controlling for participants' cognitive status, heart rate (change), sociodemographic factors, co-morbidities and medications with autonomic effects. Further confirmatory studies, incorporating measures of emotion regulation, are needed to support heart rate variability indices as potential agitation propensity markers in Alzheimer's disease and to explore underlying mechanisms as targets for treatment development.

Learning potential and visuospatial memory could predict amyloid-beta positron emission tomography positivity in amnestic mild cognitive impairment

We investigate the role of neuropsychological tests, including the learning potential, in predicting amyloid-beta positron emission tomography (Aβ-PET) status in amnestic mild cognitive impairment (aMCI). This cross-sectional study included 64 patients with aMCI (31 Aβ-PET (-) and 33 (+)) who visited a memory impairment clinic at Pusan National University Hospital between 2014 and 2019. Patients underwent Aβ-PET scans using 18F-florbetaben and the Seoul Neuropsychological Screening Battery. Learning potential was determined based on the difference in scores between the first and third trials of the Seoul Verbal Learning test (SVLT). Binary logistic regression was used to demonstrate the association between Aβ-PET status and cognitive tests. Predictive ability of cognitive tests for Aβ deposition was investigated using receiver operating characteristic curves analysis. From logistic regression models, the SVLT learning potential and Rey-Osterrieth Complex Figure Test (RCFT) delayed recall were found to predict Aβ-PET positivity. The areas under the curve (AUC) of the SVLT learning potential and RCFT delayed recall were significantly different from 0.5. Our findings of an association between Aβ deposition status and learning potential and visuospatial memory suggest that these cognitive tests could be used to screen patients with aMCI for Aβ deposition status.

Advances in diagnosing mild cognitive impairment and Alzheimer's disease using 11C-PIB- PET/CT and common neuropsychological tests

Alzheimer's disease (AD) is a critical health issue worldwide that has a negative impact on patients' quality of life, as well as on caregivers, society, and the environment. Positron emission tomography (PET)/computed tomography (CT) and neuropsychological scales can be used to identify AD and mild cognitive impairment (MCI) early, provide a differential diagnosis, and offer early therapies to impede the course of the illness. However, there are few reports of large-scale ¹¹C-PIB-PET/CT investigations that focus on the pathology of AD and MCI. Therefore, further research is needed to determine how neuropsychological test scales and PET/CT measurements of disease progression interact.

Differential associations of clinical features with cerebrospinal fluid biomarkers in dementia with Lewy bodies and Alzheimer's disease

AIM

To explore associations of cerebrospinal fluid biomarkers of neurodegeneration and amyloidosis with caregiver burden, cognition and functionality in dementia with Lewy bodies (DLB) paired with late-onset Alzheimer's disease (AD) and healthy older people.

METHODS

Consecutive outpatients with DLB were matched with outpatients with AD according to sex, cognitive scores and dementia stage, and with cognitively healthy controls according to age and sex to investigate associations of cerebrospinal fluid amyloid-β (Aβ₄₂,Aβ₄₀,Aβ₃₈), tau, phospho-tau Thr₁₈₁, ubiquitin, α-synuclein and neurofilament light with caregiver burden, functionality, reverse digit span, a clock drawing test, Mini-Mental State Examination (MMSE) and Severe MMSE, adjusted for sex, age, education, dementia duration and APOE-ε4 alleles.

RESULTS

Overall, 27 patients with DLB (78.98 ± 9.0 years-old; eleven APOE-ε4 +) were paired with 27 patients with AD (81.50 ± 5.8 years-old; twelve APOE-ε4 +) and 27 controls (78.98 ± 8.7 years-old; four APOE-ε4 +); two-thirds were women. In AD, Aβ₄₂/Aβ₃₈ and Aβ₄₂ were lower, while tau/Aβ₄₂ and phospho-tau Thr₁₈₁/Aβ₄₂ were higher; α-synuclein/Aβ₄₂ was lower in DLB and higher in AD. The following corrected associations remained significant: in DLB, instrumental functionality was inversely associated with tau/phospho-tau Thr₁₈₁ and tau/Aβ₄₂, and reverse digit span associated with α-synuclein; in AD, instrumental functionality was inversely associated with neurofilament light, clock drawing test scores inversely associated with phospho-tau Thr₁₈₁/Aβ₄₂ and α-synuclein/Aβ₄₂, and Severe MMSE inversely associated with tau/Aβ₄₂ and tau/phospho-tau Thr₁₈₁.

CONCLUSIONS

Cerebrospinal fluid phospho-tau Thr₁₈₁ in DLB was similar to AD, but not Aβ₄₂. In associations with test scores, biomarker ratios were superior to isolated biomarkers, while worse functionality was associated with axonal degeneration only in AD.

Prediction of Amyloid β-Positivity with both MRI Parameters and Cognitive Function Using Machine Learning

Purpose

To investigate the MRI markers for the prediction of amyloid β (Aβ)-positivity in mild cognitive impairment (MCI) and Alzheimer's disease (AD), and to evaluate the differences in MRI markers between Aβ-positive (Aβ [+]) and -negative groups using the machine learning (ML) method.

Materials and Methods

This study included 139 patients with MCI and AD who underwent amyloid PET-CT and brain MRI. Patients were divided into Aβ (+) (n = 84) and Aβ-negative (n = 55) groups. Visual analysis was performed with the Fazekas scale of white matter hyperintensity (WMH) and cerebral microbleeds (CMB) scores. The WMH volume and regional brain volume were quantitatively measured. The multivariable logistic regression and ML using support vector machine, and logistic regression were used to identify the best MRI predictors of Aβ-positivity.

Results

The Fazekas scale of WMH (p = 0.02) and CMB scores (p = 0.04) were higher in Aβ (+). The volumes of hippocampus, entorhinal cortex, and precuneus were smaller in Aβ (+) (p < 0.05). The third ventricle volume was larger in Aβ (+) (p = 0.002). The logistic regression of ML showed a good accuracy (81.1%) with mini-mental state examination (MMSE) and regional brain volumes.

Conclusion

The application of ML using the MMSE, third ventricle, and hippocampal volume is helpful in predicting Aβ-positivity with a good accuracy.

Predicting Brain Amyloid Positivity from T1 weighted brain MRI and MRI-derived Gray Matter, White Matter and CSF maps using Transfer Learning on 3D CNNs

Abnormal β-amyloid (Aβ) accumulation in the brain is an early indicator of Alzheimer's disease and practical tests could help identify patients who could respond to treatment, now that promising anti-amyloid drugs are available. Even so, Aβ positivity (Aβ+) is assessed using PET or CSF assays, both highly invasive procedures. Here, we investigate how well Aβ+ can be predicted from T1 weighted brain MRI and gray matter, white matter and cerebrospinal fluid segmentations from T1-weighted brain MRI (T1w), a less invasive alternative. We used 3D convolutional neural networks to predict Aβ+ based on 3D brain MRI data, from 762 elderly subjects (mean age: 75.1 yrs. ± 7.6SD; 394F/368M; 459 healthy controls, 67 with MCI and 236 with dementia) scanned as part of the Alzheimer's Disease Neuroimaging Initiative. We also tested whether the accuracy increases when using transfer learning from the larger UK Biobank dataset. Overall, the 3D CNN predicted Aβ+ with 76% balanced accuracy from T1w scans. The closest performance to this was using white matter maps alone when the model was pre-trained on an age prediction in the UK Biobank. The performance of individual tissue maps was less than the T1w, but transfer learning helped increase the accuracy. Although tests on more diverse data are warranted, deep learned models from standard MRI show initial promise for Aβ+ estimation, before considering more invasive procedures.

Plasma extracellular vesicles reveal early molecular differences in amyloid positive patients with early-onset mild cognitive impairment

In the clinical course of Alzheimer's disease (AD) development, the dementia phase is commonly preceded by a prodromal AD phase, which is mainly characterized by reaching the highest levels of Aβ and p-tau-mediated neuronal injury and a mild cognitive impairment (MCI) clinical status. Because of that, most AD cases are diagnosed when neuronal damage is already established and irreversible. Therefore, a differential diagnosis of MCI causes in these prodromal stages is one of the greatest challenges for clinicians. Blood biomarkers are emerging as desirable tools for pre-screening purposes, but the current results are still being analyzed and much more data is needed to be implemented in clinical practice. Because of that, plasma extracellular vesicles (pEVs) are gaining popularity as a new source of biomarkers for the early stages of AD development. To identify an exosome proteomics signature linked to prodromal AD, we performed a cross-sectional study in a cohort of early-onset MCI (EOMCI) patients in which 184 biomarkers were measured in pEVs, cerebrospinal fluid (CSF), and plasma samples using multiplex PEA technology of Olink^© proteomics. The obtained results showed that proteins measured in pEVs from EOMCI patients with established amyloidosis correlated with CSF p-tau¹⁸¹ levels, brain ventricle volume changes, brain hyperintensities, and MMSE scores. In addition, the correlations of pEVs proteins with different parameters distinguished between EOMCI Aβ( +) and Aβ(-) patients, whereas the CSF or plasma proteome did not. In conclusion, our findings suggest that pEVs may be able to provide information regarding the initial amyloidotic changes of AD. Circulating exosomes may acquire a pathological protein signature of AD before raw plasma, becoming potential biomarkers for identifying subjects at the earliest stages of AD development.

Cognitive Trajectories and Associated Biomarkers in Patients with Mild Cognitive Impairment

BACKGROUND

To diagnose mild cognitive impairment (MCI) patients at risk of progression to dementia is clinically important but challenging.

OBJECTIVE

We classified MCI patients based on cognitive trajectories and compared biomarkers among groups.

METHODS

This study analyzed amnestic MCI patients with at least three Clinical Dementia Rating (CDR) scores available over a minimum of 36 months from the Alzheimer's Disease Neuroimaging Initiative database. Patients were classified based on their progression using trajectory modeling with the CDR-sum of box scores. We compared clinical and neuroimaging biomarkers across groups.

RESULTS

Of 569 eligible MCI patients (age 72.7±7.4 years, women n = 223), three trajectory groups were identified: stable (58.2%), slow decliners (24.6%), and fast decliners (17.2%). In the fifth year after diagnosis, the CDR-sum of box scores increased by 1.2, 5.4, and 11.8 points for the stable, slow, and fast decliners, respectively. Biomarkers associated with cognitive decline were amyloid-β 42, total tau, and phosphorylated tau protein in cerebrospinal fluid, hippocampal volume, cortical metabolism, and amount of cortical and subcortical amyloid deposits. Cortical metabolism and the amount of amyloid deposits were associated with the rate of cognitive decline.

CONCLUSION

Data-driven trajectory analysis provides new insights into the various cognitive trajectories of MCI. Baseline brain metabolism, and the amount of cortical and subcortical amyloid burden can provide additional information on the rate of cognitive decline.

Altered Feedback-Related Negativity in Mild Cognitive Impairment

INTRODUCTION

Feedback-related negativity (FRN) is electrical brain activity related to the function of monitoring behavior and its outcome. FRN is generated by negative feedback input, such as punishment or monetary loss, and its potential is distributed maximally over the frontal-central part of the skull. Our previous study demonstrated that FRN latency was delayed and that the amplitude was increased in patients with mild Alzheimer's disease (AD). As mild cognitive impairment (MCI) is considered to be a prodromal stage of AD, we speculated that FRN would also be altered in MCI, as in AD. The aim of this study is to examine whether MCI patients showed changes in FRN during a gambling task.

METHODS

Thirteen MCI patients and thirteen age-matched healthy elderly individuals participated in a simple gambling task and underwent neuro-psychological assessments. The participants were asked to choose one out of two options and randomly received positive or negative feedback to their response. An EEG was recorded during the task, and FRN was obtained by subtracting the positive feedback-related activity from the negative feedback-related activity.

RESULTS

The reaction time to probe stimuli was comparable in the two groups. The group comparisons revealed that the FRN amplitude was significantly larger for the MCI group than for the healthy elderly (F(1,24) = 6.4, η_p² = 0.22, p = 0.019), but there was no group difference in the FRN latency. The FRN amplitude at the frontocentral electrode positively correlated with the mini-mental state examination score (Spearman's rho_partial = 0.41, p = 0.043). The finding of increased FRN amplitude in MCI was consistent with the previous finding in AD.

CONCLUSION

Our findings indicate that monitoring dysfunction might also be involved in the prodromal stage of dementia.

PET molecular imaging for pathophysiological visualization in Alzheimer's disease

Alzheimer's disease (AD) is the most common dementia worldwide. The exact etiology of AD is unclear as yet, and no effective treatments are currently available, making AD a tremendous burden posed on the whole society. As AD is a multifaceted and heterogeneous disease, and most biomarkers are dynamic in the course of AD, a range of biomarkers should be established to evaluate the severity and prognosis. Positron emission tomography (PET) offers a great opportunity to visualize AD from diverse perspectives by using radiolabeled agents involved in various pathophysiological processes; PET imaging technique helps to explore the pathomechanisms of AD comprehensively and find out the most appropriate biomarker in each AD phase, leading to a better evaluation of the disease. In this review, we discuss the application of PET in the course of AD and summarized radiolabeled compounds with favorable imaging characteristics.

Amyloid-β PET in Alzheimer's disease: A systematic review and Bayesian meta-analysis

BACKGROUND

In recent years, longitudinal studies of Alzheimer's disease (AD) have been successively concluded. Our aim is to determine the efficacy of amyloid-β (Aβ) PET in diagnosing AD and early prediction of mild cognitive impairment (MCI) converting to AD. By pooling studies from different centers to explore in-depth whether diagnostic performance varies by population type, radiotracer type, and diagnostic approach, thus providing a more comprehensive theoretical basis for the subsequent widespread application of Aβ PET in the clinical setting.

METHODS

Relevant studies were searched through PubMed. The pooled sensitivities, specificities, DOR, and the summary ROC curve were obtained based on a Bayesian random-effects model.

RESULTS

Forty-eight studies, including 5967 patients, were included. Overall, the pooled sensitivity, specificity, DOR, and AUC of Aβ PET for diagnosing AD were 0.90, 0.80, 35.68, and 0.91, respectively. Subgroup analysis showed that Aβ PET had high sensitivity (0.91) and specificity (0.81) for differentiating AD from normal controls but very poor specificity (0.49) for determining AD from MCI. The pooled sensitivity and specificity were 0.84 and 0.62, respectively, for predicting the conversion of MCI to AD. The differences in diagnostic efficacy between visual assessment and quantitative analysis and between ¹¹ C-PIB PET and ¹⁸ F-florbetapir PET were insignificant.

CONCLUSIONS

The overall performance of Aβ PET in diagnosing AD is favorable, but the differentiation between MCI and AD patients should consider that some MCI may be at risk of conversion to AD and may be misdiagnosed. A multimodal diagnostic approach and machine learning analysis may be effective in improving diagnostic accuracy.

Impact of Amyloid Pathology in Mild Cognitive Impairment Subjects: The Longitudinal Cognition and Surface Morphometry Data

The amyloid framework forms the central medical theory related to Alzheimer disease (AD), and the in vivo demonstration of amyloid positivity is essential for diagnosing AD. On the basis of a longitudinal cohort design, the study investigated clinical progressive patterns by obtaining cognitive and structural measurements from a group of patients with amnestic mild cognitive impairment (MCI); the measurements were classified by the positivity (Aβ+) or absence (Aβ-) of the amyloid biomarker. We enrolled 185 patients (64 controls, 121 patients with MCI). The patients with MCI were classified into two groups on the basis of their [¹⁸F]flubetaben or [¹⁸F]florbetapir amyloid positron-emission tomography scan (Aβ+ vs. Aβ-, 67 vs. 54 patients) results. Data from annual cognitive measurements and three-dimensional T1 magnetic resonance imaging scans were used for between-group comparisons. To obtain longitudinal cognitive test scores, generalized estimating equations were applied. A linear mixed effects model was used to compare the time effect of cortical thickness degeneration. The cognitive decline trajectory of the Aβ+ group was obvious, whereas the Aβ- and control groups did not exhibit a noticeable decline over time. The group effects of cortical thickness indicated decreased entorhinal cortex in the Aβ+ group and supramarginal gyrus in the Aβ- group. The topology of neurodegeneration in the Aβ- group was emphasized in posterior cortical regions. A comparison of the changes in the Aβ+ and Aβ- groups over time revealed a higher rate of cortical thickness decline in the Aβ+ group than in the Aβ- group in the default mode network. The Aβ+ and Aβ- groups experienced different APOE ε4 effects. For cortical-cognitive correlations, the regions associated with cognitive decline in the Aβ+ group were mainly localized in the perisylvian and anterior cingulate regions. By contrast, the degenerative topography of Aβ- MCI was scattered. The memory learning curves, cognitive decline patterns, and cortical degeneration topographies of the two MCI groups were revealed to be different, suggesting a difference in pathophysiology. Longitudinal analysis may help to differentiate between these two MCI groups if biomarker access is unavailable in clinical settings.

Novel brain PET imaging agents: Strategies for imaging neuroinflammation in Alzheimer’s disease and mild cognitive impairment

Alzheimer’s disease (AD) is a devastating neurodegenerative disease with a concealed onset and continuous deterioration. Mild cognitive impairment (MCI) is the prodromal stage of AD. Molecule-based imaging with positron emission tomography (PET) is critical in tracking pathophysiological changes among AD and MCI patients. PET with novel targets is a promising approach for diagnostic imaging, particularly in AD patients. Our present review overviews the current status and applications of in vivo molecular imaging toward neuroinflammation. Although radiotracers can remarkably diagnose AD and MCI patients, a variety of limitations prevent the recommendation of a single technique. Recent studies examining neuroinflammation PET imaging suggest an alternative approach to evaluate disease progression. This review concludes that PET imaging towards neuroinflammation is considered a promising approach to deciphering the enigma of the pathophysiological process of AD and MCI.

Change in brain amyloid load and cognition in patients with amnestic mild cognitive impairment: a 3-year follow-up study

Background

Our aim was to investigate the discriminative value of ¹⁸F-Flutemetamol PET in longitudinal assessment of amyloid beta accumulation in amnestic mild cognitive impairment (aMCI) patients, in relation to longitudinal cognitive changes.

Methods

We investigated the change in ¹⁸F-Flutemetamol uptake and cognitive impairment in aMCI patients over time up to 3 years which enabled us to investigate possible association between changes in brain amyloid load and cognition over time. Thirty-four patients with aMCI (mean age 73.4 years, SD 6.6) were examined with ¹⁸F-Flutemetamol PET scan, brain MRI and cognitive tests at baseline and after 3-year follow-up or earlier if the patient had converted to Alzheimer´s disease (AD). ¹⁸F-Flutemetamol data were analyzed both with automated region-of-interest analysis and voxel-based statistical parametric mapping.

Results

¹⁸F-flutemetamol uptake increased during the follow-up, and the increase was significantly higher in patients who were amyloid positive at baseline as compared to the amyloid-negative ones. At follow-up, there was a significant association between ¹⁸F-Flutemetamol uptake and MMSE, logical memory I (immediate recall), logical memory II (delayed recall) and verbal fluency. An association was seen between the increase in ¹⁸F-Flutemetamol uptake and decline in MMSE and logical memory I scores.

Conclusions

In the early phase of aMCI, presence of amyloid pathology at baseline strongly predicted amyloid accumulation during follow-up, which was further paralleled by cognitive declines. Inversely, some of our patients remained amyloid negative also at the end of the study without significant change in ¹⁸F-Flutemetamol uptake or cognition. Future studies with longer follow-up are needed to distinguish whether the underlying pathophysiology of aMCI in such patients is other than AD.

Microglia in Alzheimer’s Disease: A Favorable Cellular Target to Ameliorate Alzheimer’s Pathogenesis

Microglial cells serve as molecular sensors of the brain that play a role in physiological and pathological conditions. Under normal physiology, microglia are primarily responsible for regulating central nervous system homeostasis through the phagocytic clearance of redundant protein aggregates, apoptotic cells, damaged neurons, and synapses. Furthermore, microglial cells can promote and mitigate amyloid β phagocytosis and tau phosphorylation. Dysregulation of the microglial programming alters cellular morphology, molecular signaling, and secretory inflammatory molecules that contribute to various neurodegenerative disorders especially Alzheimer’s disease (AD). Furthermore, microglia are considered primary sources of inflammatory molecules and can induce or regulate a broad spectrum of cellular responses. Interestingly, in AD, microglia play a double-edged role in disease progression; for instance, the detrimental microglial effects increase in AD while microglial beneficiary mechanisms are jeopardized. Depending on the disease stages, microglial cells are expressed differently, which may open new avenues for AD therapy. However, the disease-related role of microglial cells and their receptors in the AD brain remain unclear. Therefore, this review represents the role of microglial cells and their involvement in AD pathogenesis.

A Single Baseline Amyloid Positron Emission Tomography Could Be Sufficient for Predicting Alzheimer's Disease Conversion in Mild Cognitive Impairment

OBJECTIVE

Baseline amyloid burden in mild cognitive impairment (MCI) has been linked to conversion to Alzheimer's disease (AD), but the comparison of baseline and longitudinal changes in amyloid burden for predicting AD remains unresolved. The objectives of this study aimed to compare the prognostic ability of baseline and longitudinal changes in amyloid burden in MCI patients.

METHODS

Seventy-five individuals with MCI were recruited and examined annually by clinical interviews for a mean follow-up of 24 months (range, 11.6-42.0). [18F]Florbetaben positron emission tomography (PET) scans were performed. T1-weighted 3D volumes were acquired for co-registration, and to define regions of interest. We examined whether baseline and longitudinal amyloid burden changes can improve AD conversion by Cox proportional hazard model analysis and receiver operating characteristic (ROC) curve analysis.

RESULTS

Cox proportional hazards model analysis showed that baseline amyloid burden was significantly associated with increased risk of conversion to AD (hazard ratio [HR]=10.0; 95% confidence interval [CI], 1.15-85.39; p=0.04), but longitudinal amyloid burden changes was not (HR=0.2; 95% CI, 0.02-1.18; p=0.07). When predicting AD, longitudinal amyloid burden changes had better ROC accuracy of 65.2% (95% CI, 48.4-82.0) than baseline amyloid burden of 59.6% (95% CI, 40.3-79.0), without statistical significance in pairwise comparison.

CONCLUSION

A single baseline amyloid PET could be sufficient in the prediction of AD conversion in MCI.

Sex Modulates the Pathological Aging Effect on Caudate Functional Connectivity in Mild Cognitive Impairment

Purpose

To assess the pathological aging effect on caudate functional connectivity among mild cognitive impairment (MCI) participants and examine whether and how sex and amyloid contribute to this process.

Materials and Methods

Two hundred and seventy-seven functional magnetic resonance imaging (fMRI) sessions from 163 cognitive normal (CN) older adults and 309 sessions from 139 participants with MCI were included as the main sample in our analysis. Pearson's correlation was used to characterize the functional connectivity (FC) between caudate nuclei and each brain region, then caudate nodal strength was computed to quantify the overall caudate FC strength. Association analysis between caudate nodal strength and age was carried out in MCI and CN separately using linear mixed effect (LME) model with covariates (education, handedness, sex, Apolipoprotein E4, and intra-subject effect). Analysis of covariance was conducted to investigate sex, amyloid status, and their interaction effects on aging with the fMRI data subset having amyloid status available. LME model was applied to women and men separately within MCI group to evaluate aging effects on caudate nodal strength and each region's connectivity with caudate nuclei. We then evaluated the roles of sex and amyloid status in the associations of neuropsychological scores with age or caudate nodal strength. An independent cohort was used to validate the sex-dependent aging effects in MCI.

Results

The MCI group had significantly stronger age-related increase of caudate nodal strength compared to the CN group. Analyzing women and men separately revealed that the aging effect on caudate nodal strength among MCI participants was significant only for women (left: P = 6.23 × 10-7, right: P = 3.37 × 10-8), but not for men (P > 0.3 for bilateral caudate nuclei). The aging effects on caudate nodal strength were not significantly mediated by brain amyloid burden. Caudate connectivity with ventral prefrontal cortex substantially contributed to the aging effect on caudate nodal strength in women with MCI. Higher caudate nodal strength is significantly related to worse cognitive performance in women but not in men with MCI.

Conclusion

Sex modulates the pathological aging effects on caudate nodal strength in MCI regardless of amyloid status. Caudate nodal strength may be a sensitive biomarker of pathological aging in women with MCI.

Impact of TOF on Brain PET With Short-Lived 11C-Labeled Tracers Among Suspected Patients With AD/PD: Using Hybrid PET/MRI

Objective

To explore the impact of the time-of-flight (TOF) reconstruction on brain PET with short-lived 11C-labeled tracers in PET magnetic resonance (PET/MR) brain images among suspected patients with Alzheimer's and Parkinson's disease (AD/PD).

Methods

Patients who underwent 11C-2-ß-carbomethoxy-3-b-(4-fluorophenyl) tropane (11C-CFT) and 2-(4-N-[11C] methylaminophenyl)-6-hydroxybenzothiazole (11C-PiB) PET/MRI were retrospectively included in the study. Each PET LIST mode data were reconstructed with and without the TOF reconstruction algorithm. Standard uptake values (SUVs) of Caudate Nucleus (CN), Putamen (PU), and Whole-brain (WB) were measured. TOF and non-TOF SUVs were assessed by using paired t-test. Standard formulas were applied to measure contrast, signal-to-noise ratio (SNR), and percentage relative average difference of SUVs (%RAD-SUVs).

Results

Total 75 patients were included with the median age (years) and body mass index (BMI-kg/m2) of 60.2 ± 10.9 years and 23.9 ± 3.7 kg/m2 in 11C-CFT (n = 41) and 62.2 ± 6.8 years and 24.7 ± 2.9 kg/m2 in 11C-PiB (n = 34), respectively. Higher average SUVs and positive %RAD-SUVs were observed in CN and PU in TOF compared with non-TOF reconstructions for the two 11C-labeled radiotracers. Differences of SUVmean were significant (p < 0.05) in CN and PU for both 11C-labeled radiotracers. SUVmax was enhanced significantly in CN and PU for 11C-CFT and CN for 11C-PiB, but not in PU. Significant contrast enhancement was observed in PU for both 11C-labeled radiotracers, whereas SNR gain was significant in PU, only for 11C-PiB in TOF reconstruction.

Conclusion

Time-of-flight leads to a better signal vs. noise trade-off than non-TOF in 11C-labeled tracers between CN and PU, improving the SUVs, contrast, and SNR, which were valuable for reducing injected radiation dose. Improved timing resolution aided the rapid decay rate of short-lived 11C-labeled tracers, and it shortened the scan time, increasing the patient comfort, and reducing the motion artifact among patients with AD/PD. However, one should adopt the combined TOF algorithm with caution for the quantitative analysis because it has different effects on the SUVmax, contrast, and SNR of different brain regions.

The Relationship of Plasma Transthyretin Level with Global or Regional Amyloid Beta Burden in Subjects with Amnestic Mild Cognitive Impairment: Cross-Sectional Amyloid PET Study

Background

To investigate the relationships of plasma transthyretin levels with amyloid beta deposition and medial temporal atrophy in amnestic mild cognitive impairment.

Methods

This is a cross-sectional study of association of subjects with amnestic mild cognitive impairment. Plasma transthyretin levels, brain magnetic resonance imaging, and 18F-florbetaben positron emission tomography were simultaneously measured in subjects with amnestic mild cognitive impairment.

Results

Plasma transthyretin levels were positively associated with amyloid beta deposition in global (r = 0.394, P = .009), frontal cortex (r = 0.316, P = .039), parietal cortex (r = 0.346, P = .023), temporal cortex (r = 0.372, P = .014), occipital cortex (r = 0.310, P = .043), right posterior cingulate (r = 0.350, P = .021), left precuneus (r = 0.314, P = .040), and right precuneus (r = 0.398, P = .008). No association between plasma transthyretin level and medial temporal sub-regional atrophies was found.

Conclusions

Our findings of positive association of plasma transthyretin levels with global and regional amyloid beta burden suggest upregulation of transthyretin level as a reactive response to amyloid beta deposition during the early stages of the Alzheimer's disease process.

Regional amyloid correlates of cognitive performance in ageing and mild cognitive impairment

Beta-amyloid deposition is one of the earliest pathological markers associated with Alzheimer's disease. Mild cognitive impairment in the setting of beta-amyloid deposition is considered to represent a preclinical manifestation of Alzheimer's disease. In vivo imaging studies are unique in their potential to advance our understanding of the role of beta-amyloid deposition in cognitive deficits in Alzheimer's disease and in mild cognitive impairment. Previous work has shown an association between global cortical measures of beta-amyloid deposition ('amyloid positivity') in mild cognitive impairment with greater cognitive deficits and greater risk of progression to Alzheimer's disease. The focus of the present study was to examine the relationship between the regional distribution of beta-amyloid deposition and specific cognitive deficits in people with mild cognitive impairment and cognitively normal elderly individuals. Forty-seven participants with multi-domain, amnestic mild cognitive impairment (43% female, aged 57-82 years) and 37 healthy, cognitively normal comparison subjects (42% female, aged 55-82 years) underwent clinical and neuropsychological assessments and high-resolution positron emission tomography with the radiotracer 11C-labelled Pittsburgh compound B to measure beta-amyloid deposition. Brain-behaviour partial least-squares analysis was conducted to identify spatial patterns of beta-amyloid deposition that correlated with the performance on neuropsychological assessments. Partial least-squares analysis identified a single significant (P < 0.001) latent variable which accounted for 80% of the covariance between demographic and cognitive measures and beta-amyloid deposition. Performance in immediate verbal recall (R = -0.46 ± 0.07, P < 0.001), delayed verbal recall (R = -0.39 ± 0.09, P < 0.001), immediate visual-spatial recall (R = -0.39 ± 0.08, P < 0.001), delayed visual-spatial recall (R = -0.45 ± 0.08, P < 0.001) and semantic fluency (R = -0.33 ± 0.11, P = 0.002) but not phonemic fluency (R = -0.05 ± 0.12, P < 0.705) negatively covaried with beta-amyloid deposition in the identified regions. Partial least-squares analysis of the same cognitive measures with grey matter volumes showed similar associations in overlapping brain regions. These findings suggest that the regional distribution of beta-amyloid deposition and grey matter volumetric decreases is associated with deficits in executive function and memory in mild cognitive impairment. Longitudinal analysis of these relationships may advance our understanding of the role of beta-amyloid deposition in relation to grey matter volumetric decreases in cognitive decline.

Development of an MRI contrast agent for both detection and inhibition of the amyloid-β fibrillation process

A curcumin derivative conjugated with Gd-DO3A (Gd-DO3A-Comp.B) was synthesised as an MRI contrast agent for detecting the amyloid-β (Aβ) fibrillation process. Gd-DO3A-Comp.B inhibited Aβ aggregation significantly and detected the fibril growth at 20 μM of Aβ with 10 μM of probe concentration by T₁-weighted MR imaging.

A curcumin derivative conjugated with Gd-DO3A (Gd-DO3A-Comp.B) was developed to significantly inhibit the amyloid-β (Aβ) aggregation and detect the fibril growth by T₁-weighted MR imaging.

Tracers progress for positron emission tomography imaging of glial-related disease

Glial cells play an essential part in the neuron system. They can not only serve as structural blocks in the human brain but also participate in many biological processes. Extensive studies have shown that astrocytes and microglia play an important role in neurodegenerative diseases, such as Alzheimer's disease, Parkinson's disease, Huntington's disease, as well as glioma, epilepsy, ischemic stroke, and infections. Positron emission tomography is a functional imaging technique providing molecular-level information before anatomic changes are visible and has been widely used in many above-mentioned diseases. In this review, we focus on the positron emission tomography tracers used in pathologies related to glial cells, such as glioma, Alzheimer's disease, and neuroinflammation.

Relationship between Amyloid-β Deposition and the Coupling between Structural and Functional Brain Networks in Patients with Mild Cognitive Impairment and Alzheimer's Disease

Previous studies have demonstrated that the accumulation of amyloid-β (Aβ) pathologies has distinctive stage-specific effects on the structural and functional brain networks along the Alzheimer's disease (AD) continuum. A more comprehensive account of both types of brain network may provide a better characterization of the stage-specific effects of Aβ pathologies. A potential candidate for this joint characterization is the coupling between the structural and functional brain networks (SC-FC coupling). We therefore investigated the effect of Aβ accumulation on global SC-FC coupling in patients with mild cognitive impairment (MCI), AD, and healthy controls. Patients with MCI were dichotomized according to their level of Aβ pathology seen in ¹⁸F-flutemetamol PET-CT scans-namely, Aβ-negative and Aβ-positive. Our results show that there was no difference in global SC-FC coupling between different cohorts. During the prodromal AD stage, there was a significant negative correlation between the level of Aβ pathology and the global SC-FC coupling of MCI patients with positive Aβ, but no significant correlation for MCI patients with negative Aβ. During the AD dementia stage, the correlation between Aβ pathology and global SC-FC coupling in patients with AD was positive. Our results suggest that Aβ pathology has distinctive stage-specific effects on global coupling between the structural and functional brain networks along the AD continuum.

Amyloid and Tau in Alzheimer's Disease: Biomarkers or Molecular Targets for Therapy? Are We Shooting the Messenger?

Alzheimer's disease is a neuropsychiatric disorder with devastating clinical and socioeconomic consequences. Since the original description of the neuropathological correlates of the disorder, neuritic plaques and neurofibrillary tangles have been presumed to be critical to the underlying pathophysiology of the illness. The authors review the clinical and neuropathological origins of Alzheimer's disease and trace the evolution of modern biomarkers from their historical roots. They describe how technological innovations such as neuroimaging and biochemical assays have been used to measure and quantify key proteins and lipids in the brain, cerebrospinal fluid, and blood and advance their role as biomarkers of Alzheimer's disease. Together with genomics, these approaches have led to the development of a thematic and focused science in the area of degenerative disorders. The authors conclude by drawing distinctions between legitimate biomarkers of disease and molecular targets for therapeutic intervention and discuss future approaches to this complex neurobehavioral illness.

Can we learn lessons from the FDA's approval of aducanumab?

On 7 June 2021, aducanumab was granted accelerated approval for the treatment of Alzheimer disease (AD) by the FDA on the basis of amyloid-lowering effects considered reasonably likely to confer clinical benefit. This decision makes aducanumab the first new drug to be approved for the treatment of AD since 2003 and the first drug to ever be approved for modification of the course of AD. Many have questioned how scientific evidence, expert advice and the best interests of patients and families were considered in the approval decision. In this article, we argue that prior to approval, the FDA and Biogen's shared interpretation of clinical trial data - that high-dose aducanumab was substantially clinically effective - avoided conventional scientific scrutiny, was prominently advanced by patient representative groups who had been major recipients of Biogen funds, and raised concerns that safeguards were insufficient to mitigate regulatory capture within the FDA. Here, we reflect on events leading to the FDA's decision on 7 June 2021 and consider whether any lessons can be learned for the field.

Network-constrained technique to characterize pathology progression rate in Alzheimer's disease

Current methods for measuring the chronic rates of cognitive decline and degeneration in Alzheimer’s disease rely on the sensitivity of longitudinal neuropsychological batteries and clinical neuroimaging, particularly structural magnetic resonance imaging of brain atrophy, either at a global or regional scale. There is particular interest in approaches predictive of future disease progression and clinical outcomes using a single time point. If successful, such approaches could have great impact on differential diagnosis, therapeutic treatment and clinical trial inclusion. Unfortunately, it has proven quite challenging to accurately predict clinical and degeneration progression rates from baseline data. Specifically, a key limitation of the previously proposed approaches for disease progression based on the brain atrophy measures has been the limited incorporation of the knowledge from disease pathology progression models, which suggest a prion-like spread of disease pathology and hence the neurodegeneration. Here, we present a new metric for disease progression rate in Alzheimer that uses only MRI-derived atrophy data yet is able to infer the underlying rate of pathology transmission. This is enabled by imposing a spread process driven by the brain networks using a Network Diffusion Model. We first fit this model to each patient’s longitudinal brain atrophy data defined on a brain network structure to estimate a patient-specific rate of pathology diffusion, called the pathology progression rate. Using machine learning algorithms, we then build a baseline data model and tested this rate metric on data from longitudinal Alzheimer’s Disease Neuroimaging Initiative study including 810 subjects. Our measure of disease progression differed significantly across diagnostic groups as well as between groups with different genetic risk factors. Remarkably, hierarchical clustering revealed 3 distinct clusters based on CSF profiles with >90% accuracy. These pathological clusters exhibit progressive atrophy and clinical impairments that correspond to the proposed rate measure. We demonstrate that a subject’s degeneration speed can be best predicted from baseline neuroimaging volumetrics and fluid biomarkers for subjects in the middle of their degenerative course, which may be a practical, inexpensive screening tool for future prognostic applications.

When Does Alzheimer's Disease Really Start? The Role of Biomarkers

(Appeared originally in Int J Mol Sci 2019, 20 5536).

Improvement of cognitive performance by a nutraceutical formulation: Underlying mechanisms revealed by laboratory studies

Cognitive decline, decrease in neuronal function and neuronal loss that accompany normal aging and dementia are the result of multiple mechanisms, many of which involve oxidative stress. Herein, we review these various mechanisms and identify pharmacological and non-pharmacological approaches, including modification of diet, that may reduce the risk and progression of cognitive decline. The optimal degree of neuronal protection is derived by combinations of, rather than individual, compounds. Compounds that provide antioxidant protection are particularly effective at delaying or improving cognitive performance in the early stages of Mild Cognitive Impairment and Alzheimer's disease. Laboratory studies confirm alleviation of oxidative damage in brain tissue. Lifestyle modifications show a degree of efficacy and may augment pharmacological approaches. Unfortunately, oxidative damage and resultant accumulation of biomarkers of neuronal damage can precede cognitive decline by years to decades. This underscores the importance of optimization of dietary enrichment, antioxidant supplementation and other lifestyle modifications during aging even for individuals who are cognitively intact.

Cognitive decline according to amyloid uptake in patients with poststroke cognitive impairment

BACKGROUND AND PURPOSE

Poststroke cognitive impairment (PSCI) is common, but the impact of β-amyloid (Aβ) on PSCI is uncertain. The proposed study will investigate amyloid pathology in participants with PSCI and how differently their cognition progress according to the amyloid pathology.

METHODS

This multicenter study was designed to be prospective and observational based on a projected cohort size of 196 participants with either newly developed cognitive impairment, or rapidly aggravated CI, within 3 months after acute cerebral infarction. They will undergo 18F-flutemetamol positron emission tomography at baseline and will be categorized as either amyloid-positive (A+) or amyloid-negative (A-) by visual rating. The primary outcome measures will be based on Korean Mini-Mental State Examination changes (baseline to 12 months) between the A+ and A- groups. The secondary outcome measures will be the dementia-conversion rate and changes in the Korean version of the Montreal Cognitive Assessment (baseline to 12 months) between the A+ and A- groups.

CONCLUSIONS

This study will provide a broadened perspective on the impact of Aβ on the cause and outcomes of PSCI in clinical practice. Identifying amyloid pathology in patients with PSCI will help select patients who need more focused treatments such as acetylcholinesterase inhibitors.

TRIAL REGISTRATION

Clinical Research Information Service identifier: KCT0005086.

Machine Learning for the Prediction of Amyloid Positivity in Amnestic Mild Cognitive Impairment

BACKGROUND

Amyloid-β (Aβ) evaluation in amnestic mild cognitive impairment (aMCI) patients is important for predicting conversion to Alzheimer's disease. However, Aβ evaluation through Aβ positron emission tomography (PET) is limited due to high cost and safety issues.

OBJECTIVE

We therefore aimed to develop and validate prediction models of Aβ positivity for aMCI using optimal interpretable machine learning (ML) approaches utilizing multimodal markers.

METHODS

We recruited 529 aMCI patients from multiple centers who underwent Aβ PET. We trained ML algorithms using a training cohort (324 aMCI from Samsung medical center) with two-phase modelling: model 1 included age, gender, education, diabetes, hypertension, apolipoprotein E genotype, and neuropsychological test scores; model 2 included the same variables as model 1 with additional MRI features. We used four-fold cross-validation during the modelling and evaluated the models on an external validation cohort (187 aMCI from the other centers).

RESULTS

Model 1 showed good accuracy (area under the receiver operating characteristic curve [AUROC] 0.837) in cross-validation, and fair accuracy (AUROC 0.765) in external validation. Model 2 led to improvement in the prediction performance with good accuracy (AUROC 0.892) in cross validation compared to model 1. Apolipoprotein E genotype, delayed recall task scores, and interaction between cortical thickness in the temporal region and hippocampal volume were the most important predictors of Aβ positivity.

CONCLUSION

Our results suggest that ML models are effective in predicting Aβ positivity at the individual level and could help the biomarker-guided diagnosis of prodromal AD.

Astrocytic TSPO Upregulation Appears Before Microglial TSPO in Alzheimer's Disease

Background:

In vivo PET/SPECT imaging of neuroinflammation is primarily based on the estimation of the 18 kDa-translocator-protein (TSPO). However, TSPO is expressed by different cell types which complicates the interpretation.

Objective:

The present study evaluates the cellular origin of TSPO alterations in Alzheimer’s disease (AD).

Methods:

The TSPO cell origin was evaluated by combining radioactive imaging approaches using the TSPO radiotracer [¹²⁵I]CLINDE and fluorescence-activated cell sorting, in a rat model of AD (TgF344-AD) and in AD subjects.

Results:

In the hippocampus of TgF344-AD rats, TSPO overexpression not only concerns glial cells but the increase is visible at 12 and 24 months in astrocytes and only at 24 months in microglia. In the temporal cortex of AD subjects, TSPO upregulation involved only glial cells. However, the mechanism of this upregulation appears different with an increase in the number of TSPO binding sites per cell without cell proliferation in the rat, and a microglial cell population expansion with a constant number of binding sites per cell in human AD.

Conclusion:

These data indicate an earlier astrocyte intervention than microglia and that TSPO in AD probably is an exclusive marker of glial activity without interference from other TSPO-expressing cells. This observation indicates that the interpretation of TSPO imaging depends on the stage of the pathology, and highlights the particular role of astrocytes.

Association of walking energetics with amyloid beta status: Findings from the Baltimore Longitudinal Study of Aging

INTRODUCTION

Higher energetic costs for mobility predict gait speed decline. Slow gait is linked to cognitive decline and Alzheimer's disease (AD). Whether the energetic cost of walking is linked to AD pathology is unknown. We investigated the cross-sectional association between the energetic cost of walking, gait speed, and amyloid beta (Aβ) status (+/-) in older adults.

METHODS

One hundred forty-nine cognitively normal adults (56% women, mean age 77.5 ± 8.4 years) completed customary-paced walking assessments with indirect calorimetry and 11C-Pittsburgh compound B positron emission tomography. Logistic regression models examined associations adjusted for demographics, body composition, comorbid conditions, and apolipoprotein E ε4.

RESULTS

Each 0.01 mL/kg/m greater energy cost was associated with 18% higher odds of being Aβ+ (odds ratio [OR] = 1.18; 95% confidence interval [CI]: 1.04 to 1.34; P = .011). These findings were not observed when investigating gait speed (OR = 0.99; 95% CI: 0.97 to 1.01; P = .321).

DISCUSSION

High energetic cost of walking is linked to AD pathology and may be a potential target for therapeutic intervention.

Novel Plasma miRNAs as Biomarkers and Therapeutic Targets of Alzheimer's Disease at the Prodromal Stage

BACKGROUND

Amnestic mild cognitive impairment (aMCI) is a prodromal stage of Alzheimer's disease (AD) involving imbalanced beta-site amyloid precursor protein cleaving enzyme 1 (BACE1). MicroRNAs (miRNAs) are associated with AD.

OBJECTIVE

This study aimed to investigated whether plasma miRNAs can predict prodromal AD or are associated with AD pathology.

METHODS

Participants in the discovery set (n = 10), analysis set (n = 30), and validation set (n = 80) were screened from the China Longitudinal Aging Study. RNA was extracted from the participants' plasma. Microarray sequencing provided miRNA profiles and differentially expressed miRNAs (DEmiRNAs) in the discovery set included patients with 18F-Flutemetamol positron emission tomography scan-confirmed aMCI. Potential biomarkers were screened in the analysis set. The predict capability of candidate miRNAs was assessed in the validation set. Candidate miRNAs modulation of BACE1 expression was explored in rat and human hippocampal neurons in vitro.

RESULTS

We verified 46 significant DEmiRNAs between the aMCI and NC groups (p <  0.05), among which 33 were downregulated. In the analysis set, miR-1185-2-3p, miR-1909-3p, miR-22-5p, and miR-134-3p levels decreased significantly in the aMCI group. These miRNAs and previously identified miR-107 were selected as potential biomarkers. A prediction model comprising these five miRNAs showed outstanding accuracy (81.25%) to discriminate aMCI at cut-off value of 0.174. Except for miR-134-3p, the other four miRNAs significantly suppressed Bace1 expression in rat hippocampal neurons in vitro. BACE1 modulation of miR-1185-2-3p, miR-1909-3p, and miR-134-3p was confirmed in human hippocampal neurons in vitro.

CONCLUSION

A predictive model consisting of five BACE1-related plasma miRNAs could be a novel biomarker for aMCI.

Transcranial direct current stimulation as an adjunct to cognitive training for older adults with mild cognitive impairment: A randomized controlled trial

BACKGROUND

Cognitive training (CT) for individuals with mild cognitive impairment (MCI) may not be optimal for enhancing cognitive functioning. Coupling CT with transcranial direct current stimulation (tDCS) may maximize the strength of transmission across synaptic circuits in pathways that are stimulated by CT. The synergistic effects arising from this combination could be superior to those with administration of CT alone.

OBJECTIVES

To investigate whether the receiving tDCS combined with CT is superior to CT alone on domain-specific and task-specific cognitive outcomes in older adults with MCI.

METHODS

This double-blind, sham-controlled randomized trial included 67 older adults with MCI assigned to 3 groups: 1) tDCS combined with CT (tDCS+CT), 2) sham tDCS combined with CT (sham tDCS+CT) and 3) CT alone. Nine sessions of computerized CT were administered to the 3 groups for 3 weeks. In addition, tDCS and sham tDCS was delivered to the left dorsolateral prefrontal cortex to the tDCS+CT and sham tDCS+CT groups, respectively, simultaneously with CT. Standardized cognitive assessments were performed at baseline, post-intervention, and at 6-week follow-up. Participants' performance in the CT tasks was rated every session.

RESULTS

The 3 groups showed improvements in global cognition and everyday memory (P<0.017) after the intervention and at follow-up, with larger effect sizes in the tDCS+CT than other groups (d>0.94) but with no significant differences between groups. Regarding CT outcomes, the groups showed significant differences in favour of the tDCS+CT group in decreasing the completion and reaction times of working memory and attention activities (P<0.017).

CONCLUSIONS

tDCS combined with CT was not superior to sham tDCS with CT and CT alone in its effects on domain-specific cognitive outcomes, but it did provide comparatively larger effect sizes and improve the processing speed of task-specific outcomes. CLINICALTRIALS.GOV: NCT03441152.

Heterogeneity of Cerebrospinal Fluid Biomarkers Profiles in Individuals with Distinct Levels of Cognitive Decline: A Cross-Sectional Study

BACKGROUND

Decreased cerebrospinal fluid (CSF) concentrations of the amyloid-β (Aβ), along with increased total (T-tau) and phosphorylated tau protein (P-tau), are widely accepted as core biomarkers of Alzheimer's disease (AD) pathology. Nonetheless, there are a few remaining caveats that still preclude the full incorporation of AD biomarkers into clinical practice.

OBJECTIVE

To determine the frequency of clinical-biological mismatches in a clinical sample of older adults with varying degrees of cognitive impairment.

METHODS

204 participants were enrolled for a cross-sectional assessment and allocated into diagnostic groups: probable AD (n = 60, 29.4%); MCI (n = 84, 41.2%); or normal cognition (NC, n = 60, 29.4%). CSF concentrations of Aβ42, T-tau, and 181Thr-P-tau were determined, and Aβ42/P-tau ratio below 9.53 was used as a proxy of AD pathology. The AT(N) classification was further used as a framework to ascertain the biological evidence of AD.

RESULTS

The majority (73.7%) of patients in the AD group had the Aβ42/P-tau ratio below the cut-off score for AD, as opposed to a smaller proportion in the MCI (42.9%) and NC (23.3%) groups. In the latter, 21 subjects (35%) were classified as A+, 28 (46.7%) as T+, and 23 (38.3%) as N + . In the AD group, 66.7%of the cases were classified as A+, 78.3%as T+, and 80%as N+.

CONCLUSION

Analysis of CSF biomarkers was able to discriminate between AD, MCI, and NC. However, clinical-biological mismatches were observed in a non-negligible proportion of cases.

The Effects of Amyloid and Tau on Functional Network Connectivity in Older Populations

Background: Neuroimaging studies suggest that aged brains show altered connectivity within and across functional networks. Similar changes in functional network integrity are also linked to the accumulation of pathological proteins in the brain, such as amyloid-beta plaques and neurofibrillary tau tangles seen in Alzheimer's disease. However, less is known about the specific impacts of amyloid and tau on functional network connectivity in cognitively normal older adults who harbor these proteins. Methods: We briefly summarize recent neuroimaging studies of aging and then thoroughly review positron emission tomography and functional magnetic resonance imaging studies measuring the relationship between amyloid-tau pathology and functional connectivity in cognitively normal older individuals. Results: The literature overall suggests that amyloid-positive older individuals show minor cognitive dysfunction and aberrant default mode network connectivity compared with amyloid-negative individuals. Tau, however, is more closely associated with network hypoconnectivity and poorer cognition. Those with substantial amyloid and tau experience even greater cognitive decline compared with those with primarily amyloid or tau, suggesting a potential interaction. Multimodal neuroimaging studies suggest that older adults with pathological protein deposits show amyloid-related hyperconnectivity and tau-related hypoconnectivity in multiple functional networks, including the default mode and frontoparietal networks. Discussion: We propose an updated model considering the effects of amyloid and tau on functional connectivity in older individuals. Large, longitudinal neuroimaging studies with multiple levels of analysis are required to obtain a deeper understanding of the dynamic relationship between pathological protein accumulation and functional connectivity changes, as amyloid- and tau-induced connectivity alterations may have critical and time-varying effects on neurodegeneration and cognitive decline. Impact statement Amyloid and tau accumulation have been linked with altered functional connectivity in cognitively normal older adults. This review synthesized recent functional imaging literatures in a discussion of how amyloid and tau can interactively affect functional connectivity in nonlinear ways, which can explain previous conflicting findings. Changes in connectivity strength may depend on the accumulation of both amyloid and tau, and their integrative effects seem to have critical consequences on cognition. Elucidating the effects of these pathological proteins on brain functioning is paramount to understand the etiology of Alzheimer's disease and the aging process overall.

Comparison of Diagnostic Performances Between Cerebrospinal Fluid Biomarkers and Amyloid PET in a Clinical Setting

The diagnostic performances of cerebrospinal fluid (CSF) biomarkers and amyloid positron emission tomography (PET) were compared by examining the association and concordance or discordance between CSF Aβ1-42 and amyloid PET, after determining our own cut-off values for CSF Alzheimer's disease (AD) biomarkers. Furthermore, we evaluated the ability of CSF biomarkers and amyloid PET to predict clinical progression. CSF Aβ1-42, t-tau, and p-tau levels were analyzed in 203 individuals [27 normal controls, 38 mild cognitive impairment (MCI), 62 AD dementia, and 76 patients with other neurodegenerative diseases] consecutively recruited from two dementia clinics. We used both visual and standardized uptake value ratio (SUVR)-based amyloid PET assessments for analyses. The association of CSF biomarkers with amyloid PET SUVR, hippocampal atrophy, and cognitive function were investigated by linear regression analysis, and the risk of conversion from MCI to AD dementia was assessed using a Cox proportional hazards model. CSF p-tau/Aβ1-42 and t-tau/Aβ1-42 exhibited the best diagnostic accuracies among the CSF AD biomarkers examined. Correlations were observed between CSF biomarkers and global SUVR, hippocampal volume, and cognitive function. Overall concordance and discordance between CSF Aβ1-42 and amyloid PET was 77% and 23%, respectively. Baseline positive CSF Aβ1-42 for MCI demonstrated a 5.6-fold greater conversion risk than negative CSF Aβ1-42 .  However, amyloid PET findings failed to exhibit significant prognostic value. Therefore, despite presence of a significant correlation between the CSF Aβ1-42 level and SUVR of amyloid PET, and a relevant concordance between CSF Aβ1-42 and amyloid PET, baseline CSF Aβ1-42 better predicted AD conversion.

PET Neuroimaging of Alzheimer's Disease: Radiotracers and Their Utility in Clinical Research

Alzheimer's Disease (AD), the leading cause of senile dementia, is a progressive neurodegenerative disorder affecting millions of people worldwide and exerting tremendous socioeconomic burden on all societies. Although definitive diagnosis of AD is often made in the presence of clinical manifestations in late stages, it is now universally believed that AD is a continuum of disease commencing from the preclinical stage with typical neuropathological alterations appearing decades prior to its first symptom, to the prodromal stage with slight symptoms of amnesia (amnestic mild cognitive impairment, aMCI), and then to the terminal stage with extensive loss of basic cognitive functions, i.e., AD-dementia. Positron emission tomography (PET) radiotracers have been developed in a search to meet the increasing clinical need of early detection and treatment monitoring for AD, with reference to the pathophysiological targets in Alzheimer's brain. These include the pathological aggregations of misfolded proteins such as β-amyloid (Aβ) plagues and neurofibrillary tangles (NFTs), impaired neurotransmitter system, neuroinflammation, as well as deficient synaptic vesicles and glucose utilization. In this article we survey the various PET radiotracers available for AD imaging and discuss their clinical applications especially in terms of early detection and cognitive relevance.

The Association of β-Amyloid with Cognition and Striatal Dopamine in Early, Non-Demented Parkinson's Disease

BACKGROUND

Co-occurrence of β-amyloid (Aβ) pathology has been reported in Parkinson's disease (PD), and Aβ deposition in the brain may contribute to cognitive decline in patients with PD. Whether striatal dopamine uptake and cognitive status differ with amyloid deposition has been reported in only a few studies.

OBJECTIVE

The purpose of this study was to investigate the association among striatal dopaminergic availability, Aβ-positivity, and motor and cognitive status in early and non-demented PD.

METHODS

A total of 98 newly-diagnosed, non-medicated, and non-demented patients with PD were included in this study. Cognitive status was assessed using neuropsychological testing. Patients with mild cognitive impairment (MCI) were stratified into two groups: amnestic MCI (aMCI) and non-amnestic MCI (naMCI). Patient motor status was examined using the Unified Parkinson's Disease Rating Scale (UPDRS) and positron emission tomography (PET) with 18F-N-(3-fluoropropyl)-2beta-carbon ethoxy-3beta-(4-iodophenyl) nortropane (18F-FP-CIT). All patients also underwent 18F-florbetaben (18F-FBB) PET and were divided based on the results into Aβ-positive and Aβ-negative groups.

RESULTS

Eighteen patients had Aβ-positivity in 18F-FBB PET and 67 had MCI. Sixteen of 18 with Aβ-positive patients had MCI. The Aβ-positive group had higher frequency of MCI, especially amnestic-type, and lower dopaminergic activities in the left ventral striatum, but not with UPDRS motor score.

CONCLUSION

Amyloid pathology was associated with MCI, especially amnestic-subtype, in early and non-demented PD patients and with low dopaminergic activities in the left ventral striatum. This finding suggests that PD patients with Aβ-positivity have AD-related cognitive pathophysiology in PD and associated impaired dopaminergic availability in the ventral striatum can affect the pathophysiology in various ways.

Deficits in saccadic eye movements differ between subtypes of patients with mild cognitive impairment

Introduction: Mild cognitive impairment (MCI) is known to be heterogeneous in its cognitive features and course of progression. Whilst memory impairment is characteristic of amnestic MCI (aMCI), cognitive deficits other than memory can occur in both aMCI and non-amnestic MCI (naMCI) and accurate assessment of the subtypes of MCI is difficult for clinicians without the application of extensive neuropsychological testing. In this study, we examine metrics derived from recording of reflexive and voluntary saccadic eye movements as a potential alternative method for discriminating between subtypes and assessing cognitive functions in MCI.Method: A total of 29 MCI patients and 29 age- and education-matched healthy controls (HCs) participated in the cross-sectional study. We recorded horizontal and vertical pro-saccades and anti-saccade responses. All the participants also completed a comprehensive neuropsychological tests battery.Results: Significant differences in saccadic eye movement were found between the subtypes of MCI and HCs. Patients with aMCI had a higher percentage of short latency "express" saccades than HCs. We found strong associations between saccadic reaction times and cognitive domains, including executive functions and attention. The mini-mental state examination (MMSE) was also found to correlate with uncorrected errors in the anti-saccade task.Conclusions: The increased proportion of saccades in the express latency range in aMCI may be indicative of problems with cognitive inhibitory control in these patients. A focus on this and other saccade metrics in the preclinical and prodromal stages of dementia may help to predict the clinical progression of the disease and direct interventions for the management of MCI. The clinical significance of saccadic eye movement impairments in MCI is not yet fully understood and should be investigated in further studies using larger samples.

Prediction of tau accumulation in prodromal Alzheimer's disease using an ensemble machine learning approach

We developed machine learning (ML) algorithms to predict abnormal tau accumulation among patients with prodromal AD. We recruited 64 patients with prodromal AD using the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. Supervised ML approaches based on the random forest (RF) and a gradient boosting machine (GBM) were used. The GBM resulted in an AUC of 0.61 (95% confidence interval [CI] 0.579–0.647) with clinical data (age, sex, years of education) and a higher AUC of 0.817 (95% CI 0.804–0.830) with clinical and neuropsychological data. The highest AUC was 0.86 (95% CI 0.839–0.885) achieved with additional information such as cortical thickness in clinical data and neuropsychological results. Through the analysis of the impact order of the variables in each ML classifier, cortical thickness of the parietal lobe and occipital lobe and neuropsychological tests of memory domain were found to be more important features for each classifier. Our ML algorithms predicting tau burden may provide important information for the recruitment of participants in potential clinical trials of tau targeting therapies.