The Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog): Modifications and Responsiveness in Pre-Dementia Populations. A Narrative Review

Effects of multisite anodal transcranial direct current stimulation combined with cognitive stimulation in patients with Alzheimer's disease and its neurophysiological correlates: A double-blind randomized clinical trial

OBJECTIVES

We aimed to examine the effects of multisite anodal transcranial direct current stimulation (tDCS) combined with cognitive stimulation (CS) over 2 months on cognitive performance and brain activity, and the relationship between them, in patients with Alzheimer's disease (AD).

METHODS

Patients with AD were randomly assigned to an active tDCS+CS (n=18) or a sham tDCS+CS (n=18) group. Cognitive performance was assessed using the Alzheimer Disease Assessment Scale-cognitive subscale (ADAS-cog) and brain activity using EEG (spectral power and coherence analysis) before and after the intervention. Multisite anodal tDCS (2 mA, 30 min) was applied over six brain regions [left and right dorsolateral prefrontal cortex (F3 and F4), Broca's area (F5), Wernicke's area (CP5), left and right somatosensory association cortex (P3 and P4)] for 24 sessions (three times a week). Both groups performed CS during tDCS.

RESULTS

Anodal tDCS+CS delays cognitive decline (ADAS-cog change) to a greater extent than sham tDCS+CS (-3.4±1.1 vs. -1.7±0.4; p=.03). Bilateral EEG coherence at high and low frequencies was greater for the active tDCS+CS than sham+CS group for most electrode pairs assessed (p < .05). The post-intervention ADAS-cog change score was predictive for EEG coherence at different sites (R²=.59 to .68; p < .05) in the active but not in the sham tDCS+CS group.

CONCLUSION

Anodal tDCS+CS improved overall cognitive function and changed EEG brain activity compared to sham tDCS+CS. Changes in cognitive performance were associated with changes in EEG measures of brain activity. Anodal tDCS+CS appears to be a promising therapeutic strategy to modulate cortical activity and improve cognitive function in patients with AD.

Alzheimer's Disease: Key Insights from Two Decades of Clinical Trial Failures

Given the acknowledged lack of success in Alzheimer’s disease (AD) drug development over the past two decades, the objective of this review was to derive key insights from the myriad failures to inform future drug development. A systematic and exhaustive review was performed on all failed AD compounds for dementia (interventional phase II and III clinical trials from ClinicalTrials.gov) from 2004 to the present. Starting with the initial ∼2,700 AD clinical trials, ∼550 trials met our initial criteria, from which 98 unique phase II and III compounds with various mechanisms of action met our criteria of a failed compound. The two recent reported phase III successes of aducanumab and oligomannate are very encouraging; however, we are awaiting real-world validation of their effectiveness. These two successes against the 98 failures gives a 2.0% phase II and III success rate since 2003, when the previous novel compound was approved. Potential contributing methodological factors for the clinical trial failures were categorized into 1) insufficient evidence to initiate the pivotal trials, and 2) pivotal trial design shortcomings. Our evaluation found that rational drug development principles were not always followed for AD therapeutics development, and the question remains whether some of the failed compounds may have shown efficacy if the principles were better adhered to. Several recommendations are made for future AD therapeutic development. The whole database of the 98 failed compounds is presented in the Supplementary Material.

Neuromodulation of cognition in Parkinson's disease

Neuromodulation is a widely used treatment for motor symptoms of Parkinson's disease (PD). It can be a highly effective treatment as a result of knowledge of circuit dysfunction associated with motor symptoms in PD. However, the mechanisms underlying cognitive symptoms of PD are less well-known, and the effects of neuromodulation on these symptoms are less consistent. Nonetheless, neuromodulation provides a unique opportunity to modulate motor and cognitive circuits while minimizing off-target side effects. We review the modalities of neuromodulation used in PD and the potential implications for cognitive symptoms. There have been some encouraging findings with both invasive and noninvasive modalities of neuromodulation, and there are promising advances being made in the field of therapeutic neuromodulation. Substantial work is needed to determine which modulation targets are most effective for the different types of cognitive deficits of PD.

The Effect of Guilingji Capsules on Vascular Mild Cognitive Impairment: A Randomized, Double-Blind, Controlled Trial

Guilingji capsules (GLJC) have been shown to have antiaging effects and improve cognitive function. The aim of this study was to evaluate the clinical efficacy and safety of GLJC for the treatment of vascular mild cognitive impairment (VaMCI). A total of 96 patients with VaMCI (aged 60–85 years) were enrolled in this 24-week, randomized, double-blind, controlled clinical trial. The patients were randomly assigned to a GLJC group (n = 48) or a Ginkgo group (n = 48). Patients in the GLJC group were treated using GLJC, whereas those in the Ginkgo group received Ginkgo extract tablets. We evaluated the participants at baseline and after a 12- and 24-week treatment period using the Montreal Cognitive Assessment (MoCA), Mini-Mental State Examination (MMSE), Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog), and Chinese Medicine Symptom Scale (CM-SS). The serum acetylcholine (Ach), acetylcholinesterase (AchE), homocysteine (Hcy), and high-sensitivity C-reactive protein (hs-CRP) serum levels of the patients were measured before and after 24-week treatment. Analysis of the results of both groups showed that both interventions significantly increased the MoCA and MMSE scores of the patients and decreased their ADAS-Cog and CM-SS scores (P < 0.05). The GLJC group showed greater improvement in MoCA, MMSE, and CM-SS scores than the Ginkgo group (P < 0.05). However, both groups showed a significant increase in serum Ach and a decrease in serum AchE, Hcy, and hs-CRP levels (P < 0.05). Furthermore, serum Ach increased and Hcy decreased more significantly in the GLJC group than in the Ginkgo group (P < 0.05). These findings indicate that GLJC can improve the cognitive function, cholinergic system, and inflammatory cytokine levels of patients with VaMCI. Furthermore, this treatment can improve symptoms of syndromes diagnosed according to traditional Chinese medicine practice in patients with VaMCI.

Digital Phenotyping in Clinical Neurology

Internet-connected devices, including personal computers, smartphones, smartwatches, and voice assistants, have evolved into powerful multisensor technologies that billions of people interact with daily to connect with friends and colleagues, access and share information, purchase goods, play games, and navigate their environment. Digital phenotyping taps into the data streams captured by these devices to characterize and understand health and disease. The purpose of this article is to summarize opportunities for digital phenotyping in neurology, review studies using everyday technologies to obtain motor and cognitive information, and provide a perspective on how neurologists can embrace and accelerate progress in this emerging field.

Can We Use Ginkgo biloba Extract to Treat Alzheimer’s Disease? Lessons from Preclinical and Clinical Studies

(1) Background: Ginkgo biloba extract (GBE) has been widely used to treat central nervous system and cardiovascular diseases. Accumulating evidence has revealed the therapeutic potential of GBE against AD; however, no systematic evaluation has been performed; (2) Methods: a total of 17 preclinical studies and 20 clinical trials assessing the therapeutic effects of GBE against AD were identified from electronic databases. The data in the reports were extracted to conduct a meta-analysis of the AD-related pathological features or symptoms; (3) Results: For the preclinical reports, 45 animals treated with GBE, in six studies, were subjected to cognitive function assessments by the Morris water maze. GBE was shown to reduce the escape latencies in several studies, in both rats and mice (I2 > 70%, p < 0.005). For the clinical trials, eight trials, including 2100 individuals, were conducted. The results show that GBE improved the SKT and ADAS-Cog scores in early-stage AD patients after high doses and long-term administration; (4) Conclusions: GBE displayed generally consistent anti-AD effects in animal experiments, and it might improve AD symptoms in early-stage AD patients after high doses and long-term administration. A lack of sample size calculations and the poor quality of the methods are two obvious limitations of the studies. Nevertheless, the preclinical and clinical data suggest that further large-scale clinical trials may be needed in order to examine the effects of long-term GEB administration on early-stage AD.

The Calcium-free form of Atorvastatin inhibits amyloid-β(1-42) aggregation in vitro

Alzheimer's disease is characterized by the presence of extraneuronal amyloid plaques composed of amyloid-beta (Aβ) fibrillar aggregates in the brains of patients. In mouse models, it has previously been shown that atorvastatin (Ator), a cholesterol-lowering drug, has some reducing effect on the production of cerebral Aβ. A meta-analysis on humans showed moderate effects in the short term but no improvement in the Alzheimer's Disease Assessment Scale—Cognitive Subscale behavioral test. Here, we explore a potential direct effect of Ator on Aβ42 aggregation. Using NMR-based monomer consumption assays and CD spectroscopy, we observed a promoting effect of Ator in its original form (Ator-calcium) on Aβ42 aggregation, as expected because of the presence of calcium ions. The effect was reversed when applying a CaCO₃-based calcium ion scavenging method, which was validated by the aforementioned methods as well as thioflavin-T fluorescence assays and transmission electron microscopy. We found that the aggregation was inhibited significantly when the concentration of calcium-free Ator exceeded that of Aβ by at least a factor of 2. The ¹H–¹⁵N heteronuclear single quantum correlation and saturation-transfer difference NMR data suggest that calcium-free Ator exerts its effect through interaction with the ¹⁶KLVF¹⁹ binding site on the Aβ peptide via its aromatic rings as well as hydroxyl and methyl groups. On the other hand, molecular dynamics simulations confirmed that the increasing concentration of Ator is necessary for the inhibition of the conformational transition of Aβ from an α-helix-dominant to a β-sheet-dominant structure.

Efficacy and Safety of DL-3-n-Butylphthalide in the Treatment of Poststroke Cognitive Impairment: A Systematic Review and Meta-Analysis

Background: Poststroke cognitive impairment (PSCI) is a common complication observed after stroke. Current pharmacologic therapies have no definitive evidence for cognitive recovery or disease progression. Recent studies have verified the positive effect of DL-3-n-butylphthalide (NBP). However, the clinical efficacy and safety are still unclear. The aim of this study was to assess the efficacy of NBP and its harmful effect in the treatment of PSCI.

Method: Eligible randomized controlled trials (RCTs) were retrieved from inception to June 2021 from seven medical databases and two clinical registries. The revised Cochrane risk of bias tool (RoB 2.0) was used for methodological quality. RevMan v5.4.1 from Cochrane Collaboration was used for statistical analysis, and Hartung-Knapp-Sidik-Jonkman (HKSJ) method was used for post hoc testing depend on the number of studies. This study has been submitted to PROSPERO with registration number is CRD42021274123.

Result: We identified 26 studies with a total sample size of 2,571 patients. The results of this study showed that NBP as monotherapy or combination therapy had better performance in increasing the MoCA (monotherapy: SMD_N = 1.05, 95% CI [0.69, 1.42], p < 0.00001; SMD_P = 1.06, 95% CI [0.59, 1.52], p < 0.00001. combination: SMD_O = 0.81, 95% CI [0.62, 1.01], p < 0.00001; SMD_N = 0.90, 95% CI [0.46, 1.33], p < 0.0001; SMD_D = 1.04, 95% CI [0.71, 1.38], p < 0.00001), MMSE (monotherapy: MD_N = 4.89, 95% CI [4.14, 5.63]), p < 0.00001). combination: SMD_O = 1.26, 95% CI [0.97, 1.56], p < 0.00001; SMD_C = 1.63, 95% CI [1.28, 1.98], p < 0.00001; SMD_N = 2.13, 95% CI [1.52, 2.75], p < 0.00001) and BI (monotherapy: MD_N = 13.53, HKSJ 95% CI [9.84, 17.22], p = 0.014. combination: SMD_O = 2.24, HKSJ 95%CI [0.37, 4.11], p = 0.032; SMD_C = 3.36, 95%CI [2.80, 3.93], p < 0.00001; SMD_D = 1.48, 95%CI [1.13, 1.83], p < 0.00001); and decreasing the NIHSS (monotherapy: MD_N = −3.86, 95% CI [−5.22, −2.50], p < 0.00001. combination: SMD_O = −1.15, 95% CI [−1.31, −0.98], p < 0.00001; SMD_C = −1.82, 95% CI [−2.25, −1.40], p < 0.00001) and CSS (combination: MD_O = −7.11, 95% CI [−8.42, −5.80], p < 0.00001), with no serious adverse reactions observed. The funnel plot verified the possibility of publication bias.

Conclusion: NBP maintains a stable pattern in promoting the recovery of cognitive function and abilities of daily living, as well as reducing the symptoms of neurological deficits. However, there is still a need for more high-quality RCTs to verify its efficacy and safety.

Prediction and Modeling of Neuropsychological Scores in Alzheimer's Disease Using Multimodal Neuroimaging Data and Artificial Neural Networks

Background: In recent years, predicting and modeling the progression of Alzheimer's disease (AD) based on neuropsychological tests has become increasingly appealing in AD research. Objective: In this study, we aimed to predict the neuropsychological scores and investigate the non-linear progression trend of the cognitive declines based on multimodal neuroimaging data. Methods: We utilized unimodal/bimodal neuroimaging measures and a non-linear regression method (based on artificial neural networks) to predict the neuropsychological scores in a large number of subjects (n = 1143), including healthy controls (HC) and patients with mild cognitive impairment non-converter (MCI-NC), mild cognitive impairment converter (MCI-C), and AD. We predicted two neuropsychological scores, i.e., the clinical dementia rating sum of boxes (CDRSB) and Alzheimer's disease assessment scale cognitive 13 (ADAS13), based on structural magnetic resonance imaging (sMRI) and positron emission tomography (PET) biomarkers. Results: Our results revealed that volumes of the entorhinal cortex and hippocampus and the average fluorodeoxyglucose (FDG)-PET of the angular gyrus, temporal gyrus, and posterior cingulate outperform other neuroimaging features in predicting ADAS13 and CDRSB scores. Compared to a unimodal approach, our results showed that a bimodal approach of integrating the top two neuroimaging features (i.e., the entorhinal volume and the average FDG of the angular gyrus, temporal gyrus, and posterior cingulate) increased the prediction performance of ADAS13 and CDRSB scores in the converting and stable stages of MCI and AD. Finally, a non-linear AD progression trend was modeled to describe the cognitive decline based on neuroimaging biomarkers in different stages of AD. Conclusion: Findings in this study show an association between neuropsychological scores and sMRI and FDG-PET biomarkers from normal aging to severe AD.

Omega-3 fatty acids and blood-based biomarkers in Alzheimer's disease and mild cognitive impairment: A randomized placebo-controlled trial

BACKGROUND

Increased serum levels of pro-inflammatory biomarkers are consistently associated with cognitive decline. The omega-3 unsaturated fatty acids (n-3 PUFAs) had been linked to slowing cognitive decline due to their potential anti-inflammatory effects. To our knowledge, the different regiments of pure DHA, pure EPA, and their combination on various associated symptoms of dementia, including a mild form of cognitive impairment (MCI) and Alzheimer's disease (AD), have never been studied.

METHODS

This multisite, randomized, double-blind, placebo-controlled trial was conducted at two veteran's retirement centers and one medical center in central Taiwan between 2013 and 2015. 163 MCI or AD patients were randomly assigned to placebo (n = 40), docosahexaenoic acid (DHA, 0.7 g/day, n = 41), eicosapentaenoic acid (EPA, 1.6 g/day, n = 40), or EPA (0.8 g/day) + DHA (0.35 g/day) (n = 42) group for 24 months. The results were measured as the cognitive and functional abilities, biochemical, and inflammatory cytokines profiles. Chi-square tests, two-sample t-test, ANOVA, and linear mixedeffects models were conducted with p < 0.05.

RESULTS

131 (80%) participants had completed the trial with all cognitive, functional, and mood status assessments. The statistically significant difference between the placebo and treatment groups was not determined, concerning the changes in cognitive, functional, and mood status scores, the biochemical profiles, and inflammatory cytokines levels. However, EPA was found to reduce the C-C motif ligands 4 (CCL4) level (p < 0.001). Additionally, EPA could reduce the constructional praxis (p < 0.05) and spoken language ability scores (p < 0.01), and DHA also reduced the spoken language ability score (p < 0.05).

CONCLUSION

Overall, n-3 PUFAs supplements did not reduce cognitive, functional, and depressive symptom outcomes, but spoken language ability and constructional praxis subitems of ADAS-cog. These findings show that attention to clinical heterogeneity in dementia is crucial when studying nutrients interventions, such as n-3 PUFAs. In addition, with small effect size CCL4 is a better indicator than other inflammatory cytokines for EPA treatment response.

Neuronavigated Magnetic Stimulation combined with cognitive training for Alzheimer's patients: an EEG graph study

Alzheimer's disease (AD) is the most common neurodegenerative disorder in elderly subjects. Recent studies verified the effects of cognitive training combined with repetitive transcranial magnetic stimulation (rTMS-COG) in AD patients. Here, we analyzed neuropsychological and neurophysiological data, derived from electroencephalography (EEG), to evaluate the effects of a 6-week protocol of rTMS-COG in 72 AD. We designed a randomized, double-blind, sham-controlled trial to evaluate efficacy of rTMS on 6 brain regions obtained by an individual MRI combined with COG related to brain areas to stimulate (i.e., syntax and grammar tasks, comprehension of lexical meaning and categorization tasks, action naming, object naming, spatial memory, spatial attention). Patients underwent neuropsychological and EEG examination before (T₀), after treatment (T₁), and after 40 weeks (T₂), to evaluate the effects of rehabilitation therapy. "Small World" (SW) graph approach was introduced allowing us to model the architecture of brain connectivity in order to correlate it with cognitive improvements. We found that following 6 weeks of intensive daily treatment the immediate results showed an improvement in cognitive scales among AD patients. SW present no differences before and after the treatment, whereas a crucial SW modulation emerges at 40-week follow-up, emphasizing the importance of rTMS-COG rehabilitation treatment for AD. Additional results demonstrated that the delta and alpha1 SW seem to be diagnostic biomarkers of AD, whereas alpha2 SW might represent a prognostic biomarker of cognitive recovery. Derived EEG parameters can be awarded the role of diagnostic and predictive biomarkers of AD progression, and rTMS-COG can be regarded as a potentially useful treatment for AD.

A Machine Learning-Based Holistic Approach to Predict the Clinical Course of Patients within the Alzheimer's Disease Spectrum

BACKGROUND

Alzheimer's disease (AD) is a neurodegenerative condition driven by multifactorial etiology. Mild cognitive impairment (MCI) is a transitional condition between healthy aging and dementia. No reliable biomarkers are available to predict the conversion from MCI to AD.

OBJECTIVE

To evaluate the use of machine learning (ML) on a wealth of data offered by the Alzheimer's Disease Neuroimaging Initiative (ADNI) and Alzheimer's Disease Metabolomics Consortium (ADMC) database in the prediction of the MCI to AD conversion.

METHODS

We implemented an ML-based Random Forest (RF) algorithm to predict conversion from MCI to AD. Data related to the study population (587 MCI subjects) were analyzed by RF as separate or combined features and assessed for classification power. Four classes of variables were considered: neuropsychological test scores, AD-related cerebrospinal fluid (CSF) biomarkers, peripheral biomarkers, and structural magnetic resonance imaging (MRI) variables.

RESULTS

The ML-based algorithm exhibited 86% accuracy in predicting the AD conversion of MCI subjects. When assessing the features that helped the most, neuropsychological test scores, MRI data, and CSF biomarkers were the most relevant in the MCI to AD prediction. Peripheral parameters were effective when employed in association with neuropsychological test scores. Age and sex differences modulated the prediction accuracy. AD conversion was more effectively predicted in females and younger subjects.

CONCLUSION

Our findings support the notion that AD-related neurodegenerative processes result from the concerted activity of multiple pathological mechanisms and factors that act inside and outside the brain and are dynamically affected by age and sex.

Multi-view prediction of Alzheimer's disease progression with end-to-end integrated framework

Alzheimer's disease is a common neurodegenerative brain disease that affects the elderly population worldwide. Its early automatic detection is vital for early intervention and treatment. A common solution is to perform future cognitive score prediction based on the baseline brain structural magnetic resonance image (MRI), which can directly infer the potential severity of disease. Recently, several studies have modelled disease progression by predicting the future brain MRI that can provide visual information of brain changes over time. Nevertheless, no studies explore the intra correlation of these two solutions, and it is unknown whether the predicted MRI can assist the prediction of cognitive score. Here, instead of independent prediction, we aim to predict disease progression in multi-view, i.e., predicting subject-specific changes of cognitive score and MRI volume concurrently. To achieve this, we propose an end-to-end integrated framework, where a regression model and a generative adversarial network are integrated together and then jointly optimized. Three integration strategies are exploited to unify these two models. Moreover, considering that some brain regions, such as hippocampus and middle temporal gyrus, could change significantly during the disease progression, a region-of-interest (ROI) mask and a ROI loss are introduced into the integrated framework to leverage this anatomical prior knowledge. Experimental results on the longitudinal Alzheimer's Disease Neuroimaging Initiative dataset demonstrated that the integrated framework outperformed the independent regression model for cognitive score prediction. And its performance can be further improved with the ROI loss for both cognitive score and MRI prediction.

Efficacy of non-invasive brain stimulation on global cognition and neuropsychiatric symptoms in Alzheimer's disease and mild cognitive impairment: A meta-analysis and systematic review

BACKGROUND

Non-invasive brain stimulation (NIBS) techniques have shown some promise in improving cognitive and neuropsychiatric symptoms (NPS) in people with Alzheimer's disease (AD) and its prodromal stage, mild cognitive impairment (MCI). However, data from clinical trials involving NIBS have shown inconsistent results. This meta-analysis investigated the efficacy of NIBS, specifically repetitive transcranial magnetic stimulation (rTMS), and transcranial direct current stimulation (tDCS) compared to sham stimulation on global cognition and NPS in people with AD and MCI.

METHOD

Multi-session randomized sham-controlled clinical trials were identified through MEDLINE, PsycINFO, and Embase until June 2021. Standardized mean difference (SMD) and 95% confidence interval (CI) between the active and sham treatments were calculated using random-effects meta-analyses. Included studies reported outcome measures for global cognition and/or NPS. Heterogeneity, from different NIBS techniques, disease populations, or tests used to assess global cognition or NPS, was measured using chi-square and I², and investigated using subgroup analyses. Possible effects of covariates were also investigated using meta-regressions.

RESULT

The pooled meta-analyses included 19 studies measuring global cognition (N_active=288, N_sham=264), and 9 studies investigating NPS (N_active=165, N_sham=140). NIBS significantly improved global cognition (SMD=1.14; 95% CI=0.49,1.78; p = 0.001; I² = 90.2%) and NPS (SMD=0.82; 95% CI=0.13, 1.50; p = 0.019; I² = 86.1%) relative to sham stimulation in patients with AD and MCI. Subgroup analyses found these effects were restricted to rTMS but not tDCS, and to patients with AD but not MCI. Meta-regression showed that age was significantly associated with global cognition response (N_studies=16, p = 0.020, I² = 89.51%, R² = 28.96%), with larger effects sizes in younger populations. All significant meta-analyses had large effect sizes (SMD ≥0.8), suggesting clinical utility of NIBS in the short term. There remained substantial heterogeneity across all subgroup analyses and meta-regressions (all I² > 50%). Egger's tests showed no evidence of publication biases.

CONCLUSION

rTMS improved global cognition and NPS in those with AD. Further studies in MCI and using tDCS will help to fully evaluate the specific NIBS techniques and populations most likely to benefit on global cognition and NPS measures. Additional research should investigate the long term clinical utility of NIBS in these populations.

It Is Time to Study Overlapping Molecular and Circuit Pathophysiologies in Alzheimer's and Lewy Body Disease Spectra

Alzheimer's disease (AD) is the leading cause of dementia due to neurodegeneration and is characterized by extracellular senile plaques composed of amyloid β1 - 42 (Aβ) as well as intracellular neurofibrillary tangles consisting of phosphorylated tau (p-tau). Dementia with Lewy bodies constitutes a continuous spectrum with Parkinson's disease, collectively termed Lewy body disease (LBD). LBD is characterized by intracellular Lewy bodies containing α-synuclein (α-syn). The core clinical features of AD and LBD spectra are distinct, but the two spectra share common cognitive and behavioral symptoms. The accumulation of pathological proteins, which acquire pathogenicity through conformational changes, has long been investigated on a protein-by-protein basis. However, recent evidence suggests that interactions among these molecules may be critical to pathogenesis. For example, Aβ/tau promotes α-syn pathology, and α-syn modulates p-tau pathology. Furthermore, clinical evidence suggests that these interactions may explain the overlapping pathology between AD and LBD in molecular imaging and post-mortem studies. Additionally, a recent hypothesis points to a common mechanism of prion-like progression of these pathological proteins, via neural circuits, in both AD and LBD. This suggests a need for understanding connectomics and their alterations in AD and LBD from both pathological and functional perspectives. In AD, reduced connectivity in the default mode network is considered a hallmark of the disease. In LBD, previous studies have emphasized abnormalities in the basal ganglia and sensorimotor networks; however, these account for movement disorders only. Knowledge about network abnormalities common to AD and LBD is scarce because few previous neuroimaging studies investigated AD and LBD as a comprehensive cohort. In this paper, we review research on the distribution and interactions of pathological proteins in the brain in AD and LBD, after briefly summarizing their clinical and neuropsychological manifestations. We also describe the brain functional and connectivity changes following abnormal protein accumulation in AD and LBD. Finally, we argue for the necessity of neuroimaging studies that examine AD and LBD cases as a continuous spectrum especially from the proteinopathy and neurocircuitopathy viewpoints. The findings from such a unified AD and Parkinson's disease (PD) cohort study should provide a new comprehensive perspective and key data for guiding disease modification therapies targeting the pathological proteins in AD and LBD.

Does Certainty of Genuine Treatment Increase the Drug Response in Alzheimer's Disease Patients: A Meta-Analysis and Critical Discussion

BACKGROUND

Non-specific treatment effects, such as expectations, contribute to the effectiveness of pharmacological treatments across diseases. However, the contribution of expectancy, i.e., certainty of receiving treatment, in patients with Alzheimer's disease (AD) is unknown.

OBJECTIVE

The aim is to investigate whether certainty of receiving a genuine treatment influences the response to active treatment in AD patients.

METHODS

The efficacy of active treatments in open-label trials, where patients are certain of receiving treatment (100%certainty), was compared to the same active treatments in randomized controlled trials (RCT), where patients are uncertain of receiving treatment or placebo (50%certainty).

RESULTS

In the seven open-label trials, there was no significant difference between post- and pre-treatment scores (difference in means = 0.14, 95%CI [-0.51; 0.81], p = 0.66). In the eight RCT trials, there was a significant difference between post- and pre-treatment (difference in means = -0.91, 95%CI [-1.43; -0.41], p < 0.001). There was a statistically significant difference between open-label and RCT trials (difference = 1.06, 95%CI [0.23; 1.90], p = 0.001).

CONCLUSION

Patients with AD did not benefit from certainty of receiving genuine treatment. This could be due to the nature/progression of the disease, but it could also be related to an order effect in the practice of running AD trials, where RCTs are conducted prior to open label. These findings have implications for the understanding of non-specific treatment effects in AD patients as well as for the design of clinical trials that test pharmacological treatments in AD.

Use of Fast Gamma Magnetic Stimulation Over the Left Prefrontal Dorsolateral Cortex for the Treatment of MCI and Mild Alzheimer's Disease: A Double-Blind, Randomized, Sham-Controlled, Pilot Study

Background: Alzheimer's disease (AD) animal models have shown a reduced gamma power in several brain areas, and induction of these oscillations by non-invasive methods has been shown to modify several pathogenic mechanisms of AD. In humans, the application of low-intensity magnetic fields has shown to be able to produce neural entrainment at the magnetic pulse frequency, making it useful to induce gamma frequencies. Objective: The aim of this study was to assess if the application of fast gamma magnetic stimulation (FGMS) over the left prefrontal dorsolateral cortex would be a safe and well-tolerated intervention that could potentially improve cognitive scores in subjects with mild cognitive impairment and mild AD. Methods: In these randomized, double-blind, sham-controlled study, participants were assigned to either receive daily sessions two times a day of active or sham FGMS for 6 months. Afterward, measurements of adverse effects, cognition, functionality, and depression were taken. Results: Thirty-four patients, 17 in each group, were analyzed for the primary outcome. FGMS was adequately tolerated by most of the subjects. Only four patients from the active FGMS group (23.52%) and one patient from the sham FGMS group (5.88%) presented any kind of adverse effects, showing no significant difference between groups. Nevertheless, FGMS did not significantly change cognitive, functionality, or depressive evaluations. Conclusion: FGMS over the left prefrontal dorsolateral cortex applied twice a day for 6 months resulted to be a viable intervention that can be applied safely directly from home without supervision of a healthcare provider. However, no statistically significant changes in cognitive, functionality, or depression scores compared to sham stimulation were observed. Clinical Trial Registration:www.ClinicalTrials.gov, Identifier: NCT03983655, URL: https://clinicaltrials.gov/ct2/show/NCT03983655.

Predicting progression and cognitive decline in amyloid-positive patients with Alzheimer's disease

BACKGROUND

In Alzheimer's disease, amyloid- β (A β) peptides aggregate in the lowering CSF amyloid levels - a key pathological hallmark of the disease. However, lowered CSF amyloid levels may also be present in cognitively unimpaired elderly individuals. Therefore, it is of great value to explain the variance in disease progression among patients with A β pathology.

METHODS

A cohort of n=2293 participants, of whom n=749 were A β positive, was selected from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database to study heterogeneity in disease progression for individuals with A β pathology. The analysis used baseline clinical variables including demographics, genetic markers, and neuropsychological data to predict how the cognitive ability and AD diagnosis of subjects progressed using statistical models and machine learning. Due to the relatively low prevalence of A β pathology, models fit only to A β-positive subjects were compared to models fit to an extended cohort including subjects without established A β pathology, adjusting for covariate differences between the cohorts.

RESULTS

A β pathology status was determined based on the A β₄₂/A β₄₀ ratio. The best predictive model of change in cognitive test scores for A β-positive subjects at the 2-year follow-up achieved an R² score of 0.388 while the best model predicting adverse changes in diagnosis achieved a weighted F₁ score of 0.791. A β-positive subjects declined faster on average than those without A β pathology, but the specific level of CSF A β was not predictive of progression rate. When predicting cognitive score change 4 years after baseline, the best model achieved an R² score of 0.325 and it was found that fitting models to the extended cohort improved performance. Moreover, using all clinical variables outperformed the best model based only on a suite of cognitive test scores which achieved an R² score of 0.228.

CONCLUSION

Our analysis shows that CSF levels of A β are not strong predictors of the rate of cognitive decline in A β-positive subjects when adjusting for other variables. Baseline assessments of cognitive function accounts for the majority of variance explained in the prediction of 2-year decline but is insufficient for achieving optimal results in longer-term predictions. Predicting changes both in cognitive test scores and in diagnosis provides multiple perspectives of the progression of potential AD subjects.

Questioning the Meaning of a Change on the Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog): Noncomparable Scores and Item-Specific Effects Over Time

Longitudinal invariance indicates that a construct is measured over time in the same way, and this fundamental scale property is a sine qua non to track change over time using ordinary mean comparisons. The Alzheimer's Disease Assessment Scale-cognitive (ADAS-Cog) and its subscale scores are often used to monitor the progression of Alzheimer's disease, but longitudinal invariance has not been formally evaluated. A configural invariance model was used to evaluate ADAS-Cog data as a three correlated factors structure for two visits over 6 months, and four visits over 2 years (baseline, 6, 12, and 24 months) among 341 participants with Alzheimer's disease. We also attempted to model ADAS-Cog subscales individually, and furthermore added item-specific latent variables. Neither the three-correlated factors ADAS-Cog model, nor its subscales viewed unidimensionally, achieved longitudinal configural invariance under a traditional modeling approach. No subscale achieved scalar invariance when considered unidimensional across 6 months or 2 years of assessment. In models accounting for item-specific effects, configural and metric invariance were achieved for language and memory subscales. Although some of the ADAS-Cog individual items were reliable, comparisons of summed ADAS-Cog scores and subscale scores over time may not be meaningful due to a lack of longitudinal invariance.

Preventing Loss of Independence through Exercise (PLIÉ): A Pilot Trial in Older Adults with Subjective Memory Decline and Mild Cognitive Impairment

BACKGROUND

Preventing Loss of Independence through Exercise (PLIÉ) is a group movement program initially developed for people with mild-to-moderate dementia that integrates principles from several well-established traditions to specifically address the needs of people with cognitive impairment.

OBJECTIVE

To investigate whether PLIÉ would benefit cognitive and behavioral outcomes and functional brain connectivity in older adults with milder forms of cognitive impairment.

METHODS

Participants (≥55 y) with subjective memory decline (SMD) or mild cognitive impairment (MCI) were assessed with tests of cognitive and physical function, self-report questionnaires, and resting state functional magnetic resonance imaging (rs-fMRI) on a 3 Tesla scanner before and after participating in twice weekly PLIÉ classes for 12 weeks at the San Francisco Veterans Affairs Medical Center.

RESULTS

Eighteen participants completed the pre-post intervention pilot trial. We observed significant improvements on the Alzheimer's Disease Assessment Scale cognitive subscale (ADAS-cog; effect size 0.34, p = 0.002) and enhanced functional connections between the medial prefrontal cortex (mPFC) and other nodes of the default mode network (DMN) after PLIÉ. Improvements (i.e., lower scores) on ADAS-cog were significantly correlated with enhanced functional connectivity between the mPFC and left lateral parietal cortex (Spearman's ρ= -0.74, p = 0.001) and between the mPFC and right hippocampus (Spearman's ρ= -0.83, p = 0.001). After completing PLIÉ, participants reported significant reductions in feelings of social isolation and improvements in well-being and interoceptive self-regulation.

CONCLUSION

These preliminary findings of post-PLIÉ improvements in DMN functional connectivity, cognition, interoceptive self-regulation, well-being and reduced feelings of social isolation warrant larger randomized, controlled trials of PLIÉ in older adults with SMD and MCI.

Segmented Linear Mixed Model Analysis Reveals Association of the APOEɛ4 Allele with Faster Rate of Alzheimer's Disease Dementia Progression

Background:

APOEɛ4 allele carriers present with an increased risk for late-onset Alzheimer’s disease (AD), show cognitive symptoms at an earlier age, and are more likely to transition from mild cognitive impairment (MCI) to dementia but despite this, it remains unclear whether or not the ɛ4 allele controls the rate of disease progression.

Objective:

To determine the effects of the ɛ4 allele on rates of cognitive decline and brain atrophy during MCI and dementia stages of AD.

Methods:

A segmented linear mixed model was chosen for longitudinal modeling of cognitive and brain volumetric data of 73 ɛ3/ɛ3, 99 ɛ3/ɛ4, and 39 ɛ4/ɛ4 Alzheimer’s Disease Neuroimaging Initiative participants who transitioned during the study from MCI to AD dementia.

Results:

ɛ4 carriers showed faster decline on MMSE, ADAS-11, CDR-SB, and MoCA scales, with the last two measures showing significant ɛ4 allele-dose effects after dementia transition but not during MCI. The ɛ4 effect was more prevalent in younger participants and in females. ɛ4 carriers also demonstrated faster rates of atrophy of the whole brain, the hippocampus, the entorhinal cortex, the middle temporal gyrus, and expansion of the ventricles after transitioning to dementia but not during MCI.

Conclusion:

Possession of the ɛ4 allele is associated with a faster progression of dementia due to AD. Our observations support the notion that APOE genotype not only controls AD risk but also differentially regulates mechanisms of neurodegeneration underlying disease advancement. Furthermore, our findings carry significance for AD clinical trial design.

The Role of Apolipoprotein E ε4 in Early and Late Mild Cognitive Impairment

BACKGROUND

Apolipoprotein E (APOE) ε4 is highly associated with mild cognitive impairment (MCI). However, the specific influence of APOE ε4 status on tau pathology and cognitive decline in early MCI (EMCI) and late MCI (LMCI) is poorly understood. Our goal was to evaluate the association of APOE ε4 with cerebrospinal fluid (CSF) tau levels and cognition in EMCI and LMCI patients in the Alzheimer's Disease Neuroimaging Initiative database, and whether this association was mediated by amyloid-β (Aβ).

METHODS

Participants were 269 cognitively normal (CN), 262 EMCI, and 344 LMCI patients. They underwent CSF Aβ42 and tau detection, APOE ε4 genotyping, Mini-Mental State Examination, (MMSE), and Alzheimer's disease assessment scale (ADAS)-cog assessments. Linear regressions were used to examine the relation of APOE ε4 and CSF tau levels and cognitive scores in persons with and without Aβ deposition (Aβ+ and Aβ-).

RESULTS

The prevalence of APOE ε4 is higher in EMCI and LMCI than in CN (p < 0.001 for both), and in LMCI than in EMCI (p = 0.001). APOE ε4 allele was significantly higher in Aβ+ subjects than in Aβ- subjects (p < 0.001). Subjects who had a lower CSF Aβ42 level and were APOE ε4-positive experienced higher levels of CSF tau and cognitive scores in EMCI and/or LMCI.

CONCLUSIONS

An APOE ε4 allele is associated with increased CSF tau and worse cognition in both EMCI and LMCI, and this association may be mediated by Aβ. We conclude that APOE ε4 may be an important mediator of tau pathology and cognition in the early stages of AD.

The Efficacy of Ketogenic Therapies in the Clinical Management of People with Neurodegenerative Disease: A Systematic Review

Ketone bodies have potential disease-modifying activity that represent a novel therapeutic approach for neurodegenerative diseases (NDD). The aim of this systematic review was to summarize and evaluate the evidence for the application of ketogenic therapies (dietary or exogenous ketogenic agents) for NDD and provide recommendations for future research. Eight databases were electronically searched for articles reporting on controlled trials (≥4 wk duration) that induced ketosis or elevated serum ketone concentrations in people with NDD. Of 4498 records identified, 17 articles met the inclusion criteria with a total of 979 participants including studies on mild cognitive impairment (MCI; n = 6), multiple sclerosis (n = 4), Alzheimer's disease (n = 5), Parkinson's disease (n = 1), and MCI secondary to Parkinson's disease (n = 1). Of 17 studies, 7 were randomized double-blind placebo-controlled trials. Most studies used dietary interventions (n = 9), followed by medium-chain triglycerides (n = 7) and a fasting protocol (n = 1). Generally, trials were 6 wk in duration and assessed cognition as the primary outcome. Studies were heterogeneous in type and severity of NDD, interventions used, and outcomes assessed. Overall, 3/17 studies carried a low risk of bias. Based on available evidence, exogenous ketogenic agents may be more feasible than dietary interventions in NDD from a compliance and adherence perspective; more research is required to confirm this. Recommendations for future research include improving exogenous formulations to reduce adverse effects, exploring interindividual factors affecting response-to-treatment, and establishing a "minimum required dose" for clinically meaningful improvements in disease-specific symptoms, such as cognition or motor function.

Association of Tau Pathology With Clinical Symptoms in the Subfields of Hippocampal Formation

Objective: To delineate the relationship between clinical symptoms and tauopathy of the hippocampal subfields under different amyloid statuses. Methods: One hundred and forty-three subjects were obtained from the ADNI project, including 87 individuals with normal cognition, 46 with mild cognitive impairment, and 10 with Alzheimer's disease (AD). All subjects underwent the tau PET, amyloid PET, T1W, and high-resolution T2W scans. Clinical symptoms were assessed by the Neuropsychiatric Inventory (NPI) total score and Alzheimer's Disease Assessment Scale cognition 13 (ADAS-cog-13) total score, comprising memory and executive function scores. The hippocampal subfields including Cornu Ammonis (CA1-3), subiculum (Sub), and dentate gyrus (DG), as well as the adjacent para-hippocampus (PHC) and entorhinal cortex (ERC), were segmented automatically using the Automatic Segmentation of Hippocampal Subfields (ASHS) software. The relationship between tauopathy/volume of the hippocampal subfields and assessment scores was calculated using partial correlation analysis under different amyloid status, by controlling age, gender, education, apolipoprotein E (APOE) allele ɛ4 carrier status, and, time interval between the acquisition time of tau PET and amyloid PET scans. Results: Compared with amyloid negative (A-) group, individuals from amyloid positive (A+) group are more impaired based on the Mini-mental State Examination (MMSE; p = 3.82e-05), memory (p = 6.30e-04), executive function (p = 0.0016), and ADAS-cog-13 scores (p = 5.11e-04). Significant decrease of volume (CA1, DG, and Sub) and increase of tau deposition (CA1, Sub, ERC, and PHC) of the hippocampal subfields of both hemispheres were observed for the A+ group compared to the A- group. Tauopathy of ERC is significantly associated with memory score for the A- group, and the associated regions spread into Sub and PHC for the A+ group. The relationship between the impairment of behavior or executive function and tauopathy of the hippocampal subfield was discovered within the A+ group. Leftward asymmetry was observed with the association between assessment scores and tauopathy of the hippocampal subfield, which is more prominent for the NPI score for the A+ group. Conclusion: The associations of tauopathy/volume of the hippocampal subfields with clinical symptoms provide additional insight into the understanding of local changes of the human HF during the AD continuum and can be used as a reference for future studies.

Interventional Study to Evaluate the Clinical Effects and Safety of the Nutraceutical Compound BrainUp-10® in a Cohort of Patients with Alzheimer's Disease: A Multicenter, Randomized, Double-Blind, and Placebo-Controlled Trial

BACKGROUND

Clinically-evaluated nutraceuticals are candidates for Alzheimer's disease (AD) prevention and treatment. Phase I studies showed biological safety of the nutraceutical BrainUp-10®, while a pilot trial demonstrated efficacy for treatment. Cell studies demonstrated neuroprotection. BrainUp-10® blocks tau self-assembly. Apathy is the most common of behavioral alterations.

OBJECTIVE

The aim was to explore efficacy of BrainUp-10® in mitigating cognitive and behavioral symptoms and in providing life quality, in a cohort of Chilean patients with mild to moderate AD.

METHODS

The was a multicenter, randomized, double blind, placebo-controlled phase II clinical study in mild to moderate AD patients treated with BrainUp-10® daily, while controls received a placebo. Primary endpoint was Apathy (AES scale), while secondary endpoints included Mini-Mental State Examination (MMSE), Trail Making Test (TMT A and TMT B), and Neuropsychiatry Index (NPI). AD blood biomarkers were analyzed. Laboratory tests were applied to all subjects.

RESULTS

82 patients were enrolled. The MMSE score improved significantly at week 24 compared to baseline with tendency to increase, which met the pre-defined superiority criteria. NPI scores improved, the same for caregiver distress at 12th week (p = 0.0557), and the alimentary response (p = 0.0333). Apathy tests showed a statistically significant decrease in group treated with BrainUp-10®, with p = 0.0321 at week 4 and p = 0.0480 at week 12 treatment. A marked decrease in homocysteine was shown with BrainUp-10® (p = 0.0222).

CONCLUSION

Data show that BrainUp-10® produces a statistically significant improvement in apathy, ameliorating neuropsychiatric distress of patients. There were no compound-related adverse events. BrainUp-10® technology may enable patients to receive the benefits for their cognitive and behavioral problems.

A Randomized Clinical Trial of Greek High Phenolic Early Harvest Extra Virgin Olive Oil in Mild Cognitive Impairment: The MICOIL Pilot Study

BACKGROUND

Extra virgin olive oil (EVOO) constitutes a natural compound with high protection over cognitive function.

OBJECTIVE

To investigate for the first time the effect of Greek High Phenolic Early Harvest Extra Virgin Olive Oil (HP-EH-EVOO) versus Moderate Phenolic (MP-EVOO) and Mediterranean Diet (MeDi) in people with mild cognitive impairment (MCI).

METHODS

We conducted a randomized prospective study so as to examine the HP-EH-EVOO and MP-EVOO versus MeDi in MCI. Genetic predisposition (APOEɛ4) to Alzheimer's disease (AD) was tested and an extensive neuropsychological battery was administered at baseline and after 12 months. Each participant was randomized and assigned one of three groups: 1) Group 1 received the HP-EH-EVOO (50 mL/day); 2) Group 2 received the MP-EVOO (50 mL/day), and 3) Group 3 received only the MeDi instructions.

RESULTS

Better follow-up performance was found in Group 1 compared to Group 2 and Group 3 in the almost all cognitive domains. Moreover, Group 2 showed also significant improvement compared to Group 3 in ADAS-cog (p = 0.001) and MMSE (p = 0.05), whereas Group 3 exhibited worse or similar to baseline performance in almost all domains. In particular, Group 1 and Group 2 had better outcomes with regards to ADAS-cog (p = 0.003), Digit Span (p = 0.006), and Letter fluency (p = 0.003). Moreover, there was a significant difference (p = 0.001) in the presence of APOEɛ4 between the Groups 1 and 2 versus Group 3.

CONCLUSION

Long-term intervention with HP-EH-EVOO or MP-EVOO was associated with significant improvement in cognitive function compared to MeDi, independent of the presence of APOEɛ4.

Neurocognitive effects of melatonin treatment in healthy adults and individuals with Alzheimer's disease and insomnia: A systematic review and meta-analysis of randomized controlled trials

Endogenous melatonin levels are inversely associated with age and cognitive deficits. Although melatonin can improve psychopathological behavior disturbances in clinical trials, whether melatonin may also enhance cognitive function remains elusive. This study examined cognitive outcomes from randomized trials of melatonin treatment for Alzheimer's disease (AD), insomnia, and healthy-subjects. Twenty-two studies met the inclusion criteria (AD = 9, insomnia = 2, healthy-subjects = 11). AD patients receiving >12 weeks of melatonin treatment improved mini-mental state examination (MMSE) score [MD: 1.82 (1.01; 2.63) p < 0.0001]. Importantly, melatonin significantly improved MMSE score in mild stage of AD [MD: 1.89 (0.96; 2.82) p < 0.0001]. In healthy-subjects, although daytime melatonin treatment notably decreased in accuracy by correct responses [SMD: -0.74 (-1.03; -0.45) p < 0.00001], the reaction-time score on different stimuli (p = 0.37) did not increased. Additionally, by pooling of short-term, spatial, and visual memory scores, melatonin did not reduce memory function (p = 0.08). Meta-analysis of MMSE score suggested that melatonin is effective in treatment for mild stage of AD. Additionally, we propose that melatonin may be preferable to traditional hypnotics in management of insomnia.

Linking the Mini-Mental State Examination, the Alzheimer's Disease Assessment Scale-Cognitive Subscale and the Severe Impairment Battery: evidence from individual participant data from five randomised clinical trials of donepezil

BACKGROUND

The Mini-Mental State Examination (MMSE), the Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog) and the Severe Impairment Battery (SIB) are widely used rating scales to assess cognition in Alzheimer's disease.

OBJECTIVE

To understand the correspondence between these rating scales, we aimed to examine the linkage of MMSE with the ADAS-Cog and SIB total and change scores.

METHODS

We used individual-level data on participants with Alzheimer's disease (n=2925) from five pivotal clinical trials of donepezil. Data were collected at baseline and scheduled visits for up to 6 months. We used equipercentile linking to identify the correspondence between simultaneous measurements of MMSE with ADAS-Cog, and SIB total and change ratings.

FINDINGS

Spearman's correlation coefficients were of strong magnitude between the MMSE total score and the ADAS-Cog (rs from -0.82 to -0.87; p<0.05) and SIB total scores (rs from 0.70 to 0.75; p<0.05). Weaker correlations between the change scores were observed between the MMSE change score and the ADAS-Cog (week 1: r=-0.11, p=0.18; rs thereafter: -0.28 to -0.45; p<0.05) and SIB change scores (rs from 0.31 to 0.44; p<0.05). Linking suggested that the MMSE total scores were sensitive to moderate and severe cognitive impairment levels. Despite weak to moderate correlations for the change scores, moderate change levels linked well, indicating ceiling and floor effects.

CONCLUSIONS

The current results can be used in meta-analyses, data harmonisation and may contribute to increasing statistical power when pooling data from multiple sources.

CLINICAL IMPLICATIONS

The current study results help clinicians to understand these cognitive rating scale scores.

A Review of Brain Atrophy Subtypes Definition and Analysis for Alzheimer’s Disease Heterogeneity Studies

Alzheimer’s disease (AD) is a heterogeneous disease with different subtypes. Studying AD subtypes from brain structure, neuropathology, and cognition are of great importance for AD heterogeneity research. Starting from the study of constructing AD subtypes based on the features of T1-weighted structural magnetic resonance imaging, this paper introduces the major connections between the subtype definition and analysis strategies, including brain region-based subtype definition, and their demographic, neuropathological, and neuropsychological characteristics. The advantages and existing problems are analyzed, and reasonable improvement schemes are prospected. Overall, this review offers a more comprehensive view in the field of atrophy subtype in AD, along with their advantages, challenges, and future prospects, and provide a basis for improving individualized AD diagnosis.

Psychometric properties of outcome measures in non-pharmacological interventions of persons with dementia in low-and middle-income countries: A systematic review

Despite high burden of dementia in low-and middle-income countries (LMICs), only a small number of clinical trials of psychosocial interventions for persons with dementia (PwD) have been conducted in these settings. It is essential that such trials use appropriate outcome measures that are methodologically robust and culturally appropriate to evaluate the effectiveness of interventions. We carried out a systematic review to examine the evidence base and psychometric properties of measures employed in these studies in LMICs. A systematic search of published literature on randomised controlled trials (RCT) of psychosocial interventions for PwD in LMICs between 2008 and April 2020 was carried out. Measures employed in each of the eligible studies were identified and through a focused search, we further explored the evidence base and psychometric properties employing Terwee criteria. Data extraction and quality appraisal were conducted by two independent reviewers. The review identified 41 measures from 17 RCTS which fulfilled eligibility criteria and they examined effectiveness across the domains of cognition (n = 16), behaviour and psychological symptoms (n = 11) and quality of life (n = 8). Of these 41, we were able to access relevant literature only for 18 and they were subject to psychometric analysis. Psychometric properties of these 18 instruments were at best modest, with Terwee scores ranging from 3 (low) to 15 (moderate). A majority of the studies were from China (n = 5) and Brazil (n = 6). The evidence base for the routinely employed measures in RCTs of non-pharmacological interventions for PwD in LMICs is limited. The quality of adaptation and validation of these instruments is variable and studies are largely uninformative about their psychometric properties and cultural appropriateness to the study setting. There is an urgent need to develop scientifically robust instruments in LMIC settings that can be confidently employed to measure outcomes in trials of psychosocial interventions for PwD.

Quantifying the heterogeneity of cognitive functioning in Alzheimer's disease to extend the placebo-treatment dichotomy: Latent class analysis of individual-participant data from five pivotal randomized clinical trials of donepezil

BACKGROUND

The extent and profiles of heterogeneity in cognitive functioning among participants in clinical trials of antidementia medication are unknown. We aimed to quantify and identify profiles of heterogeneity of cognition in Alzheimer's disease.

METHODS

Individual-level participant data were analyzed from five pivotal clinical trials of donepezil for Alzheimer's disease (N = 2,919). Based on Alzheimer's Disease Assessment Scale-Cognitive Subscale total scores from baseline up to week 12, a latent class model was used to identify heterogeneous groups. A logistic regression model was used to examine factors associated with group membership. Sensitivity analysis was conducted, restricted to the donepezil, and then the placebo arm.

RESULTS

The latent class model identified three classes labeled as low scorers (i.e., least cognitive impairment; N = 1,666, 76.04%), improvers (N = 27, 1.23%), and high scorers (N = 498, 22.73%). Logistic modeling showed that donepezil compared to placebo was significantly (p < 0.05) positively associated with membership in the improvers class (OR = 6.88, 95% CI = 2.03, 42.95), and negatively with high scorers (OR = 0.79, 95% CI = 0.64, 0.98). Sensitivity analysis restricted to the placebo, then donepezil arms replicated similar heterogeneity patterns.

CONCLUSIONS

Our results inform clinicians regarding the extent of heterogeneity in cognitive functioning during treatment and contribute to trial design considerations.

A White Matter Connection of Schizophrenia and Alzheimer's Disease

Schizophrenia (SZ) is a severe psychiatric illness associated with an elevated risk for developing Alzheimer's disease (AD). Both SZ and AD have white matter abnormalities and cognitive deficits as core disease features. We hypothesized that aging in SZ patients may be associated with the development of cerebral white matter deficit patterns similar to those observed in AD. We identified and replicated aging-related increases in the similarity between white matter deficit patterns in patients with SZ and AD. The white matter "regional vulnerability index" (RVI) for AD was significantly higher in SZ patients compared with healthy controls in both the independent discovery (Cohen's d = 0.44, P = 1·10-5, N = 173 patients/230 control) and replication (Cohen's d = 0.78, P = 9·10-7, N = 122 patients/64 controls) samples. The degree of overlap with the AD deficit pattern was significantly correlated with age in patients (r = .21 and .29, P < .01 in discovery and replication cohorts, respectively) but not in controls. Elevated RVI-AD was significantly associated with cognitive measures in both SZ and AD. Disease and cognitive specificities were also tested in patients with mild cognitive impairment and showed intermediate overlap. SZ and AD have diverse etiologies and clinical courses; our findings suggest that white matter deficits may represent a key intersecting point for these 2 otherwise distinct diseases. Identifying mechanisms underlying this white matter deficit pattern may yield preventative and treatment targets for cognitive deficits in both SZ and AD patients.

Cognitive and MRI trajectories for prediction of Alzheimer's disease

The concept of Mild Cognitive Impairment (MCI) is used to describe the early stages of Alzheimer's disease (AD), and identification and treatment before further decline is an important clinical task. We selected longitudinal data from the ADNI database to investigate how well normal function (HC, n= 134) vs. conversion to MCI (cMCI, n= 134) and stable MCI (sMCI, n=333) vs. conversion to AD (cAD, n= 333) could be predicted from cognitive tests, and whether the predictions improve by adding information from magnetic resonance imaging (MRI) examinations. Features representing trajectories of change in the selected cognitive and MRI measures were derived from mixed effects models and used to train ensemble machine learning models to classify the pairs of subgroups based on a subset of the data set. Evaluation in an independent test set showed that the predictions for HC vs. cMCI improved substantially when MRI features were added, with an increase in [Formula: see text]-score from 60 to 77%. The [Formula: see text]-scores for sMCI vs. cAD were 77% without and 78% with inclusion of MRI features. The results are in-line with findings showing that cognitive changes tend to manifest themselves several years after the Alzheimer's disease is well-established in the brain.

Quantitative Longitudinal Predictions of Alzheimer's Disease by Multi-Modal Predictive Learning

BACKGROUND

Quantitatively predicting the progression of Alzheimer's disease (AD) in an individual on a continuous scale, such as the Alzheimer's Disease Assessment Scale-cognitive (ADAS-cog) scores, is informative for a personalized approach as opposed to qualitatively classifying the individual into a broad disease category.

OBJECTIVE

To evaluate the hypothesis that the multi-modal data and predictive learning models can be employed for future predicting ADAS-cog scores.

METHODS

Unimodal and multi-modal regression models were trained on baseline data comprised of demographics, neuroimaging, and cerebrospinal fluid based markers, and genetic factors to predict future ADAS-cog scores for 12, 24, and 36 months. We subjected the prediction models to repeated cross-validation and assessed the resulting mean absolute error (MAE) and cross-validated correlation (ρ) of the model.

RESULTS

Prediction models trained on multi-modal data outperformed the models trained on single modal data in predicting future ADAS-cog scores (MAE12, 24 & 36 months= 4.1, 4.5, and 5.0, ρ12, 24 & 36 months= 0.88, 0.82, and 0.75). Including baseline ADAS-cog scores to prediction models improved predictive performance (MAE12, 24 & 36 months= 3.5, 3.7, and 4.6, ρ12, 24 & 36 months= 0.89, 0.87, and 0.80).

CONCLUSION

Future ADAS-cog scores were predicted which could aid clinicians in identifying those at greater risk of decline and apply interventions at an earlier disease stage and inform likely future disease progression in individuals enrolled in AD clinical trials.

Cognitive Improvement Effects of Electroacupuncture Combined with Computer-Based Cognitive Rehabilitation in Patients with Mild Cognitive Impairment: A Randomized Controlled Trial

This outcome assessor-blinded, randomized controlled clinical trial investigated the effects of electroacupuncture combined with computer-based cognitive rehabilitation (EA-CCR) on mild cognitive impairment (MCI). A per-protocol analysis was employed to compare the efficacy of EA-CCR to that of computer-based cognitive rehabilitation (CCR). Thirty-two patients with MCI completed the trial (EA-CCR group, 16; CCR group, 16). Patients received EA-CCR or CCR treatment once daily three days per week for eight weeks. Outcome (primary, ADAS-K-cog; secondary, MoCA-K, CES-D, K-ADL, K-IADL, and EQ-5D-5L) measurements were performed at baseline (week 0), at the end of the intervention (week 8), and at 12 weeks after completion of the intervention (week 20). Both groups showed significant changes in ADAS-K-cog score (EA-CCR, p < 0.001; CCR, p < 0.001) and MoCA-K (EA-CCR, p < 0.001; CCR, p < 0.001). Only the EA-CCR group had a significant change in CES-D (p = 0.024). No significant differences in outcomes and in the results of a subanalysis based on age were noted between the groups. These results indicate that EA-CCR and CCR have beneficial effects on improving cognitive function in patients with MCI. However, electroacupuncture in EA-CCR showed no positive add-on effects on improving cognitive function, depression, activities of daily living, and quality of life in patients with MCI.

Predicting the outcome of non-pharmacological treatment for patients with dementia-related mild cognitive impairment

Dementia is a progressive cognitive syndrome, with few effective pharmacological treatments that can slow its progress. Hence, non-pharmacological treatments (NPTs) play an important role in improving patient symptoms and quality of life. Designing the optimal personalised NPT strategy relies on objectively and quantitatively predicting the treatment outcome. Magnetoencephalography (MEG) findings can reflect the cognitive status of patients with dementia, and thus potentially predict NPT outcome. In the present study, 16 participants with cognitive impairment underwent NPT for several months. Their cognitive performance was evaluated based on the Mini-Mental State Examination and the Alzheimer's Disease Assessment Scale - Cognitive at the beginning and end of the NPT period, while resting-state brain activity was evaluated using MEG during the NPT period. Our results showed that the spectral properties of MEG signals predicted the changes in cognitive performance scores. High frequency oscillatory intensity at the right superior frontal gyrus medial segment, opercular part of the inferior frontal gyrus, triangular part of the inferior frontal gyrus, post central gyrus, and angular gyrus predicted the changes in cognitive performance scores. Thus, resting-state brain activity may be a powerful tool in designing personalised NPT.

Restoration of BMI1 levels after the administration of early harvest extra virgin olive oil as a therapeutic strategy against Alzheimer's disease

Even though Alzheimer's disease (AD) is the most common cause of dementia, the mechanisms governing the establishment and progression of the disease remain largely unknown. Here, we investigated the implication of the neuroprotective protein BMI1 (B lymphoma Mo-MLV insertion region 1 homolog) in AD and the possibility to reverse the onset of the disease through the administration of extra virgin olive oil (EVOO) in Mild Cognitive Impairment (MCI) patients. For this purpose, we utilized a wide bank of MCI patient samples to examine the potential effects of EVOO. We found that while EVOO treatment increases BMI1 levels, p53 levels drop in MCI patient serum after EVOO treatment for 12 months. Additionally, AD-related biomarkers (p-tau, Aβ1-42 and Aβ1-42/Aβ-40 ratio) return to normal levels after administration of EVOO in MCI patients for 12 months. Moreover, we show that upon EVOO administration, BMI1-upregulation correlates with reduction of oxidative stress and inflammatory responses. In conclusion, we provide clinical trial evidence to confirm that restoration of BMI1 activity through EVOO administration in MCI patients constitutes a potential therapeutic approach against neurodegeneration leading to AD.

Early detection and personalized medicine: Future strategies against Alzheimer's disease

Alzheimer's disease (AD) is the leading cause of dementia and sixth cause of death in elderly adults. AD poses a huge economic burden on society and constitutes an unprecedented challenge for caregivers and families affected. Aging of the population is projected to drastically aggravate the situation in the near future. To date, no therapy is available to prevent or ameliorate the disease. Moreover, several clinical trials for promising therapeutic agents have failed. Lack of supporting biomarker data for pre-symptomatic enrollment and inaccurate stratification of patients based on genetic heterogeneity appear to be contributing factors to this lack of success. Recently, the treatment of cancer has seen enormous advances based on the personalized genetics and biomarkers of the individual patient, forming the foundation of precision medicine for cancer. Likewise, technological progress in AD biomarker research promises the availability of reliable assays for pathology staging on a routine basis relatively soon. Moreover, tremendous achievements in AD genetics and high-throughput genotyping technology allow identification of predisposing risk alleles accurately and on a large scale. Finally, availability of electronic health records (EHR) promises the opportunity to integrate biomarker, genomic and clinical data efficiently. Together, these advances will form the basis of precision medicine for AD.

The use of the Hungarian Test Your Memory (TYM-HUN), MMSE, and ADAS-Cog tests for patients with mild cognitive impairment (MCI) in a Hungarian population: a cross-sectional study

BACKGROUND

Mild cognitive impairment (MCI) often presages the development of Alzheimer's disease (AD). Accurate and early identification of cognitive impairment will substantially reduce the burden on the family and alleviate the costs for the whole society. There is a need for testing methods that are easy to perform even in a general practitioner's office, inexpensive and non-invasive, which could help the early recognition of mental decline. We have selected the Test Your Memory (TYM), which has proven to be reliable for detecting AD and MCI in several countries. Our study was designed to test the usability of the Hungarian version of the TYM (TYM-HUN) comparing with the Mini-Mental State Examination (MMSE) and the Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog) in MCI recognition in the Hungarian population.

METHODS

TYM test was translated and validated into Hungarian (TYM-HUN) in a previous study. The TYM-HUN test was used in conjunction with and compared with the MMSE and the ADAS-Cog. For our study, 50 subjects were selected: 25 MCI patients and 25 healthy controls (HC). Spearman's rank correlation was used to analyse the correlation between the scores of MMSE and ADAS-Cog with TYM-HUN and the receiver operating characteristic (ROC) curve was established.

RESULTS

MCI can be distinguished from normal aging using TYM-HUN. We established a 'cut-off' point of TYM-HUN (44/45points) where optimal sensitivity (80%) and specificity (96%) values were obtained to screen MCI. The total TYM-HUN scores significantly correlated with the MMSE scores (ρ = 0.626; p < 0.001) and ADAS-Cog scores (ρ = - 0.723; p < 0.001).

CONCLUSIONS

Our results showed that the TYM-HUN is a reliable, fast, self-administered questionnaire with the right low threshold regarding MCI and can be used for the early diagnosis of cognitive impairment.

Association between Structural Connectivity and Generalized Cognitive Spectrum in Alzheimer's Disease

Modeling disease progression through the cognitive scores has become an attractive challenge in the field of computational neuroscience due to its importance for early diagnosis of Alzheimer's disease (AD). Several scores such as Alzheimer's Disease Assessment Scale cognitive total score, Mini Mental State Exam score and Rey Auditory Verbal Learning Test provide a quantitative assessment of the cognitive conditions of the patients and are commonly used as objective criteria for clinical diagnosis of dementia and mild cognitive impairment (MCI). On the other hand, connectivity patterns extracted from diffusion tensor imaging (DTI) have been successfully used to classify AD and MCI subjects with machine learning algorithms proving their potential application in the clinical setting. In this work, we carried out a pilot study to investigate the strength of association between DTI structural connectivity of a mixed ADNI cohort and cognitive spectrum in AD. We developed a machine learning framework to find a generalized cognitive score that summarizes the different functional domains reflected by each cognitive clinical index and to identify the connectivity biomarkers more significantly associated with the score. The results indicate that the efficiency and the centrality of some regions can effectively track cognitive impairment in AD showing a significant correlation with the generalized cognitive score (R = 0.7).

Clustering of Alzheimer's and Parkinson's disease based on genetic burden of shared molecular mechanisms

One of the visions of precision medicine has been to re-define disease taxonomies based on molecular characteristics rather than on phenotypic evidence. However, achieving this goal is highly challenging, specifically in neurology. Our contribution is a machine-learning based joint molecular subtyping of Alzheimer's (AD) and Parkinson's Disease (PD), based on the genetic burden of 15 molecular mechanisms comprising 27 proteins (e.g. APOE) that have been described in both diseases. We demonstrate that our joint AD/PD clustering using a combination of sparse autoencoders and sparse non-negative matrix factorization is reproducible and can be associated with significant differences of AD and PD patient subgroups on a clinical, pathophysiological and molecular level. Hence, clusters are disease-associated. To our knowledge this work is the first demonstration of a mechanism based stratification in the field of neurodegenerative diseases. Overall, we thus see this work as an important step towards a molecular mechanism-based taxonomy of neurological disorders, which could help in developing better targeted therapies in the future by going beyond classical phenotype based disease definitions.

Scope of β-Secretase (BACE1)-Targeted Therapy in Alzheimer's Disease: Emphasizing the Flavonoid Based Natural Scaffold for BACE1 Inhibition

Alzheimer's disease (AD) is a progressive neurodegenerative disease and the most common form of dementia in the world. Studies report the presence of extracellular amyloid plaques consisting of β-amyloid peptide and intracellular tangles consisting of hyperphosphorylated tau proteins as the histopathological indicators of AD. The process of β-amyloid peptide generation by sequential cleavage of amyloid precursor protein by β-secretase (BACE1) and γ-secretase, followed by its aggregation to form amyloid plaques, is the mechanistic basis of the amyloid hypothesis. Other popular hypotheses related to the pathogenesis of AD include the tau hypothesis and the oxidative stress hypothesis. Various targets of the amyloid cascade are now in prime focus to develop drugs for AD. Many BACE1 inhibitors, β-amyloid aggregation inhibitors, and Aβ clearance strategies using monoclonal antibodies are in various stages of clinical trials. This review provides an in-depth evaluation of the role of BACE1 in disease pathogenesis and also highlights the therapeutic approaches developed to find more potent but less toxic inhibitors for BACE1, particularly emphasizing the natural scaffold as a nontoxic lead for BACE1 inhibition. Cellular targets and signaling cascades involving BACE1 have been highlighted to understand the physiological role of BACE1. This knowledge is extremely crucial to understand the toxicity evaluations for BACE1-targeted therapy. We have particularly highlighted the scope of flavonoids as a new generation of nontoxic BACE1 inhibitory scaffolds. The structure-activity relationship of BACE1 inhibition for this group of compounds has been highlighted to provide a guideline to design more selective highly potent inhibitors. The review aims to provide a holistic overview of BACE1-targeted therapy for AD that paves the way for future drug development.

Memantine, Donepezil, or Combination Therapy-What is the best therapy for Alzheimer's Disease? A Network Meta-Analysis

INTRODUCTION

Alzheimer's disease (AD) is a degenerative brain disease that progresses over time, heavily burdening patients, families, and aging societies worldwide. Memantine and donepezil are frequently used in its treatment, both as monotherapy and in combination. This multiple treatment comparison meta-analysis assessed the efficacy of these regimens and placebo in the management of AD.

METHODS

We searched PubMed, Embase, the Cochrane Library, and Wanfang Med Online and China National Knowledge Infrastructure for English and Chinese publications from the first records to 17 April 2020. Two investigators scanned articles for placebo-controlled trials of memantine and donepezil alone and in combination. We extracted data on the following outcomes: cognition, global assessment, daily activities, neuropsychiatric symptoms, adverse events, and the acceptability and cost of these treatment regimens.

RESULTS

Of 936 records screened, we included 54 trials in this analysis. The combination therapy was more effective in improving cognition (mean difference (MD)-5.01, 95% credible interval (95% Crl) -10.73 to 0.86 in the Alzheimer's Disease Assessment Scale-Cognitive Subscale; MD 9.61, 95% Crl 2.29 to 16.97 in the Severe Impairment Battery), global assessment (MD -2.88, 95% Crl -6.04 to 0.40), daily activities (MD 13.06, 95% Crl -34.04 to 58.92), and neuropsychiatric symptoms (MD -6.84, 95% Crl -10.62 to -2.82) compared with placebo. Memantine was more acceptable than placebo (MD 0.93, 95% Crl 0.69 to 1.22).

CONCLUSIONS

Memantine plus donepezil showed superior outcomes for cognition, global assessment, daily activities, and neuropsychiatric symptoms, but lower acceptability than monotherapy and placebo. Combination therapy may be more cost-effective, because memantine slows the progression of AD.

Detect and correct bias in multi-site neuroimaging datasets

The desire to train complex machine learning algorithms and to increase the statistical power in association studies drives neuroimaging research to use ever-larger datasets. The most obvious way to increase sample size is by pooling scans from independent studies. However, simple pooling is often ill-advised as selection, measurement, and confounding biases may creep in and yield spurious correlations. In this work, we combine 35,320 magnetic resonance images of the brain from 17 studies to examine bias in neuroimaging. In the first experiment, Name That Dataset, we provide empirical evidence for the presence of bias by showing that scans can be correctly assigned to their respective dataset with 71.5% accuracy. Given such evidence, we take a closer look at confounding bias, which is often viewed as the main shortcoming in observational studies. In practice, we neither know all potential confounders nor do we have data on them. Hence, we model confounders as unknown, latent variables. Kolmogorov complexity is then used to decide whether the confounded or the causal model provides the simplest factorization of the graphical model. Finally, we present methods for dataset harmonization and study their ability to remove bias in imaging features. In particular, we propose an extension of the recently introduced ComBat algorithm to control for global variation across image features, inspired by adjusting for unknown population stratification in genetics. Our results demonstrate that harmonization can reduce dataset-specific information in image features. Further, confounding bias can be reduced and even turned into a causal relationship. However, harmonization also requires caution as it can easily remove relevant subject-specific information. Code is available at https://github.com/ai-med/Dataset-Bias.

A Brief Version of the LASSI-L Detects Prodromal Alzheimer's Disease States

BACKGROUND

The Loewenstein-Acevedo Scales for Semantic Interference and Learning (LASSI-L) is an increasingly utilized cognitive stress test designed to identify early cognitive changes associated with incipient neurodegenerative disease.

OBJECTIVE

To examine previously derived cut-points for cognitively unimpaired older adults that were suggestive of performance impairment on multiple subscales of the LASSI-L. These cut-points were applied to a new sample of older adults who were cognitive healthy controls (HC: n = 26) and those on the Alzheimer's disease (AD) continuum from early stage mild cognitive impairment (EMCI: n = 28), late stage MCI (LMCI: n = 18) to mild AD (AD: n = 27).

METHODS

All participants were administered the LASSI-L. All cognitively impaired participants were PET amyloid positive which likely reflects underlying AD neuropathology, while cognitively normal counterparts were deemed to have amyloid negative scans.

RESULTS

There was a monotonic relationship between the number of deficits on LASSI-L subscales and independent classification of study groups with greater severity of cognitive impairment. Importantly, taken together, impairment on maximum learning ability and measures of proactive semantic interference (both reflected by cued recall and intrusion errors) correctly classified 74.1% of EMCI, 94.4% of LMCI, and 96.3% of AD. Only 7.7% of HC were incorrectly classified as having impairments.

CONCLUSION

A modest number of LASSI-L subscales taking approximately 8 minutes to administer, had excellent discriminative ability using established cut-offs among individuals with presumptive stages of AD. This has potential implications for both clinical practice and clinical research settings targeting AD during early prodromal stages.

Rivastigmine in Parkinson's Disease Dementia with Orthostatic Hypotension

OBJECTIVE

The purpose of this study was to evaluate if the cognitive benefit of rivastigmine is affected by the presence of orthostatic hypotension (OH) in patients with Parkinson's disease dementia (PDD).

METHODS

We conducted a post hoc analysis on 1,047 patients with PDD from 2 randomized controlled trials comparing rivastigmine versus placebo at week 24 (n = 501) and rivastigmine patch versus capsule at week 76 (n = 546). A drop ≥ 20 mm Hg in systolic blood pressure (SBP) or ≥ 10 in diastolic blood pressure (DBP) upon standing classified subjects as OH positive (OH+); otherwise, OH negative (OH-). The primary end point was the Alzheimer's Disease Assessment Scale - Cognitive subscale (ADAS-Cog) at week 24 and the Mattis Dementia Rating Scale (MDRS) at week 76, using intention-to-treat with retrieved dropout at week 24 and observed cases at week 76, consistent with the original analyses.

RESULTS

Overall safety was comparable between OH+ (n = 288, 27.5%) and OH- (n = 730, 69.7%), except for higher frequency of syncope (9.2%) in the OH+ placebo arm. The placebo-adjusted effect of rivastigmine on ADAS-Cog at week 24 was 5.6 ± 1.2 for OH+ and 1.9 ± 0.9 in OH- (p = 0.0165). Among subjects with OH, the MDRS change from baseline at week 76 was higher for rivastigmine capsules versus patch (10.6 ± 2.9 vs -1.5 ± 3.0, p = 0.031). The overall prevalence of OH was lower for rivastigmine than placebo at week 24 (28.3% vs 44.6%, p = 0.0476).

INTERPRETATION

The cognitive benefit from rivastigmine is larger in patients with PDD with OH, possibly mediated by a direct antihypotensive effect. ANN NEUROL 2021;89:91-98.

Interaction between high-density lipoproteins and inflammation: Function matters more than concentration!

High-density lipoprotein (HDL) plays an important role in lipid metabolism and especially contributes to the reverse cholesterol transport pathway. Over recent years it has become clear that the effect of HDL on immune-modulation is not only dependent on HDL concentration but also and perhaps even more so on HDL function. This review will provide a concise general introduction to HDL followed by an overview of post-translational modifications of HDL and a detailed overview of the role of HDL in inflammatory diseases. The clinical potential of HDL and its main apolipoprotein constituent, apoA-I, is also addressed in this context. Finally, some conclusions and remarks that are important for future HDL-based research and further development of HDL-focused therapies are discussed.

Positron Emission Tomography in the Inflamed Cerebellum: Addressing Novel Targets among G Protein-Coupled Receptors and Immune Receptors

Inflammatory processes preceding clinical manifestation of brain diseases are moving increasingly into the focus of positron emission tomographic (PET) investigations. A key role in inflammation and as a target of PET imaging efforts is attributed to microglia. Cerebellar microglia, with a predominant ameboid and activated subtype, is of special interest also regarding improved and changing knowledge on functional involvement of the cerebellum in mental activities in addition to its regulatory role in motor function. The present contribution considers small molecule ligands as potential PET tools for the visualization of several receptors recognized to be overexpressed in microglia and which can potentially serve as indicators of inflammatory processes in the cerebellum. The sphingosine 1 phosphate receptor 1 (S1P1), neuropeptide Y receptor 2 (NPY2) and purinoceptor Y12 (P2Y12) cannabinoid receptors and the chemokine receptor CX3CR1 as G-protein-coupled receptors and the ionotropic purinoceptor P2X7 provide structures with rather classical binding behavior, while the immune receptor for advanced glycation end products (RAGE) and the triggering receptor expressed on myeloid cells 2 (TREM2) might depend for instance on further accessory proteins. Improvement in differentiation between microglial functional subtypes in comparison to the presently used 18 kDa translocator protein ligands as well as of the knowledge on the role of polymorphisms are special challenges in such developments.