Mild Alzheimer's Disease Patients Research Articles

Safety and efficacy of Lomecel‐B in patients with mild Alzheimer’s disease: Results of a double‐blinded, randomized, placebo‐controlled phase 1 clinical trial

AbstractBackgroundLomecel‐B is a formulation of allogeneic medicinal signaling cells (MSCs), which exert pleiotropic mechanisms of action (MOAs) with potential to simultaneously target multiple pathophysiological features of Alzheimer’s disease (AD).MethodWe conducted a double‐blinded, randomized, placebo‐controlled trial (ClinicalTrials.gov: NCT02600130). Mild AD patients (Table) were infused with Lomecel‐B at 20 (20M, N=15) or 100 million cells (100M, N=10), or placebo (N=8). Eligibility screening included clinical evaluation, MRI to exclude other etiologies, and beta‐amyloid tracer PET to confirm AD. Scheduled follow‐ups were conducted through 1‐year post‐treatment. The primary endpoint was safety. Pre‐specified secondary endpoints evaluated efficacy in neurocognitive/neuropsychological, quality‐of‐life (QOL)/activities of daily living (ADL), and biomarker domains.ResultLomecel‐B was well‐tolerated and did not trigger safety stopping rules, meeting the primary endpoint. Efficacy endpoints were improved in the Lomecel‐B groups. Whereas the Mini Mental State Exam (MMSE) declined in placebo by 2.99±1.12 points at Week 13 (p=0.0337; 95%CI ‐5.84 – ‐0.31), the 20M Lomecel‐B group showed minimal decline (difference from placebo: 2.69±1.39 points; p=0.0182; 95%CI 0.51 – 4.97). This difference persisted over one year (Figure). On the QOL‐AD patient version, the 20M Lomecel‐B group significantly improved versus placebo at Week 26 by 3.85±1.94 points (p=0.0444; 95%CI 0.13 – 9.12). On the ADCS‐ADL, the placebo group significantly declined at Week 26 by 9.27±2.78 points (p=0.0211; 95%CI ‐17.83 – ‐2.10), and was significantly worse versus 20M Lomecel‐B by 6.95±3.46 points (p=0.0118; 95%CI 1.99 – 13.94). In contrast, these assessments did not significantly differ in the 100M Lomecel‐B group versus placebo. Anti‐inflammatory (IL‐10, IL‐12, sIL‐2Rα) and pro‐vascular (VEGF, IL‐4, IL‐6) serum biomarkers were significantly higher in both Lomecel‐B groups versus placebo, with 100M Lomecel‐B generally showing the greatest rises. Left hippocampal volume increased in the 100M Lomecel‐B group versus placebo at Week 13 (p=0.0311).ConclusionThese results support the safety and clinical potential of Lomecel‐B for AD. These hypothesis‐generating results also revealed potentially important biomarkers which are consistent with multiple MOAs of Lomecel‐B. Ongoing investigation of Lomecel‐B for AD in larger clinical trials powered for clinical efficacy is warranted. This study was supported through Alzheimer’s Association Part the Cloud Challenge on Neuroinflammation grants #PTC C‐16‐422443 and PTC‐CS‐19‐623225.

Complementary analyses of the AMBAR trial: Individual items of CDR and ADAS‐Cog12 in Alzheimer’s disease patients treated with plasma exchange with albumin replacement

AbstractBackgroundAMBAR (Alzheimer’s Management By Albumin Replacement) study results demonstrated that plasma exchange and albumin replacement (PE‐A) with or without intravenous immunoglobulin slows the progression of Alzheimer’s disease (AD) as measured by cognitive (ADAS‐Cog12), functional (ADCS‐ADL), and global assessment (CDR) (Boada et al. Alzheimers Dement 2020;16:1412). In this complementary analysis, we explored the association of ADAS‐Cog12 and CDR subdomains with treatment effects overall as well as stratified by AD severity.MethodAD patients (N=347) were randomized (1:1:1:1) to one of the three different PE‐A treatments or placebo (sham PE‐A). We analyzed the performance of active (all 3 PE‐A‐treated groups) relative to placebo overall as well as stratified by AD severity for each of the 6 domains of CDR scale and 12 items of ADAS‐Cog12 grouped in three categories of “Memory”, “Language” and “Praxis” (Verna et al. Alzheimer Res Ther 2015;7:64). Language was also assessed through Phonetic and Semantic Verbal Fluency (PVF, SVF) tests and Neuropsychological Assessment Battery (NAB) naming test. Changes from baseline were analyzed using a mixed model for repeated measures (MMRM).ResultPE‐A‐treated patients showed improvement by month 14 (p<0.05) in 5 of 6 CDR domains (“Memory”; “Orientation”; “Judgement & Problem solving”; “Home & Hobbies”; “Personal care”), with effect sizes from 71% (less decline) to >100% (improvement over baseline). The “Community affairs” domain had borderline significance (p=0.08). PE‐A‐treated moderate AD patients (MMSE: 18‐21) exhibited improvement over control whereas PE‐A‐treated mild AD patients (MMSE: 22‐26) were not significantly different. Among ADAS‐Cog12 items, PE‐A‐treated patients showed improvement by month 12 or 14 (p<0.05) in at least one of the categories “Language”, “Memory” or “Praxis” with effect sizes from 76 to >100%. PVF and SVF also demonstrated improvements by month 14 (all effect sizes >100%; p‐values: 0.003‐0.04). For the stratified analysis, this improvement, favoring PE‐A‐treated individuals, was only observed in the mild AD group (p= 0.0040 [PVF] and 0.02 [SVF]). Finally, NAB demonstrated improvement by 12 months only in the moderate group (p=0.04).ConclusionPE‐A demonstrated beneficial effects across all CDR domains and language tests, while the ADAS‐Cog12 benefit may be more prominent in specific subdomains of memory, language and praxis.

Gamma frequency sensory stimulation prevents brain atrophy, improves sleep and memory in probable mild Alzheimer’s patients

AbstractBackgroundNon‐invasive gamma frequency light and sound stimulation at 40Hz reduced Alzheimer’s disease (AD) pathology and improved performance during behavioral testing in mouse models of AD (Iaccarino et al., Nature, 2016; Martorell et al., Cell, 2019; Adaikkan et al., Neuron, 2019). Sensory stimulation inducing 40Hz entrainment reduced amyloid and hyperphosphorylated tau burden and prevented brain atrophy in different mouse models of AD. Performance on tasks testing short‐term memory and spatial learning improved after 6 weeks of daily 40Hz stimulation. We therefore hypothesized that translation of gamma entrainment with light and sound can be used as a disease‐modifying therapeutic for AD.MethodsWe conducted a placebo‐controlled, randomized control trial (n = 15) in volunteers with probable mild AD to use our light and sound device at home for one hour daily (NCT 04042922). Control devices delivered constant light and white noise while devices with the active setting produced patterned and synchronized light and sound at 40Hz. Electroencephalogram (EEG) was used to evaluate for safety and entrainment when using the 40Hz stimulation. Weekly phone questionnaires were used to assess safety. Magnetic resonance imaging was used to evaluate brain structure and actigraphy was used to record sleep. Face‐name association delayed recall was done to assess changes in cognition.ResultsWe report interim results after 3 months of daily 40Hz stimulation. Mild AD patients were highly compliant with usage in both the control and active groups. EEG data show that our novel light and sound device safely and effectively induced 40Hz entrainment in subjects with mild AD. After 3 months of daily stimulation, 40Hz entrainment prevents both hippocampal atrophy and ventricular enlargement and the extent of ventricular change differs between groups (p = 0.034, p = 0.024, p = 0.043, respectively). Circadian rhythmicity also improved with 40Hz stimulation (p = 0.03). Performance on the face‐name association delayed recall test improved in accuracy (p = 0.004).ConclusionsGamma frequency light and sound stimulation can be used safely daily for 3 months and prevents AD‐related degeneration. Induced entrainment using sensory stimulation at 40Hz shows promise as a novel disease modifying therapeutic for Alzheimer’s dementia.

The association between brain‐derived neurotrophic factor and improved cognition in mild cognitive impairment and Alzheimer's disease patients in an exercise‐primed transcranial‐direct current stimulation study

AbstractBackgroundBrain derived neurotrophic factor (BDNF) has been associated with cognitive decline in Alzheimer’s disease (AD) and mild cognitive impairment (MCI). Transcranial direct current stimulation (tDCS), a non‐invasive brain stimulation, has been found to improve cognitive functions in AD/MCI, particularly after priming. While the mechanism of tDCS response remains unclear, BDNF has been proposed to be involved with the beneficial effects of tDCS. However, few studies have investigated the direct relationship between cognition and BDNF in individuals receiving tDCS. With data from an ongoing clinical trial (the EXPRESS study), we examined the relationship between BDNF and changes in cognition before and after intervention in individuals with MCI/mild AD.MethodParticipants completed a 5‐week, blinded, randomized trial investigating the effects of exercise priming on tDCS. The Montreal Cognitive Asssessment (MoCA), to assess global cognition, was administered and blood samples were collected to quantify serum BDNF at baseline and endpoint visits. Baseline BDNF concentrations were log‐transformed prior to analyses. A Pearson’s partial correlation was used to assess the relationship between baseline BDNF and change in MoCA (ΔMoCA) over time across all participants.ResultIn 18 participants (10 males [55.6%], mean [±SD] age 73.9±8.5 years, education 17.1±2.0 years, and baseline MoCA score 21.5 ± 3.5), mean baseline BDNF concentration was 116.0 ± 40.9 (ng/mL). A Pearson’s partial correlation, controlling for age, showed a significant positive correlation between baseline BDNF concentrations and ΔMoCA score over time (rpartial(15) = .517, p = 0.034).ConclusionHigher baseline BDNF levels were correlated with greater improvement in global cognition over time in MCI/mild AD patients. This finding contributes to current literature that suggests BDNF as a therapeutic target in AD treatment. Further analyses upon unblinding will be done to evaluate the predictive capacity of baseline BDNF concentrations on cognitive improvement across treatment groups.

Gamma phase synchronization during olfactory stimulation as a marker for Alzheimer’s disease

AbstractBackgroundAltered gamma oscillations have been observed in patients of Alzheimer’s disease (AD). A large number of studies have linked the quality of gamma oscillations in the frontal cortex to the performance of memory retrieval tasks. Synchronization of gamma oscillations has a strong correlation with cognitive functions (Fell et al., Nature Reviews Neuroscience 2011), and deficit in gamma synchronization in the frontal cortex has been reported as a marker for AD (Sedghizadeh et al., PLOS One 2020). In this study, we examine the phase synchronization of gamma oscillations in the EEG data recorded from the frontal cortex during olfactory stimulation as a marker for AD.MethodTwenty‐four elderly participants (13 Normal and 11 mild AD patients) participated in this study. The cognitive status of the participants was quantified using the MMSE test. Then, each participant underwent an olfactory stimulation session consisting of 120 trials of 2s stimuli presentation with a random selection of two odors (lemon as the frequent and rose as the rare odor) followed by 8s of rest. EEG data were simultaneously recorded and pre‐processed for artifact and noise removal and trial averaging. To analyze gamma band synchronization, the phase‐locking value (PLV) for lower gamma oscillations (35‐45Hz) was calculated between the Fz and Cz electrodes. Fig. 1 illustrates the measurement and processing flow.ResultOur study shows that the PLV is significantly higher for normal participants compared to AD patients (Fig. 2). Also, the phase difference between the Fz and Cz electrodes in the lower gamma band remains unchanged across trials for normal participants while it widely varies between ‐180 and 180 degrees for AD patients (Fig. 3).ConclusionThis study shows that there is a significant difference between normal participants and AD patients in terms of the synchronization of gamma oscillations in the frontal cortex in response to olfactory stimulation. These results suggest that the PLV between the Fz and Cz electrodes under olfactory stimulation can be used as a marker for AD diagnosis.

A remote digital tool for diagnosis and monitoring of Alzheimer’s disease

AbstractBackgroundEarly detection and monitoring of mild cognitive impairment (MCI) and Alzheimer’s Disease (AD) patients are key to tackling dementia and providing benefits to patients, caregivers, healthcare providers and society.MethodWe developed the Integrated Cognitive Assessment (ICA); a 5 minute computerised cognitive test employs Artificial Intelligence (AI) to improve its accuracy in detecting cognitive impairment. ICA presents a series of rapidly changing images on a mobile device to measure cognitive impairment via a person's accuracy and response time in categorising those images.We studied the ICA in a total of 230 participants. 95 healthy volunteers, 80 MCI, and 55 mild AD participants completed the ICA, the Montreal Cognitive Assessment (MoCA) and Addenbrooke’s Cognitive Examination (ACE) cognitive tests.ResultThe ICA demonstrated convergent validity with MoCA (r=0.58) and ACE (r=0.62). The ICA AI model was able to detect cognitive impairment with an area under the curve of 81% for MCI patients (MoCA 77%), and 88% for mild AD patients (MoCA 89%). The AI classifier, based on an explainable logistic regression model, demonstrated improved performance with increased training data. Furthermore it showed generalisability in performance from one population to another. The ICA was able to detect cognitive impairment with high accuracy when trained with one cohort and tested in an independent cohort with different cultural and demographic characteristics, a prerequisite for large population deployment.In a monitoring study, 12 healthy participants self‐administered 78 ICA tests remotely over a period of 3 months (936 tests in total). The ICA demonstrated no significant practice effect observed over the duration of the study.ConclusionThe ICA can support clinicians by aiding accurate diagnosis of MCI and AD and is appropriate for large‐scale screening of cognitive impairment. The ICA is unbiased by differences in language, culture and education and has additional advantages over standard of care tests because of its shorter duration, automatic scoring and potential for medical record or research database integration.The pandemic has presented a challenge for face‐face assessments. A digital tool such as the ICA allows us to adapt to these changes by administering assessments remotely and monitoring disease progression.

Whole Blood Expression Pattern of Inflammation and Redox Genes in Mild Alzheimer's Disease.

BackgroundAlthough Alzheimer’s disease (AD) is associated with alterations of the central nervous system, this disease has an echo in blood that might represent a valuable source of biomarkers for improved diagnosis, prognosis and for monitoring drug response.MethodsWe performed a targeted transcriptomics study on 38 mild Alzheimer’s disease (AD) patients and 38 matched controls for evaluating the expression levels of 136 inflammation and 84 redox genes in whole blood. Patients were diagnosed as mild AD based on altered levels of total TAU, phospho-TAU and Abeta(1–42) in cerebrospinal fluid, and Abeta(1–40), Abeta(1–42) and total TAU levels in plasma. Whenever possible, blood and brain comparisons were made using public datasets.ResultsWe found 48 inflammation and 34 redox genes differentially expressed in the blood of AD patients vs controls (FC >1.5, p < 0.01), out of which 22 pro-inflammatory and 12 redox genes exhibited FC >2 and p < 0.001. Receiver operating characteristic (ROC) analysis identified nine inflammation and seven redox genes that discriminated between AD patients and controls (area under the curve >0.9). Correlations of the dysregulated inflammation and redox transcripts indicated that RELA may regulate several redox genes including DUOX1 and GSR. Based on the gene expression profile, we have found that the master regulators of inflammation and redox homeostasis, NFκB and NRF2, were significantly disturbed in the blood of AD patients, as well as several zinc finger and helix-loop-helix transcription factors.ConclusionThe selected inflammation and redox genes might be useful biomarkers for monitoring anti-inflammatory therapy in mild AD.

Levels of Receptor for Advanced Glycation End Products and Glyoxalase-1 in the Total Circulating Extracellular Vesicles from Mild Cognitive Impairment and Different Stages of Alzheimer's Disease Patients.

Growing evidence supports that receptor for advanced glycation end products (RAGE) and glyoxalase-1 (GLO-1) are implicated in the pathophysiology of Alzheimer's disease (AD). Extracellular vesicles (EVs) are nanovesicles secreted by almost all cell types, contribute to cellular communication, and are implicated in AD pathology. Recently, EVs are considered as promising tools to identify reliable biomarkers in AD. The aim of our study was to determine the levels of RAGE and GLO-1 in circulating EVs from mild cognitive impairment (MCI) and AD patients and to analyze their correlation with the clinical Mini-Mental State Examination and Montreal Cognitive Assessment scores. We have studied the possibility that neuronal cells could release and transfer GLO-1 through EVs. RAGE and GLO-1 levels were measured in circulating EVs, respectively, by Luminex assay and western blot. Released-EVs from SK-N-SH neuronal cells were isolated and GLO-1 levels were determined by western blot. Our data showed higher levels of RAGE in EVs from late AD patients while GLO-1 levels in EVs from early AD were lower as compared to control and MCI patients. Interestingly, levels of RAGE and GLO-1 in EVs were correlated with the cognitive scores regardless of age. For the first time, we demonstrated that GLO-1 was released from neuronal cells through EVs. Although more samples will be needed, our preliminary results support the use of peripheral EVs cargo as new tools for the discovery of peripheral AD biomarkers.

Corpus Callosum Atrophy in Detection of Mild and Moderate Alzheimer's Disease Using Brain Magnetic Resonance Image Processing and Machine Learning Techniques.

Background:The total number of people with dementia is projected to reach 82 million in 2030 and 152 in 2050. Early and accurate identification of the underlying causes of dementia, such as Alzheimer’s disease (AD) is of utmost importance. A large body of research has shown that imaging techniques are most promising technologies to improve subclinical and early diagnosis of dementia. Morphological changes, especially atrophy in various structures like cingulate gyri, caudate nucleus, hippocampus, frontotemporal lobe, etc., have been established as markers for AD. Being the largest white matter structure with a high demand of blood supply from several main arterial systems, anatomical alterations of the corpus callosum (CC) may serve as potential indication neurodegenerative disease.Objective:To detect mild and moderate AD using brain magnetic resonance image (MRI) processing and machine learning techniques.Methods:We have performed automatic detection and segmentation of the CC and calculated its morphological features to feed into a multivariate pattern analysis using support vector machine (SVM) learning techniques.Results:Our results using large patients’ cohort show CC atrophy-based features are capable of distinguishing healthy and mild/moderate AD patients. Our classifiers obtain more than 90%sensitivity and specificity in differentiating demented patients from healthy cohorts and importantly, achieved more than 90%sensitivity and > 80%specificity in detecting mild AD patients.Conclusion:Results from this analysis are encouraging and advocate development of an image analysis software package to detect dementia from brain MRI using morphological alterations of the CC.

The Apathy Evaluation Scale (AES-C): Psychometric Properties and Invariance of Italian Version in Mild Cognitive Impairment and Alzheimer's Disease.

Apathy is a neuropsychiatric symptom observed in different neurological and psychiatric disorders. Although apathy is considered a symptom, it has been recently reconsidered as a syndrome characterised by three dimensions: cognitive symptoms, affective symptoms and behavioural symptoms. Recent studies have shown that apathy can be considered as a prodromal symptom of Alzheimer’s disease (AD), but also an indicator of the transition from mild cognitive impairment to AD. According to this scenario, an early detection of apathy in subjects with Mild Cognitive Impairment (MCI) and Mild AD can be a valid psychometric strategy to improve an early diagnosis and promote a prompt intervention. The Apathy Evaluation Scale is a validated tool composed of 18 items that assess and quantify emotional, behavioural and cognitive aspects of apathy. The aim of this study is to assess the specific reliability and validity of the Italian version of the Apathy Evaluation Scale—Clinician Version (AES-C) to detect apathy both in amnestic MCI and mild AD patients. In the present paper, we therefore examined the psychometric properties and the invariance of the Italian Version of the AES-C conducted on a sample composed of an experimental group of amnestic MCI and AD patients (N = 107) and a control group (N = 107) constituted by Age- and Sex-matched healthy controls. Results confirm the goodness of the scale. Confirmatory factory analysis confirmed that the AES-C Italian Version presents the same stability of one second-order factor and three first-order factors identified in the original version, and all items are predicted by a single general factor. Moreover, the scale was found to be invariant across both populations. Moreover, reliability and discriminant analysis showed good values. We found in the experimental group a negative correlation between the AES-C and Frontal Assessment Battery (FAB) (rs = −0.21, p < 0.001) and Mini Mental State Examination (MMSE) (rs = −0.04, p < 0.001), while a positive correlation was found between the AES-C and Hamilton psychiatric Rating scale for Depression (HAM-D) scores (rs = 0.58, p < 0.001) Overall, our data demonstrated the validity of the Italian version of the AES-C for the assessment of apathy both in MCI and in AD patients.

Validation of Slovenian version of ADAS-Cog for patients with mild cognitive impairment and Alzheimer's disease.

Alzheimer's disease (AD) is the most common cause of neurodegenerative dementia where the most prominent cognitive impairment is memory loss. Screening tests are valuable tools for detecting cognitive impairment. One such test is the Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog) which consists of 11 tasks. The main goal of our study was to validate the Slovenian version of the ADAS-Cog for detecting mild cognitive impairment (MCI) and AD patients. Our sample included 128 participants: 61 healthy controls, 32 people with MCI, and 35 with AD. All participants were evaluated with the Slovenian translation of ADAS-Cog. The optimal cut-off for the ADAS-Cog for MCI was 10/11 points. The sensitivity was 88%, specificity 85% and likelihood ratio 6. The optimal cut-off for AD was 11/12 points. Sensitivity was 100%, specificity 95% and likelihood ratio 20. The obtained cut-off values are comparable to the results from similar validation studies. We can conclude that the ADAS-Cog is a reliable and valid tool for identifying people with MCI and AD from among healthy controls in the Slovenian population.

Diagnosis of mild Alzheimer's disease by EEG and ERP signals using linear and nonlinear classifiers

A new method for the diagnosis of Alzheimer's disease in the mild stage is presented due to its association with the characteristics of the EEG brain signal. In the proposed method, three channels Pz, Cz, and Fz of brain signals were recorded from 40 participants in the four modes of closed eyes, open eyes, recall, and stimulation. After preprocessing, wide various features of EEG signals were extracted. Results have shown that after stimulation, the amplitude and the latency of the P300 component change with increasing age and the stages of Alzheimer's disease. In addition, the first changes in brain signal in mild Alzheimer's patients are increased activity in the theta band and decreased activity in the beta band, which is associated with a decrease in alpha-band activity. After selecting the proper features, linear discriminant analysis, and Elman and convolutional neural networks were used to classify the participants' features. The results showed that the Pz channel among three EEG signals and the stimulation mode among the four recording steps had greater accuracy than the others. By using features of the Pz channel, the accuracy of LDA was 59.4% and 66.4% in the recall and excitation modes, accuracy of Elman neural network was 92.3% and 94.1%, and CNN was 97.5% and 99% respectively. Results have shown that extracting appropriate linear and nonlinear features has increased the accuracy of the classifiers. In addition, due to the dynamic nature of the brain signal, the convolutional neural network had better performance than LDA and Elman.

Detection of retinal changes with optical coherence tomography angiography in mild cognitive impairment and Alzheimer's disease patients: A meta-analysis.

To assess retinal microvascular network impairments in the eyes of mild cognitive impairment (MCI) and Alzheimer's disease (AD) patients with optical coherence tomography angiography (OCTA). Systematic review and meta-analysis. A literature search was conducted in the PubMed and EMBASE databases to identify relevant studies detecting retinal microvascular attenuation among AD, MCI patients and cognitively healthy controls (HCs) by OCTA. Data were extracted by Review Manager V.5.4 and Stata V.14.0. Eight investigations were included in this meta-analysis, with 150 AD patients, 195 MCI patients and 226 HCs were eligible for meta-analysis. Evidence based on these studies demonstrated that there was a significantly decreased vessel density (VD) of the Optovue group in superficial capillary plexus (SCP): WMD = -2.26, 95% CI: -3.98 to -0.55, p = 0.01; in deep capillary plexus (DCP): WMD = -3.40, 95% CI: -5.99 to -0.81, p = 0.01, VD of the Zeiss group in SCP:WMD = -0.91, 95% CI: -1.79 to -0.02, p = 0.05 and an enlarged fovea avascular zone (FAZ):WMD = 0.06, 95% CI: 0.01 to 0.11, P = 0.02 in OCTA measurements of MCI patients. Additionally, in OCTA measurements of AD patients, there was a significantly decreased VD in the SCP: WMD = -1.88, 95% CI: -2.7 to -1.07, p<0.00001. In contrast, there was no significant decrease in DCP nor enlargement of FAZ in AD patients. Retinal microvascular alternations could be optimally screened in MCI patients detected by OCTA, which could be a warning sign of relative changes in the MCI before progressing to AD. Retinal microvasculature changes worth further investigation in larger scale clinical trials.

Validity and Cultural Generalisability of a 5-Minute AI-Based, Computerised Cognitive Assessment in Mild Cognitive Impairment and Alzheimer's Dementia.

Introduction: Early detection and monitoring of mild cognitive impairment (MCI) and Alzheimer's Disease (AD) patients are key to tackling dementia and providing benefits to patients, caregivers, healthcare providers and society. We developed the Integrated Cognitive Assessment (ICA); a 5-min, language independent computerised cognitive test that employs an Artificial Intelligence (AI) model to improve its accuracy in detecting cognitive impairment. In this study, we aimed to evaluate the generalisability of the ICA in detecting cognitive impairment in MCI and mild AD patients.Methods: We studied the ICA in 230 participants. 95 healthy volunteers, 80 MCI, and 55 mild AD participants completed the ICA, Montreal Cognitive Assessment (MoCA) and Addenbrooke's Cognitive Examination (ACE) cognitive tests.Results: The ICA demonstrated convergent validity with MoCA (Pearson r=0.58, p<0.0001) and ACE (r=0.62, p<0.0001). The ICA AI model was able to detect cognitive impairment with an AUC of 81% for MCI patients, and 88% for mild AD patients. The AI model demonstrated improved performance with increased training data and showed generalisability in performance from one population to another. The ICA correlation of 0.17 (p = 0.01) with education years is considerably smaller than that of MoCA (r = 0.34, p < 0.0001) and ACE (r = 0.41, p < 0.0001) which displayed significant correlations. In a separate study the ICA demonstrated no significant practise effect over the duration of the study.Discussion: The ICA can support clinicians by aiding accurate diagnosis of MCI and AD and is appropriate for large-scale screening of cognitive impairment. The ICA is unbiased by differences in language, culture, and education.

Altered intrinsic brain activity in mild Alzheimer's disease patients with sleep disturbances.

Sleep disturbances are one of the preventive factors to delay the onset and progression of Alzheimer's disease. Early identification of Alzheimer's disease patients prone to develop sleep disturbances to offer early medical intervention is important. Resting-state functional MRI is a widely used method to investigate the neural mechanisms and find neuroimaging biomarkers in neuropsychiatric diseases. In this study, we applied percent amplitude of fluctuation (PerAF) and mPerAF (divided by global mean PerAF) to test the strength of intrinsic brain activity in 38 mild Alzheimer's disease patients with sleep disturbances (ADSD) and 21 mild Alzheimer's disease patients without sleep disturbances (ADNSD). Compared with ADNSD, we found decreased intrinsic brain activity in the calcarine gyrus, the lingual gyrus, the fusiform gyrus extending to the parahippocampal gyrus, the precentral gyrus, the postcentral gyrus (all in the left hemisphere) and the left brainstem. Conclusively, ADSD exhibited reduced neural activity in specific brain regions related to the sensorimotor network and the visual network, which indicated the contribution of sleep disturbances to the progression of Alzheimer's disease. Especially, the ventral visual pathway to the hippocampus might serve for the memory impaired by sleep disturbances in Alzheimer's disease, and the brainstem might be critical in the initiation of sleep disturbances in Alzheimer's disease. These findings further elucidate the interactions between Alzheimer's disease and sleep disturbances and could help with the early recognition of Alzheimer's disease patients who tend to develop sleep disturbances.

Distinguishing Alzheimer's Disease Patients and Biochemical Phenotype Analysis Using a Novel Serum Profiling Platform: Potential Involvement of the VWF/ADAMTS13 Axis.

It is important to develop minimally invasive biomarker platforms to help in the identification and monitoring of patients with Alzheimer’s disease (AD). Assisting in the understanding of biochemical mechanisms as well as identifying potential novel biomarkers and therapeutic targets would be an added benefit of such platforms. This study utilizes a simplified and novel serum profiling platform, using mass spectrometry (MS), to help distinguish AD patient groups (mild and moderate) and controls, as well as to aid in understanding of biochemical phenotypes and possible disease development. A comparison of discriminating sera mass peaks between AD patients and control individuals was performed using leave one [serum sample] out cross validation (LOOCV) combined with a novel peak classification valuation (PCV) procedure. LOOCV/PCV was able to distinguish significant sera mass peak differences between a group of mild AD patients and control individuals with a p value of 10−13. This value became non-significant (p = 0.09) when the same sera samples were randomly allocated between the two groups and reanalyzed by LOOCV/PCV. This is indicative of physiological group differences in the original true-pathology binary group comparison. Similarities and differences between AD patients and traumatic brain injury (TBI) patients were also discernable using this novel LOOCV/PCV platform. MS/MS peptide analysis was performed on serum mass peaks comparing mild AD patients with control individuals. Bioinformatics analysis suggested that cell pathways/biochemical phenotypes affected in AD include those involving neuronal cell death, vasculature, neurogenesis, and AD/dementia/amyloidosis. Inflammation, autoimmunity, autophagy, and blood–brain barrier pathways also appear to be relevant to AD. An impaired VWF/ADAMTS13 vasculature axis with connections to F8 (factor VIII) and LRP1 and NOTCH1 was indicated and is proposed to be important in AD development.

Sleep-Based Interventions in Alzheimer's Disease: Promising Approaches from Prevention to Treatment along the Disease Trajectory.

The multifactorial nature of Alzheimer’s disease (AD) has led scientific researchers to focus on the modifiable and treatable risk factors of AD. Sleep fits into this context, given the bidirectional relationship with AD confirmed by several studies over the last years. Sleep disorders appear at an early stage of AD and continue throughout the entire course of the pathology. Specifically, sleep abnormalities, such as more fragmented sleep, increase in time of awakenings, worsening of sleep quality and primary sleep disorders raise with the severity and progression of AD. Intervening on sleep, therefore, means acting both with prevention strategies in the pre-clinical phase and with treatments during the course of the disease. This review explores sleep disturbances in the different stages of AD, starting from the pre-clinical stage. Particular attention is given to the empirical evidence investigating obstructive sleep apnea (OSA) disorder and the mechanisms overlapping and sharing with AD. Next, we discuss sleep-based intervention strategies in the healthy elderly population, mild cognitive impairment (MCI) and AD patients. We mention interventions related to behavioral strategies, combination therapies, and bright light therapy, leaving extensive space for new and raising evidence on continuous positive air pressure (CPAP) treatment effectiveness. Finally, we clarify the role of NREM sleep across the AD trajectory and consider the most recent studies based on the promising results of NREM sleep enhancement, which use innovative experimental designs and techniques.

Bacterial rhamnolipids (RLs) in saliva of Alzheimer's disease and Mild Cognitive Impairment patients and correlation with neuroinflammation and cognitive state

Alzheimer’s disease (AD) is increasingly affecting the aging population and the estimated prevalence reaches 50 million people worldwide. The need for the discovery of new biomarkers for AD diagnosis is urgent and especially in biological fluids other than cerebrospinal fluid (CSF), as its collection is invasive. Arguments are numerous that chronic bacterial infections might be considered as one of the possible causes of AD. Rhamnolipids (RLs) are bacterial virulence factors, suspicious for dysfunctions and disorders including AD. The aim of this pilot trial was to investigate RLs levels in saliva of Mild Cognitive Impairment (MCI) and AD patients with indirect ELISA. Specifically, salivary RLs were determined in 30 AD patients, 24 MCI patients and 15 cognitively healthy individuals and were found elevated in AD and MCI patients compared to those of the control group. The established biomarkers of AD, tau and Aβ42 amyloid, and the inflammatory markers cyclooxygenases (COX-1 and COX-2) were also determined, to evaluate their possible interdependence from RLs levels. Levels of RLs positively correlate with COX-2 levels and negatively with the mental state according to Mini–Mental State Examination (MMSE) score of donors. Multilinear regression verified the tight interrelation of RLs with COX-2 in saliva of MCI and AD patients. The results of this study stand by the hypothesis of inflammatory involvement in AD and indicate that RLs could be suggested as eventual biomarkers for AD diagnosis using saliva as biological fluid.

TMS-EEG Co-Registration in Patients with Mild Cognitive Impairment, Alzheimer's Disease and Other Dementias: A Systematic Review.

An established method to assess effective brain connectivity is the combined use of transcranial magnetic stimulation with simultaneous electroencephalography (TMS–EEG) because TMS-induced cortical responses propagate to distant anatomically connected brain areas. Alzheimer’s disease (AD) and other dementias are associated with changes in brain networks and connectivity, but the underlying pathophysiology of these processes is poorly defined. We performed here a systematic review of the studies employing TMS–EEG co-registration in patients with dementias. TMS–EEG studies targeting the motor cortex have revealed a significantly reduced TMS-evoked P30 in AD patients in the temporo-parietal cortex ipsilateral to stimulation side as well as in the contralateral fronto-central area, and we have demonstrated a deep rearrangement of the sensorimotor system even in mild AD patients. TMS–EEG studies targeting other cortical areas showed alterations of effective dorsolateral prefrontal cortex connectivity as well as an inverse correlation between prefrontal-to-parietal connectivity and cognitive impairment. Moreover, TMS–EEG analysis showed a selective increase in precuneus neural activity. TMS–EEG co-registrations can also been used to investigate whether different drugs may affect cognitive functions in patients with dementias.

A new method to build multiplex networks using canonical correlation analysis for the characterization of the Alzheimer’s disease continuum

Objective. The aim of this study was to solve one of the current limitations for the characterization of the brain network in the Alzheimer’s disease (AD) continuum. Nowadays, frequency-dependent approaches have reached contradictory results depending on the frequency band under study, tangling the possible clinical interpretations. Approach. To overcome this issue, we proposed a new method to build multiplex networks based on canonical correlation analysis (CCA). Our method determines two basis vectors using the source and electrode-level frequency-specific network parameters for a reference group, and then project the results for the rest of the groups into these hyperplanes to make them comparable. It was applied to: (i) synthetic signals generated with a Kuramoto-based model; and (ii) a resting-state electroencephalography (EEG) database formed by recordings from 51 cognitively healthy controls, 51 mild cognitive impairment subjects, 51 mild AD patients, 50 moderate AD patients, and 50 severe AD patients. Main results. Our results using synthetic signals showed that the interpretation of the proposed CCA-based multiplex parameters (multiplex strength, multiplex characteristic path length and multiplex clustering coefficient) can be analogous to their frequency-specific counterparts, as they displayed similar behaviors in terms of average connectivity, integration, and segregation. Findings using real EEG recordings revealed that dementia due to AD is characterized by a significant increase in average connectivity, and by a loss of integration and segregation. Significance. We can conclude that CCA can be used to build multiplex networks based from frequency-specific results, summarizing all the available information and avoiding the limitations of possible frequency-specific conflicts. Additionally, our method supposes a novel approach for the construction and analysis of multiplex networks during AD continuum.