Current Alzheimer Research - Volume 18, Issue 2, 2021

Alzheimer’s disease (AD) is a neurodegenerative disorder, the most common form of dementia. AD is characterised by amyloid-β (Aβ) plaques and neurofibrillary tangles (NFT) in the brain, in association with neuronal loss and synaptic failure, causing cognitive deficits. Accurate and early diagnosis is currently unavailable in lifespan, hampering early intervention of potential new treatments. Visual deficits have been well documented in AD patients, and the pathological changes identified in the brain are also believed to be found in the retina, an integral part of the central nervous system. Retinal changes can be detected by real-time non-invasive imaging, due to the transparent nature of the ocular media, potentially allowing an earlier diagnosis as well as monitoring disease progression and treatment outcome. Animal models are essential for AD research, and this review has a focus on retinal changes in various transgenic AD mouse models with retinal imaging and immunohistochemical analysis as well as therapeutic effects in those models. We also discuss the limitations of transgenic AD models in clinical translations.

Introduction: Responsiveness to treatment with cholinesterase inhibitors (ChEIs) is difficult to predict in Alzheimer’s disease (AD). In the current review, vascular burden is considered as a potential moderator of treatment responsiveness. Cerebrovascular burden co-occurs in at least 30% of AD brains, although it is debated if vascular pathology plays a causal or synergistic role in AD pathogenesis. Vascular burden, therefore, could potentially limit response to treatment due to limited brain reserve or foster treatment efficacy as those with vascular pathology may represent a subgroup with comparable clinical expression but less progressed AD neurodegeneration. Methods: A systematic search of Web of Science, Pubmed, Scopus and EthoS identified 32 papers which met the criteria for inclusion. Association of treatment response and vascular burden across five broad markers are discussed: cerebral hypoperfusion, intima-media thickness, white matter changes, cerebral microbleeds and co-existing diagnosis of cerebrovascular disease. Results: Analysis of frontal regional cerebral blood flow and intima-media thickness may have predictive ability to distinguish those with AD who may respond optimally to short-term treatment with ChEIs. The impact of white matter changes is less consistent; the majority of studies demonstrates no association with treatment response and those that do implicate changes in executive functioning. There is preliminary evidence that deep cerebral microbleeds limit treatment response in subcortical cognitive domains, but this finding requires replication. The use of diagnosis of co-occurring cerebrovascular disease yields no robust variability in response to ChEIs in AD. Conclusion: There is limited evidence that markers of cerebral hypoperfusion, intima-media thickness and cerebral microbleeds moderate response to ChEIs. Findings for other markers of vascular burden are less consistent and do not support any moderating effect.

Background: Weight loss is a common phenomenon among the elderly and is identified as an important indicator of health status. Many epidemiology studies have investigated the association between weight loss and dementia, but the results were inconsistent. Objective: To examine and determine the association between weight loss and the risk of dementia. Methods: Eligible cohort studies involving weight loss and dementia were searched from PubMed, Embase, and Ovid databases through October 2018. Pooled relative risks (RRs) with its 95% confidence intervals (CIs) were used to estimate the effects of weight loss on the risk of dementia. Subgroup and sensitivity analyses were performed to explore the potential sources of heterogeneity. The Begg’s test and Egger’s test were used to assess the publication bias. Results: A total of 20 cohort studies with 38,141 participants were included in this meta-analysis. Weight loss was significantly associated with the risk of dementia (RR=1.26, 95% CI=1.15-1.38). BMI decline ≥0.8 units (RR=1.31, 95% CI=1.10-1.56) and ≥4% (RR=1.19, 95% CI=1.03-1.38) could increase the risk of dementia. The risk of all-cause dementia for people with weight loss increased by 31% (RR=1.31, 95% CI=1.15-1.49), and 25% higher for incident Alzheimer’s disease (RR=1.25, 95% CI=1.07-1.46). Weight loss in participants with normal weight had a similar dementia risk (RR=1.21, 95% CI=1.06-1.38) with the overweight individuals (RR=1.22, 95% CI=1.11-1.34). Conclusion: Weight loss may be associated with an increased risk of dementia, especially for Alzheimer's disease. Maintaining weight stability may help prevent dementia.

Background: Subjective memory complaints are a key component in mild cognitive impairment (MCI) diagnosis. However, studies that examined memory awareness among MCI participants have published contradictory results. One possible explanation for the inconsistent findings could be the disregard from the multidimensional structure of subjective memory. Objectives: The present study is directed at assessing subjective memory among healthy and MCI participants, referring to three main types of memory: episodic, semantic, and working memory. Methods: Participants were 123 adults (aged 50-90). They were divided into two groups, the MCI group, and the control group, according to their objective cognitive performance in RAVL or Mo- CA tests. All participants filled a subjective memory questionnaire, assessing their awareness of episodic, semantic, and working memory. Results: MCI participants estimated their semantic memory as significantly lower in comparison to the estimation of the healthy controls. By contrast, MCI participants showed an overestimation of their episodic memory capabilities compared to the control group. No significant difference was found between groups (MCI and healthy controls) in evaluating their working memory. In addition, for both groups, Pearson’s correlation revealed a significant negative correlation between age and semantic memory evaluation. Such correlation was not found for subjective episodic memory. Discussion: Findings suggest that while people with MCI exhibit poor awareness of their episodic and working memory capabilities, their awareness of their decrease in semantic memory is apparently intact. Therefore, it is suggested that when using the self-report criterion for MCI diagnosis, clinicians should consider the patient’s’ semantic memory complaints.

Background: Administrative data are used in the field of Alzheimer’s Disease and Related Syndromes (ADRS), however their performance to identify ADRS is unknown. Objective: i) To develop and validate a model to identify ADRS prevalent cases in French administrative data (SNDS), ii) to identify factors associated with false negatives. Methods: Retrospective cohort of subjects ≥ 65 years, living in South-Western France, who attended a memory clinic between April and December 2013. Gold standard for ADRS diagnosis was the memory clinic specialized diagnosis. Memory clinics’ data were matched to administrative data (drug reimbursements, diagnoses during hospitalizations, registration with costly chronic conditions). Prediction models were developed for 1-year and 3-year periods of administrative data using multivariable logistic regression models. Overall model performance, discrimination, and calibration were estimated and corrected for optimism by resampling. Youden index was used to define ADRS positivity and to estimate sensitivity, specificity, positive predictive and negative probabilities. Factors associated with false negatives were identified using multivariable logistic regressions. Results: 3360 subjects were studied, 52% diagnosed with ADRS by memory clinics. Prediction model based on age, all-cause hospitalization, registration with ADRS as a chronic condition, number of anti-dementia drugs, mention of ADRS during hospitalizations had good discriminative performance (c-statistic: 0.814, sensitivity: 76.0%, specificity: 74.2% for 2013 data). 419 false negatives (24.0%) were younger, had more often ADRS types other than Alzheimer’s disease, moderate forms of ADRS, recent diagnosis, and suffered from other comorbidities than true positives. Conclusion: Administrative data presented acceptable performance for detecting ADRS. External validation studies should be encouraged.

Background: Alzheimer's disease (AD) develops into dementia after several years, and subjective cognitive impairment (SCI) and mild cognitive impairment (MCI) are used as intermediary diagnoses of increasing severity. Inflammation is an important part of AD pathology and provides potential novel biomarkers and treatment targets. Objective: To identify novel potential biomarkers of AD in cerebrospinal fluid (CSF) and create a molecular pattern of inflammatory factors providing differentiation between AD and SCI. Methods: We analyzed 43 inflammatory-related mediators in CSF samples from a cohort of SCI and AD cases vetted for confounding factors (Training cohort). Using multivariate analysis (MVA), a model for discrimination between SCI and AD was produced, which we then applied to a larger nonvetted cohort (named Test cohort). The data were analyzed for factors showing differences between diagnostic groups and factors that differed between the vetted and non-vetted cohorts. The relationship of the factors to the agreement between model and clinical diagnosis was investigated. Results: A good MVA model able to discriminate AD from SCI without including tangle and plaque biomarkers was produced from the Training cohort. The model showed 50% agreement with clinical diagnosis in the Test cohort. Comparison of the cohorts indicated different patterns of factors distinguishing SCI from AD. As an example, soluble interleukin (IL)-6Rα showed lower levels in AD cases in the Training cohort, whereas placental growth factor (PlGF) and serum amyloid A (SAA) levels were higher in AD cases of the Test cohort. The levels of p-tau were also higher in the Training cohort. Conclusion: This study provides new knowledge regarding the involvement of inflammation in AD by indicating different patterns of factors in CSF depending on whether potential confounding comorbidities are present or not, and presents sIL-6Rα as a potential new biomarker for improved diagnosis of AD.

Background: Age-related comorbidity is common and significantly increases the burden for the healthcare of the elderly. Alzheimer’s disease (AD) and hypertension are the two most prevalent age-related conditions and are highly comorbid. While hypertension is a risk factor for vascular dementia (VD), hypertension with AD (ADHyp+) is often characterized as probable vascular dementia. In the absence of imaging and other diagnostic tests, differentiating the two pathological states is difficult. Objective: Our goals are to (1) identify differences in CSF-based vascular dementia profiles, if any, between individuals who have AD only (ADHyp-), and individuals with ADHyp+ using CSF levels of amyloid β, tau and p-tau, and (2) compare genome-wide DNA profiles of ADHyp- and ADHyp+ with an unaffected control population. Method: Genotype and clinical data were used to compare healthy controls to AD Hyp- vs. AD Hyp+. We compared the CSF biomarkers followed by evaluating genome wide profiles in three groups, and mapped SNPs to genes based on position and lowest p-value. The significant genes were examined for co-expression and known disease networks. Results: We found no differences between Aβ, tau and p-tau levels between ADHyp- and ADHyp+. We found TOMM40 to be associated with ADHyp- as expected but not with ADHyp+. Interestingly, SLC9A3R2 polymorphism was associated with ADHyp+, and significant gene expression changes were observed for neighboring genes. Conclusion: Through this exploratory study using a novel cohort stratification design, we highlight the genetic differences in clinically similar phenotypes, indicating the utility of genetic profiling in aiding differential diagnosis of ADHyp+ and VD.

Background: Little is known so far about the brain phenotype and the spatial interplay of different Alzheimer’s disease (AD) biomarkers with structural and functional brain connectivity in the early phase of autosomal-dominant AD (ADAD). Multimodal PET/MRI might be suitable to fill this gap. Material and Methods: We presented a 31-year-old male patient without a family history of dementia with progressive worsening of memory and motor function. Two separate sessions of 3T PET/MRI acquisitions were arranged with the ß-amyloid tracer [¹⁸F]Florbetaben and the secondgeneration tau tracer [¹⁸F]PI-2620. Simultaneously acquired MRI consisted of high-resolution 3D T1, diffusion-tensor imaging (DTI), and resting-state fMRI. PET/MRI data were compared with ten age-matched healthy controls. Results: Widespread β-amyloid depositions were found in cortical regions, and striatum (Thal stage III) along with tau pathology restricted to the mesial-temporal structures (Braak stage III/IV). Volumetric/shape analysis of subcortical structures revealed atrophy of the hippocampal-amygdala complex. In addition, cortical thinning was detected in the right middle temporal pole. Alterations of multiple DTI indices were noted in the major white matter fiber bundles, together with disruption of default mode and sensory-motor network functional connectivity. Molecular genetic analysis by next-generation sequencing revealed a heterozygote missense pathogenic variant of the PSEN1 (Met233Val). Conclusion : Multimodal PET/MR imaging is able to deliver, in a one-stop-shop approach, an array of molecular, structural and functional brain information in AD due to de novo pathogenic variant, which can be studied for spatial interplay and might provide a rationale for initiating anti- amyloid/tau therapeutic approaches.