Patients with Alzheimer's disease have increased cellular amyloid uptake

Amyloid plaques are the main signature of Alzheimer's disease (AD). Beta-amyloid (Aβ) concentration in cerebrospinal fluid (CSF-Aβ) and the density of amyloid depositions have a strong negative correlation. However, AD patients have lower CSF-Aβ levels compared to cognitively normal people even after accounting for this correlation. The goal of this study was to infer variations of parameters in Aβ metabolism of AD patients that underlie this difference using data from the Alzheimer's Disease Neuroimaging Initiative cohort. We found that AD patients had dramatically increased rates of cellular amyloid uptake compared to individuals with normal cognition (NC). A group with late-onset mild cognitive impairment (LMCI) also exhibited stronger amyloid uptake, however this was less pronounced than in the AD group. Estimated parameters in the early-onset MCI group did not differ significantly from those in the NC group. Aβ cytotoxicity depends on both the amount of peptide internalized by cells and its intracellular degradation into toxic products. Based on our results, we speculate that AD and LMCI are associated with increased cellular amyloid uptake which leads to faster disease progression, whereas the early-onset MCI may be mediated by the increased production of toxic amyloid metabolites.

The Red and Orange Complex Subgingival Microbiome of Cognitive Impairment and Cognitively Normal Elderly with Periodontitis

Increasing evidence has shown an association between periodontitis and cognitive impairment. Subgingival microbiota play a great role in periodontitis pathogenesis. However, the correlation between the subgingival microbiome and cognitive impairment remains unclear. This study aimed to evaluate the red and orange complex subgingival microbiome of cognitively impaired and cognitively normal elderly Indonesian subjects with periodontitis. Twenty-eight elderly subjects diagnosed with periodontitis underwent two cognitive examinations using the Hopkins Verbal Learning Test and the Mini-Mental State Examination. Gingival crevicular fluid taken from the periodontal pocket, at a depth between 5 and 7 mm, using a paper point was used as the subgingival samples. The subgingival microbiome in the cognitive impairment group (n = 14) and cognitively normal group (n = 14) was compared using the 16S rRNA Metagenomic iSeq™ 100 Sequencing System. There was β-diversity in the subgingival microbiota between the cognitively impaired and cognitively normal subjects. The metagenomic analysis showed a higher abundance of Porphyromonas and Treponema bacteria in the cognitive impairment group than in the normal cognitive group (p < 0.05). The abundance of Porphyromonas gingivalis and Treponema denticola was higher in the cognitively impaired elderly subjects. The role of P. gingivalis and T. denticola in the pathogenesis of cognitive impairment needs further investigation.

Investigating neurotrophin genetics and hippocampal volume

As individuals get older, the structural integrity of brain regions becomes progressively diminished. Neurotrophic function might aid in preventing such losses through increased synaptogenesis and neurogenesis, particularly in the hippocampus, a brain structure relevant for cognitive function. However, the carriage of certain genetic alleles for genes involved in neurotrophic function might restrain the effectiveness of neurotrophin signalling, hindering neuroprotection. Yet, research on the contribution of single nucleotide polymorphisms (SNPs) within genes coding for neurotrophins and their receptors to hippocampal volumes is scarce, with the exception of rs6265 within the brain-derived neurotrophic factor gene. Therefore, the aim of this study was to identify SNPs within genes involved neurotrophic function that are associated with hippocampal volume in a sample of 23,776 cognitively normal older adults from the UK Biobank. We found that, in individuals older than 50, homozygote carriage of the major alleles rs4839435-A within nerve growth factor gene and rs56405676-T within the neurotrophic receptor tyrosine kinase 2 gene, were associated with increase hippocampal volumes, compared to carriage of 1 or 2 copies of the minor alleles. However, only rs56405676-T was significantly associated with greater hippocampal volumes in individuals older than 60. Hence this study might serve to identify populations at higher risk of hippocampal attrition and cognitive decline.

Classification of 18F-Flutemetamol Scans in Cognitively Normal Older Adults Using Machine Learning Trained with Neuropathology as Groundtruth

PURPOSE: End-of-life studies have validated the binary visual reads of 18F-labeled amyloid PET tracers as an accurate tool for the presence or absence of increased neuritic amyloid plaque density. In this study, the performance of a support vector machine (SVM) based classifier will be tested against pathological groundtruths and its performance determined in cognitively healthy older adults.METHODS: We applied SVM with a linear kernel to an 18F-Flutemetamol end-of-life dataset to determine the regions with the highest feature weights in a data-driven manner and to compare between two different pathological groundtruths: based on neuritic amyloid plaque density or on amyloid phases, respectively. We also trained and tested classifiers based on the 10% voxels with the highest feature weights for each of the two neuropathological groundtruths. Next, we tested the classifiers’ diagnostic performance in the asymptomatic Alzheimer’s disease (AD) phase, a phase of interest for future drug development, in an independent dataset of cognitively intact older adults, the Flemish Prevent AD Cohort-KU Leuven (F-PACK). A regression analysis was conducted between the Centiloid (CL) value in a composite volume of interest (VOI), as index for amyloid load, and the distance to the hyperplane for each of the two classifiers, based on the two pathological groundtruths. A Receiver-Operating-Characteristic analysis was also performed to determine the CL threshold that optimally discriminates between neuritic amyloid plaque positivity versus negativity, or amyloid phase positivity versus negativity, within F-PACK.RESULTS: The classifiers yielded adequate sensitivity and specificity within the end-of-life dataset (neuritic amyloid plaque density classifier: specificity of 90.2% and sensitivity of 83.7%; amyloid phase classifier: specificity of 98.4% and sensitivity of 84.0%). The regions with the highest feature weights corresponded to precuneus, caudate, anteromedial prefrontal, and also posterior inferior temporal and inferior parietal cortex. In the cognitively normal cohort, the correlation coefficient between CL and distance to the hyperplane was -0.66 for the classifier trained with neuritic amyloid plaque density, and -0.88 for the classifier trained with amyloid phases. This difference was significant. The optimal CL cut-off for discriminating positive versus negative scans was CL = 48-51 for the different classifiers (area under the curve (AUC) = 99.9%), except for the classifier trained with amyloid phases and based on the 10% voxels with highest feature weights. There the cut-off was CL = 26 (AUC = 99.5%).DISCUSSION: A neuropathologically validated classifier applied in cognitively normal older adults reveals that amyloid PET values (Centiloids) correlate best with amyloid phases. A CL cut-off of 26 reliably discriminated between amyloid phase 0-2 and 3-5 while only a CL around 50 discriminated between no or sparse and moderate to severe neuritic amyloid plaque density.

Modifiable Factors Associated with Reversion from Mild Cognitive Impairment to Cognitively Normal Status: A Prospective Cohort Study

Background Previous studies found that about 24% of the mild cognitive impairment (MCI) patients reverse to cognitively normal (CN) status. However, it is unclear which modifiable factors are associated with this reversion. Method We conducted a prospective community-based cohort study based on 2002-2018 Chinese Longitudinal Health Longevity Survey (CLHLS). Of 35,474 older adults from 22 provinces in China in the 5 waves of CLHLS, 7,422 eligible participants with MCI were included. Multivariable Cox regression with least absolute shrinkage and selection operator (LASSO) penalty for variable selection was adopted to investigate the associations between reversion to CN and potential modifiable dietary/lifestyle, cardiometabolic, and psychological factors. Results Our analysis included 7,422 MCI participants [average age: 90.0 (SD 9.5) years]. Among these participants, 1,604 (21.6%) reversed from MCI to CN with a mean (SD) follow-up of 2.9 (1.8) years. Several dietary/lifestyle factors, including daily consumption of fresh fruits (Hazard Ratio [HR]: 1.28, 95% CI: 1.15 to 1.42; P༜.001), engagement in reading (HR: 1.24, 95% CI: 1.00 to 1.54; P =.047), housework (HR: 1.21, 95% CI: 1.08 to 1.35; P =.001), and mah-jong or other card games (HR: 1.23, 95% CI: 1.08 to 1.39; P =.001), were positively associated with possibility of reversion. Cigarette smoking (HR: 0.92, 95% CI: 0.84 to 1.00; P= .041) and duration of alcohol drinking (HR: 0.97, 95% CI: 0.94 to 0.99; P = .012) were negatively associated with possibility of reversion. None of the modifiable cardiometabolic and psychological factors was found to be significantly associated with reversion to CN. Difference was identified among different age and gender group. Conclusion This study identified several dietary/lifestyle factors associated with MCI reversion that may transfer into large-scale dementia prevention practices.

“What Is Hidden behind the Mask?” Facial Emotion Recognition at the Time of COVID-19 Pandemic in Cognitively Normal Multiple Sclerosis Patients

Social cognition deficits have been described in people with multiple sclerosis (PwMS), even in absence of a global cognitive impairment, affecting predominantly the ability to adequately process emotions from human faces. The COVID-19 pandemic has forced people to wear face masks that might interfere with facial emotion recognition. Therefore, in the present study, we aimed at investigating the ability of emotion recognition in PwMS from faces wearing masks. We enrolled a total of 42 cognitively normal relapsing–remitting PwMS and a matched group of 20 healthy controls (HCs). Participants underwent a facial emotion recognition task in which they had to recognize from faces wearing or not surgical masks which of the six basic emotions (happiness, anger, fear, sadness, surprise, disgust) was presented. Results showed that face masks negatively affected emotion recognition in all participants (p < 0.001); in particular, PwMS showed a global worse accuracy than HCs (p = 0.005), mainly driven by the “no masked” (p = 0.021) than the “masked” (p = 0.064) condition. Considering individual emotions, PwMS showed a selective impairment in the recognition of fear, compared with HCs, in both the conditions investigated (“masked”: p = 0.023; “no masked”: p = 0.016). Face masks affected negatively also response times (p < 0.001); in particular, PwMS were globally hastier than HCs (p = 0.024), especially in the “masked” condition (p = 0.013). Furthermore, a detailed characterization of the performance of PwMS and HCs in terms of accuracy and response speed was proposed. Results from the present study showed the effect of face masks on the ability to process facial emotions in PwMS, compared with HCs. Healthcare professionals working with PwMS at the time of the COVID-19 outbreak should take into consideration this effect in their clinical practice. Implications in the everyday life of PwMS are also discussed.

Apathy as a Risky Neuropsychiatric Syndrome of Progression From Normal Aging to Mild Cognitive Impairment and Dementia: A Systematic Review and Meta-Analysis

Background: Apathy has been suggested as a potential predictor of mild cognitive impairment (MCI) progression to dementia. Whether it might predict the transition from normal cognitive function to cognitive impairment has been less studied. The current study aimed to provide a comprehensive summary of the evidence on the association between apathy and the transition from normal cognitive function to cognitive impairment.Methods: We searched the PubMed, Embase, and Web of Science databases for longitudinal prospective cohort studies that evaluated apathy at baseline in the cognitively normal population and had cognitive impairment as the outcome. Random effects models were used, and heterogeneity was explored with stratification. The stability of the synthesized result was indicated using sensitivity analysis by excluding one study each time and recalculating the overall effect.Results: Ten studies comprising 26,195 participants were included. Apathy status was available for 22,101 participants. Apathy was present in 1,803 of 22,101 participants (8.16%). Follow-up ranged from 1 to 13 years. The combined odds ratio (OR) of cognitive impairment for patients with apathy was 2.07 (95% CI: 1.43–2.99; I2 = 86%), and the combined hazard ratio was 2.70 (95% CI: 1.38–5.27; I2 = 94%). The OR meta-analyses for different conversion outcomes were MCI (OR = 3.38, 95% CI: 1.57–7.28; I2 =71%), cognitive decline (OR = 1.27, 95% CI: 0.81–2.00; I2 = 64%) and dementia (OR = 2.12, 95% CI: 1.32–3.41; I2 = 86%). Subgroup analysis suggested that the association between apathy and cognitive impairment changed with age, depression adjustments, apathy measurement, and follow-up time.Conclusions: Apathy was associated with a greater than 2-fold increased risk of progression to cognitive impairment in the cognitively normal population. Future interventions targeting apathy management in the general population may reduce the risk of cognitive impairment.