non-Alzheimer Dementia Research Articles

The Microbiota-Gut-Brain Axis and Neurological Disorders: A Comprehensive Review.

Microbes have inhabited the earth for hundreds of millions of years longer than humans. The microbiota-gut-brain axis (MGBA) represents a bidirectional communication pathway. These communications occur between the central nervous system (CNS), the enteric nervous system (ENS), and the emotional and cognitive centres of the brain. The field of research on the gut-brain axis has grown significantly during the past two decades. Signalling occurs between the gut microbiota and the brain through the neural, endocrine, immune, and humoral pathways. A substantial body of evidence indicates that the MGBA plays a pivotal role in various neurological diseases. These include Alzheimer's disease (AD), autism spectrum disorder (ASD), Rett syndrome, attention deficit hyperactivity disorder (ADHD), non-Alzheimer's neurodegeneration and dementias, fronto-temporal lobe dementia (FTLD), Wilson-Konovalov disease (WD), multisystem atrophy (MSA), Huntington's chorea (HC), Parkinson's disease (PD), multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS), temporal lobe epilepsy (TLE), depression, and schizophrenia (SCZ). Furthermore, the bidirectional correlation between therapeutics and the gut-brain axis will be discussed. Conversely, the mood of delivery, exercise, psychotropic agents, stress, and neurologic drugs can influence the MGBA. By understanding the MGBA, it may be possible to facilitate research into microbial-based interventions and therapeutic strategies for neurological diseases.

Air pollution: a latent key driving force of dementia

Many researchers have studied the role of air pollutants on cognitive function, changes in brain structure, and occurrence of dementia. Due to the wide range of studies and often contradictory results, the present systematic review was conducted to try and clarify the relationship between air pollutants and dementia. To identify studies for this review, a systematic search was conducted in Scopus, PubMed, and Web of Science databases (without historical restrictions) until May 22, 2023. The PECO statement was created to clarify the research question, and articles that did not meet the criteria of this statement were excluded. In this review, animal studies, laboratory studies, books, review articles, conference papers and letters to the editors were avoided. Also, studies focused on the effect of air pollutants on cellular and biochemical changes (without investigating dementia) were also excluded. A quality assessment was done according to the type of design of each article, using the checklist developed by the Joanna Briggs Institute (JBI). Finally, selected studies were reviewed and discussed in terms of Alzheimer's dementia and non-Alzheimer's dementia. We identified 14,924 articles through a systematic search in databases, and after comprehensive reviews, 53 articles were found to be eligible for inclusion in the current systematic review. The results showed that chronic exposure to higher levels of air pollutants was associated with adverse effects on cognitive abilities and the presence of dementia. Studies strongly supported the negative effects of PM2.5 and then NO2 on the brain and the development of neurodegenerative disorders in old age. Because the onset of brain structural changes due to dementia begins decades before the onset of disease symptoms, and that exposure to air pollution is considered a modifiable risk factor, taking preventive measures to reduce air pollution and introducing behavioral interventions to reduce people's exposure to pollutants is advisable.

A comparison of dementia diagnoses and cognitive function measures in Medicare claims and the Minimum Data Set.

Gold standard dementia assessments are rarely available in large real-world datasets, leaving researchers to choose among methods with imperfect but acceptable accuracy to identify nursing home (NH) residents with dementia. In healthcare claims, options include claims-based diagnosis algorithms, diagnosis indicators, and cognitive function measures in the Minimum Data Set (MDS), but few studies have compared these. We evaluated the proportion of NH residents identified with possible dementia and concordance of these three. Using a 20% random sample of 2018-2019 Medicare beneficiaries, we identified MDS admission assessments for non-skilled NH stays among individuals with continuous enrollment in Medicare Parts A, B, and D. Dementia was identified using: (1) Chronic Conditions Warehouse (CCW) claims-based algorithm for Alzheimer's disease and non-Alzheimer's dementia; (2) MDS active diagnosis indicators for Alzheimer's disease and non-Alzheimer's dementias; and (3) the MDS Cognitive Function Scale (CFS) (at least mild cognitive impairment). We compared the proportion of admissions with evidence of possible dementia using each criterion and calculated the sensitivity, specificity, and agreement of the CCW claims definition and MDS indicators for identifying any impairment on the CFS. Among 346,013 non-SNF NH admissions between 2018 and 2019, 57.2% met criteria for at least one definition (44.7% CFS, 40.7% CCW algorithm, 26.0% MDS indicators). The MDS CFS uniquely identified the greatest proportion with evidence of dementia. The CCW claims algorithm had 63.7% sensitivity and 78.1% specificity for identifying any cognitive impairment on the CFS. Active diagnosis indicators from the MDS had lower sensitivity (47.0%), but higher specificity (91.0%). Claims- and MDS-based methods for identifying NH residents with possible dementia have only partial overlap in the cohorts they identify, and neither is an obvious gold standard. Future studies should seek to determine whether additional functional assessments from the MDS or prescriptions can improve identification of possible dementia in this population.

MRI-derived brain iron, grey matter volume, and risk of dementia and Parkinson's disease: Observational and genetic analysis in the UK Biobank cohort

BackgroundIron overload is observed in neurodegenerative diseases, especially Alzheimer's disease (AD) and Parkinson's disease (PD). Homozygotes for the iron-overload (haemochromatosis) causing HFE p.C282Y variant have increased risk of dementia and PD. Whether brain iron deposition is causal or secondary to the neurodegenerative processes in the general population is unclear. MethodsWe analysed 39,533 UK Biobank participants of European genetic ancestry with brain MRI data. We studied brain iron estimated by R2* and quantitative susceptibility mapping (QSM) in 8 subcortical regions: accumbens, amygdala, caudate, hippocampus, pallidum, putamen, substantia nigra, and thalamus. We performed genome-wide associations studies (GWAS) and used Mendelian Randomization (MR) methods to estimate the causal effect of brain iron on grey matter volume, and risk of AD, non-AD and PD. We also used MR to test whether genetic liability to AD or PD causally increased brain iron (R2* and QSM). FindingsIn GWAS of R2* and QSM we replicated 83% of previously reported genetic loci and identified 174 further loci across all eight brain regions. Higher genetically predicted brain iron, using both R2* and QSM, was associated with lower grey matter volumes in the caudate, putamen and thalamus (e.g., Beta-putamenQSM: −0.37, p = 2*10–46). Higher genetically predicted thalamus R2* was associated with increased risk of non-AD dementia (OR 1.36(1.16;1.60), p = 2*10–4) but not AD (p > 0.05). In males, genetically predicted putamen R2* increased non-AD dementia risk, but not in females. Higher genetically predicted iron in the caudate, putamen, and substantia nigra was associated with an increased risk of PD (Odds Ratio QSM ∼ substantia-nigra 1.21(1.07;1.37), p = 0.003). Genetic liability to AD or PD was not associated with R2* or QSM in the dementia or PD-associated regions. InterpretationOur genetic analysis supports a causal effect of higher iron deposition in specific subcortical brain regions for Parkinson's disease, grey matter volume, and non-Alzheimer's dementia.

Multi-branch attention Raman network and surface-enhanced Raman spectroscopy for the classification of neurological disorders.

Surface-enhanced Raman spectroscopy (SERS), a rapid, low-cost, non-invasive, ultrasensitive, and label-free technique, has been widely used in-situ and ex-situ biomedical diagnostics questions. However, analyzing and interpreting the untargeted spectral data remains challenging due to the difficulty of designing an optimal data pre-processing and modelling procedure. In this paper, we propose a Multi-branch Attention Raman Network (MBA-RamanNet) with a multi-branch attention module, including the convolutional block attention module (CBAM) branch, deep convolution module (DCM) branch, and branch weights, to extract more global and local information of characteristic Raman peaks which are more distinctive for classification tasks. CBAM, including channel and spatial aspects, is adopted to enhance the distinctive global information on Raman peaks. DCM is used to supplement local information of Raman peaks. Autonomously trained branch weights are applied to fuse the features of each branch, thereby optimizing the global and local information of the characteristic Raman peaks for identifying diseases. Extensive experiments are performed for two different neurological disorders classification tasks via untargeted serum SERS data. The results demonstrate that MBA-RamanNet outperforms commonly used CNN methods with an accuracy of 88.24% for the classification of healthy controls, mild cognitive impairment, Alzheimer's disease, and Non-Alzheimer's dementia; an accuracy of 90% for the classification of healthy controls, elderly depression, and elderly anxiety.

Serum GFAP levels correlate with astrocyte reactivity, post-mortem brain atrophy and neurofibrillary tangles.

Glial fibrillary acidic protein (GFAP), a proxy of astrocyte reactivity, has been proposed as biomarker of Alzheimer's disease. However, there is limited information about the correlation between blood biomarkers and post-mortem neuropathology. In a single-centre prospective clinicopathological cohort of 139 dementia patients, for which the time-frame between GFAP level determination and neuropathological assessment was exceptionally short (on average 139 days), we analysed this biomarker, measured at three time points, in relation to proxies of disease progression such as cognitive decline and brain weight. Most importantly, we investigated the use of blood GFAP to detect the neuropathological hallmarks of Alzheimer's disease, while accounting for potential influences of the most frequent brain co-pathologies. The main findings demonstrated an association between serum GFAP level and post-mortem tau pathology (β = 12.85; P < 0.001) that was independent of amyloid deposits (β = 13.23; P = 0.02). A mediation analysis provided additional support for the role of astrocytic activation as a link between amyloid and tau pathology in Alzheimer's disease. Furthermore, a negative correlation was observed between pre-mortem serum GFAP and brain weight at post-mortem (r = -0.35; P < 0.001). This finding, together with evidence of a negative correlation with cognitive assessments (r = -0.27; P = 0.005), supports the role of GFAP as a biomarker for disease monitoring, even in the late phases of Alzheimer's disease. Moreover, the diagnostic performance of GFAP in advanced dementia patients was explored, and its discriminative power (area under the receiver operator characteristic curve at baseline = 0.91) in differentiating neuropathologically-confirmed Alzheimer's disease dementias from non-Alzheimer's disease dementias was determined, despite the challenging scenario of advanced age and frequent co-pathologies in these patients. Independently of Alzheimer's disease, serum GFAP levels were shown to be associated with two other pathologies targeting the temporal lobes-hippocampal sclerosis (β = 3.64; P = 0.03) and argyrophilic grain disease (β = -6.11; P = 0.02). Finally, serum GFAP levels were revealed to be correlated with astrocyte reactivity, using the brain GFAP-immunostained area as a proxy (ρ = 0.21; P = 0.02). Our results contribute to increasing evidence suggesting a role for blood GFAP as an Alzheimer's disease biomarker, and the findings offer mechanistic insights into the relationship between blood GFAP and Alzheimer's disease neuropathology, highlighting its ties with tau burden. Moreover, the data highlighting an independent association between serum GFAP levels and other neuropathological lesions provide information for clinicians to consider when interpreting test results. The longitudinal design and correlation with post-mortem data reinforce the robustness of our findings. However, studies correlating blood biomarkers and neuropathological assessments are still scant, and further research is needed to replicate and validate these results in diverse populations.

Plasma biomarkers for predicting the development of dementia in a community-dwelling older Japanese population.

To assess the association between plasma amyloid β (Aβ) 42/40, phosphorylated tau (p-τ)181, glial fibrillary acidic protein (GFAP), or neurofilament light chain (NfL) and the risk of dementia and to determine whether these plasma biomarkers could improve the ability to predict incident dementia in a general older population. A total of 1346 Japanese community-dwelling individuals aged ≥65 years without dementia were followed prospectively for 5.0 years. Plasma biomarkers were quantified using a Simoa HD-X analyzer. A Cox proportional hazards model was used to estimate the hazard ratios of each plasma biomarker level for the risk of dementia. During the follow-up, 151 participants developed dementia, of whom 108 had Alzheimer disease (AD) and 43 non-Alzheimer dementia (non-AD). Lower plasma Aβ42/40 levels and higher plasma p-τ181 levels were significantly associated with developing AD but not non-AD, whereas significant associations were observed between higher plasma levels of GFAP and NfL and risk of both AD and non-AD (all P for trend <0.05). In addition, adding these four plasma biomarkers into a model consisting of the total score of the dementia risk model significantly improved the predictive ability for incident dementia. Our findings suggest that plasma Aβ42/40 and p-τ181 are specific markers of AD, and plasma GFAP and NfL are potential biomarkers for all-cause dementia in the general Japanese older population. In addition, the measurement of these plasma biomarkers may be a useful and relatively low-invasive procedure for identifying individuals at high risk for developing dementia in clinical practice.

Comparison of consistency in centiloid scale among different analytical methods in amyloid PET: the CapAIBL, VIZCalc, and Amyquant methods.

The Centiloid (CL) scale is a standardized measure for quantifying amyloid deposition in amyloid positron emission tomography (PET) imaging. We aimed to assess the agreement among 3 CL calculation methods: CapAIBL, VIZCalc, and Amyquant. This study included 192 participants (mean age: 71.5years, range: 50-87years), comprising 55 with Alzheimer's disease, 65 with mild cognitive impairment, 13 with non-Alzheimer's dementia, and 59 cognitively normal participants. All the participants were assessed using the three CL calculation methods. Spearman's rank correlation, linear regression, Friedman tests, Wilcoxon signed-rank tests, and Bland-Altman analysis were employed to assess data correlations, linear associations, method differences, and systematic bias, respectively. Strong correlations (rho = 0.99, p < .001) were observed among the CL values calculated using the three methods. Scatter plots and regression lines visually confirmed these strong correlations and met the validation criteria. Despite the robust correlations, a significant difference in CL value between CapAIBL and Amyquant was observed (36.1 ± 39.7 vs. 34.9 ± 39.4; p < .001). In contrast, no significant differences were found between CapAIBL and VIZCalc or between VIZCalc and Amyquant. The Bland-Altman analysis showed no observable systematic bias between the methods. The study demonstrated strong agreement among the three methods for calculating CL values. Despite minor variations in the absolute values of the Centiloid scores obtained using these methods, the overall agreement suggests that they are interchangeable.

Early intervention and adding effective doses of EGb761 like Ginkgo extract slow down dementia progression: insights to the neurovascular unit.

Dementia is a progressive neurodegenerative disorder characterized by cognitive decline, memory impairment, and functional deterioration. Pharmacological interventions play a crucial role in managing dementia symptoms and potentially slowing down disease progression. This study aimed to investigate the impact of pharmacological interventions, including acetylcholinesterase inhibitors (AChEIs), memantine, and Gingko extract, on the progression of dementia, with a specific focus on mild cognitive impairment (MCI), Alzheimer's disease (AD), and non-Alzheimer dementias. A total of 547 participants out of 3,547 cases in a specific dataset followed by the same author, including healthy controls, individuals with MCI, AD, and non-Alzheimer dementias, were included in this study. The follow-up duration was up to 211 months, allowing for a minimum 3 visits comprehensive assessment of disease progression. The treatment approaches included AChEIs, memantine, and combination therapy, with variations in the starting time for these treatments based on the dementia type. The use of AChEIs and memantine showed efficacy in improving cognitive function and overall function in individuals with MCI, AD, and non-AD dementias. Combination therapy EGb761 like Gingko extract with AChEIs and/or Memantine demonstrated a slower progression compared to AChEIs alone in individuals with prodromal dementia (MCI) and AD. The starting time for memantine and combination therapy was earlier in non-AD dementia cases compared to AD dementia cases and prodromal dementia. Pharmacological interventions, particularly the use of AChEIs and memantine, can have a positive impact on cognitive function and overall function in individuals with dementia. The combination of AChEIs with EGb761 like Gingko extract may provide additional benefits in slowing down disease progression in AD cases. Early recognition and accurate classification of MCI subtypes are crucial, and the use of EGb761 like Gingko extract is recommended for symptomatic treatment. Future personalized risk predictions based on biomarker constellations may further enhance the multi-target treatment approaches of MCI and different dementia types.

Hearing impairment and risk of dementia in The HUNT Study (HUNT4 70+): a Norwegian cohort study

Hearing impairment is strongly associated with future dementia. No studies have reported objectively measured hearing impairment in a cohort with a long period of follow-up (>20 years), and few have reported follow-up over 10 years. Hence, there is a need for high quality studies with sufficient follow-up time and data to account for reverse causality and confounding. We aimed to address this knowledge gap. This cohort study used individual participant data from The Trøndelag Health Study (HUNT) in Norway. All current residents aged at least 20 years in the former Norwegian Nord-Trøndelag County were invited to participate in four decennial surveys: HUNT1 (1984-1986), HUNT2 (1995-1997), HUNT3 (2006-2008), and HUNT4 (2017-2019) with individuals aged at least 70 years included in a substudy, known as HUNT4 70+. Here, we report the findings of this substudy. HUNT4 70+ comprised 7135 participants who were assessed for dementia using the Diagnostic and Statistical Manual of Mental Disorders 5 criteria and who had audiometry between 1996 and 1998. The primary objective was to investigate, with gold standard audiometric testing and dementia diagnostic assessment, whether hearing impairment was an independent risk factor for all-cause dementia. The secondary objective was to investigate if a risk also applied to Alzheimer dementia and non-Alzheimer dementia. We analysed the association using Poisson regression and adjusted for confounders. This study is registered with ClinicalTrials.gov (NCT04284384). At baseline, 1058 (15%) individuals had acquired hearing impairment with a hearing threshold of at least 25 decibel (dB) and, at follow-up, 1089 (15%) had dementia. In the total group, people with hearing impairment had a relative risk (RR) 1.04 (95% confidence interval (CI) 1.00-1.09) per 10dB increase in hearing thresholds. For individuals younger than 85 years at follow-up the RR was 1.12 (95% CI 1.05-1.21). Associations between hearing impairment and Alzheimer dementia and non-Alzheimer dementia were similar. There was no association for individuals aged at least 85 years. We found a moderate association between objectively measured hearing impairment and dementia in the younger age group (<85 years). The findings of no association in the older age group (≥85 years) might be due to the competing risk of death. The present study adds to the literature showing that acquired hearing impairment is a risk for dementias over a period which is too long for reverse causation, and with thorough consideration of confounders. Further research is needed to investigate associations between the different aetiologies of hearing loss and dementia subtypes, and risk differences for sexes. The Norwegian National Centre for Ageing and Health with a grant from Health South-East.

Risk of dementia among older patients with lymphoma: A Danish nationwide matched cohort study

IntroductionTreatment of lymphoma can be associated with cognitive challenges, and some patients may fear development of dementia as long-term complication. Studies report a lower risk of dementia after cancer. Some believe this difference to be a protective mechanism of cancer, others believe it to be driven by bias. The risk of developing dementia after lymphoma has not been investigated in a population-based setting. The aim of this study was to identify the risk of being diagnosed with dementia after lymphoma treatment. Materials and MethodsThis Danish nationwide matched cohort study included patients aged ≥65 years with a first-time diagnosis of a non-central nervous system lymphoma between 2005 and 2018 in complete remission after treatment with chemotherapy. Patients diagnosed with dementia or treated with dementia medication before lymphoma diagnosis were excluded. Each patient was matched 1:5 on sex, year of birth, and a modified Charlson comorbidity index. Patients and matched comparators were followed from the corresponding patient's date of complete remission. The risk of developing dementia was calculated using cause-specific hazard ratios (HR), and the cumulative risk was estimated by Aalen-Johansen with death as the competing risk. ResultsA total of 3,244 patients and 16,220 matched comparators were included in the study. There was no difference in risk of all-cause dementia among patients with lymphoma compared to matched comparators with cause-specific HR of 0.85 (95% confidence interval [CI]: 0.70;1.04). The risk of both Alzheimer's disease and non-Alzheimer's dementia was equal among patients and comparators: HR 0.89 (95% CI: 0.66;1.21) and 0.82 (95% CI: 0.63;1.07), respectively. Stratified by lymphoma subtype, age, or year of diagnosis, the risk of all-cause dementia remained equal among patients and matched comparators. The cumulative risk of all-cause dementia was significantly lower among patients with lymphoma compared to matched comparators (Gray's test p < 0.001), probably reflecting higher mortality in patients with lymphoma. DiscussionThe risk of all-cause dementia, Alzheimer's disease, and non-Alzheimer's dementia was equal among older patients with lymphoma compared to matched comparators. Our data suggests that risk of developing dementia is not changed after lymphoma treatment.

Explainable AI-based Alzheimer's prediction and management using multimodal data.

According to the World Health Organization (WHO), dementia is the seventh leading reason of death among all illnesses and one of the leading causes of disability among the world's elderly people. Day by day the number of Alzheimer's patients is rising. Considering the increasing rate and the dangers, Alzheimer's disease should be diagnosed carefully. Machine learning is a potential technique for Alzheimer's diagnosis but general users do not trust machine learning models due to the black-box nature. Even, some of those models do not provide the best performance because of using only neuroimaging data. To solve these issues, this paper proposes a novel explainable Alzheimer's disease prediction model using a multimodal dataset. This approach performs a data-level fusion using clinical data, MRI segmentation data, and psychological data. However, currently, there is very little understanding of multimodal five-class classification of Alzheimer's disease. For predicting five class classifications, 9 most popular Machine Learning models are used. These models are Random Forest (RF), Logistic Regression (LR), Decision Tree (DT), Multi-Layer Perceptron (MLP), K-Nearest Neighbor (KNN), Gradient Boosting (GB), Adaptive Boosting (AdaB), Support Vector Machine (SVM), and Naive Bayes (NB). Among these models RF has scored the highest value. Besides for explainability, SHapley Additive exPlanation (SHAP) is used in this research work. The performance evaluation demonstrates that the RF classifier has a 10-fold cross-validation accuracy of 98.81% for predicting Alzheimer's disease, cognitively normal, non-Alzheimer's dementia, uncertain dementia, and others. In addition, the study utilized Explainable Artificial Intelligence based on the SHAP model and analyzed the causes of prediction. To the best of our knowledge, we are the first to present this multimodal (Clinical, Psychological, and MRI segmentation data) five-class classification of Alzheimer's disease using Open Access Series of Imaging Studies (OASIS-3) dataset. Besides, a novel Alzheimer's patient management architecture is also proposed in this work.

Factors affecting progression of non-Alzheimer dementia: a retrospective analysis with long-term follow-up.

Non-Alzheimer's dementias, including vascular dementia (VaD), frontotemporal dementia (FTD), Lewy body dementia (LBD), and Parkinson's disease dementia (PDD), possess unique characteristics and prognostic factors that remain poorly understood. This study aims to investigate the temporal course of these subtypes and identify the impact of functional, neuropsychiatric, and comorbid medical conditions on prognosis. Additionally, the relationship between hippocampal atrophy, white matter intensities, and disease progression will be examined, along with the identification of key covariates influencing slow or fast progression in non-Alzheimer's dementias. A total of 196 patients with non-Alzheimer's dementias who underwent at least three comprehensive evaluations were included, with proportions of VaD, FTD, LBD, and PDD being 50, 19.39, 19.90, and 10.71%, respectively. Patient demographics, comorbidities, neuropsychiatric and neuroimaging parameters, and global evaluation were analyzed using appropriate statistical methods. The study followed patients for a mean duration of 62.57 ± 33.45 months (ranging from 11 to 198 months). The results from three different visits for each non-AD dementia case demonstrated significant differences in various measures across visits, including functional capacity (BDLAS), cognition (MMSE), and other neuropsychological tests. Notably, certain genotypes and hippocampal atrophy grades were more prevalent in specific subtypes. The results indicate that Fazekas grading and hippocampal atrophy were significant predictors of disease progression, while epilepsy, extrapyramidal symptoms, thyroid dysfunction, coronary artery disease, diabetes mellitus, hypertension, stroke, hyperlipidemia, sleep disorders, smoking, and family history of dementia were not significant predictors. BDLAS and EDLAS scores at the first and second visits showed significant associations with disease progression, while scores at the third visit did not. Group-based trajectory analysis revealed that non-AD cases separated into two reliable subgroups with slow/fast prognosis, showing high reliability (Entropy = 0.790, 51.8 vs. 48.2%). This study provides valuable insights into the temporal course and prognostic factors of non-Alzheimer's dementias. The findings underscore the importance of considering functional, neuropsychological, and comorbid medical conditions in understanding disease progression. The significant associations between hippocampal atrophy, white matter intensities, and prognosis highlight potential avenues for further research and therapeutic interventions.

The role of oestrogen therapy in reducing risk of Alzheimer's disease: systematic review.

Studies have shown a relationship between oestrogen and Alzheimer's disease. However, there is neither clear nor strong evidence on the use of oestrogen-only therapy in reducing the risk of Alzheimer's disease. To assess the effects of oestrogen-only therapy on reducing the risk of Alzheimer's disease. Inclusion criteria was determined with the PICO framework. Outcome was cognitive function measured by neuropsychological tests and strict protocols. Exclusion criteria included non-Alzheimer's dementia, progesterone-only therapy and pre-menopausal women. Searches were conducted in nine electronic healthcare databases, last searched in July 2022. Quality assessments conducted on randomised controlled trials (RCTs) were performed with the GRADE assessment, and cohort studies and case-control studies were assessed with the Newcastle-Ottawa Scale. Extracted data were used to analyse participants, interventions and outcomes. Twenty-four studies satisfied the search criteria (four RCTs, nine cohort studies, 11 case-control studies). Fifteen studies showed positive associations for oestrogen-only therapy reducing the risk of Alzheimer's disease, and the remaining nine found no evidence of association. Fifteen studies showed that oestrogen-only therapy effectively reduced the risk of Alzheimer's disease, whereas nine showed no correlation. Studies also investigated oestrogen-related variables such as length of oestrogen exposure, being an apolipoprotein E ε4 carrier and concomitant use of non-steroidal anti-inflammatory drugs, and their role in neuroprotection. This review was limited by the limited ranges of duration of oestrogen treatment and type of oestrogen-only therapy used. In conclusion, oestrogen-only therapy has potential for use in preventing Alzheimer's disease, although current evidence is inconclusive and requires further study.

The Association Between Neutrophil-Lymphocyte Ratio and Variability with New-Onset Dementia: A Population-Based Cohort Study.

Previous studies identified that neutrophil-to-lymphocyte ratio (NLR) may be a predictor of dementia. However, the associations between NLR and dementia at the population level were less explored. This retrospective population-based cohort study was designed to identify the associations between NLR and dementia among patients visiting for family medicine consultation in Hong Kong. The patients were recruited from January 1, 2000, to December 31, 2003, and followed up until December 31, 2019. The demographics, prior comorbidities, medications, and laboratory results were collected. The primary outcomes were Alzheimer's disease and related dementia and non-Alzheimer's dementia. Cox regression and restricted cubic spline were applied to identify associations between NLR and dementia. A cohort of 9,760 patients (male: 41.08% ; baseline age median: 70.2; median follow-up duration: 4756.5 days) with complete NLR were included. Multivariable Cox regression identified that patients with NLR >5.44 had higher risks of developing Alzheimer's disease and related dementia (hazard ratio [HR]: 1.50, 95% Confidence interval [CI]: 1.17-1.93) but not non-Alzheimer's dementia (HR: 1.33; 95% CI: 0.60-2.95). The restricted cubic splines demonstrated that higher NLR was associated with Alzheimer's disease and related dementia. The relationship between the NLR variability and dementia was also explored; of all the NLR variability measures, only the coefficient of variation was predictive of non-Alzheimer's dementia (HR: 4.93; 95% CI: 1.03-23.61). In this population-based cohort, the baseline NLR predicts the risks of developing dementia. Utilizing the baseline NLR during family medicine consultation may help predict the risks of dementia.

Healthy lifestyle and all-cause and cause-specific dementia in individuals with type 2 diabetes and the roles of diabetes duration and insulin use in UK Biobank cohort.

To examine the effect of a healthy lifestyle score derived from seven lifestyle factors recommended by the diabetes management guidelines on all-cause and cause-specific dementia in individuals with type 2 diabetes mellitus (T2DM), and how diabetes duration and insulin use status modify their association. This study analysed data of 459 840 participants from the UK Biobank. We used Cox proportional hazards models to estimate hazard ratios (HRs) and 95% confidence intervals for the association of an overall healthy lifestyle score with all-cause and cause-specific dementia of Alzheimer's disease, vascular dementia and non-Alzheimer non-vascular dementia. Using diabetes-free participants who scored 5-7 as the reference group, in diabetes-free participants, we observed higher healthy lifestyle score was related to lower risk of all-cause and cause-specific dementia. However, in people with T2DM, those scored 2-3, 4 and 5-7 all had around the two-time risk of all-cause dementia (HR: 2.20-2.36), while those scored 0-1 had over a three-time risk (HR: 3.14, 95% confidence interval 2.34-4.21). A dose-response trend was observed with vascular dementia (each 2-point increase: 0.75, 0.61-0.93) and no significant association with Alzheimer's disease (0.95, 0.77-1.16). The reduced risk of all-cause and cause-specific dementia with higher lifestyle score was observed in patients with a diabetes duration less than 10 years, or in patients with no insulin use. In people with T2DM, higher healthy lifestyle score was associated with lower risk of all-cause dementia. Diabetes duration and insulin use moderated the association between healthy lifestyle score and risk of dementia.

Can Depressive Symptomatology at Diagnosis Predict Cognitive and Functional Decline Over 1 Year in Rural Canadian Patients With Dementia?

Depressive symptomatology is often associated with the onset of dementia, although the exact form and directionality of this association is still unclear. The aim of this study is to investigate whether depressive symptomatology at the time of dementia diagnosis was predictive of cognitive, functional, and behavioral decline over 1 year. In a Rural and Remote Memory Clinic, 375 patients consecutively diagnosed with mild cognitive impairment, Alzheimer disease, or non-Alzheimer disease dementia completed the Center for Epidemiological Studies Depression Scale at first visit and 1-year follow-up to assess depressive symptomatology. The same cohort was evaluated for cognitive, functional, and behavioral decline through the completion of 5 clinical tests performed at the first visit and at 1-year follow-up. Depressive symptomatology at time of dementia diagnosis did not predict cognitive or functional decline over 1 year, although increases in depressive symptomatology over 1 year significantly correlated with higher caregiver ratings of neuropsychiatric symptom severity and related distress over that time. Increasingly severe depressive symptomatology over 1 year correlated with greater caregiver distress. This study points the way for future studies delineating the relationship between depression, dementia progression, and caregiver distress.

The effect of single and repeated doses of rivastigmine on gastric myoelectric activity in experimental pigs.

Rivastigmine is a pseudo-irreversible cholinesterase inhibitor used for therapy of Alzheimer's disease and non-Alzheimer dementia syndromes. In humans, rivastigmine can cause significant gastrointestinal side effects that can limit its clinical use. The aim of this study was to assess the impact of rivastigmine on gastric motor function by means of electrogastrography (EGG) in experimental pigs. Six experimental adult female pigs (Sus scrofa f. domestica, hybrids of Czech White and Landrace breeds; 3-month-old; mean weight 30.7 ± 1.2 kg) were enrolled into the study twice and created two experimental groups. In group A, a single intragastric dose of 6 mg rivastigmine hydrogen tartate was administered in the morning to fasting pigs before EGG recording. In group B, rivastigmine was administered to overnight fasting animals in a dietary bolus in the morning for 7 days (6 mg per day). On day 8, an intragastric dose of 12 mg rivastigmine was given in the morning to fasting pigs before EGG. EGG recording was accomplished by means of an EGG standalone system. Recordings from both groups were evaluated in dominant frequency and EGG power (areas of amplitudes). In total, 1,980 one-minute EGG intervals were evaluated. In group A, basal EGG power (median 1290.5; interquartile range 736.5-2330 μV2) was significantly higher in comparison with the power of intervals T6 (882; 577-1375; p = 0.001) and T10 (992.5; 385-2859; p = 0.032). In group B, the dominant frequency increased significantly from basal values (1.97 ± 1.57 cycles per minute) to intervals T9 (3.26 ± 2.16; p < 0.001) and T10 (2.14 ± 1.16; p = 0.012), respectively. In group B, basal EGG power (median 1030.5; interquartile range 549-5093) was significantly higher in comparison with the power of intervals T7 (692.5; 434-1476; p = 0.002) and T8 (799; 435-1463 μV2; p = 0.004). Both single as well as repeated intragastric administration of rivastigmine hydrogen tartrate caused a significant decrease of EGG power (areas of amplitudes) in experimental pigs. EGG power may serve as an indirect indicator of gastric motor competence. These findings might provide a possible explanation of rivastigmine-associated dyspepsia in humans.

Genome-wide structural variant analysis identifies risk loci for non-Alzheimer’s dementias

We characterized the role of structural variants, a largely unexplored type of genetic variation, in two non-Alzheimer's dementias, namely Lewy body dementia (LBD) and frontotemporal dementia (FTD)/amyotrophic lateral sclerosis (ALS). To do this, we applied an advanced structural variant calling pipeline (GATK-SV) to short-read whole-genome sequence data from 5,213 European-ancestry cases and 4,132 controls. We discovered, replicated, and validated a deletion in TPCN1 as a novel risk locus for LBD and detected the known structural variants at the C9orf72 and MAPT loci as associated with FTD/ALS. We also identified rare pathogenic structural variants in both LBD and FTD/ALS. Finally, we assembled a catalog of structural variants that can be mined for new insights into the pathogenesis of these understudied forms of dementia.

RETRACTED: Association between hearing aid use and all-cause and cause-specific dementia: an analysis of the UK Biobank cohort

Dementia and hearing loss are both highly prevalent conditions among older adults. We aimed to examine the association between hearing aid use and risk of all-cause and cause-specific dementia among middle-aged and older-aged adults, and to explore the roles of mediators and moderators in their association. We used data from the UK Biobank, a population-based cohort study, which recruited adults aged 40-69 years between 2006 and 2010 across 22 centres in England, Scotland, and Wales. We used Cox proportional hazards models to estimate hazard ratios (HRs) and 95% CIs between self-reported hearing aid use status (hearing loss with or without hearing aids) at baseline and risk of dementia (all-cause dementia, Alzheimer's disease, vascular dementia, and non-Alzheimer's disease non-vascular dementia). Dementia diagnoses were ascertained using hospital records and death-register data. We also analysed the roles of mediators (self-reported social isolation, loneliness, and mood) and moderators (self-reported education and income, smoking, morbidity, and measured APOE allele status). After the exclusion of people who did not answer the question on hearing difficulties (n=25 081 [5·0%]) and those with dementia at baseline visit (n=283 [0·1%]), we included 437 704 people in the analyses. Compared with participants without hearing loss, people with hearing loss without hearing aids had an increased risk of all-cause dementia (HR 1·42 [95% CI 1·29-1·56]); we found no increased risk in people with hearing loss with hearing aids (1·04 [0·98-1·10]). The positive association of hearing aid use was observed in all-cause dementia and cause-specific dementia subtypes (Alzheimer's disease, vascular dementia, and non-Alzheimer's disease non-vascular dementia). The attributable risk proportion of dementia for hearing loss was estimated to be 29·6%. Of the total association between hearing aid use and all-cause dementia, 1·5% was mediated by reducing social isolation, 2·3% by reducing loneliness, and 7·1% by reducing depressed mood. In people with hearing loss, hearing aid use is associated with a risk of dementia of a similar level to that of people without hearing loss. With the postulation that up to 8% of dementia cases could be prevented with proper hearing loss management, our findings highlight the urgent need to take measures to address hearing loss to improve cognitive decline. National Natural Science Foundation of China and Shandong Province, Taishan Scholars Project, China Medical Board, and China Postdoctoral Science Foundation.