Explore the vast range of titles available.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder associated with abnormal protein modification, inflammation and memory impairment. Aggregated amyloid beta (Aβ) and phosphorylated tau proteins are medical diagnostic features. Loss of memory in AD has been associated with central cholinergic dysfunction in basal forebrain, from where the cholinergic circuitry projects to cerebral cortex and hippocampus. Various reports link AD progression with declining activity of cholinergic neurons in basal forebrain. The neurotrophic molecule, nerve growth factor (NGF), plays a major role in the maintenance of cholinergic neurons integrity and function, both during development and adulthood. Numerous studies have also shown that NGF contributes to the survival and regeneration of neurons during aging and in age-related diseases such as AD. Changes in neurotrophic signaling pathways are involved in the aging process and contribute to cholinergic and cognitive decline as observed in AD. Further, gradual dysregulation of neurotrophic factors like NGF and brain derived neurotrophic factor (BDNF) have been reported during AD development thus intensifying further research in targeting these factors as disease modifying therapies against AD. Today, there is no cure available for AD and the effects of the symptomatic treatment like cholinesterase inhibitors (ChEIs) and memantine are transient and moderate. Although many AD treatment studies are being carried out, there has not been any breakthrough and new therapies are thus highly needed. Long-term effective therapy for alleviating cognitive impairment is a major unmet need. Discussion and summarizing the new advancements of using NGF as a potential therapeutic implication in AD are important. In summary, the intent of this review is describing available experimental and clinical data related to AD therapy, priming to gain additional facts associated with the importance of NGF for AD treatment, and encapsulated cell biodelivery (ECB) as an efficient tool for NGF delivery.

The integrity of the cholinergic system plays a central role in cognitive decline both in normal aging and neurological disorders including Alzheimer’s disease and vascular cognitive impairment. Most of the previous neuroimaging research has focused on the integrity of the cholinergic basal forebrain, or its sub-region the nucleus basalis of Meynert (NBM). Tractography using diffusion tensor imaging data may enable modelling of the NBM white matter projections. We investigated the contribution of NBM volume, NBM white matter projections, small vessel disease (SVD), and age to performance in attention and memory in 262 cognitively normal individuals (39–77 years of age, 53% female). We developed a multimodal MRI pipeline for NBM segmentation and diffusion-based tracking of NBM white matter projections, and computed white matter hypointensities (WM-hypo) as a marker of SVD. We successfully tracked pathways that closely resemble the spatial layout of the cholinergic system as seen in previous post-mortem and DTI tractography studies. We found that high WM-hypo load was associated with older age, male sex, and lower performance in attention and memory. A high WM-hypo load was also associated with lower integrity of the cholinergic system above and beyond the effect of age. In a multivariate model, age and integrity of NBM white matter projections were stronger contributors than WM-hypo load and NBM volume to performance in attention and memory. We conclude that the integrity of NBM white matter projections plays a fundamental role in cognitive aging. This and other modern neuroimaging methods offer new opportunities to re-evaluate the cholinergic hypothesis of cognitive aging. [Display omitted] •Cholinergic pathways can be modelled in vivo with multimodal MRI.•Integrity of cholinergic pathways and age are strong contributors to cognition.•New opportunities emerge to re-evaluate the cholinergic hypothesis of aging.

Alzheimer's disease (AD) is the most prevalent form of dementia with symptoms of deteriorating cognitive functions and memory loss, partially as a result of a decrease in cholinergic neurotransmission. The disease is incurable and treatment with cholinesterase inhibitors (ChEIs) is symptomatic. Choline acetyltransferase (ChAT), the enzyme that synthesizes acetylcholine (ACh), has been proven recently to be present in both cerebrospinal fluid (CSF) and plasma. As ChAT plays a role in regulating the extracellular ACh levels, it may have an impact on prognosis and cognitive performance in AD patients. To measure ChAT activity and its protein concentration in CSF and plasma from patients with AD, mild cognitive impairment (MCI), or Subjective cognitive impairment (SCI). Plasma and CSF samples were obtained from 21 AD, 32 MCI, and 30 SCI patients. The activity and protein levels of ChAT and acetylcholinesterase (AChE), the enzyme catalyzing the hydrolysis of ACh, were analyzed using an integrated activity and protein concentration ELISA-like assay. A Cholinergic Index was calculated as the ratio of ChAT to AChE activities in CSF. The data were analyzed in relation to dementia biomarkers and cognitive performance of the patients. The CSF ChAT activity was significantly higher (55-67%) in MCI patients compared to AD and SCI cases. The CSF Cholinergic Index was 41 and 22% lower in AD patients than in MCI and SCI subjects, respectively. This index correlated positively with the Aβ /p-tau ratio in CSF in SCI but negatively with that in AD and MCI. The ChAT activity and protein levels in plasma exhibited significant differences with the pattern of AD>> >SCI. This is the first study investigating soluble levels of the key cholinergic enzyme, ChAT, in both plasma and CSF of individuals at different clinical stages of dementia. Although further validation is needed, the overall pattern of the results suggests that in the continuum of AD, the cholinergic signaling exhibits an inverse U-shape dynamic of changes in the brain that greatly differs from the changes observed in the plasma compartment.

Machine learning (ML) could have advantages over traditional statistical models in identifying risk factors. Using ML algorithms, our objective was to identify the most important variables associated with mortality after dementia diagnosis in the Swedish Registry for Cognitive/Dementia Disorders (SveDem). From SveDem, a longitudinal cohort of 28,023 dementia-diagnosed patients was selected for this study. Sixty variables were considered as potential predictors of mortality risk, such as age at dementia diagnosis, dementia type, sex, body mass index (BMI), mini-mental state examination (MMSE) score, time from referral to initiation of work-up, time from initiation of work-up to diagnosis, dementia medications, comorbidities, and some specific medications for chronic comorbidities (e.g., cardiovascular disease). We applied sparsity-inducing penalties for three ML algorithms and identified twenty important variables for the binary classification task in mortality risk prediction and fifteen variables to predict time to death. Area-under-ROC curve (AUC) measure was used to evaluate the classification algorithms. Then, an unsupervised clustering algorithm was applied on the set of twenty-selected variables to find two main clusters which accurately matched surviving and dead patient clusters. A support-vector-machines with an appropriate sparsity penalty provided the classification of mortality risk with accuracy = 0.7077, AUROC = 0.7375, sensitivity = 0.6436, and specificity = 0.740. Across three ML algorithms, the majority of the identified twenty variables were compatible with literature and with our previous studies on SveDem. We also found new variables which were not previously reported in literature as associated with mortality in dementia. Performance of basic dementia diagnostic work-up, time from referral to initiation of work-up, and time from initiation of work-up to diagnosis were found to be elements of the diagnostic process identified by the ML algorithms. The median follow-up time was 1053 (IQR = 516–1771) days in surviving and 1125 (IQR = 605–1770) days in dead patients. For prediction of time to death, the CoxBoost model identified 15 variables and classified them in order of importance. These highly important variables were age at diagnosis, MMSE score, sex, BMI, and Charlson Comorbidity Index with selection scores of 23%, 15%, 14%, 12% and 10%, respectively. This study demonstrates the potential of sparsity-inducing ML algorithms in improving our understanding of mortality risk factors in dementia patients and their application in clinical settings. Moreover, ML methods can be used as a complement to traditional statistical methods.

The Swedish Dementia Registry (SveDem) was developed with the aim to improve the quality of diagnostic work-up, treatment and care of patients with dementia disorders in Sweden. SveDem is an internet based quality registry where several indicators can be followed over time. It includes information about the diagnostic work-up, medical treatment and community support (www.svedem.se). The patients are diagnosed and followed-up yearly in specialist units, primary care centres or in nursing homes. The database was initiated in May 2007 and covers almost all of Sweden. There were 28 722 patients registered with a mean age of 79.3 years during 2007-2012. Each participating unit obtains continuous online statistics from its own registrations and they can be compared with regional and national data. A report from SveDem is published yearly to inform medical and care professionals as well as political and administrative decision-makers about the current quality of diagnostics, treatment and care of patients with dementia disorders in Sweden. SveDem provides knowledge about current dementia care in Sweden and serves as a framework for ensuring the quality of diagnostics, treatment and care across the country. It also reflects changes in quality dementia care over time. Data from SveDem can be used to further develop the national guidelines for dementia and to generate new research hypotheses.

Background Drugs with anticholinergic properties are commonly used in older adults for various medical conditions, but the long-term cardiovascular consequences of cumulative exposure have not been well established. This study aims to examine whether cumulative anticholinergic drug burden is associated with incident cardiovascular events. Methods The large population-based cohort study included 508,273 Stockholm residents aged ≥ 45 years on January 1, 2008, who had no history of major cardiovascular diseases, with follow-up until December 31, 2021. Anticholinergic burden was assessed using the Anticholinergic Cognitive Burden scale and quantified as annual consumption in defined daily doses (DDDs). Inverse probability-weighted Cox proportional hazards models were used to estimate the weighted hazard ratio (HR) and 95% confidence interval (CI) for the associations between both baseline and time-varying exposure and incident cardiovascular events, overall and by disease subtypes. Results A total of 118,266 incident cardiovascular events were recorded during a median follow-up of 14.0 years. Higher levels of anticholinergic drug exposure were significantly associated with an increased risk of cardiovascular events after adjusting for sociodemographic, lifestyle, and clinical risk factors in both baseline and time-updated models, with stronger associations observed in the latter. In the time-updated model, the HR (95% CI) increased with annual cumulative exposure: 1.16 (1.13, 1.20) for 1–89 DDDs, 1.31 (1.28, 1.34) for 90–364 DDDs, and 1.71 (1.67, 1.76) for ≥ 365 DDDs. A significant dose–response relationship was observed across event subtypes. In the highest exposure group, the HR (95% CI) was 2.70 (2.57, 2.84) for heart failure, 2.17 (2.08, 2.27) for arrhythmias, 1.48 (1.34, 1.63) for artery disease, 1.32 (1.21, 1.43) for venous thromboembolism, 1.46 (1.37, 1.55) for myocardial infarction, and 1.32 (1.25, 1.39) for cerebrovascular disease. Results were consistent in subgroups and sensitivity analyses. Conclusions These findings highlight the potential cardiovascular harms of anticholinergic drug burden in middle-aged and older adults and underscore the need for careful prescribing and monitoring of such medications.

Introduction There is a growing body of evidence that subtle deficits in instrumental activities of daily living (IADL) may be present in mild cognitive impairment (MCI). However, it is not clear if there are IADL domains that are consistently affected across patients with MCI. In this systematic review, therefore, we aimed to summarize research results regarding the performance of MCI patients in specific IADL (sub)domains compared with persons who are cognitively normal and/or patients with dementia. Methods The databases PsycINFO, PubMed and Web of Science were searched for relevant literature in December 2013. Publications from 1999 onward were considered for inclusion. Altogether, 497 articles were retrieved. Reference lists of selected articles were searched for potentially relevant articles. After screening the abstracts of these 497 articles, 37 articles were included in this review. Results In 35 studies, IADL deficits (such as problems with medication intake, telephone use, keeping appointments, finding things at home and using everyday technology) were documented in patients with MCI. Financial capacity in patients with MCI was affected in the majority of studies. Effect sizes for group differences between patients with MCI and healthy controls were predominantly moderate to large. Performance-based instruments showed slight advantages (in terms of effect sizes) in detecting group differences in IADL functioning between patients with MCI, patients with Alzheimer’s disease and healthy controls. Conclusion IADL requiring higher neuropsychological functioning seem to be most severely affected in patients with MCI. A reliable identification of such deficits is necessary, as patients with MCI with IADL deficits seem to have a higher risk of converting to dementia than patients with MCI without IADL deficits. The use of assessment tools specifically designed and validated for patients with MCI is therefore strongly recommended. Furthermore, the development of performance-based assessment instruments should be intensified, as they allow a valid and reliable assessment of subtle IADL deficits in MCI, even if a proxy is not available. Another important point to consider when designing new scales is the inclusion of technology-associated IADL. Novel instruments for clinical practice should be time-efficient and easy to administer.

Background Dementia is associated with psychiatric symptoms but the effects of antidepressants on cognitive function in dementia are understudied. We aimed to investigate the association between antidepressants and cognitive decline in patients with dementia, and the risk of severe dementia, fractures and death, depending on antidepressant class, drug, and dose. Methods This is a national cohort study. Patients with dementia registered in the Swedish Registry for Cognitive/Dementia Disorders-SveDem from May 1, 2007, until October 16, 2018, with at least one follow-up after dementia diagnosis, and who were new users of antidepressants, were included. Antidepressant use as a time varying exposure defined during the 6 months leading up to dementia diagnosis or each subsequent follow-up. We used linear mixed models to examine the association between antidepressant use and cognitive trajectories assessed by Mini-Mental State Examination (MMSE) scores. We used Cox proportional hazards models to calculate the hazard ratios for severe dementia (MMSE score < 10), fracture, and death. We compared antidepressant classes and drugs, and analyzed dose–response. Results We included 18740 patients (10 205 women [54.5%]; mean [SD] age, 78.2[7.4] years), of which 4271 (22.8%) received at least one prescription for an antidepressant. During follow-up, a total of 11912 prescriptions for antidepressants were issued, with selective serotonin reuptake inhibitors (SSRI) being the most common (64.8%). Antidepressant use was associated with faster cognitive decline ( β (95% CI) = − 0.30(− 0.39, − 0.21) points/year), in particular sertraline (− 0.25(− 0.43, − 0.06) points/year), citalopram (− 0.41(− 0.55, − 0.27) points/year), escitalopram (− 0.76(− 1.09, − 0.44) points/year), and mirtazapine (− 0.19(− 0.34, − 0.04) points/year) compared with non-use. The association was stronger in patients with severe dementia (initial MMSE scores 0–9). Escitalopram showed a greater decline rate than sertraline. Compared with non-use, dose response of SSRIs on greater cognitive decline and higher risks of severe dementia, all-cause mortality, and fracture were observed. Conclusions In this cohort study, current antidepressant use was associated with faster cognitive decline; furthermore, higher dispensed doses of SSRIs were associated with higher risk for severe dementia, fractures, and all-cause mortality. These findings highlight the significance of careful and regular monitoring to assess the risks and benefits of different antidepressants use in patients with dementia.

Background Alzheimer’s disease (AD) and mixed dementia (MxD) represent major public health concerns, yet there is limited real-world evidence on the long-term associations of commonly prescribed pharmacological treatments, particularly cholinesterase inhibitors (ChEIs) and their combination with memantine. This study aims to evaluate the long-term, time-varying associations of ChEIs and memantine on cognitive decline in a large, nationwide cohort of individuals diagnosed with AD or MxD. Methods This observational study utilized data from the Swedish registry for cognitive/dementia disorders (SveDem), analyzing 32,282 individuals diagnosed with AD or MxD between 2007 and 2022. Patients were followed for up to 11 years to track treatment patterns and cognitive trajectories. Initiation of ChEIs (donepezil, galantamine, or rivastigmine) or memantine within six months after an AD or MxD diagnosis and then the time-varying medications (ChEIs alone, memantine alone or memantine added on to ChEIs) within six months after each follow-up were analyzed. Linear mixed-effects model was used to assess cognitive decline measured by Mini-Mental State Examination (MMSE) score trajectories. Results Of the 32,282 participants (mean age 78.4 years; 61% women), 78.4% initiated treatment with ChEIs alone, and 21.6% with memantine alone. Over time, prescription patterns shifted from monotherapy to combination therapy, with donepezil and galantamine more likely to achieve 1 Defined Daily Dosages (DDD) than rivastigmine users. Memantine alone users experienced a yearly cognitive decline of 1.79 MMSE points (95% CI: −1.85, −1.73). Compared with memantine users, patients on ChEIs alone declined 0.65 points less per year (95% CI: −0.59, −0.72), while those on combination therapy declined 0.19 points less per year (95% CI: −0.10, −0.28). Among ChEIs, donepezil users experienced an annual decline of 1.02 points (95% CI: −1.06, −0.98). In comparison, galantamine users declined an additional 0.05 points per year (95% CI: −0.11, 0.01), and rivastigmine users declined an additional 0.17 points per year (95% CI: −0.24, −0.11), relative to donepezil. Conclusions In this large cohort of patients with AD or MxD, ChEIs users alone, particularly donepezil and galantamine, showed slower cognitive decline compared to users of memantine or combination therapy users. While differences were modest, the results contribute to a better understanding of treatment trajectories in routine clinical practice.

Background Disturbances in brain cholesterol homeostasis may be involved in the pathogenesis of Alzheimer’s disease (AD). Lipid-lowering medications could interfere with neurodegenerative processes in AD through cholesterol metabolism or other mechanisms. Objective To explore the association between the use of lipid-lowering medications and cognitive decline over time in a cohort of patients with AD or mixed dementia with indication for lipid-lowering treatment. Methods A longitudinal cohort study using the Swedish Registry for Cognitive/Dementia Disorders, linked with other Swedish national registries. Cognitive trajectories evaluated with mini-mental state examination (MMSE) were compared between statin users and non-users, individual statin users, groups of statins and non-statin lipid-lowering medications using mixed-effect regression models with inverse probability of drop out weighting. A dose-response analysis included statin users compared to non-users. Results Our cohort consisted of 15,586 patients with mean age of 79.5 years at diagnosis and a majority of women (59.2 %). A dose-response effect was demonstrated: taking one defined daily dose of statins on average was associated with 0.63 more MMSE points after 3 years compared to no use of statins (95% CI: 0.33;0.94). Simvastatin users showed 1.01 more MMSE points (95% CI: 0.06;1.97) after 3 years compared to atorvastatin users. Younger (< 79.5 years at index date) simvastatin users had 0.80 more MMSE points compared to younger atorvastatin users (95% CI: 0.05;1.55) after 3 years. Simvastatin users had 1.03 more MMSE points (95% CI: 0.26;1.80) compared to rosuvastatin users after 3 years. No differences regarding statin lipophilicity were observed. The results of sensitivity analysis restricted to incident users were not consistent. Conclusions Some patients with AD or mixed dementia with indication for lipid-lowering medication may benefit cognitively from statin treatment; however, further research is needed to clarify the findings of sensitivity analyses.