Platelet Function Is Associated With Dementia Risk in the Framingham Heart Study

Antidepressant exposure and long-term dementia risk in a nationwide retrospective study on US veterans with midlife major depressive disorder

INTRODUCTION

The use of antidepressants in major depressive disorder (MDD) has been reported to influence long-term risk of Alzheimer's disease (AD) and AD-related dementias (AD/ADRD), but studies are conflicting.

METHODS

We used inverse probability weighted (IPW) Cox models with time-varying covariates in a retrospective cohort study among midlife veterans with MDD within the US Veterans Affairs healthcare system from January 1, 2000 to June 1, 2022.

RESULTS

A total of 35,200 patients with MDD were identified. No associations were seen regarding the effect of being exposed to any antidepressant versus no exposure on AD/ADRD risk (events = 1,056, hazard ratio = 0.94, 95% confidence interval: 0.81 to 1.09) or the exposure to specific antidepressant classes versus no exposure. A risk reduction was observed for female patients in a stratified analysis; however, the number of cases was small.

DISCUSSION

Our study suggests that antidepressant exposure has no effect on AD/ADRD risk. The association in female patients should be interpreted with caution and requires further attention.

HIGHLIGHTS

We studied whether antidepressant use was associated with future dementia risk. We specifically focused on patients after their first-ever diagnosis of depression. We used IPW Cox models with time-varying covariates and a large observation window. Our study did not identify an effect of antidepressant use on dementia risk. A risk reduction was observed in female patients, but the number of cases was small.

Potential links between platelets and amyloid-β in the pathogenesis of Alzheimer's disease: Evidence from in vitro, in vivo, and clinical studies

Cerebral amyloid angiopathy (CAA) is a prevalent comorbidity among patients with Alzheimer's disease (AD), present in up to 80% of cases with varying levels of severity. There is evidence to suggest that CAA might intensify cognitive deterioration in AD patients, thereby accelerating the development of AD pathology. As a source of amyloids, it has been postulated that platelets play a significant role in the pathogenesis of both AD and CAA. Although several studies have demonstrated that platelet activation plays an important role in the pathogenesis of AD and CAA, a clear understanding of the mechanisms involved in the three steps: platelet activation, platelet adhesion, and platelet aggregation in AD pathogenesis still remains elusive. Moreover, potential therapeutic targets in platelet-mediated AD pathogenesis have not been explicitly addressed. Therefore, the aim of this review is to collate and discuss the in vitro, in vivo, and clinical evidence related to platelet dysfunction, including associated activation, adhesion, and aggregation, with specific reference to amyloid-related AD pathogenesis. Potential therapeutic targets of platelet-mediated AD pathogenesis are also discussed. By enriching the understanding of the intricate relationship between platelet dysfunction and onset of AD, researchers may unveil new therapeutic targets or strategies to tackle this devastating neurodegeneration.

Myeloid cells in vascular dementia and Alzheimer's disease: Possible therapeutic targets?

Growing evidence supports the suggestion that the peripheral immune system plays a role in different pathologies associated with cognitive impairment, such as vascular dementia (VD) or Alzheimer's disease (AD). The aim of this review is to summarize, within the peripheral immune system, the implications of different types of myeloid cells in AD and VD, with a special focus on post-stroke cognitive impairment and dementia (PSCID). We will review the contributions of the myeloid lineage, from peripheral cells (neutrophils, platelets, monocytes and monocyte-derived macrophages) to central nervous system (CNS)-associated cells (perivascular macrophages and microglia). Finally, we will evaluate different potential strategies for pharmacological modulation of pathological processes mediated by myeloid cell subsets, with an emphasis on neutrophils, their interaction with platelets and the process of immunothrombosis that triggers neutrophil-dependent capillary stall and hypoperfusion, as possible effector mechanisms that may pave the way to novel therapeutic avenues to stop dementia, the epidemic of our time. LINKED ARTICLES: This article is part of a themed issue From Alzheimer's Disease to Vascular Dementia: Different Roads Leading to Cognitive Decline. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v181.6/issuetoc.

Chronic inflammation, neuroglial dysfunction, and plasmalogen deficiency as a new pathobiological hypothesis addressing the overlap between post-COVID-19 symptoms and myalgic encephalomyelitis/chronic fatigue syndrome

After five waves of coronavirus disease 2019 (COVID-19) outbreaks, it has been recognized that a significant portion of the affected individuals developed long-term debilitating symptoms marked by chronic fatigue, cognitive difficulties ("brain fog"), post-exertional malaise, and autonomic dysfunction. The onset, progression, and clinical presentation of this condition, generically named post-COVID-19 syndrome, overlap significantly with another enigmatic condition, referred to as myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Several pathobiological mechanisms have been proposed for ME/CFS, including redox imbalance, systemic and central nervous system inflammation, and mitochondrial dysfunction. Chronic inflammation and glial pathological reactivity are common hallmarks of several neurodegenerative and neuropsychiatric disorders and have been consistently associated with reduced central and peripheral levels of plasmalogens, one of the major phospholipid components of cell membranes with several homeostatic functions. Of great interest, recent evidence revealed a significant reduction of plasmalogen contents, biosynthesis, and metabolism in ME/CFS and acute COVID-19, with a strong association to symptom severity and other relevant clinical outcomes. These bioactive lipids have increasingly attracted attention due to their reduced levels representing a common pathophysiological manifestation between several disorders associated with aging and chronic inflammation. However, alterations in plasmalogen levels or their lipidic metabolism have not yet been examined in individuals suffering from post-COVID-19 symptoms. Here, we proposed a pathobiological model for post-COVID-19 and ME/CFS based on their common inflammation and dysfunctional glial reactivity, and highlighted the emerging implications of plasmalogen deficiency in the underlying mechanisms. Along with the promising outcomes of plasmalogen replacement therapy (PRT) for various neurodegenerative/neuropsychiatric disorders, we sought to propose PRT as a simple, effective, and safe strategy for the potential relief of the debilitating symptoms associated with ME/CFS and post-COVID-19 syndrome.

Platelet Membrane Proteins as Pain Biomarkers in Patients with Severe Dementia

Pain is one of the most frequent health problems, and its evaluation and therapeutic approach largely depend on patient self-report. When it is not possible to obtain a self-report, the therapeutic decision becomes more difficult and limited. This study aims to evaluate whether some membrane platelet proteins could be of value in pain characterization. To achieve this goal, we used 53 blood samples obtained from palliative patients, 44 with non-oncological pain and nine without pain. We observed in patients with pain a decrease in the percentage of platelets expressing CD36, CD49f, and CD61 and in the expression levels of CD49f and CD61 when compared with patients without pain. Besides that, an increase in the percentage of platelets expressing CD62p was observed in patients with pain. These results suggest that the levels of these platelet cluster differentiations (CDs) could have some value as pain biomarkers objectively since they are not dependent on the patient's participation. Likewise, CD40 seems to have some importance as a biomarker of moderate and/or severe pain. The identification of pain biomarkers such as CD40, CD49f, CD62p and CD61 can lead to an adjustment of the therapeutic strategy, contributing to a faster and more adequate control of pain and reduction in patient-associated suffering.

Platelet Activation and Alzheimer’s Disease: The Probable Role of PI3K/AKT Pathway

In recent years, the association between the activity of platelets and risk of Alzheimer’s disease (AD) risk has been noticed in numerous studies. However, there in no investigations on the role of specific intracellular pathways to explain this connection. The phosphatidylinositol 3 kinase (PI3K)/AKT pathway is one of the main regulators of cell survival which regulates cellular responses to environmental changes. This pathway also regulates the activity of platelets, and its aberrant activity has been linked to platelet dysfunction in different pathologies. On the other hand, the PI3K/AKT pathway regulates amyloid-β (Aβ) production through regulation of amyloid-β protein precursor (AβPP), BACE-1, ADAMs, and γ-secretase. In addition, alterations in the activity of all of these factors in platelets has been shown in AD-related pathologies. Therefore, this paper aims to introduce the PI3K/AKT pathway as a molecular inducer of platelet dysfunction during aging and AD progression.

An Intelligent Learning System for Unbiased Prediction of Dementia Based on Autoencoder and Adaboost Ensemble Learning

Dementia is a neurological condition that primarily affects older adults and there is still no cure or therapy available to cure it. The symptoms of dementia can appear as early as 10 years before the beginning of actual diagnosed dementia. Hence, machine learning (ML) researchers have presented several methods for early detection of dementia based on symptoms. However, these techniques suffer from two major flaws. The first issue is the bias of ML models caused by imbalanced classes in the dataset. Past research did not address this issue well and did not take preventative precautions. Different ML models were developed to illustrate this bias. To alleviate the problem of bias, we deployed a synthetic minority oversampling technique (SMOTE) to balance the training process of the proposed ML model. The second issue is the poor classification accuracy of ML models, which leads to a limited clinical significance. To improve dementia prediction accuracy, we proposed an intelligent learning system that is a hybrid of an autoencoder and adaptive boost model. The autoencoder is used to extract relevant features from the feature space and the Adaboost model is deployed for the classification of dementia by using an extracted subset of features. The hyperparameters of the Adaboost model are fine-tuned using a grid search algorithm. Experimental findings reveal that the suggested learning system outperforms eleven similar systems which were proposed in the literature. Furthermore, it was also observed that the proposed learning system improves the strength of the conventional Adaboost model by 9.8% and reduces its time complexity. Lastly, the proposed learning system achieved classification accuracy of 90.23%, sensitivity of 98.00% and specificity of 96.65%.