Sex Differences in Dementia

Does acute aerobic exercise enhance selective attention, working memory, and problem-solving abilities in Alzheimer's patients? A sex-based comparative study

Introduction

The present study aimed to evaluate the effect of acute aerobic exercise on certain cognitive functions known to be affected by Alzheimer's disease (AD), with a particular emphasis on sex differences.

Methods

A total of 53 patients, with a mean age of 70.54 ± 0.88 years and moderate AD, voluntarily participated in the study. Participants were randomly assigned to two groups: the experimental group (EG), which participated in a 20-min moderate-intensity cycling session (60% of the individual maximum target heart rate recorded at the end of the 6-min walk test); and the control group (CG), which participated in a 20-min reading activity. Cognitive abilities were assessed before and after the physical exercise or reading session using the Stroop test for selective attention, the forward and backward digit span test for working memory, and the Tower of Hanoi task for problem-solving abilities.

Results

At baseline, both groups had comparable cognitive performance (p > 0.05 in all tests). Regardless of sex, aerobic acute exercise improved attention in the Stroop test (p < 0.001), enhanced memory performance in both forward (p < 0.001) and backward (p < 0.001) conditions, and reduced the time required to solve the problem in the Tower of Hanoi task (p < 0.001). No significant differences were observed in the number of movements. In contrast, the CG did not significantly improve after the reading session for any of the cognitive tasks (p > 0.05). Consequently, the EG recorded greater performance improvements than the CG in most cognitive tasks tested (p < 0.0001) after the intervention session.

Discussion

These findings demonstrate that, irrespective to sex, a single aerobic exercise session on an ergocycle can improve cognitive function in patients with moderate AD. The results suggest that acute aerobic exercise enhances cognitive function similarly in both female and male patients, indicating promising directions for inclusive therapeutic strategies.

Predictive Models for the Transition from Mild Neurocognitive Disorder to Major Neurocognitive Disorder: Insights from Clinical, Demographic, and Neuropsychological Data

Neurocognitive disorders (NCDs) are progressive conditions that severely impact cognitive function and daily living. Understanding the transition from mild to major NCD is crucial for personalized early intervention and effective management. Predictive models incorporating demographic variables, clinical data, and scores on neuropsychological and emotional tests can significantly enhance early detection and intervention strategies in primary healthcare settings. We aimed to develop and validate predictive models for the progression from mild NCD to major NCD using demographic, clinical, and neuropsychological data from 132 participants over a two-year period. Generalized Estimating Equations were employed for data analysis. Our final model achieved an accuracy of 83.7%. A higher body mass index and alcohol drinking increased the risk of progression from mild NCD to major NCD, while female sex, higher praxis abilities, and a higher score on the Geriatric Depression Scale reduced the risk. Here, we show that integrating multiple factors-ones that can be easily examined in clinical settings-into predictive models can improve early diagnosis of major NCD. This approach could facilitate timely interventions, potentially mitigating the progression of cognitive decline and improving patient outcomes in primary healthcare settings. Further research should focus on validating these models across diverse populations and exploring their implementation in various clinical contexts.

Integrating Demographics and Imaging Features for Various Stages of Dementia Classification: Feed Forward Neural Network Multi-Class Approach

BACKGROUND

MRI magnetization-prepared rapid acquisition (MPRAGE) is an easily available imaging modality for dementia diagnosis. Previous studies suggested that volumetric analysis plays a crucial role in various stages of dementia classification. In this study, volumetry, radiomics and demographics were integrated as inputs to develop an artificial intelligence model for various stages, including Alzheimer's disease (AD), mild cognitive decline (MCI) and cognitive normal (CN) dementia classifications.

METHOD

The Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset was separated into training and testing groups, and the Open Access Series of Imaging Studies (OASIS) dataset was used as the second testing group. The MRI MPRAGE image was reoriented via statistical parametric mapping (SPM12). Freesurfer was employed for brain segmentation, and 45 regional brain volumes were retrieved. The 3D Slicer software was employed for 107 radiomics feature extractions from within the whole brain. Data on patient demographics were collected from the datasets. The feed-forward neural network (FFNN) and the other most common artificial intelligence algorithms, including support vector machine (SVM), ensemble classifier (EC) and decision tree (DT), were used to build the models using various features.

RESULTS

The integration of brain regional volumes, radiomics and patient demographics attained the highest overall accuracy at 76.57% and 73.14% in ADNI and OASIS testing, respectively. The subclass accuracies in MCI, AD and CN were 78.29%, 89.71% and 85.14%, respectively, in ADNI testing, as well as 74.86%, 88% and 83.43% in OASIS testing. Balanced sensitivity and specificity were obtained for all subclass classifications in MCI, AD and CN.

CONCLUSION

The FFNN yielded good overall accuracy for MCI, AD and CN categorization, with balanced subclass accuracy, sensitivity and specificity. The proposed FFNN model is simple, and it may support the triage of patients for further confirmation of the diagnosis.

The Heterogeneity of Post-Menopausal Disease Risk: Could the Basis for Why Only Subsets of Females Are Affected Be Due to a Reversible Epigenetic Modification System Associated with Puberty, Menstrual Cycles, Pregnancy and Lactation, and, Ultimately, Menopause?

For much of human evolution, the average lifespan was <40 years, due in part to disease, infant mortality, predators, food insecurity, and, for females, complications of childbirth. Thus, for much of evolution, many females did not reach the age of menopause (45-50 years of age) and it is mainly in the past several hundred years that the lifespan has been extended to >75 years, primarily due to public health advances, medical interventions, antibiotics, and nutrition. Therefore, the underlying biological mechanisms responsible for disease risk following menopause must have evolved during the complex processes leading to Homo sapiens to serve functions in the pre-menopausal state. Furthermore, as a primary function for the survival of the species is effective reproduction, it is likely that most of the advantages of having such post-menopausal risks relate to reproduction and the ability to address environmental stresses. This opinion/perspective will be discussed in the context of how such post-menopausal risks could enhance reproduction, with improved survival of offspring, and perhaps why such risks are preserved. Not all post-menopausal females exhibit risk for this set of diseases, and those who do develop such diseases do not have all of the conditions. The diseases of the post-menopausal state do not operate as a unified complex, but as independent variables, with the potential for some overlap. The how and why there would be such heterogeneity if the risk factors serve essential functions during the reproductive years is also discussed and the concept of sets of reversible epigenetic changes associated with puberty, pregnancy, and lactation is offered to explain the observations regarding the distribution of post-menopausal conditions and their potential roles in reproduction. While the involvement of an epigenetic system with a dynamic "modification-demodification-remodification" paradigm contributing to disease risk is a hypothesis at this point, validation of it could lead to a better understanding of post-menopausal disease risk in the context of reproduction with commonalities may also lead to future improved interventions to control such risk after menopause.

Association between serum lipoprotein(a) and mildly reduced eGFR: a cross-sectional study

Lipoprotein(a) [Lp(a)] is a risk factor for cardiovascular disease (CVD) and aortic stenosis. However, the data on the relationship between Lp(a) and mildly reduced estimated glomerular filtration rate (eGFR) has been disputed. This study was conducted to assess the relationship between Lp(a) concentrations and mildly reduced eGFR in healthy subjects.This community-based, cross-sectional study enrolled 1,064 volunteers aged ≥ 40 years who lived in Yonghong Community, Zhonglou District, Changzhou, China, between December 2016 and December 2017. A mildly reduced eGFR was defined as eGFR between 60 and 90 mL/min/1.73m2. A standardized questionnaire and biochemical measurements were used to gather information about participants. The serum concentration of Lp(a) was determined using the latex-enhanced immunoturbidimetric test. Of the total study population, 34.8% (n = 370) were men, and the mean age was 66.8 ± 8.5 years. A significant association existed between Lp(a) levels and the risk of mildly reduced eGFR. Individuals with the highest tertile of Lp(a) had higher odds of mildly reduced eGFR after adjusting for various confounders (adjusted odds ratio [OR]: 1.80, 95% confidence interval [CI]: 1.24-2.60, P = 0.0025) compared to those with the lowest tertile of Lp(a). Multivariable logistic regression of studies in which Lp(a) was presented as continuous variables showed consistent results (adjusted OR: 1.23 for 1-SD increment of Ln-Lp(a), 95% CI: 1.05-1.43). Subgroup analyses showed that study characteristics such as age, sex, obesity, diabetes, and hypertension status did not significantly affect the association (P for all interactions > 0.05). These results suggest that higher serum Lp(a) level was an independent risk factor for mildly reduced eGFR.

Nicotinic acetylcholine receptors and learning and memory deficits in Neuroinflammatory diseases

Animal survival depends on cognitive abilities such as learning and memory to adapt to environmental changes. Memory functions require an enhanced activity and connectivity of a particular arrangement of engram neurons, supported by the concerted action of neurons, glia, and vascular cells. The deterioration of the cholinergic system is a common occurrence in neurological conditions exacerbated by aging such as traumatic brain injury (TBI), posttraumatic stress disorder (PTSD), Alzheimer's disease (AD), and Parkinson's disease (PD). Cotinine is a cholinergic modulator with neuroprotective, antidepressant, anti-inflammatory, antioxidant, and memory-enhancing effects. Current evidence suggests Cotinine's beneficial effects on cognition results from the positive modulation of the α7-nicotinic acetylcholine receptors (nAChRs) and the inhibition of the toll-like receptors (TLRs). The α7nAChR affects brain functions by modulating the function of neurons, glia, endothelial, immune, and dendritic cells and regulates inhibitory and excitatory neurotransmission throughout the GABA interneurons. In addition, Cotinine acting on the α7 nAChRs and TLR reduces neuroinflammation by inhibiting the release of pro-inflammatory cytokines by the immune cells. Also, α7nAChRs stimulate signaling pathways supporting structural, biochemical, electrochemical, and cellular changes in the Central nervous system during the cognitive processes, including Neurogenesis. Here, the mechanisms of memory formation as well as potential mechanisms of action of Cotinine on memory preservation in aging and neurological diseases are discussed.

Complexity of Sex Differences and Their Impact on Alzheimer's Disease

Sex differences are present in brain morphology, sex hormones, aging processes and immune responses. These differences need to be considered for proper modelling of neurological diseases with clear sex differences. This is the case for Alzheimer's disease (AD), a fatal neurodegenerative disorder with two-thirds of cases diagnosed in women. It is becoming clear that there is a complex interplay between the immune system, sex hormones and AD. Microglia are major players in the neuroinflammatory process occurring in AD and have been shown to be directly affected by sex hormones. However, many unanswered questions remain as the importance of including both sexes in research studies has only recently started receiving attention. In this review, we provide a summary of sex differences and their implications in AD, with a focus on microglia action. Furthermore, we discuss current available study models, including emerging complex microfluidic and 3D cellular models and their usefulness for studying hormonal effects in this disease.

The APOE-TOMM40 Humanized Mouse Model: Characterization of Age, Sex, and PolyT Variant Effects on Gene Expression

BACKGROUND

The human chromosome 19q13.32 is a gene rich region and has been associated with multiple phenotypes, including late onset Alzheimer's disease (LOAD) and other age-related conditions.

OBJECTIVE

Here we developed the first humanized mouse model that contains the entire TOMM40 and APOE genes with all intronic and intergenic sequences including the upstream and downstream regions. Thus, the mouse model carries the human TOMM40 and APOE genes and their intact regulatory sequences.

METHODS

We generated the APOE-TOMM40 humanized mouse model in which the entire mouse region was replaced with the human (h)APOE-TOMM40 loci including their upstream and downstream flanking regulatory sequences using recombineering technologies. We then measured the expression of the human TOMM40 and APOE genes in the mice brain, liver, and spleen tissues using TaqMan based mRNA expression assays.

RESULTS

We investigated the effects of the '523' polyT genotype (S/S or VL/VL), sex, and age on the human TOMM40- and APOE-mRNAs expression levels using our new humanized mouse model. The analysis revealed tissue specific and shared effects of the '523' polyT genotype, sex, and age on the regulation of the human TOMM40 and APOE genes. Noteworthy, the regulatory effect of the '523' polyT genotype was observed for all studied organs.

CONCLUSION

The model offers new opportunities for basic science, translational, and preclinical drug discovery studies focused on the APOE genomic region in relation to LOAD and other conditions in adulthood.