Altered Cerebral Blood Flow in Alzheimer's Disease With Depression

Transient Changes in Cerebral Tissue Oxygen, Glucose, and Temperature by Microstrokes: A Computational Study

OBJECTIVE

This study focuses on evaluating the disruptions in key physiological parameters during microstroke events to assess their severity.

METHODS

A mathematical model was developed to simulate the changes in cerebral tissue pO2, glucose concentration, and temperature due to blood flow interruptions. The model considers variations in baseline cerebral blood flow (CBF), capillary density, and blood oxygen/glucose levels, as well as ambient temperature changes.

RESULTS

Simulations indicate that complete blood flow obstruction still allows for limited glucose availability, supporting nonoxidative metabolism and potentially exacerbating lactate buildup and acidosis. Partial obstructions decrease tissue pO2, with minimal impact on glucose level, which can remain almost unchanged or even slightly increase. Reduced CBF, capillary density, or blood oxygen due to aging or disease enhances hypoxia risk at lower obstruction levels, with capillary density having a significant effect on stroke severity by influencing both pO2 and glucose levels. Conditions could lead to co-occurrence of hypoxia/hypoglycemia or hypoxia/hyperglycemia, each worsening outcomes. Temperature effects were minimal in deep brain regions but varied near the skull by 0.2-0.8°C depending on ambient temperature.

CONCLUSIONS

The model provides insights into the conditions driving severe stroke outcomes based on estimated levels of hypoxia, hypoglycemia, hyperglycemia, and temperature changes.

Sex-dependent changes in emotional memory associated with cerebral blood flow alterations during Alzheimer's disease progression

PURPOSE

Sex differences in Alzheimer's disease (AD) progression provide clues to pathogenesis and better patient management. We examined sex differences in emotional memory among AD patients, amnestic mild cognitive impairment (aMCI) patients, and healthy controls (HCs) as well as potential associations with altered regional cerebral blood flow (rCBF).

METHODS

The recognition memory task with emotional pictures was applied to evaluate enhancement of emotional memory (EEM) and 3D pseudo-continuous arterial spin labeling MRI was performed to measure the rCBF in 74 AD patients (41 females), 74 aMCI patients (45 females), and 74 HCs (43 females). Group differences in EEM were tested by two-way analysis of covariance (ANCOVA) with repeated measures. The main effects of clinical group and sex as well as group × sex interactions on rCBF were assessed by two-way ANCOVA. Correlation analyses were conducted to investigate associations between EEM and rCBF.

RESULTS

With disease progression, EEM gradually disappeared. Among aMCI patients, females exhibited a greater index of recollection (Pr) for positive/high-arousal and negative/low-arousal pictures versus neutral pictures (P = 0.005, P = 0.003), while males exhibited a greater Pr for negative/high-arousal versus neutral pictures (P = 0.001). There were significant sex × group effects on rCBF in left inferior parietal, supramarginal, superior temporal and middle temporal gyri, and rCBF of left inferior parietal gyrus was correlated with Pr for positive/high-arousal pictures among female aMCI patients (r = 0.584, q = 0.005).

CONCLUSION

Males and females exhibit distinct changes in EEM associated with altered rCBF, which should be considered in future neuroimaging studies.

Reduced cardiovagal baroreflex sensitivity is associated with postural orthostatic tachycardia syndrome (POTS) and pain chronification in patients with headache

Background

Non-cephalgic symptoms including orthostatic intolerance, fatigue, and cognitive impairment, are common in patients with chronic headache disorders and may result from alterations in the autonomic nervous system. However, little is known about the function of autonomic reflexes, which regulate cardiovascular homeostasis and cerebral perfusion in patients with headache.

Methods

Autonomic function testing data from patients with headache collected between January 2018 and April 2022 was retrospectively analyzed. Through review of EMR we determined headache pain chronicity and patient self-report of orthostatic intolerance, fatigue, and cognitive impairment. Composite Autonomic Severity Score (CASS), CASS subscale scores, and cardiovagal and adrenergic baroreflex sensitivities were used to quantify autonomic reflex dysfunction. Descriptive analyses (Mann-Whitney-U or χ2, as appropriate) determined associations between autonomic reflex dysfunction and POTS as well as chronic headache. Binomial logistic regression adjusted for age and sex. Spearman’s rank correlation determined the association between the total CASS score and the number of painless symptoms reported by each participant.

Results

We identified 34 patients meeting inclusion criteria, of whom there were 16 (47.0%) with orthostatic intolerance, 17 (50.0%) with fatigue, 11 (32.4%) with cognitive complaints, and 11 (32.4%) with Postural Orthostatic Tachycardia Syndrome (POTS). The majority of participants had migraine (n = 24, 70.6%), were female (n = 23, 67.6%) and had a chronic (>15 headache days in a month) headache disorder (n = 26, 76.5%). Reduced cardiovagal baroreflex sensitivity (BRS-V) independently predicted chronic headache [aOR: 18.59 (1.16, 297.05), p = 0.039] and POTS [aOR: 5.78 (1.0, 32.5), p = 0.047]. The total CASS was correlated with the total number of non-painful features in the expected direction (r = 0.46, p = 0.007).

Conclusion

Abnormal autonomic reflexes may play an important role in pain chronification and the development of POTS in patients with headache.

Feature aggregation graph convolutional network based on imaging genetic data for diagnosis and pathogeny identification of Alzheimer's disease

The roles of brain regions activities and gene expressions in the development of Alzheimer's disease (AD) remain unclear. Existing imaging genetic studies usually has the problem of inefficiency and inadequate fusion of data. This study proposes a novel deep learning method to efficiently capture the development pattern of AD. First, we model the interaction between brain regions and genes as node-to-node feature aggregation in a brain region-gene network. Second, we propose a feature aggregation graph convolutional network (FAGCN) to transmit and update the node feature. Compared with the trivial graph convolutional procedure, we replace the input from the adjacency matrix with a weight matrix based on correlation analysis and consider common neighbor similarity to discover broader associations of nodes. Finally, we use a full-gradient saliency graph mechanism to score and extract the pathogenetic brain regions and risk genes. According to the results, FAGCN achieved the best performance among both traditional and cutting-edge methods and extracted AD-related brain regions and genes, providing theoretical and methodological support for the research of related diseases.

Targeting the M1 muscarinic acetylcholine receptor in Alzheimer’s disease

Alzheimer’s disease (AD) remains a major cause of morbidity and mortality worldwide, and despite extensive research, only a few drugs are available for management of the disease. One strategy has been to up-regulate cholinergic neurotransmission to improve cognitive function, but this approach has dose-limiting adverse effects. To avoid these adverse effects, new drugs that target specific receptor subtypes of the cholinergic system are needed, and the M1 subtype of muscarinic acetylcholine receptor (M1-mAChR) has been shown to be a good target for this approach. By using several strategies, M1-mAChR ligands have been developed and trialled in preclinical animal models and in human studies, with varying degrees of success. This article reviews the different approaches to targeting the M1-mAChR in AD and discusses the advantages and limitations of these strategies. The factors to consider in targeting the M1-mAChR in AD are also discussed.