Current Alzheimer Research - Online First

Type 2 Diabetes Mellitus (T2DM) patients are 50-60% more likely to develop Alzheimer’s Disease (AD). T2DM has many risk factors, including inflammation. Previous studies suggest that CRP was higher in diabetic patients, indicating that it may play a role in diabetogenesis and insulin resistance. Many diseases are prevalent in older age, including T2DM and AD. Moreover, multiple studies suggested a possible association between vitamin A levels, AD, and T2DM. However, the role of Vitamin A in Alzheimer's patients with T2DM has not yet been fully investigated. Therefore, this study aims to measure the association between dietary vitamin A deficiency and AD patients with T2DM in King Abdulaziz Medical City, Jeddah, Western Region, Saudi Arabia, to help expand the preexisting knowledge of the diagnostic risk factors of both the diseases and to determine the significance of vitamin A as a nutritional factor in their management and prevention.

This case-control study investigates the prevalence of vitamin A deficiency (VAD) among Alzheimer's disease (AD) patients with and without type 2 diabetes mellitus (T2DM). Participants included 103 AD patients aged 40 and older from the National Guard Hospital in Saudi Arabia, recruited between 2016 and 2022. Data collection occurred in two phases: first, through a review of medical records to gather demographic and health history information, including retrospective blood tests for systemic C-reactive protein (CRP) levels and comorbidities; second, using the HKI Food Frequency Questionnaire (FFQ) to assess dietary intake of vitamin A-rich foods over the past week, with caregiver interviews facilitating this process. Each subject was also prospectively interviewed to assess the presence of VAD events. The study aims to elucidate the relationship between dietary habits and VAD prevalence in AD patients, contributing to the understanding of nutritional impacts on cognitive health in this population.

This study examined demographic and clinical characteristics of the Alzheimer’s group, with 70.1% having both Alzheimer's with T2DM and 29.9% having Alzheimer's alone. Significant differences in age were found (p-value = 0.03), but gender distribution was similar (p-value = 0.45). Most caregivers were sons, and 81.43% of patients received oral feeding. Comorbidities included hypertension (94.90%) and dyslipidemia (63.4%), with significant differences (p-value < 0.001). Correlation analyses showed weak negative correlations between CRP and vitamin A concentrations in both groups (Alzheimer with T2DM: p-value = 0.713, rho = -0.064; AD only: p-value = 0.223, rho = -0.121). Age and vitamin A levels also exhibited weak correlations: Alzheimer’s with 2DM (p-value = 0.727, rho = 0.053) and Alzheimer’s only (p-value = 0.223, rho = -0.253), neither of them was statistically significant. Symptoms of vitamin A deficiency were noted in Alzheimer's patients with T2DM, with no significant differences between groups. Dietary intake was lower for vitamin B complex, vitamin D, and multivitamins in AD patients with T2DM.

The findings highlight the need for further investigation into the factors influencing vitamin A metabolism in these populations. Additionally, the prevalence of vitamin A deficiency symptoms and low dietary intake of essential nutrients among patients with Alzheimer's with T2DM suggests critical areas for nutritional intervention. Addressing these deficits may improve patient outcomes and enhance overall care strategies for individuals living with Alzheimer's disease.

Primary progressive aphasia (PPA) is a clinical syndrome characterized by progressive language impairment. Three subtypes have been identified: semantic (svPPA), nonfluent (nfPPA), and logopenic (lvPPA). Although clinical criteria exist to classify these subtypes, the specific ways in which semantic cognition is impaired across these variants have not yet been fully elucidated. This cross-sectional study aimed to analyze the effects of cognitive demand and imaginability on semantic cognition in patients with PPA.

Fifteen patients with PPA (five per variant) and 20 healthy controls completed a semantic association task comprising 20 items. The task included two levels of cognitive demand (low and high) and two types of concepts (concrete and abstract). Participants selected the word with the strongest semantic link to a probe word, based on synonymy, categorical relations, or shared features. Accuracy and reaction times were recorded and analyzed using nonparametric statistics.

All PPA groups performed significantly worse than controls, showing fewer correct responses and longer reaction times. svPPA patients exhibited the greatest impairment across all conditions. nfPPA patients performed similarly to controls with concrete concepts but showed deficits with abstract words. lvPPA patients experienced greater difficulty under high cognitive demand, particularly with abstract words, indicating impaired semantic control.

These findings suggest that svPPA is characterized by global impairment of conceptual knowledge, whereas nfPPA and lvPPA exhibit more selective deficits depending on concept type and cognitive demand.

The research herein highlights the importance of considering cognitive demand and imaginability when assessing semantic cognition in PPA.

Alzheimer's disease is expressed as chronic neuroinflammation in the brain, which results in neuronal dysfunction, aberrant protein folding, and declining cognitive abilities. miR-146a-5p is a potent anti-inflammatory agent that can attenuate several inflammatory diseases and promote wound healing. Our research aimed to utilize network pharmacology to elucidate the therapeutic potential of miR-146a-5p in treating Alzheimer's disease using a biocomputational approach.

Alzheimer's disease genes were extracted from DisGeNET, OMIM, and GeneCards databases. At the same time, miR-146a-5p candidate genes were sourced from four prediction databases: miRDB, miRWalk, miRNet, and TargetScan.

The overlap between miR-146a-5p and Alzheimer's disease genes was established using STRING, with a score greater than 0.9, revealing a total of 157 nodes in the compound-target disease network.

Pathway enrichment analysis further revealed key candidate genes associated with Alzheimer's, including those involved in neuronal death, leukocyte migration, and axon development. EGFR, IL6, NFKB1, TLR4, CXCL8, FN1, CXCR4, and BCL2 were pinpointed as the top 8 key candidate genes of miR-146a-5p. Between these key candidate genes, the miR-146a-5p Regulatory Network also demonstrated that miR-146a-5p downregulates EGFR and CXCR4. Furthermore, this research revealed the regulatory network of miR-146a-5p, which modulates the transcriptional activities of IL6, NFKB1, TLR4, CXCL8, FN1, and BCL2.

Therefore, the current network pharmacology study explored the principal mechanism behind the anti-inflammatory effects of miR-146a-5p in treating Alzheimer's disease, and potentially to be applied to other neurodegenerative diseases.

Cerebral Amyloid Angiopathy (CAA) is a common form of cerebral small vessel disease (CSVD), characterized by the accumulation of amyloid-β (Aβ) protein in the walls of cortical and leptomeningeal arteries and arterioles. The sporadic form primarily affects the elderly and is closely associated with Alzheimer’s disease (AD). Despite previous studies on cognition, the specific neuropsychological profile of CAA remains unclear. This study aims to describe the cognitive profile of CAA patients and characterize their neuropsychological aspects in the absence of a clinical diagnosis of AD.

We present a case series of six patients with probable CAA, without clinical evidence of AD, who underwent extensive neuropsychological assessment. Additionally, a narrative review was conducted to synthesize current knowledge of the cognitive and neuropsychological aspects of sporadic CAA.

The narrative review indicates that CAA predominantly affects executive functioning, processing speed, episodic memory, global cognition, and visuospatial functions. In our case series, all patients exhibited impairments in these domains, except for global cognition. Notably, a specific dissociation was observed in the Rey Auditory Verbal Learning Test (RAVLT), with impaired delayed recall but preserved recognition.

Sporadic CAA in patients without AD contributes to cognitive impairment, particularly affecting executive functioning, processing speed, visuospatial functions, and episodic memory. In our sample, memory impairment in CAA follows a dysexecutive pattern, characterized by retrieval deficits with preserved storage. This contrasts with the amnestic profile seen in AD and amnestic mild cognitive impairment (aMCI), where both retrieval and storage are compromised.

This distinct memory profile may represent a useful neuropsychological marker for differentiating CAA-related cognitive impairment from that associated with AD and its prodromal forms. This differentiation has potential implications for diagnosis, prognosis, and the development of tailored therapeutic strategies.

Much emphasis has been given to the biological activities of Fenugreek against various diseased conditions. This study investigated the effect of fenugreek leaf extract on behavioural and cognitive function of transgenic Drosophila having human Aβ-42 expression in the neurons, herein referred as Alzheimer’s disease model flies (AD flies).

AD flies were exposed to four different doses of fenugreek leaf extract (FE) containing i.e., 0.005, 0.010, 0.015 and 0.02 g/ml for 30 days. Thereafter, behavioural and cognitive assessment was done using climbing ability, activity pattern, aversive phototaxis and odour choice indexes. The life span of different groups of flies was also recorded. The effect of FE on the oxidative stress markers, acetylcholinesterase, monoamine oxidase (MAO) and caspase 3 and 9 activities were determined. The deposition of Aβ-42 aggregates in the brain tissue of the flies was studied by performing immunostaining. Also, the metabolic profile of different groups of flies was studied by performing LC-MS/MS. Compared with control flies, 22 selected metabolites were found to be upregulated and downregulated among transgenic AD flies and FE exposed AD flies compared to control.

The findings of this study showed the neuroprotective role of fenugreek extract, which could be employed for the treatment of Alzheimer’s disease. The AD flies exposed to FE showed a dose-dependent postponement in the decline of climbing ability, activity and cognitive impairments. A significant dose dependent increase in the life span was also noticed in the AD flies exposed to FE. A significant reduction in the oxidative stress, acetylcholinesterase, monoamine oxidase, and caspase-3&9 activities was also observed in a dose dependent manner. The results obtained from the immunostaining suggest the reduction in the deposition of Aβ-42 fibril, which was also confirmed by the docking studies showed the energetically favoured interaction useful for inhibiting the acetylcholinesterase and Aβ-42 aggregates.

This study demonstrates the neurological potency of fenugreek leaf extract (FE) in a Drosophila model of AD due to its antioxidantive, anti-cholinesterase, and neuroprotective properties. Using a combination of behavioral, biochemical, histological, and metabolomic approaches, we evaluated the therapeutic potential of FE in mitigating AD-like symptoms in transgenic flies expressing Aβ-42.

Fenugreek leaf extract may serve as a potential natural remedy for slowing down or alleviating the progression of AD.

Khat (Catha edulis (Vahl) Forssk. ex Endl.), a stimulant plant native to Africa and Asia, contains psychoactive compounds such as cathinone and cathine that affect the central nervous system. This study aims to investigate the potential neurotoxicological risks associated with these compounds, particularly focusing on their possible relationship with neurodegenerative disorders like Alzheimer's disease (AD). The primary objective was to evaluate the toxicity of khat's main compounds and examine their molecular interactions with Monoamine Oxidase A (MAO-A), an enzyme implicated in the pathology of AD.

The toxicological profiles of cathinone, cathine, amphetamine, and the AD medication Donepezil were assessed using the Protox-3 server, which predicted toxicity class, potential for liver damage, carcinogenicity, immunotoxicity, mutagenicity, and cytotoxicity. Molecular docking studies were conducted to analyse the binding interactions of these compounds with MAO-A (PDB ID: 2Z5X). Binding affinities and key interacting residues were identified. The steric effects of the ligands within the enzyme's binding site were quantified by calculating the buried volume (%VBur) using the centroid of centres method.

Protox-3 classified cathine and amphetamine as Class 3 toxicants (moderate toxicity), while cathinone and Donepezil were assigned to Class 4 (lower toxicity). Cathinone also demonstrated a moderate probability (0.64) of carcinogenicity. Molecular docking revealed that khat compounds had an average binding affinity of -5.81 ± 0.27 kcal/mol, which was lower than that of amphetamine (-6.10 ± 0.27 kcal/mol) and Donepezil (-7.80 ± 0.38 kcal/mol). Buried volume analysis indicated that khat compounds and amphetamine were more deeply embedded in the MAO-A binding site, correlating with stronger binding affinity.

The computational results suggest that khat compounds exhibit moderate neurotoxic potential and interact with MAO-A in a manner that could be relevant to AD pathology. Although the binding affinities are lower than those of Amphetamine and Donepezil, they point to possible molecular-level interactions significant for neurodegeneration. Steric hindrance, as quantified by %VBur, appeared to influence binding strength, highlighting the importance of molecular fit within the active site.

This study presents evidence of a potential molecular link between khat consumption and an increased risk of Alzheimer's disease. The findings underscore the necessity for further in vivo and epidemiological research, particularly in regions with high rates of khat use, to assess its long-term neurotoxic effects.

Dementia is a set of acquired and progressive neuropsychiatric disorders. The most common types of dementia include Alzheimer’s Disease (AD) and Frontotemporal Dementia (FTD). Early intravital diagnosis of both types of dementia is difficult. Both molecular and neuroimaging markers are important for the diagnosis of different types of dementia.

This review employed freely accessible databases, including PubMed, Google Scholar, and ScienceDirect, using keywords such as molecular parameters, neuroimaging factors, dementia, FTD, Alzheimer’s disease, and fMRI.

Among the molecular markers of dementia, there are parameters common to its various types and enabling their differentiation. These parameters include both genetic and biochemical factors. Markers include genetic factors that help differentiate AD (APP, PSEN1, PSEN2) from FTD (e.g., TARDBP, FUS, MAPT). Simultaneously, there are important biochemical parameters differentiating AD (amyloid-beta (Aβ), neurofibrillary tangles) from FTD (TDP-43, FUS, and different forms of tau protein aggregates). Currently, there is growing interest in neuroimaging studies in the differential diagnosis of dementia. Positron Emission Tomography (PET) imaging enables the quantification and localization of Aβ deposits in the brain through the selective binding of the Pittsburgh Compound-B (PiB) ligand. This method has become the standard in AD diagnostics. In the context of magnetic resonance imaging studies, it is worth noting the search for structural differences between AD (mainly affecting the temporal lobe, including the hippocampus and entorhinal cortex, and the parietal lobe) and FTD (primarily involving the prefrontal cortex, anterior temporal lobes, and subcortical structures, as well as exhibiting an anteroposterior gradient of atrophy). However, the method of the future appears to be functional Magnetic Resonance Imaging (fMRI), especially since functional changes precede structural changes in the development of dementia.

The review encompasses the basic diagnostic criteria for AD and FTD dementia, as well as molecular and neuroimaging parameters important for the intravital diagnosis of these dementias. It seems that the use of fMRI can contribute to both early diagnosis and early introduction of targeted treatment in developing dementia. Although it is not yet widely used clinically, its diagnostic value is increasingly recognized.

The benefits of fMRI studies complementing molecular markers in the diagnosis of dementia were highlighted.

Type 2 diabetes mellitus (T2D) is a known risk factor for developing Alzheimer’s disease (AD). Recent research shows that both diseases share complex and related pathophysiological processes. Network medicine approaches can help to elucidate common dysregulated processes among different diseases, such as AD and T2D. Thus, the aim of this work was to determine differentially expressed genes (DEGs) in AD and T2D and to apply a network medicine approach to identify the microRNAs (miRNAs) involved in the AD-T2D association.

Gene expression microarray data sets consisting of 384 control samples and 399 samples belonging to AD and T2D disease were analyzed to obtain DEGs shared by both diseases; the miRNAs associated with these DEGs were predicted using a network medicine approach. Finally, potential small molecules targeting these potentially deregulated miRNAs were identified.

AD and T2D shared a subset of 82 downregulated DEGs. These genes were significantly associated (p < 0.01) with the ontology terms of chemical synaptic deregulation. DEGs were associated with 12 miRNAs expressed in specific tissues for AD and T2D. Such miRNAs were also primarily associated with the ontology terms related to synaptic deregulation and cancer, and AKT signaling pathways. Steroid anti-inflammatory drugs, antineoplastics, and glucose metabolites were predicted to be potential regulators of the 12 shared miRNAs.

The network medicine approach integrating DEGs and miRNAs enabled the identification of shared, potentially deregulated biological processes and pathways underlying the pathophysiology of AD and T2D. These common molecular mechanisms were also linked to drugs currently used in clinical practice, suggesting that this strategy may inform future drug repurposing efforts. Nonetheless, further in-depth biological validation is required to confirm these findings.

Network medicine allowed identifying 12 miRNAs involved in the AD-T2D association, and these could be drug targets for the design of new treatments; however, the identified miRNAs need further experimental confirmation.

Alzheimer's disease (AD) is a leading cause of death, making early detection critical to improve survival rates. Conventional manual techniques struggle with early diagnosis due to the brain's complex structure, necessitating the use of dependable deep learning (DL) methods. This research proposes a novel RESIGN model is a combination of Res-InceptionSeg for detecting AD utilizing MRI images.

The input MRI images were pre-processed using a Non-Local Means (NLM) filter to reduce noise artifacts. A ResNet-LSTM model was used for feature extraction, targeting White Matter (WM), Grey Matter (GM), and Cerebrospinal Fluid (CSF). The extracted features were concatenated and classified into Normal, MCI, and AD categories using an Inception V3-based classifier. Additionally, SegNet was employed for abnormal brain region segmentation.

The RESIGN model achieved an accuracy of 99.46%, specificity of 98.68%, precision of 95.63%, recall of 97.10%, and an F1 score of 95.42%. It outperformed ResNet, AlexNet, DenseNet, and LSTM by 7.87%, 5.65%, 3.92%, and 1.53%, respectively, and further improved accuracy by 25.69%, 5.29%, 2.03%, and 1.71% over ResNet18, CLSTM, VGG19, and CNN, respectively.

The integration of spatial-temporal feature extraction, hybrid classification, and deep segmentation makes RESIGN highly reliable in detecting AD. A 5-fold cross-validation proved its robustness, and its performance exceeded that of existing models on the ADNI dataset. However, there are potential limitations related to dataset bias and limited generalizability due to uniform imaging conditions.

The proposed RESIGN model demonstrates significant improvement in early AD detection through robust feature extraction and classification by offering a reliable tool for clinical diagnosis.

At present, there is limited research on the association between dietary intake of anthocyanidins and Alzheimer's disease (AD). More epidemiological studies are needed to better understand this relationship.

We explored the relationship between dietary Anthocyanidins intake and AD among 3806 American adults in the National Health and Nutrition Examination Survey (NHANES) and the United States Department of Agriculture’s Food and Nutrient Database for Dietary Studies (FNDDS) from 2007 to 2010, and 2017 to 2018. We use weighted logistic regression model, restricted cubic spline (RCS) and weighted quantile sum (WQS) regression analysis to analyze the relationship between anthocyanidins monomer and AD.

The weighted logistic regression model showed that the total intake of anthocyanidins was the fourth (OR:0.979; 95% CI: 0.966-0.992) quantile (relative to the lowest quantile) is related to the reduction of AD risk. RCS analysis showed that the total intake of anthocyanidins was negatively linearly correlated with AD (nonlinear P value was 0.002). The WQS regression analysis shows that cyanidin and malvidin are the main contributors to the comprehensive effects of six anthocyanidins.

Our findings indicate that higher dietary anthocyanin intake may reduce the risk of AD and alleviate neurodegenerative processes. However, the mechanisms underlying this relationship remain unclear. Future studies should confirm these associations and investigate the relevant biological pathways.

Our results show that a higher dietary intake of anthocyanidins is associated with a lower risk of AD.