2019 Alzheimer's disease facts and figures

An Alzheimer's Disease classification network based on MRI utilizing diffusion maps for multi-scale feature fusion in graph convolution

Graph convolutional networks (GCN) have been widely utilized in Alzheimer's disease (AD) classification research due to its ability to automatically learn robust and powerful feature representations. Inter-patient relationships are effectively captured by constructing patients magnetic resonance imaging (MRI) data as graph data, where nodes represent individuals and edges denote the relationships between them. However, the performance of GCNs might be constrained by the construction of the graph adjacency matrix, thereby leading to learned features potentially overlooking intrinsic correlations among patients, which ultimately causes inaccurate disease classifications. To address this issue, we propose an Alzheimer's disease Classification network based on MRI utilizing diffusion maps for multi-scale feature fusion in graph convolution. This method aims to tackle the problem of features neglecting intrinsic relationships among patients while integrating features from diffusion mapping with different neighbor counts to better represent patients and achieve an accurate AD classification. Initially, the diffusion maps method conducts diffusion information in the feature space, thus breaking free from the constraints of diffusion based on the adjacency matrix. Subsequently, the diffusion features with different neighbor counts are merged, and a self-attention mechanism is employed to adaptively adjust the weights of diffusion features at different scales, thereby comprehensively and accurately capturing patient characteristics. Finally, metric learning techniques enhance the similarity of node features within the same category in the graph structure and bring node features of different categories more distant from each other. This study aims to enhance the classification accuracy of AD, by providing an effective tool for early diagnosis and intervention. It offers valuable information for clinical decisions and personalized treatment. Experimentation on the publicly accessible Alzheimer's disease neuroimaging initiative (ADNI) dataset validated our method's competitive performance across various AD-related classification tasks. Compared to existing methodologies, our approach captures patient characteristics more effectively and demonstrates superior generalization capabilities.

Factor structure of the Harmonized Cognitive Assessment Protocol neuropsychological battery in the Health and Retirement Study

OBJECTIVE

The Harmonized Cognitive Assessment Protocol (HCAP) describes an assessment battery and a family of population-representative studies measuring neuropsychological performance. We describe the factorial structure of the HCAP battery in the US Health and Retirement Study (HRS).

METHOD

The HCAP battery was compiled from existing measures by a cross-disciplinary and international panel of researchers. The HCAP battery was used in the 2016 wave of the HRS. We used factor analysis methods to assess and refine a theoretically driven single and multiple domain factor structure for tests included in the HCAP battery among 3,347 participants with evaluable performance data.

RESULTS

For the eight domains of cognitive functioning identified (orientation, memory [immediate, delayed, and recognition], set shifting, attention/speed, language/fluency, and visuospatial), all single factor models fit reasonably well, although four of these domains had either 2 or 3 indicators where fit must be perfect and is not informative. Multidimensional models suggested the eight-domain model was overly complex. A five-domain model (orientation, memory delayed and recognition, executive functioning, language/fluency, visuospatial) was identified as a reasonable model for summarizing performance in this sample (standardized root mean square residual = 0.05, root mean square error of approximation = 0.05, confirmatory fit index = 0.94).

CONCLUSIONS

The HCAP battery conforms adequately to a multidimensional structure of neuropsychological performance. The derived measurement models can be used to operationalize notions of neurocognitive impairment, and as a starting point for prioritizing pre-statistical harmonization and evaluating configural invariance in cross-national research.

Alzheimer's disease-related brain insulin resistance and the prospective therapeutic impact of metformin

Besides COVID-19, two of the most critical outbreaks of our day are insulin resistance, type 2 diabetes mellitus (T2DM), and Alzheimer's disease (AD). Each disease's pathophysiology is well established. Furthermore, a substantial overlap between them has coexisted. Uncertainty remains on whether T2DM and AD are parallel illnesses with the same origin or separate illnesses linked through violent pathways. The current study was aimed at testing whether the insulin resistance in the brain results in AD symptoms or not. Insulin resistance was induced in the brains of rats using a single intracerebroventricular streptozotocin (STZ) dose. We then measured glucose, insulin receptor substrate 2 (IRS-2), amyloid β (Aβ) deposition, and tau phosphorylation in the brain to look for signs of insulin resistance and AD. The results of this study indicated that a single dose of STZ was able to induce insulin resistance in the brain and significantly decline IRS-2. This resistance was accompanied by obvious memory loss, Aβ deposition, and tau phosphorylation, further visible diminishing in neurotransmitters such as dopamine and acetylcholine. Furthermore, oxidative stress was increased due to the antioxidant system being compromised. Interestingly, the pancreas injury and peripheral insulin resistance coexisted with brain insulin resistance. Indeed, the antidiabetic metformin was able to enhance all these drastic effects. In conclusion, brain insulin resistance could lead to AD and vice versa. These are highly linked syndromes that could influence peripheral organs. Further studies are required to stabilize this putative pathobiology relationship between them.

Targeted Treatment Strategies for Mitochondria Dysfunction: Correlation with Neurological Disorders

Mitochondria are an essential intracellular organelle for medication targeting and delivery since they seem to create energy and conduct many other cellular tasks, and mitochondrial dysfunctions and malfunctions lead to many illnesses. Many initiatives have been taken to detect, diagnose, and image mitochondrial abnormalities, and to transport and accumulate medicines precisely to mitochondria, all because of special mitochondrial aspects of the pathophysiology of cancer. In addition to the negative membrane potential and paradoxical mitochondrial dynamics, they include high temperatures, high levels of reactive oxygen species, high levels of glutathione, and high temperatures. Neurodegenerative diseases represent a broad spectrum of debilitating illnesses. They are linked to the loss of certain groups of neurons based on an individual's physiology or anatomy. The mitochondria in a cell are generally accepted as the authority with respect to ATP production. Disruption of this system is linked to several cellular physiological issues. The development of neurodegenerative disorders has been linked to mitochondrial malfunction, according to pathophysiological studies. There seems to be substantial evidence connecting mitochondrial dysfunction and oxidative stress to the development of neurodegenerative disorders. It has been extensively observed that mitochondrial malfunction triggers autophagy, which plays a role in neurodegenerative disorders. In addition, excitotoxicity and mitochondrial dysfunction have been linked to the development of neurodegenerative disorders. The pathophysiology of neurodegenerative illnesses has been linked to increased apoptosis and necrosis, as well as mitochondrial malfunction. A variety of synthetic and natural treatments have shown efficacy in treating neurodegenerative illnesses caused by mitochondrial failure. Neurodegenerative illnesses can be effectively treated with existing drugs that target mitochondria, although their precise formulations are poorly understood. Therefore, there is an immediate need to focus on creating drug delivery methods specifically targeted at mitochondria in the treatment and diagnosis of neurodegenerative disorders.

A Continuous Extension of Gene Set Enrichment Analysis Using the Likelihood Ratio Test Statistics Identifies Vascular Endothelial Growth Factor as a Candidate Pathway for Alzheimer's Disease via ITGA5

BACKGROUND

Alzheimer's disease (AD) involves brain neuropathologies such as amyloid plaque and hyperphosphorylated tau tangles and is accompanied by cognitive decline. Identifying the biological mechanisms underlying disease onset and progression based on quantifiable phenotypes will help understand disease etiology and devise therapies.

OBJECTIVE

Our objective was to identify molecular pathways associated with hallmark AD biomarkers and cognitive status, accounting for variables such as age, sex, education, and APOE genotype.

METHODS

We introduce a pathway-based statistical approach, extending the gene set likelihood ratio test to continuous phenotypes. We first analyzed independently each of the three phenotypes (amyloid-β, tau, cognition) using continuous gene set likelihood ratio tests to account for covariates, including age, sex, education, and APOE genotype. The analysis involved 634 subjects with data available for all three phenotypes, allowing for the identification of common pathways.

RESULTS

We identified 14 pathways significantly associated with amyloid-β; 5 associated with tau; and 174 associated with cognition, which showed a larger number of pathways compared to biomarkers. A single pathway, vascular endothelial growth factor receptor binding (VEGF-RB), exhibited associations with all three phenotypes. Mediation analysis showed that among the VEGF-RB family genes, ITGA5 mediates the relationship between cognitive scores and pathological biomarkers.

CONCLUSIONS

We presented a new statistical approach linking continuous phenotypes, gene expression across pathways, and covariates like sex, age, and education. Our results reinforced VEGF RB2's role in AD cognition and demonstrated ITGA5's significant role in mediating the AD pathology-cognition connection.

Cognitive Performance following Single- or Multi-Session Exercise Intervention in Middle Age: A Systematic Review

BACKGROUND

Research in modifiable behaviors, like exercise, on risk for dementia is increasing. Although many studies focus on older adults, brain pathology for Alzheimer's Disease can begin in middle age, suggesting an ideal target for intervention.

METHODS

We conducted a systematic review from exercise intervention studies on cognitive function among healthy, middle-aged participants (45-65). We searched multiple databases (PubMed, PsycINFO, MEDLINE, Cochrane Central Register of Controlled Trials, Google Scholar) for studies using standard, validated, neuropsychological measures following either single- or multi-session interventions in cognitively-unimpaired, middle-aged adults.

RESULTS

We identified 13 eligible studies. There was notable heterogeneity across studies, with varying design, measures, interventions, and results. Results from single-session studies showed improvement in response inhibition, while results for cognitive flexibility were mixed. No significant changes were found on measures of attention, working memory, or processing speed. Results from multi-session studies were more varied. Verbal memory was found to improve while performance on tests of attention and working memory, processing speed, and executive function were mixed.

CONCLUSION

Importantly, for both single-session and multi-session studies, there was no standard set of neuropsychological tests administered, making it more difficult to synthesize the findings into a single narrative. We end with a discussion on future directions and implementation.

Alzheimer's disease and Alzheimer's disease-related dementias in Hispanics: Identifying influential factors and supporting caregivers

Alzheimer's disease (AD) and Alzheimer's disease-related dementias (ADRD) are the primary public health concerns in the United States and around the globe. AD/ADRD are irreversible mental illnesses that primarily impair memory and thought processes and may lead to cognitive decline among older individuals. The prevalence of AD/ADRD is higher in Native Americans, followed by African Americans and Hispanics. Increasing evidence suggests that Hispanics are the fastest-growing ethnic population in the USA and worldwide. Hispanics develop clinical symptoms of AD/ADRD and other comorbidities nearly seven years earlier than non-Hispanic whites. The consequences of AD/ADRD can be challenging for patients, their families, and caregivers. There is a significant increase in the burden of illness, primarily affecting Hispanic/Latino families. This is partly due to their strong sense of duty towards family, and it is exacerbated by the inadequacy of healthcare and community services that are culturally and linguistically suitable and responsive to their needs. With an increasing age population, low socioeconomic status, low education, high genetic predisposition to age-related conditions, unique cultural habits, and social behaviors, Hispanic Americans face a higher risk of AD/ADRD than other racial/ethnic groups. Our article highlights the status of Hispanic older adults with AD/ADRD. We also discussed the intervention to improve the quality of life in Hispanic caregivers.

Diagnosing Alzheimer's disease: Which dementia screening test to use in elderly Puerto Ricans with mild cognitive impairment and early Alzheimer's disease?

Typically, Alzheimer's disease (AD) diagnosis is not made at its earliest period, for instance, at mild cognitive impairment (MCI) and early AD (E-AD). Our study aims to demonstrate a correlation between the screening tools, including the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Clinical Dementia Rating (CDR), and the biological biomarkers in the cerebrospinal fluid (CSF) amyloid beta 1-42 (Aβ42), phosphorylated tau (p-tau) proteins and total tau (t-tau)/Aβ42 ratio in Puerto Ricans > 55 years old with MCI and E-AD. We evaluated 30 participants, including demographics, memory scales, and CSF biomarkers. Twenty-eight CSF biomarkers (Aβ42, p-tau protein, and t-tau/Aβ42 ratio) were analyzed using the Meso Scale Discovery Platform (MSD). Associations between memory scales (MoCA, MMSE, CDR) and CSF markers were performed using Spearman rho correlation. Our study revealed a statistical association favoring a direct relationship between MMSE and MoCA with t-tau/Aβ42 ratio in CSF (P = 0.022, P = 0.035, respectively). We found a trend toward significance with an inverse relationship with MMSE and Aβ42 (P = 0.069) and a direct relationship with MMSE and p-tau (P = 0.098). MMSE and MoCA screening tests were identified with a statistically significant association with the CSF biomarkers, specifically t-tau/Aβ42 ratio, in elderly Puerto Ricans with MCI and E-AD. Puerto Ricans > 55 years old with MCI and E-AD could be screened confidently with MMSE and MoCA for a higher likelihood of earlier detection and, thus, initiation of disease-modifying treatment and prompt non-pharmacological interventions.

Implications of microbe-derived ɣ-aminobutyric acid (GABA) in gut and brain barrier integrity and GABAergic signaling in Alzheimer's disease

The gut microbial ecosystem communicates bidirectionally with the brain in what is known as the gut-microbiome-brain axis. Bidirectional signaling occurs through several pathways including signaling via the vagus nerve, circulation of microbial metabolites, and immune activation. Alterations in the gut microbiota are implicated in Alzheimer's disease (AD), a progressive neurodegenerative disease. Perturbations in gut microbial communities may affect pathways within the gut-microbiome-brain axis through altered production of microbial metabolites including ɣ-aminobutyric acid (GABA), the primary inhibitory mammalian neurotransmitter. GABA has been shown to act on gut integrity through modulation of gut mucins and tight junction proteins and may be involved in vagus nerve signal inhibition. The GABAergic signaling pathway has been shown to be dysregulated in AD, and may be responsive to interventions. Gut microbial production of GABA is of recent interest in neurological disorders, including AD. Bacteroides and Lactic Acid Bacteria (LAB), including Lactobacillus, are predominant producers of GABA. This review highlights how temporal alterations in gut microbial communities associated with AD may affect the GABAergic signaling pathway, intestinal barrier integrity, and AD-associated inflammation.

A Deep Learning-Based Ensemble Method for Early Diagnosis of Alzheimer's Disease using MRI Images

Recently, the early diagnosis of Alzheimer's disease has gained major attention due to the growing prevalence of the disease and the resulting costs imposed on individuals and society. The main objective of this study was to propose an ensemble method based on deep learning for the early diagnosis of AD using MRI images. The methodology of this study consisted of collecting the dataset, preprocessing, creating the individual and ensemble models, evaluating the models based on ADNI data, and validating the trained model based on the local dataset. The proposed method was an ensemble approach selected through a comparative analysis of various ensemble scenarios. Finally, the six best individual CNN-based classifiers were selected to combine and constitute the ensemble model. The evaluation showed an accuracy rate of 98.57, 96.37, 94.22, 99.83, 93.88, and 93.92 for NC/AD, NC/EMCI, EMCI/LMCI, LMCI/AD, four-way and three-way classification groups, respectively. The validation results on the local dataset revealed an accuracy of 88.46 for three-way classification. Our performance results were higher than most reviewed studies and comparable with others. Although comparative analysis showed superior results of ensemble methods against individual architectures, there were no significant differences among various ensemble approaches. The validation results revealed the low performance of individual models in practice. In contrast, the ensemble method showed promising results. However, further studies on various and larger datasets are required to validate the generalizability of the model.

Feasibility and Determinants of Performance for a Tablet-Based Cognitive Assessment Tool in Rural and Urban Southeast Nigeria

Background

Cognitive assessment is a key component of clinical evaluations for patients with dementia and Alzheimer's disease in primary health care (PHC) settings. The need for well-validated, culturally appropriate, and easy-to-use assessments is especially urgent in low- and middle-income countries (LMICs) that are experiencing rapid growth in their older adult populations.

Objective

To examine the feasibility and demographic determinants of performance for a tablet-based cognitive assessment tool (TabCAT) battery, which includes subtests for four cognitive domains, among older PHC patients in southeastNigeria.

Methods

A cross-sectional mixed-method descriptive study evaluating the useability and performance of TabCAT.

Results

We enrolled 207 participants (mean age of 64.7±13.5 years; 52% with only primary, 41% secondary, and 7% tertiary education). Most (91%) who initiated the assessment were able to complete it, requiring 10-15 minutes to complete. More years of education was associated with better test scores across all tests (p < 0.001). Living in a rural location was also associated with better performance (p < 0.05). Male compared to female sex did not associate with performance on any of the tests (all ps > 0.05).

Conclusions

Tablet-based cognitive assessment was feasible in rural and urban settings of Nigeria. Better performance on cognitive subtests linked to more education and residing in a rural area; however, sex did not predict performance. Digital cognitive assessment tools hold potential for widespread use in healthcare and educational contexts, particularly in regions with varying levels of urbanization and educational access.

Ascertainment and Statistical Issues for Randomized Trials of Cardiovascular Interventions for Cognitive Impairment and Dementia

There has been considerable progress in the prevention and treatment of cardiovascular disease, reducing the population burden of cardiovascular morbidity and mortality. Recently, some randomized trials, including the SPRINT (Systolic Blood Pressure Intervention Trial), have suggested that improvements in cardiovascular risk factors may also slow cognitive decline and reduce the eventual development of dementia. Unfortunately, the randomized trial template that has been used repeatedly to successfully demonstrate reductions in major adverse cardiac events faces several design and analytic obstacles when applied in the context of cognitive decline and dementia. Here, we review these obstacles, motivated by SPRINT and the context of selecting an appropriate cognitive end point for future preventive randomized trials. A few options are available, spanning neuropsychological test scores or composites reflecting specific domains of cognitive function, adjudicated cognitive impairment, or potentially physiological biomarkers. This choice entails considerations around statistical power, modes of ascertainment, the clinical relevance of treatment effects, a myriad of statistical issues (interval censoring, missing data, the competing risk of death, practice effects, etc), as well as ethical considerations around equipoise. Collectively, these considerations indicate that trials aiming to mitigate the cardiovascular contribution to cognitive decline and dementia will generally need to be large, inclusive of a wide age range of older adults, and with multiple years of follow-up.

Identifying disease-related microbes based on multi-scale variational graph autoencoder embedding Wasserstein distance

BACKGROUND

Enormous clinical and biomedical researches have demonstrated that microbes are crucial to human health. Identifying associations between microbes and diseases can not only reveal potential disease mechanisms, but also facilitate early diagnosis and promote precision medicine. Due to the data perturbation and unsatisfactory latent representation, there is a significant room for improvement.

RESULTS

In this work, we proposed a novel framework, Multi-scale Variational Graph AutoEncoder embedding Wasserstein distance (MVGAEW) to predict disease-related microbes, which had the ability to resist data perturbation and effectively generate latent representations for both microbes and diseases from the perspective of distribution. First, we calculated multiple similarities and integrated them through similarity network confusion. Subsequently, we obtained node latent representations by improved variational graph autoencoder. Ultimately, XGBoost classifier was employed to predict potential disease-related microbes. We also introduced multi-order node embedding reconstruction to enhance the representation capacity. We also performed ablation studies to evaluate the contribution of each section of our model. Moreover, we conducted experiments on common drugs and case studies, including Alzheimer's disease, Crohn's disease, and colorectal neoplasms, to validate the effectiveness of our framework.

CONCLUSIONS

Significantly, our model exceeded other currently state-of-the-art methods, exhibiting a great improvement on the HMDAD database.

Assessing Ethnic Minority Representation in Fibromyalgia Clinical Trials: A Systematic Review of Recruitment Demographics

The under-representation of non-White participants in Western countries in clinical research has received increased attention, due to recognized physiological differences between ethnic groups, which may affect the efficacy and optimal dosage of some treatments. This review assessed ethnic diversity in pharmaceutical trials for fibromyalgia, a poorly understood chronic pain disorder. We also investigated longitudinal change to non-White participant proportions in trials and non-White participants' likelihood to discontinue with fibromyalgia research between trial stages (retention). First, we identified relevant trials conducted in the United States and Canada between 2000 and 2022, by searching PubMed, Web of Science, Scopus, and the Cochrane Library databases. In trials conducted both across the United States and Canada, and exclusively within the United States, approximately 90% of participants were White. A longitudinal analysis also found no change in the proportion of non-White participants in trials conducted across the United States and Canada between 2000 and 2022. Finally, we found no significant differences in trial retention between White and non-White participants. This review highlights the low numbers of ethnic minorities in fibromyalgia trials conducted in the United States and Canada, with no change to these proportions over the past 22 years. Furthermore, non-White participants were not more likely to discontinue with the fibromyalgia research once they were recruited.

Identification of candidate DNA methylation biomarkers related to Alzheimer's disease risk by integrating genome and blood methylome data

Alzheimer disease (AD) is a common neurodegenerative disease with a late onset. It is critical to identify novel blood-based DNA methylation biomarkers to better understand the extent of the molecular pathways affected in AD. Two sets of blood DNA methylation genetic prediction models developed using different reference panels and modelling strategies were leveraged to evaluate associations of genetically predicted DNA methylation levels with AD risk in 111,326 (46,828 proxy) cases and 677,663 controls. A total of 1,168 cytosine-phosphate-guanine (CpG) sites showed a significant association with AD risk at a false discovery rate (FDR) < 0.05. Methylation levels of 196 CpG sites were correlated with expression levels of 130 adjacent genes in blood. Overall, 52 CpG sites of 32 genes showed consistent association directions for the methylation-gene expression-AD risk, including nine genes (CNIH4, THUMPD3, SERPINB9, MTUS1, CISD1, FRAT2, CCDC88B, FES, and SSH2) firstly reported as AD risk genes. Nine of 32 genes were enriched in dementia and AD disease categories (P values ranged from 1.85 × 10-4 to 7.46 × 10-6), and 19 genes in a neurological disease network (score = 54) were also observed. Our findings improve the understanding of genetics and etiology for AD.

Metformin: The Winding Path from Understanding Its Molecular Mechanisms to Proving Therapeutic Benefits in Neurodegenerative Disorders

Metformin, a widely prescribed medication for type 2 diabetes, has garnered increasing attention for its potential neuroprotective properties due to the growing demand for treatments for Alzheimer's, Parkinson's, and motor neuron diseases. This review synthesizes experimental and clinical studies on metformin's mechanisms of action and potential therapeutic benefits for neurodegenerative disorders. A comprehensive search of electronic databases, including PubMed, MEDLINE, Embase, and Cochrane library, focused on key phrases such as "metformin", "neuroprotection", and "neurodegenerative diseases", with data up to September 2023. Recent research on metformin's glucoregulatory mechanisms reveals new molecular targets, including the activation of the LKB1-AMPK signaling pathway, which is crucial for chronic administration of metformin. The pleiotropic impact may involve other stress kinases that are acutely activated. The precise role of respiratory chain complexes (I and IV), of the mitochondrial targets, or of the lysosomes in metformin effects remains to be established by further research. Research on extrahepatic targets like the gut and microbiota, as well as its antioxidant and immunomodulatory properties, is crucial for understanding neurodegenerative disorders. Experimental data on animal models shows promising results, but clinical studies are inconclusive. Understanding the molecular targets and mechanisms of its effects could help design clinical trials to explore and, hopefully, prove its therapeutic effects in neurodegenerative conditions.

Association between first-line antidepressant use and risk of dementia in older adults: a retrospective cohort study

BACKGROUND

Prior studies suggested that antidepressant use is associated with an increased risk of dementia compared to no use, which is subject to confounding by indication. We aimed to compare the dementia risk among older adults with depression receiving first-line antidepressants (i.e., SSRI/SNRI) versus psychotherapy, which is also considered the first-line therapy for depression.

METHODS

This retrospective cohort study was conducted using the US Medical Expenditure Panel Survey from 2010 to 2019. We included adults aged ≥ 50 years diagnosed with depression who initiated SSRI/SNRI or psychotherapy. We excluded patients with a dementia diagnosis before the first record of SSRI/SNRI use or psychotherapy. The exposure was the patient's receipt of SSRI/SNRI (identified from self-report questionnaires) or psychotherapy (identified from the Outpatient Visits or Office-Based Medical Provider Visits files). The outcome was a new diagnosis of dementia within 2 years (i.e., survey panel period) identified using ICD-9/ICD-10 codes from the Medical Conditions file. Using a multivariable logistic regression model, we reported adjusted odds ratios (aORs) with 95% confidence intervals (CIs). We also conducted subgroup analyses by patient sex, age group, race/ethnicity, severity of depression, combined use of other non-SSRI/SNRI antidepressants, and presence of underlying cognitive impairment.

RESULTS

Among 2,710 eligible patients (mean age = 61 ± 8, female = 69%, White = 84%), 89% used SSRIs/SNRIs, and 11% received psychotherapy. The SSRI/SNRI users had a higher crude incidence of dementia than the psychotherapy group (16.4% vs. 11.8%), with an aOR of 1.36 (95% CI = 1.06-1.74). Subgroup analyses yielded similar findings as the main analyses, except no significant association for patients who were aged < 65 years (1.23, 95% CI = 0.93-1.62), male (1.34, 95% CI = 0.95-1.90), Black (0.76, 95% CI = 0.48-1.19), had a higher PHQ-2 (1.39, 95% CI = 0.90-2.15), and had underlying cognitive impairment (1.06, 95% CI = 0.80-1.42).

CONCLUSIONS

Our findings suggested that older adults with depression receiving SSRIs/SNRIs were associated with an increased dementia risk compared to those receiving psychotherapy.

Neuroprotective Effects of N-methyl-(2S, 4R)-trans-4-hydroxy-L-proline (NMP) against Amyloid-β-Induced Alzheimer's Disease Mouse Model

Alzheimer's disease (AD), is a progressive neurodegenerative disorder that involves the deposition of β-amyloid plaques and the clinical symptoms of confusion, memory loss, and cognitive dysfunction. Despite enormous progress in the field, no curative treatment is available. Therefore, the current study was designed to determine the neuroprotective effects of N-methyl-(2S, 4R)-Trans-4-hydroxy-L-proline (NMP) obtained from Sideroxylon obtusifolium, a Brazilian folk medicine with anti-inflammatory and anti-oxidative properties. Here, for the first time, we explored the neuroprotective role of NMP in the Aβ1-42-injected mouse model of AD. After acclimatization, a single intracerebroventricular injection of Aβ1-42 (5 µL/5 min/mouse) in C57BL/6N mice induced significant amyloidogenesis, reactive gliosis, oxidative stress, neuroinflammation, and synaptic and memory deficits. However, an intraperitoneal injection of NMP at a dose of (50 mg/kg/day) for three consecutive weeks remarkably decreased beta secretase1 (BACE-1) and Aβ, activated the astrocyte and microglia expression level as well as downstream inflammatory mediators such as pNF-ĸB, TNF-α, and IL-1β. NPM also strongly attenuated oxidative stress, as evaluated by the expression level of NRF2/HO-1, and synaptic failure, by improving the level of both the presynaptic (SNAP-25 and SYN) and postsynaptic (PSD-95 and SNAP-23) regions of the synapses in the cortexes and hippocampi of the Aβ1-42-injected mice, contributing to cognitive improvement in AD and improving the behavioral deficits displayed in the Morris water maze and Y-maze. Overall, our data suggest that NMP provides potent multifactorial effects, including the inhibition of amyloid plaques, oxidative stress, neuroinflammation, and cognitive deficits.

Large-scale proteome and metabolome analysis of CSF implicates altered glucose and carbon metabolism and succinylcarnitine in Alzheimer's disease

INTRODUCTION

A hallmark of Alzheimer's disease (AD) is the aggregation of proteins (amyloid beta [A] and hyperphosphorylated tau [T]) in the brain, making cerebrospinal fluid (CSF) proteins of particular interest.

METHODS

We conducted a CSF proteome-wide analysis among participants of varying AT pathology (n = 137 participants; 915 proteins) with nine CSF biomarkers of neurodegeneration and neuroinflammation.

RESULTS

We identified 61 proteins significantly associated with the AT category (P < 5.46 × 10-5 ) and 636 significant protein-biomarker associations (P < 6.07 × 10-6 ). Proteins from glucose and carbon metabolism pathways were enriched among amyloid- and tau-associated proteins, including malate dehydrogenase and aldolase A, whose associations with tau were replicated in an independent cohort (n = 717). CSF metabolomics identified and replicated an association of succinylcarnitine with phosphorylated tau and other biomarkers.

DISCUSSION

These results implicate glucose and carbon metabolic dysregulation and increased CSF succinylcarnitine levels with amyloid and tau pathology in AD.

HIGHLIGHTS

Cerebrospinal fluid (CSF) proteome enriched for extracellular, neuronal, immune, and protein processing. Glucose/carbon metabolic pathways enriched among amyloid/tau-associated proteins. Key glucose/carbon metabolism protein associations independently replicated. CSF proteome outperformed other omics data in predicting amyloid/tau positivity. CSF metabolomics identified and replicated a succinylcarnitine-phosphorylated tau association.

Gaussian Process-based prediction of memory performance and biomarker status in ageing and Alzheimer's disease-A systematic model evaluation

Neuroimaging markers based on Magnetic Resonance Imaging (MRI) combined with various other measures (such as genetic covariates, biomarkers, vascular risk factors, neuropsychological tests etc.) might provide useful predictions of clinical outcomes during the progression towards Alzheimer's disease (AD). The use of multiple features in predictive frameworks for clinical outcomes has become increasingly prevalent in AD research. However, many studies do not focus on systematically and accurately evaluating combinations of multiple input features. Hence, the aim of the present work is to explore and assess optimal combinations of various features for MR-based prediction of (1) cognitive status and (2) biomarker positivity with a multi-kernel learning Gaussian process framework. The explored features and parameters included (A) combinations of brain tissues, modulation, smoothing, and image resolution; (B) incorporating demographics & clinical covariates; (C) the impact of the size of the training data set; (D) the influence of dimensionality reduction and the choice of kernel types. The approach was tested in a large German cohort including 959 subjects from the multicentric longitudinal study of cognitive impairment and dementia (DELCODE). Our evaluation suggests the best prediction of memory performance was obtained for a combination of neuroimaging markers, demographics, genetic information (ApoE4) and CSF biomarkers explaining 57% of outcome variance in out-of-sample predictions. The highest performance for Aβ42/40 status classification was achieved for a combination of demographics, ApoE4, and a memory score while usage of structural MRI further improved the classification of individual patient's pTau status.

Conjoint hepatobiliary-enterohepatic cycles for amyloid excretion and enhancing its drug-induced clearance: a systems biology approach to Alzheimer's disease

The liver is the major organ responsible for metabolism of amyloid-beta, the primary toxic misfolded protein responsible for Alzheimer's disease (AD). The present study focuses on the crucial role of liver in AD. We have developed a framework that formulates and integrates two reciprocal transport processes of amyloid, via hepato-biliary and enterohepatic circulations (EHC). Our system analysis approach shows that activating the liver X-receptor (LXR) can reduce amyloid-beta formation by increasing expression of the genes: ATP-binding-cassette-transporter (ABCA1) and Stearoyl-CoA-desaturase (SCD). Besides, activating the pregnane-X-receptor (PXR) can enhance the clearance of amyloid-beta by increasing the expression of the genes: ATP-Binding-Cassette-Superfamily-G-member-2 (ABCG2) and multidrug-resistance protein-1 (MDR1). We also identified receptor-like apical sodium-dependent bile-acid transporter (ASBT) of intestinal enterocyte, showing affinity towards amyloid-beta, suggesting amyloid-beta's possible reuptake from intestinal contents to the systemic circulation through this receptor. Further, we have performed protein-protein interaction to evaluate the binding affinity of amyloid-beta to these receptors. Moreover, we undertook molecular docking and molecular dynamic simulation of some repurposed drugs (rifampicin, 24-hydroxycholesterols, resveratrol, cilostazol) which can target the aforesaid receptors to enhance amyloid-beta's fecal clearance, reduce amyloid-beta formation, and prevent the reuptake of amyloid-beta from intestinal feces. Additionally, network pharmacology and synergism analysis were utilized to validate our hypothesis and identify the drug combinations, respectively. Gene-ontology investigation, network pharmacology, and consolidated pathway analysis validate the alteration of the above-mentioned gene expression profiles. Furthermore, our neuropharmacological synergism study identifies the optimal combination of the repurposed drugs. Finally, our findings on candidate drugs are substantiated by clinical-trial outcomes.Communicated by Ramaswamy H. Sarma.

Presence and Persistence of Perceived Subjective Cognitive Complaints and Incident Mild Cognitive Impairments Among Community-Residing Older Adults

OBJECTIVES

To examine whether Subjective Cognitive Complaints (SCCs) predicted incident mild cognitive impairment (MCI).

DESIGN

Prospective Study.

SETTING

Central Control of Mobility and Aging (CCMA), a cohort study of community-residing older adults.

PARTICIPANTS

Participants were dementia-free community-residing older adults.

MEASUREMENTS

SCCs were assessed at the baseline and via bi-monthly structured phone interviews during the first year using the Ascertain Dementia 8 (AD8). Nonpersistent status required one or two SCCs endorsements and Persistent status required three or more SCCs endorsements. Outcome, presence of mild cognitive impairments (MCI) was determined by established case conference diagnostic procedures. Participants were followed annually. Generalized estimating equations (GEE), logistic model type, were used to determine the odds of developing MCI during follow-up. SCCs served as the three-level predictor (no/nonpersistent/persistent) and cognitive status (MCI versus normal) as the binary outcome. Analyses were adjusted for age, sex, education, race, health status, depressive symptoms, and global cognition.

RESULTS

The sample (n=454; mean age=75.67 ± 6.43; %female=55.3) included 245 participants who reported no SCCs, 156 who reported 1-2 SCCs, and 53 who reported 3 or more SCCs. Sixty-eight participants developed MCI during follow-up. Results showed that compared to no SCCs, persistent SCCs, and nonpersistent SCCs were significantly associated with increased odds of developing MCI during follow-up.

CONCLUSIONS

The presence of SCCs regardless of their persistence was associated with increased odds of developing MCI even when adjusting for objectively-assessed cognitive performance.

Multimodal learning of clinically accessible tests to aid diagnosis of neurodegenerative disorders: a scoping review

With ageing populations around the world, there is a rapid rise in the number of people with Alzheimer's disease (AD) and Parkinson's disease (PD), the two most common types of neurodegenerative disorders. There is an urgent need to find new ways of aiding early diagnosis of these conditions. Multimodal learning of clinically accessible data is a relatively new approach that holds great potential to support early precise diagnosis. This scoping review follows the PRSIMA guidelines and we analysed 46 papers, comprising 11,750 participants, 3569 with AD, 978 with PD, and 2482 healthy controls; the recency of this topic was highlighted by nearly all papers being published in the last 5 years. It highlights the effectiveness of combining different types of data, such as brain scans, cognitive scores, speech and language, gait, hand and eye movements, and genetic assessments for the early detection of AD and PD. The review also outlines the AI methods and the model used in each study, which includes feature extraction, feature selection, feature fusion, and using multi-source discriminative features for classification. The review identifies knowledge gaps around the need to validate findings and address limitations such as small sample sizes. Applying multimodal learning of clinically accessible tests holds strong potential to aid the development of low-cost, reliable, and non-invasive methods for early detection of AD and PD.

Safety, tolerability, pharmacokinetics and effects of diet on AD16, a novel neuroinflammatory inhibitor for Alzheimer's disease: a randomized phase 1 study

BACKGROUND

AD16 is a Class 1.1 new drug candidate for Alzheimer's disease (AD), which has demonstrated potential benefits in AD by reducing neuroinflammation in preclinical studies. Herein, the pharmacokinetics (PK), safety, and tolerability of single and multiple-dose AD16 and the effect of food were assessed in healthy Chinese adults.

METHODS

Single-center, randomized, placebo-controlled, double-blind studies were conducted for single and multiple ascending doses. A total of 62 subjects were enrolled in single-dose groups; 10 each in 5, 10, 20, 30, and 40 mg groups, and 6 each in 60 and 80 mg dose groups. Twenty subjects were divided equally into 30 and 40 mg groups for the multiple-dose study. To determine the effect of a high-fat diet on AD16, 16 subjects were administered a single 20 mg dose of AD16 under the fasted and fed condition in a single-center, randomized, open-label, two-cycle, two-crossover study. Moreover, safety and PK parameters were also assessed.

RESULTS

Plasma exposure to a single oral dose of AD16 increased at an approximate dose-increasing rate. The pharmacodynamic dose of the AD16 can be maintained through the accumulation effect of the drug within the safety window. Compared to fasting, ingesting a high-fat meal decelerated the rate of AD16 absorption, albeit without effect on its overall absorption. No dose-related toxicities were seen in any of the studies, all treatment-emergent adverse events were grade I/II, and no serious adverse event occurred.

CONCLUSIONS

The present study exhibited favorable safety, tolerability, and PK profile of AD16, supporting its further research as a potential drug treatment for AD.

TRIAL REGISTRATION

ClinicalTrials.gov; NCT05787028, NCT05787041, NCT05806177. The SAD and FE studies were retrospectively registered on 28 March 2023. The MAD study was retrospectively registered on 10 April 2023.

The role of the indoles in microbiota-gut-brain axis and potential therapeutic targets: A focus on human neurological and neuropsychiatric diseases

At present, a large number of relevant studies have suggested that the changes in gut microbiota are related to the course of nervous system diseases, and the microbiota-gut-brain axis is necessary for the proper functioning of the nervous system. Indole and its derivatives, as the products of the gut microbiota metabolism of tryptophan, can be used as ligands to regulate inflammation and autoimmune response in vivo. In recent years, some studies have found that the levels of indole and its derivatives differ significantly between patients with central nervous system diseases and healthy individuals, suggesting that they may be important mediators for the involvement of the microbiota-gut-brain axis in the disease course. Tryptophan metabolites produced by gut microbiota are involved in multiple physiological reactions, take indole for example, it participates in the process of inflammation and anti-inflammatory effects through various cellular physiological activities mediated by aromatic hydrocarbon receptors (AHR), which can influence a variety of neurological and neuropsychiatric diseases. This review mainly explores and summarizes the relationship between indoles and human neurological and neuropsychiatric disorders, including ischemic stroke, Alzheimer's disease, Parkinson's disease, multiple sclerosis, cognitive impairment, depression and anxiety, and puts forward that the level of indoles can be regulated through various direct or indirect ways to improve the prognosis of central nervous system diseases and reverse the dysfunction of the microbiota-gut-brain axis. This article is part of the Special Issue on "Microbiome & the Brain: Mechanisms & Maladies".

Implications of gut and oral microbiota in neuroinflammatory responses in Alzheimer's disease

A diverse and stable microbiota promotes a healthy state, nevertheless, an imbalance in gut or oral bacterial composition, called dysbiosis, can cause gastrointestinal disorders, systemic inflammatory states and oxidative stress, among others. Recently, gut and oral dysbiosis has been linked to Alzheimer's disease (AD), which is considered the most common form of dementia and a public health priority due to its high prevalence and incidence. The aim of this review is to highlight the implications of gut and oral microbiota in the neuroinflammation characteristic of AD pathology and the subsequent cognitive impairment. It is a systematic review of the current literature obtained by searching the PubMed, Web of Science and Scopus databases. The characteristic intestinal dysbiosis in AD patients leads to increased permeability of the intestinal barrier and activates immune cells in the central nervous system due to translocation of microbiota-derived metabolites and/or bacteria into the circulation leading to increased neuroinflammation and neuronal loss, thus generating the cognitive impairment characteristic of AD. The presence in the central nervous system of Porphyromonas gingivalis can cause an increased neuroinflammation and beta-amyloid peptide accumulation.

Blood-Brain Barrier Breakdown in Alzheimer's Disease: Mechanisms and Targeted Strategies

The blood-brain barrier (BBB) is a unique and selective feature of the central nervous system's vasculature. BBB dysfunction has been observed as an early sign of Alzheimer's Disease (AD) before the onset of dementia or neurodegeneration. The intricate relationship between the BBB and the pathogenesis of AD, especially in the context of neurovascular coupling and the overlap of pathophysiology in neurodegenerative and cerebrovascular diseases, underscores the urgency to understand the BBB's role more deeply. Preserving or restoring the BBB function emerges as a potentially promising strategy for mitigating the progression and severity of AD. Molecular and genetic changes, such as the isoform ε4 of apolipoprotein E (ApoEε4), a significant genetic risk factor and a promoter of the BBB dysfunction, have been shown to mediate the BBB disruption. Additionally, receptors and transporters like the low-density lipoprotein receptor-related protein 1 (LRP1), P-glycoprotein (P-gp), and the receptor for advanced glycation end products (RAGEs) have been implicated in AD's pathogenesis. In this comprehensive review, we endeavor to shed light on the intricate pathogenic and therapeutic connections between AD and the BBB. We also delve into the latest developments and pioneering strategies targeting the BBB for therapeutic interventions, addressing its potential as a barrier and a carrier. By providing an integrative perspective, we anticipate paving the way for future research and treatments focused on exploiting the BBB's role in AD pathogenesis and therapy.

The Impact of Rhythmic Physical Activity on Mental Health and Quality of Life in Older Adults with and without Cognitive Impairment: A Systematic Review and Meta-Analysis

(1) Background: Nowadays, it is essential to implement new non-pharmacological strategies, such as rhythmic physical activity, to improve mental health and quality of life in both individuals experiencing normal brain aging and those with cognitive impairment. Therefore, the objective of this study is to identify the effects of rhythmic physical activity interventions on mental health and quality of life in older adults, with or without mild cognitive impairment; (2) Methods: We conducted a systematic review with a meta-analysis, searching the Pubmed, Scopus, Web of Science, and Cochrane Plus databases using specific keywords. We selected studies that included rhythmic physical activity as the primary intervention for patients aged 65 and above, with or without cognitive impairment. We assessed the methodological quality of the articles using the PEDro scale; (3) Results: Out of 961 identified studies, we included 11 in this review, all of which employed rhythmic physical activity as an intervention. The selected studies consistently measured depression, anxiety, and quality of life; (4) Conclusions: This review demonstrates that rhythmic physical activity can effectively improve depression, anxiety, and quality of life in older adults, whether or not they have mild cognitive impairment. However, it is worth noting that while we have identified beneficial outcomes, the evidence supporting the use of rhythmic physical activity in enhancing depression, anxiety, and quality of life in older adults with or without mild cognitive impairment remains somewhat limited.

Cardiovascular Disease and Alzheimer's Disease: The Heart-Brain Axis

Cardiovascular disease (CVD) remains one of the leading causes of morbidity and mortality in aging adults across the United States. Prior studies indicate that the presence of atherosclerosis, the pathogenic basis of CVD, is linked with dementias. Alzheimer's disease (AD) and AD-related dementias are a major public health challenge in the United States. Recent studies indicate that ≈3.7 million Americans ≥65 years of age had clinical AD in 2017, with projected increases to 9.3 million by 2060. Treatment options for AD remain limited. Development of disease-modifying therapies are challenging due, in part, to the long preclinical window of AD. The preclinical incubation period of AD starts in midlife, providing a critical window for identification and optimization of AD risk factors. Studies link AD with CVD risk factors such as hypertension, inflammation, and dyslipidemia. Both AD and CVD are progressive diseases with decades-long development periods. CVD can clinically manifest several years earlier than AD, making CVD and its risk factors a potential predictor of future AD. The current review focuses on the state of literature on molecular and metabolic pathways modulating the heart-brain axis underlying the potential association of midlife CVD risk factors and their effect on AD and related dementias. Further, we explore potential CVD/dementia preventive strategies during the window of opportunity in midlife and the future of research in the field in the multiomics and novel biomarker use era.

Synthesis and Bioevaluation of 2-Styrylquinoxaline Derivatives as Tau-PET Tracers

This study focused on designing and evaluating Tau-PET tracers for noninvasive positron emission computed tomography (PET) imaging of neurofibrillary tangles (NFTs), a hallmark pathology of Alzheimer's disease (AD). The tracers were synthesized with a 2-styrylquinoxaline scaffold and varying lengths of FPEG chains. The compound [18F]15, which had two ethoxy units, showed high affinity for recombinant K18-Tau aggregates (Ki = 41.48 nM) and the highest selectivity versus Aβ1-42 aggregates (8.83-fold). In vitro autoradiography and fluorescent staining profiles further validated the binding of [18F]15 or 15 toward NFTs in brain sections from AD patients and Tau-transgenic mice. In normal ICR mice, [18F]15 exhibited an ideal initial brain uptake (11.21% ID/g at 2 min) and moderate washout ratio (2.29), and micro-PET studies in rats confirmed its ability to penetrate the blood-brain barrier with the peak SUV value of 1.94 in the cortex. These results suggest that [18F]15 has the potential to be developed into a useful Tau-PET tracer for early AD diagnosis and evaluation of anti-Tau therapeutics.

The efficacy and safety of anti-Aβ agents for delaying cognitive decline in Alzheimer's disease: a meta-analysis

Background

This meta-analysis evaluates the efficacy and safety of amyloid-β (Aβ) targeted therapies for delaying cognitive deterioration in Alzheimer's disease (AD).

Methods

PubMed, EMBASE, the Cochrane Library, and ClinicalTrials.gov were systematically searched to identify relevant studies published before January 18, 2023.

Results

We pooled 33,689 participants from 42 studies. The meta-analysis showed no difference between anti-Aβ drugs and placebo in the Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog), and anti-Aβ drugs were associated with a high risk of adverse events [ADAS-Cog: MDs = -0.08 (-0.32 to 0.15), p = 0.4785; AEs: RR = 1.07 (1.02 to 1.11), p = 0.0014]. Monoclonal antibodies outperformed the placebo in delaying cognitive deterioration as measured by ADAS-Cog, Clinical Dementia Rating-Sum of Boxes (CDR-SB), Mini-Mental State Examination (MMSE) and Alzheimer's Disease Cooperative Study-Activities of Daily Living (ADCS-ADL), without increasing the risk of adverse events [ADAS-Cog: MDs = -0.55 (-0.89 to 0.21), p = 0.001; CDR-SB: MDs = -0.19 (-0.29 to -0.10), p < 0.0001; MMSE: MDs = 0.19 (0.00 to 0.39), p = 0.05; ADCS-ADL: MDs = 1.26 (0.84 to 1.68), p < 0.00001]. Intravenous immunoglobulin and γ-secretase modulators (GSM) increased cognitive decline in CDR-SB [MDs = 0.45 (0.17 to 0.74), p = 0.002], but had acceptable safety profiles in AD patients. γ-secretase inhibitors (GSI) increased cognitive decline in ADAS-Cog, and also in MMSE and ADCS-ADL. BACE-1 inhibitors aggravated cognitive deterioration in the outcome of the Neuropsychiatric Inventory (NPI). GSI and BACE-1 inhibitors caused safety concerns. No evidence indicates active Aβ immunotherapy, MPAC, or tramiprosate have effects on cognitive function and tramiprosate is associated with serious adverse events.

Conclusion

Current evidence does not show that anti-Aβ drugs have an effect on cognitive performance in AD patients. However, monoclonal antibodies can delay cognitive decline in AD. Development of other types of anti-Aβ drugs should be cautious.

Systematic Review Registration

PROSPERO (https://www.crd.york.ac.uk/prospero/), identifier CRD42023391596.

Discovery of triazole-bridged aryl adamantane analogs as an intriguing class of multifunctional agents for treatment of Alzheimer's disease

Alzheimer's disease (AD) is a progressive brain disorder associated with slow loss of brain functions leading to memory failure and modest changes in behavior. The multifactorial neuropathological condition is due to a depletion of cholinergic neurons and accumulation of amyloid-beta (Aβ) plaques. Recently, a multi-target-directed ligand (MTDL) strategy has emerged as a robust drug discovery tool to overcome current challenges. In this research work, we aimed to design and develop a library of triazole-bridged aryl adamantane analogs for the treatment of AD. All synthesized analogs were characterized and evaluated through various in vitro and in vivo biological studies. The optimal compounds 32 and 33 exhibited potent inhibitory activities against acetylcholinesterase (AChE) (32 - IC50 = 0.086 μM; 33 - 0.135 μM), and significant Aβ aggregation inhibition (20 μM). N-methyl-d-aspartate (NMDA) receptor (GluN1-1b/GluN2B subunit combination) antagonistic activity of compounds 32 and 33 measured upon heterologous expression in Xenopus laevis oocytes showed IC50 values of 3.00 μM and 2.86 μM, respectively. The compounds possessed good blood-brain barrier permeability in the PAMPA assay and were safe for SH-SY5Y neuroblastoma (10 μM) and HEK-293 cell lines (30 μM). Furthermore, in vivo behavioral studies in rats demonstrated that both compounds improved cognitive and spatial memory impairment at a dose of 10 mg/kg oral administration. Together, our findings suggest triazole-bridged aryl adamantane as a promising new scaffold for the development of anti-Alzheimer's drugs.

The bexarotene derivative OAB-14 ameliorates cognitive decline in APP/PS1 transgenic mice by suppressing microglia-mediated neuroinflammation through the PPAR-γ pathway

Neuroinflammation is believed to be a critical process involved in the pathophysiology of Alzheimer's disease (AD). In this study, we investigated the pharmacological ability of OAB-14, a small molecule compound derived from bexarotene, to reduce neuroinflammation and improve cognitive decline in an AD mouse model (in vivo) and its ability to regulate signaling pathways implicated in neuroinflammation in vitro. It was found that OAB-14 significantly improved the cognitive function of 11-month-old AD mice (APP/PS1 transgenic mice) in a dose-dependent manner. Simultaneously, OAB-14 dramatically inhibited the activation of microglia in the cerebral cortex and hippocampus of AD mice and dose-dependently downregulated the expression of nuclear factor kappa B (NF-κB) and NOD-like receptor protein 3 (NLRP3) in the cerebral cortex. At the cellular level, OAB-14 reversed the downregulation of M2 phenotypic markers, including mannose receptor C-type 1 (MRC1) and arginase 1 (ARG1), in lipopolysaccharide (LPS)- or amyloid-β protein oligomer (oAβ1-42)-activated BV2 microglial cells and partially restored their ability to clear Aβ. However, these effects were suppressed when peroxisome proliferator-activated receptor-γ (PPAR-γ) was specifically inhibited by GW9662, a selective PPAR-γ antagonist. These results suggested that OAB-14 could regulate microglial polarization by regulating PPAR-γ signaling, thereby mitigating neuroinflammation and improving cognitive function in AD mice.

Using a dual-stream attention neural network to characterize mild cognitive impairment based on retinal images

Mild cognitive impairment (MCI) is a critical transitional stage between normal cognition and dementia, for which early detection is crucial for timely intervention. Retinal imaging has been shown as a promising potential biomarker for MCI. This study aimed to develop a dual-stream attention neural network to classify individuals with MCI based on multi-modal retinal images. Our approach incorporated a cross-modality fusion technique, a variable scale dense residual model, and a multi-classifier mechanism within the dual-stream network. The model utilized a residual module to extract image features and employed a multi-level feature aggregation method to capture complex context information. Self-attention and cross-attention modules were utilized at each convolutional layer to fuse features from optical coherence tomography (OCT) and fundus modalities, resulting in multiple output losses. The neural network was applied to classify individuals with MCI, Alzheimer's disease, and control participants with normal cognition. Through fine-tuning the pre-trained model, we classified community-dwelling participants into two groups based on cognitive impairment test scores. To identify retinal imaging biomarkers associated with accurate prediction, we used the Gradient-weighted Class Activation Mapping technique. The proposed method achieved high precision rates of 84.96% and 80.90% in classifying MCI and positive test scores for cognitive impairment, respectively. Notably, changes in the optic nerve head on fundus photographs or OCT images among patients with MCI were not used to discriminate patients from the control group. These findings demonstrate the potential of our approach in identifying individuals with MCI and emphasize the significance of retinal imaging for early detection of cognitive impairment.

Changes in late-life assistance networks for Black and White older adults during the COVID-19 pandemic

BACKGROUND

The COVID-19 pandemic has disproportionately impacted older Black Americans. Given that assistance networks play a crucial role in older adults' ability to respond to challenges, we sought to investigate whether older adults' assistance network size changed during the COVID-19 pandemic and differed by race.

METHODS

We analyzed data from the 2018-2020 rounds of the U.S. National Health and Aging Trends Study for Black and White adults aged 70 and older receiving help in the community or residential care settings. We used ordinary least squares regression to compare changes in assistance network size in the 2 years pre-COVID-19 (2018-2019, N = 3438) to changes in size at the onset of COVID-19 (2019-2020, N = 3185).

RESULTS

Black older adults had larger assistance networks with a greater number of family helpers before and during the pandemic compared to their White counterparts. Assistance network size for older adults increased before but not during the pandemic mostly due to declines in unpaid nonrelative helpers and lack of increase in paid helpers. These effects did not differ by race.

CONCLUSIONS

Black and White older adults experienced similarly sized reductions in their assistance networks as a consequence of the COVID-19 pandemic. Future research should investigate the relationship between these network changes and the unmet needs of older adults.

Women's Brain Health: Midlife Ovarian Removal Affects Associative Memory

Women with early bilateral salpingo-oophorectomy (BSO; removal of ovaries and fallopian tubes) have greater Alzheimer's disease (AD) risk than women in spontaneous/natural menopause (SM), but early biomarkers of this risk are not well-characterized. Considering associative memory deficits may presage preclinical AD, we wondered if one of the earliest changes might be in associative memory and whether younger women with BSO had changes similar to those observed in SM. Women with BSO (with and without 17β-estradiol replacement therapy (ERT)), their age-matched premenopausal controls (AMC), and older women in SM completed a functional magnetic resonance imaging face-name associative memory task shown to predict early AD. Brain activation during encoding was compared between groups: AMC (n=25), BSO no ERT (BSO; n=15), BSO+ERT (n=16), and SM without hormone therapy (n=16). Region-of-interest analyses revealed AMC did not contribute to functional group differences. BSO+ERT had higher hippocampal activation than BSO and SM. This hippocampal activation correlated positively with urinary metabolite levels of 17β-estradiol. Multivariate partial least squares analyses showed BSO+ERT had a different network-level activation pattern than BSO and SM. Thus, despite being approximately 10 years younger, women with BSO without ERT had similar brain function to those with SM, suggesting early 17β-estradiol loss may lead to an altered functional brain phenotype which could influence late-life AD risk, making face-name encoding a potential biomarker for midlife women with increased AD risk. Despite similarities in activation, BSO and SM groups showed opposite within-hippocampus connectivity, suggesting menopause type is an important consideration when assessing brain function.

Grey matter volume and CSF biomarkers predict neuropsychological subtypes of MCI

There is increasing evidence of different subtypes of individuals with mild cognitive impairment (MCI). An important line of research is whether neuropsychologically-defined subtypes have distinct patterns of neurodegeneration and cerebrospinal fluid (CSF) biomarker composition. In our study, we demonstrated that MCI participants of the ADNI database (N = 640) can be discriminated into 3 coherent neuropsychological subgroups. Our clustering approach revealed amnestic MCI, mixed MCI, and cluster-derived normal subgroups. Furthermore, classification modeling revealed that specific predictive features can be used to differentiate amnestic and mixed MCI from cognitively normal (CN) controls: CSF Aβ142 concentration for the former and CSF Aβ1-42 concentration, tau concentration as well as grey matter atrophy (especially in the temporal and occipital lobes) for the latter. In contrast, participants from the cluster-derived normal subgroup exhibited an identical profile to CN controls in terms of cognitive performance, brain structure, and CSF biomarker levels. Our comprehensive data analytics strategy provides further evidence that multimodal neuropsychological subtyping is both clinically and neurobiologically meaningful.

Role of GSK-3β Inhibitors: New Promises and Opportunities for Alzheimer's Disease

Glycogen synthase kinase-3 (GSK-3) was discovered to be a multifunctional enzyme involved in a wide variety of biological processes, including early embryo formation, oncogenesis, as well cell death in neurodegenerative diseases. Several critical cellular processes in the brain are regulated by the GSK-3β, serving as a central switch in the signaling pathways. Dysregulation of GSK-3β kinase has been reported in diabetes, cancer, Alzheimer's disease, schizophrenia, bipolar disorder, inflammation, and Huntington's disease. Thus, GSK-3β is widely regarded as a promising target for therapeutic use. The current review article focuses mainly on Alzheimer's disease, an age-related neurodegenerative brain disorder. GSK-3β activation increases amyloid-beta (Aβ) and the development of neurofibrillary tangles that are involved in the disruption of material transport between axons and dendrites. The drug-binding cavities of GSK-3β are explored, and different existing classes of GSK-3β inhibitors are explained in this review. Non-ATP competitive inhibitors, such as allosteric inhibitors, can reduce the side effects compared to ATP-competitive inhibitors. Whereas ATP-competitive inhibitors produce disarrangement of the cytoskeleton, neurofibrillary tangles formation, and lead to the death of neurons, etc. This could be because they are binding to a site separate from ATP. Owing to their interaction in particular and special binding sites, allosteric ligands interact with substrates more selectively, which will be beneficial in resolving drug-induced resistance and also helpful in reducing side effects. Hence, in this review, we focussed on the allosteric GSK-3β inhibitors and discussed their futuristic opportunities as anti-Alzheimer's compounds.

Explainable Machine Learning with Pairwise Interactions for Predicting Conversion from Mild Cognitive Impairment to Alzheimer's Disease Utilizing Multi-Modalities Data

BACKGROUND

Predicting cognition decline in patients with mild cognitive impairment (MCI) is crucial for identifying high-risk individuals and implementing effective management. To improve predicting MCI-to-AD conversion, it is necessary to consider various factors using explainable machine learning (XAI) models which provide interpretability while maintaining predictive accuracy. This study used the Explainable Boosting Machine (EBM) model with multimodal features to predict the conversion of MCI to AD during different follow-up periods while providing interpretability.

METHODS

This retrospective case-control study is conducted with data obtained from the ADNI database, with records of 1042 MCI patients from 2006 to 2022 included. The exposures included in this study were MRI biomarkers, cognitive scores, demographics, and clinical features. The main outcome was AD conversion from aMCI during follow-up. The EBM model was utilized to predict aMCI converting to AD based on three feature combinations, obtaining interpretability while ensuring accuracy. Meanwhile, the interaction effect was considered in the model. The three feature combinations were compared in different follow-up periods with accuracy, sensitivity, specificity, and AUC-ROC. The global and local explanations are displayed by importance ranking and feature interpretability plots.

RESULTS

The five-years prediction accuracy reached 85% (AUC = 0.92) using both cognitive scores and MRI markers. Apart from accuracies, we obtained features' importance in different follow-up periods. In early stage of AD, the MRI markers play a major role, while for middle-term, the cognitive scores are more important. Feature risk scoring plots demonstrated insightful nonlinear interactive associations between selected factors and outcome. In one-year prediction, lower right inferior temporal volume (<9000) is significantly associated with AD conversion. For two-year prediction, low left inferior temporal thickness (<2) is most critical. For three-year prediction, higher FAQ scores (>4) is the most important. During four-year prediction, APOE4 is the most critical. For five-year prediction, lower right entorhinal volume (<1000) is the most critical feature.

CONCLUSIONS

The established glass-box model EBMs with multimodal features demonstrated a superior ability with detailed interpretability in predicting AD conversion from MCI. Multi features with significant importance were identified. Further study may be of significance to determine whether the established prediction tool would improve clinical management for AD patients.

Progressive mechanical and structural changes in anterior cerebral arteries with Alzheimer's disease

Alzheimer's disease (AD) is a neurodegenerative disease and the main cause for dementia. The irreversible neurodegeneration leads to a gradual loss of brain function characterized predominantly by memory loss. Cerebrovascular changes are common neuropathologic findings in aged subjects with dementia. Cerebrovascular integrity is critical for proper metabolism and perfusion of the brain, as cerebrovascular remodeling may render the brain more susceptible to pulse pressure and may be associated with poorer cognitive performance and greater risk of cerebrovascular events. The objective of this study is to provide understanding of cerebrovascular remodeling with AD progression. Anterior cerebral arteries (ACAs) from a total of 19 brain donor participants from controls and pathologically diagnosed AD groups (early-Braak stages I-II; intermediate-Braak stages III-IV; and advanced-Braak stages V-VI) were included in this study. Mechanical testing, histology, advanced optical imaging, and mass spectrometry were performed to study the progressive structural and functional changes of ACAs with AD progression. Biaxial extension-inflation tests showed that ACAs became progressively less compliant, and the longitudinal stress in the intermediate and advanced AD groups was significantly higher than that from the control group. With pathological AD development, the inner and outer diameters of the ACAs remained almost unchanged; however, histology study revealed progressive smooth muscle cell atrophy and loss of elastic fibers which led to compromised structural integrity of the arterial wall. Multiphoton imaging demonstrated elastin degradation at the media-adventitia interface, which led to the formation of an empty band of 21.0 ± 15.4 μm and 32.8 ± 9.24 μm in width for the intermediate and advanced AD groups, respectively. Furthermore, quantitative birefringence microscopy showed disorganized adventitial collagen with AD development. Mass spectrometry analysis provided further evidence of altered collagen content and other extracellular matrix (ECM) molecule and smooth muscle cell changes that were consistent with the mechanical and structural alterations. Collectively, our study provides understanding of the mechanical and structural cerebrovascular deterioration in cerebral arteries with AD, which may be related to neurodegenration and pathology in the brain.

Brain Structure-Function Fusing Representation Learning Using Adversarial Decomposed-VAE for Analyzing MCI

Integrating the brain structural and functional connectivity features is of great significance in both exploring brain science and analyzing cognitive impairment clinically. However, it remains a challenge to effectively fuse structural and functional features in exploring the complex brain network. In this paper, a novel brain structure-function fusing-representation learning (BSFL) model is proposed to effectively learn fused representation from diffusion tensor imaging (DTI) and resting-state functional magnetic resonance imaging (fMRI) for mild cognitive impairment (MCI) analysis. Specifically, the decomposition-fusion framework is developed to first decompose the feature space into the union of the uniform and unique spaces for each modality, and then adaptively fuse the decomposed features to learn MCI-related representation. Moreover, a knowledge-aware transformer module is designed to automatically capture local and global connectivity features throughout the brain. Also, a uniform-unique contrastive loss is further devised to make the decomposition more effective and enhance the complementarity of structural and functional features. The extensive experiments demonstrate that the proposed model achieves better performance than other competitive methods in predicting and analyzing MCI. More importantly, the proposed model could be a potential tool for reconstructing unified brain networks and predicting abnormal connections during the degenerative processes in MCI.

Clinical safety and efficacy of allogenic human adipose mesenchymal stromal cells-derived exosomes in patients with mild to moderate Alzheimer's disease: a phase I/II clinical trial

Background

There have been no effective treatments for slowing or reversing Alzheimer's disease (AD) until now. Growing preclinical evidence, including this study, suggests that mesenchymal stem cells-secreted exosomes (MSCs-Exos) have the potential to cure AD.

Aims

The first three-arm, drug-intervention, phase I/II clinical trial was conducted to explore the safety and efficacy of allogenic human adipose MSCs-Exos (ahaMSCs-Exos) in patients with mild to moderate AD.

Methods

The eligible subjects were assigned to one of three dosage groups, intranasally administrated with ahaMSCs-Exos two times per week for 12 weeks, and underwent follow-up visits at weeks 16, 24, 36 and 48.

Results

No adverse events were reported. In the medium-dose arm, Alzheimer's Disease Assessment Scale-Cognitive section (ADAS-cog) scores decreased by 2.33 (1.19) and the basic version of Montreal Cognitive Assessment scores increased by 2.38 (0.58) at week 12 compared with baseline levels, indicating improved cognitive function. Moreover, the ADAS-cog scores in the medium-dose arm decreased continuously by 3.98 points until week 36. There were no significant differences in altered amyloid or tau deposition among the three arms, but hippocampal volume shrank less in the medium-dose arm to some extent.

Conclusions

Intranasal administration of ahaMSCs-Exos was safe and well tolerated, and a dose of at least 4×108 particles could be selected for further clinical trials.

Trial registration number

NCT04388982.

Association of Lung Function With Cognitive Decline and Incident Dementia in the Atherosclerosis Risk in Communities Study

We examined the associations between lung function and incident dementia and cognitive decline in 12,688 participants in the ARIC Study who provided lung function measurements in 1990-1992. Cognitive tests were administered up to 7 times, and dementia was ascertained through 2019. We used shared parameter models to jointly fit proportional hazard models and linear mixed-effect models to estimate lung-function-associated dementia rate and cognitive change, respectively. Higher forced expiratory volume in 1 second (FEV1) and forced vital capacity (FVC) were associated with reduced dementia (n = 2,452 persons developed dementia); hazard ratios per 1-L increase in FEV1 and FVC were 0.79 (95% confidence interval (CI): 0.71, 0.89) and 0.81 (95% CI: 0.74, 0.89), respectively. Each 1-L increase in FEV1 and FVC was associated with a 0.08-standard deviation (SD) (95% CI: 0.05, 0.12) and a 0.05-SD (95% CI: 0.02, 0.07) attenuation of 30-year cognitive decline, respectively. A 1% increase in FEV1/FVC ratio was associated with 0.008-SD (95% CI: 0.004, 0.012) less cognitive decline. We observed statistical interaction between FEV1 and FVC, suggesting that cognitive declines depended on values of specific FEV1 and FVC (as compared with FEV1, FVC, or FEV1/FVC ratio models that suggested linear incremental associations). Our findings may have important implications for reducing the burden of cognitive decline that is attributable to environmental exposures and associated lung function impairment.

Quantitative Profiling Method for Oxylipins in Neurodegenerative Diseases by Liquid Chromatography Coupled with Tandem Mass Spectrometry

Aging is one of the major risk factors for many chronic diseases, including diabetes, neuropathy, hypertension, cancer, and neurodegenerative diseases. However, the mechanism behind aging and how aging affects a variety of disease progression remains unknown. Recent research demonstrated the cytochrome P450 (CYP)-epoxide hydrolase (EH) metabolites of polyunsaturated fatty acids (PUFAs) play a critical role in the abovementioned age-associated diseases. Therefore, aging could affect the abovementioned chronic diseases by modulating CYP-EH PUFA metabolism. Unfortunately, investigating how aging affects CYP-EH metabolism in human and mammalian models poses significant challenges. In this regard, we will use C. elegans as a model organism to investigate the aging effects on CYP-EH metabolism of PUFA, owing to its long history of being used to study aging and its associated benefits of conducting aging research. This project will develop analytical tools to measure the endogenous levels of CYP-EH PUFA metabolites in C. elegans using state-of-the-art ultra-performance liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS). These metabolites are very potent but present in low abundance. The dramatic increase in sensitivity in UPLC-MS/MS allows us to monitor these metabolites over the lifespan of C. elegans with minimum samples. Our results show that C. elegans produces similar CYP PUFA metabolites to mammals and humans using our SPE-UPLC-MS/MS method. We will also show that our method successfully determined the CYP-EH PUFA metabolites profile changes induced by the inhibition of C. elegans EH. The method developed from this project will significantly improve our understanding of the role of dietary PUFAs and associated metabolism on aging and neurodegeneration and will uncover new mechanisms of how aging affects neurodegeneration through the modulation of PUFA metabolic pathways.

Design, synthesis and molecular docking and ADME studies of novel hydrazone derivatives for AChE inhibitory, BBB permeability and antioxidant effects

Alzheimer's disease (AD) is a progressive and fatal neurodegenerative disease that is characterized by memory and cognitive impairments that predominantly affects the elderly and is the most common cause of dementia. As is known, the AChE enzyme consists of two parts. In this work, 10 new hydrazones (3a-3j) were designed and synthesized. Naphthalene, indole, benzofuran and benzothiophene rings were used to interact with the PAS region. 4-fluorophenyl and 4-fluorobenzyl structures were preferred for interaction with the CAS region. In biological activity studies, the AChE and BChE inhibitory potentials of all compounds were evaluated using the in vitro Ellman method. The biological evaluation showed that compounds 3i and 3j displayed significant activity against AChE. The compounds 3i and 3j displayed IC50 values of 0.034 and 0.027 µM against AChE, respectively. The reference drug donepezil (IC50 = 0.021 µM) also displayed a significant inhibition against AChE. In addition, the antioxidant activities of the compounds were also evaluated. Derivatives 3i and 3j, which emerged active from both in vitro activity studies, were subjected to in vitro PAMPA tests to determine BBB permeability. Further docking simulation also revealed that these compounds (3i, 3j and donepezil) interacted with the enzyme active site in a similar manner to donepezil. A few parameters derived from MD simulation trajectories were computed and validated for the protein-ligand complex's stability under the dynamic conditions.Communicated by Ramaswamy H. Sarma.

The use of neuroimaging techniques in the early and differential diagnosis of dementia

Dementia is a leading cause of disability and death worldwide. At present there is no disease modifying treatment for any of the most common types of dementia such as Alzheimer's disease (AD), Vascular dementia, Lewy Body Dementia (LBD) and Frontotemporal dementia (FTD). Early and accurate diagnosis of dementia subtype is critical to improving clinical care and developing better treatments. Structural and molecular imaging has contributed to a better understanding of the pathophysiology of neurodegenerative dementias and is increasingly being adopted into clinical practice for early and accurate diagnosis. In this review we summarise the contribution imaging has made with particular focus on multimodal magnetic resonance imaging (MRI) and positron emission tomography imaging (PET). Structural MRI is widely used in clinical practice and can help exclude reversible causes of memory problems but has relatively low sensitivity for the early and differential diagnosis of dementia subtypes. 18F-fluorodeoxyglucose PET has high sensitivity and specificity for AD and FTD, while PET with ligands for amyloid and tau can improve the differential diagnosis of AD and non-AD dementias, including recognition at prodromal stages. Dopaminergic imaging can assist with the diagnosis of LBD. The lack of a validated tracer for α-synuclein or TAR DNA-binding protein 43 (TDP-43) imaging remain notable gaps, though work is ongoing. Emerging PET tracers such as 11C-UCB-J for synaptic imaging may be sensitive early markers but overall larger longitudinal multi-centre cross diagnostic imaging studies are needed.

RORB, an Alzheimer's disease susceptibility gene, is associated with viral encephalitis, an Alzheimer's disease risk factor

BACKGROUND

Viral encephalitis increases later-life risk of Alzheimer's disease (AD) by a factor of 31.

METHODS

To further evaluate this finding, we examined the relationship of West Nile virus (WNV) to Alzheimer's disease in 50 US states. In addition, we performed a genome wide association study (GWAS) of viral encephalitis cases in UK Biobank (UKBB) to see if encephalitis genes might be related to AD.

RESULTS

WNV was significantly associated with deaths from Alzheimer's disease in 50 US states (r = 0.806, p < 0.001). One gene, RORB-AS1, was most significantly related on GWAS to viral encephalitis. RORB-AS1 (RORB Antisense RNA 1) is an RNA gene. Diseases associated with RORB-AS1 include childhood epilepsy and idiopathic generalized epilepsy. The closely related RORB (Related Orphan Receptor B) is a marker of selectively AD vulnerable excitatory neurons in the entorhinal cortex; these neurons are depleted and susceptible to neurofibrillary inclusions during AD progression. RORB variants significantly decreased the risk of AD, independent of the significant effects of epilepsy, age, and years of education. The total effect size of variant RORB on AD prevalence is small, 0.19%, probably the reason RORB has not turned up on genome wide association studies of AD. But the decrease in effect size on AD, no variant versus varian is larger 0.20-0.16%. To produce the 31-fold increase in AD risk associated with viral encephalitis, non-variant RORB may need to interact with encephalitis virus.

LIMITATIONS

A weakness in our correlative analysis is possible confounding by the ecological fallacy (or ecological inference fallacy), a logical fallacy in the interpretation of statistical data where inferences about the nature of individuals are derived from inference for the group to which those individuals belong. In this case, inferences about individuals are being drawn from the characteristics of U.S. states where they reside, rather than from the individuals themselves. A weakness in our GWAS is that UK Biobank had only 18 cases of viral encephalitis and none of these had AD.

CONCLUSION

data presented here confirm the association of viral encephalitis with AD and suggest that WNV infection is a significant AD risk factor. In addition, GWAS suggests that the gene RORB, an AD vulnerability factor, is significantly related to viral encephalitis.

FUTURE PROSPECTS

A human WNV vaccine could reduce Alzheimer's disease morbidity and mortality.

Effectiveness and Safety of Pattern Identification-Based Herbal Medicine for Alzheimer's Disease: A Systematic Review and Meta-Analysis

Objective: Alzheimer's disease (AD), the most common cause of dementia, has only symptomatic treatments in conventional Western medicine (WM). Disease-modifying drugs are still under development. This study evaluated the efficacy and safety of herbal medicine (HM) based on pattern identification (PI) as a whole system practice for treating AD. Methods: Thirteen databases were searched from inception to August 31, 2021. Twenty-seven randomized controlled trials (RCTs) with 2069 patients were included in the evidence synthesis. Results: The meta-analysis showed that, compared with WM, HM prescription based on PI, either alone or in combination with WM, could significantly improve the cognitive functions of AD patients (Mini-Mental State Examination [MMSE]-HM vs. WM: mean difference [MD] = 1.96, 95% confidence intervals [CIs]: 0.28-3.64, N = 981, I2 = 96%; HM+WM vs. WM: MD = 1.33, 95% CI: 0.57-2.09, N = 695, I2 = 68%) and their ability to perform activities of daily living (ADL-HM vs. WM: standardized mean difference [SMD] = 0.71, 95% CI: 0.04-1.38, N = 639, I2 = 94%; HM+WM vs. WM: SMD = 0.60, 95% CI: 0.27-0.93, N = 669, I2 = 76%). Duration-wise, 12 weeks of HM+WM were superior to 12 weeks of WM and 24 weeks of HM were superior to 24 weeks of WM. None of the included studies found any severe safety concerns. The odds of mild-to-moderate adverse events were marginally lower in HM than in WM (odds ratio = 0.34, 95% CI: 0.11-1.02, N = 689, I2 = 55%). Conclusion: Hence, prescribing PI-based HM is a safe and effective therapeutic option for AD, either as first-line therapy or adjuvant treatment. However, most of the included studies have a high or uncertain risk of bias. Thus, well-designed RCTs with proper blinding and placebo controls are needed.

The Impact of Online and Offline Social Support on the Mental Health of Carers of Persons with Cognitive Impairments

The carers of persons with cognitive impairments, including Alzheimer's have migrated to online platforms to seek help, yet studies on the use of online social support within the context of caregiving are underdeveloped. Guided by the social support theory, we examined the association of online and offline social support with depression and anxiety in the United States. Using a subsample from the 2017 and 2018 Health Information National Trends Survey (n = 264), we conducted ordered logistic regression to test mediation and moderation effects, which revealed that only offline, not online social support had a direct association with carers' mental health. In the moderation model, online social support interacted with life stressors, while offline social support interacted with caregiving burden. Findings are supported using a hybrid model that combines online and offline social support to improve carers' mental health.