Parahippocampal gyrus expression of endothelial and insulin receptor signaling pathway genes is modulated by Alzheimer's disease and normalized by treatment with anti-diabetic agents

A feasibility study of the combination of intranasal insulin with oral semaglutide for cognition in older adults with metabolic syndrome at high dementia risk- Study rationale and design

INTRODUCTION

We present the rationale and design of a double-blind placebo-controlled feasibility trial combining intranasal insulin (INI) with semaglutide, a GLP-1 receptor agonist, to improve cognition in older adults with metabolic syndrome (MetS) and mild cognitive impairment (MCI). Since both INI and dulaglutide have beneficial effects on the cerebrovascular disease (CVD), we anticipate that improved CVD will underlie the hypothesized cognitive benefits.

METHODS

This 12-months trial will include 80 older adults aged > 60 with MetS and MCI, randomized to 4 groups: INI/oral semaglutide, intranasal placebo/oral semaglutide, INI/oral placebo, and intranasal placebo/oral placebo. Feasibility of combining INI with semaglutide will be tested by examining the ease of use of INI (20IU, twice/day) with semaglutide (14 once daily), adherence, and safety profile are the efficacy of combination therapy on global cognition and neurobiological markers: cerebral blood flow, cerebral glucose utilization, white matter hyperintensities, Alzheimer's related blood biomarkers and expression of insulin signaling proteins measured in brain-derived exosomes. Efficacy will be assessed for the intent-to-treat sample.

DISCUSSION

This feasibility study is anticipated to provide the basis for a multi-center large-scale randomized clinical trial (RCT) of the cognitive benefits of the combination of INI with semaglutide in individuals enriched for CVD and at high dementia risk.

A review: effects of neurofeedback on patients with mild cognitive impairment (MCI), and Alzheimer's disease (AD)

Neurofeedback training (NFT) is a non-invasive method and has been shown to be effective for attention deficit/hyperactivity disorder (ADHD) and various psychiatric disorders. The aim of this paper is to evaluate the effectiveness of NFT for patients with Mild Cognitive Impairment (MCI) and Alzheimer's disease (AD) or Vascular Diseases (VD), so that we searched research articles from four databases, using the keywords neurofeedback, elderly, MCI, AD, VD, and dementia. As a result, 13 articles were identified regarding the effectiveness of NFT in patients with MCI and AD. Although each study differed in study design, training protocol, electroencephalogram (EEG) electrode placement, and reward and inhibition frequency bands, all were shown to enhance memory, attention, and other cognitive abilities. Additional well-designed, randomized studies with sufficient power are needed to further confirm the effectiveness of NFT.

A feasibility study of the combination of intranasal insulin with dulaglutide for cognition in older adults with metabolic syndrome at high dementia risk - Study rationale and design

INTRODUCTION

We present the rationale and design of a double-blind placebo-controlled feasibility trial combining intranasal insulin (INI) with dulaglutide, a GLP-1 receptor agonist, to improve cognition in older adults with metabolic syndrome (MetS) and mild cognitive impairment (MCI). Since both INI and dulaglutide have beneficial effects on the cerebrovascular disease (CVD), we anticipate that improved CVD will underlie the hypothesized cognitive benefits.

METHODS

This 12-months trial will include 80 older adults aged > 60 with MetS and MCI, randomized to 4 groups: INI/dulaglutide injection, intranasal placebo/dulaglutide injection, INI/placebo injection, and intranasal placebo/placebo injection. Feasibility of combining INI with dulaglutide will be tested by examining the ease of use of INI (20IU, twice/day) with dulaglutide (1.5 mg/week), adherence, and safety profile are the efficacy of combination therapy on global cognition and neurobiological markers: cerebral blood flow, cerebral glucose utilization, white matter hyperintensities, Alzheimer's related blood biomarkers and expression of insulin signaling proteins measured in brain-derived exosomes. Efficacy will be assessed for the intent-to-treat sample.

DISCUSSION

This feasibility study is anticipated to provide the basis for a multi-center large-scale randomized clinical trial of the cognitive benefits of the combination of INI with dulaglutide in individuals enriched for CVD and at high dementia risk.

Insulin resistance, cognition, and Alzheimer disease

Chronic diseases of aging are increasingly common. Dementia, often due to multiple etiologies including Alzheimer disease (AD), is at the forefront. Previous studies have reported higher rates of dementia among persons with diabetes, yet less is known about how insulin resistance relates to cognition. This article reviews recently published data on the relationship of insulin resistance to cognition and AD, and remaining knowledge gaps in the field are discussed. A structured review of studies was conducted over a 5-year period, investigating insulin and cognitive function in adults with a baseline mean age of ≥65 years. This search yielded 146 articles, of which 26 met the predetermined inclusion and exclusion criteria. Among the nine studies that specifically examined insulin resistance and cognitive dysfunction and/or decline, eight studies suggest an association, but some only in subanalyses. Results are mixed in studies relating insulin to structural and functional changes on brain imaging, and data on intranasal insulin for cognition remain unclear. Future avenues are proposed to elucidate the impact of insulin resistance on brain structure and function, including cognition, in persons with and without AD.

Multimodal data fusion based on IGERNNC algorithm for detecting pathogenic brain regions and genes in Alzheimer's disease

At present, the study on the pathogenesis of Alzheimer's disease (AD) by multimodal data fusion analysis has been attracted wide attention. It often has the problems of small sample size and high dimension with the multimodal medical data. In view of the characteristics of multimodal medical data, the existing genetic evolution random neural network cluster (GERNNC) model combine genetic evolution algorithm and neural network for the classification of AD patients and the extraction of pathogenic factors. However, the model does not take into account the non-linear relationship between brain regions and genes and the problem that the genetic evolution algorithm can fall into local optimal solutions, which leads to the overall performance of the model is not satisfactory. In order to solve the above two problems, this paper made some improvements on the construction of fusion features and genetic evolution algorithm in GERNNC model, and proposed an improved genetic evolution random neural network cluster (IGERNNC) model. The IGERNNC model uses mutual information correlation analysis method to combine resting-state functional magnetic resonance imaging data with single nucleotide polymorphism data for the construction of fusion features. Based on the traditional genetic evolution algorithm, elite retention strategy and large variation genetic algorithm are added to avoid the model falling into the local optimal solution. Through multiple independent experimental comparisons, the IGERNNC model can more effectively identify AD patients and extract relevant pathogenic factors, which is expected to become an effective tool in the field of AD research.

Sex Matters in Aging. The Canagliflozin Story

A promising and novel approach for identifying anti-aging therapeutics has been the repurposing of clinically approved and readily available drugs in mice. Canagliflozin, a clinically approved safe, and effective drug for type 2 diabetic patients, was recently shown to robustly retard age-related lesions in male mice but less so in female mice. While this type of sex disparity is often seen in the field of aging, it does represent a dilemma of not knowing the cause or how translationally relevant the sex differences would be in older humans treated with Canagliflozin. Thoughtful and mechanistic investigations are needed to understand why these differences are present and whether they can be eliminated by new drugs or drug combinations. Success in using repurposed drugs for aging intervention studies in humans will depend on preclinical research to uncover pathways that can be targeted for the benefit of both sexes.

Engagement of vascular early response genes typifies mild cognitive impairment

INTRODUCTION

Molecular responses in the brains of persons with mild cognitive impairment (MCI), the earliest transitional state between normal aging and early Alzheimer's disease (AD), are poorly understood.

METHODS

We examined AD-related neuropathology and transcriptome changes in the neocortex of individuals with MCI relative to controls and temporal responses to the mild hypoxia in mouse brains.

RESULTS

Subsets of vascular early response to hypoxia genes were upregulated in MCI prior to the buildup of AD neuropathology. Early activation of pro-angiogenic hypoxia-inducible factor signaling in response to mild hypoxia was detected in mouse brains similar to those that were altered in MCI. Protracted responses to hypoxia were characterized by activation of phosphoinositide 3-kinase (PI3K)-protein kinase B (Akt)-the mammalian target of rapamycin (mTOR) pathways in brain microvessel isolates.

DISCUSSION

These findings suggest that cerebrovascular remodeling is an important antecedent to the development of dementia and a component of the homeostatic response to reduced oxygen tension in aging prior to the onset of AD.

Multi-Modal Feature Selection with Feature Correlation and Feature Structure Fusion for MCI and AD Classification

Feature selection for multiple types of data has been widely applied in mild cognitive impairment (MCI) and Alzheimer's disease (AD) classification research. Combining multi-modal data for classification can better realize the complementarity of valuable information. In order to improve the classification performance of feature selection on multi-modal data, we propose a multi-modal feature selection algorithm using feature correlation and feature structure fusion (FC2FS). First, we construct feature correlation regularization by fusing a similarity matrix between multi-modal feature nodes. Then, based on manifold learning, we employ feature matrix fusion to construct feature structure regularization, and learn the local geometric structure of the feature nodes. Finally, the two regularizations are embedded in a multi-task learning model that introduces low-rank constraint, the multi-modal features are selected, and the final features are linearly fused and input into a support vector machine (SVM) for classification. Different controlled experiments were set to verify the validity of the proposed method, which was applied to MCI and AD classification. The accuracy of normal controls versus Alzheimer's disease, normal controls versus late mild cognitive impairment, normal controls versus early mild cognitive impairment, and early mild cognitive impairment versus late mild cognitive impairment achieve 91.85 ± 1.42%, 85.33 ± 2.22%, 78.29 ± 2.20%, and 77.67 ± 1.65%, respectively. This method makes up for the shortcomings of the traditional multi-modal feature selection based on subjects and fully considers the relationship between feature nodes and the local geometric structure of feature space. Our study not only enhances the interpretation of feature selection but also improves the classification performance, which has certain reference values for the identification of MCI and AD.

Targeting Common Signaling Pathways for the Treatment of Stroke and Alzheimer's: a Comprehensive Review

Neurodegenerative diseases such as stroke and Alzheimer's disease (AD) are two inter-related disorders that affect the neurons in the brain and central nervous system. Alzheimer's is a disease by undefined origin and causes. Stroke and its most common type, ischemic stroke (IS), occurs due to the blockade of cerebral blood vessels. As an important feature, both of disorders are associated with irreversible damages to the brain and nervous system. In this regard, finding common signaling pathways and the same molecular origin between these two diseases may be a promising way for their solution. On the basis of literature appraisal, the most common signaling cascades implicated in the pathogenesis of AD and stroke including notch, autophagy, inflammatory, and insulin signaling pathways were reviewed. Furthermore, current therapeutic strategies including natural and synthetic pharmaceuticals aiming modulation of respective signaling factors were scrutinized to ameliorate neural deficits in AD and stroke. Taken together, digging deeper in the common connections and signal targeting can be greatly helpful in understanding and unified treating of these disorders.

Reassessment of Pioglitazone for Alzheimer's Disease

Alzheimer's disease is a quintessential 'unmet medical need', accounting for ∼65% of progressive cognitive impairment among the elderly, and 700,000 deaths in the United States in 2020. In 2019, the cost of caring for Alzheimer's sufferers was $244B, not including the emotional and physical toll on caregivers. In spite of this dismal reality, no treatments are available that reduce the risk of developing AD or that offer prolonged mitiagation of its most devestating symptoms. This review summarizes key aspects of the biology and genetics of Alzheimer's disease, and we describe how pioglitazone improves many of the patholophysiological determinants of AD. We also summarize the results of pre-clinical experiments, longitudinal observational studies, and clinical trials. The results of animal testing suggest that pioglitazone can be corrective as well as protective, and that its efficacy is enhanced in a time- and dose-dependent manner, but the dose-effect relations are not monotonic or sigmoid. Longitudinal cohort studies suggests that it delays the onset of dementia in individuals with pre-existing type 2 diabetes mellitus, which small scale, unblinded pilot studies seem to confirm. However, the results of placebo-controlled, blinded clinical trials have not borne this out, and we discuss possible explanations for these discrepancies.

Brain insulin signaling and cerebrovascular disease in human postmortem brain

Insulin is an important hormone for brain function, and alterations in insulin metabolism may be associated with neuropathology. We examined associations of molecular markers of brain insulin signaling with cerebrovascular disease. Participants were enrolled in the Religious Orders Study (ROS), an ongoing epidemiologic community-based, clinical-pathologic study of aging from across the United States. Using cross-sectional analyses, we studied a subset of ROS: 150 persons with or without diabetes, matched 1:1 by sex on age-at-death and education. We used ELISA, immunohistochemistry, and ex vivo stimulation with insulin, to document insulin signaling in postmortem midfrontal gyrus cortex tissue. Postmortem neuropathologic data identified cerebrovascular disease including brain infarcts, classified by number (as none for the reference; one; and more than one), size (gross and microscopic infarcts), and brain region/location (cortical and subcortical). Cerebral vessel pathologies were assessed, including severity of atherosclerosis, arteriolosclerosis, and amyloid angiopathy. In separate regression analyses, greater AKT1 phosphorylation at T³⁰⁸ following ex vivo stimulation with insulin (OR = 1.916; estimate = 0.650; p = 0.007) and greater pS⁶¹⁶IRS1 immunolabeling in neuronal cytoplasm (OR = 1.610; estimate = 0.476; p = 0.013), were each associated with a higher number of brain infarcts. Secondary analyses showed consistent results for gross infarcts and microinfarcts separately, but no other association including by infarct location (cortical or subcortical). AKT S⁴⁷³ phosphorylation following insulin stimulation was associated with less amyloid angiopathy severity, but not with other vessel pathology including atherosclerosis and arteriolosclerosis. In summary, insulin resistance in the human brain, even among persons without diabetes, is associated with cerebrovascular disease and especially infarcts. The underlying pathophysiologic mechanisms need further elucidation. Because brain infarcts are known to be associated with lower cognitive function and dementia, these data are relevant to better understanding the link between brain metabolism and brain function.

Deterioration in Motor Function Over Time in Older Adults With Type 2 Diabetes is Associated with Accelerated Cognitive Decline

OBJECTIVE

Type 2 diabetes (T2D) is associated with motor impairments and a higher dementia risk. The relationships of motor decline with cognitive decline in T2D older adults has rarely been studied. Using data from the Israel Diabetes and Cognitive Decline study (N = 892), we examined associations of decline in motor function with cognitive decline over a 54-month period.

METHODS

Motor function measures were strength (handgrip) and gait speed (time to walk 3 m). Participants completed a neuropsychologic battery of 13 tests transformed into z-scores, summarized into 4 cognitive domains: episodic memory, attention/working memory, executive functions, and language/semantic categorization. The average of the 4 domains' z-scores defined global cognition. Motor and cognitive functions were assessed in 18-months intervals. A random coefficients model delineated longitudinal relationships of cognitive decline with baseline and change from baseline in motor function, adjusting for sociodemographic, cardiovascular, and T2D-related covariates.

RESULTS

Slower baseline gait speed levels were significantly associated with more rapid decline in global cognition (P = .004), language/semantic categorization (P = .006) and episodic memory (P = .029). Greater decline over time in gait speed was associated with an accelerated rate of decline in global cognition (P = .050), attention/working memory (P = .047) and language/semantic categorization (P<.001). Baseline strength levels were not associated with cognitive decline but the rate of declining strength was associated with an accelerated decline in executive functions (P = .025) and language/semantic categorization (P = .006).

CONCLUSION

In T2D older adults, the rate of decline in motor function, beyond baseline levels, was associated with accelerated cognitive decline, suggesting that cognitive and motor decline share common neuropathologic mechanisms in T2D.

Functional MRI-Specific Alterations in Executive Control Network in Mild Cognitive Impairment: An ALE Meta-Analysis

Background: Mild cognitive impairment (MCI) is regarded as a transitional stage between normal aging and Alzheimer's disease (AD) dementia. MCI individuals with deficits in executive function are at higher risk for progressing to AD dementia. Currently, there is no consistent result for alterations in the executive control network (ECN) in MCI, which makes early prediction of AD conversion difficult. The aim of the study was to find functional MRI-specific alterations in ECN in MCI patients by expounding on the convergence of brain regions with functional abnormalities in ECN.

Methods: We searched PubMed, Embase, and Web of Science to identify neuroimaging studies using methods including the amplitude of low frequency fluctuation/fractional amplitude of low-frequency fluctuation, regional homogeneity, and functional connectivity in MCI patients. Based on the Activation Likelihood Estimation algorithm, the coordinate-based meta-analysis and functional meta-analytic connectivity modeling were conducted.

Results: A total of 25 functional imaging studies with MCI patients were included in a quantitative meta-analysis. By summarizing the included articles, we obtained specific brain region changes, mainly including precuneus, cuneus, lingual gyrus, middle frontal gyrus, posterior cingulate cortex, and cerebellum posterior lobe, in the ECN based on these three methods. The specific abnormal brain regions indicated that there were interactions between the ECN and other networks.

Conclusions: This study confirms functional imaging specific abnormal markers in ECN and its interaction with other networks in MCI. It provides novel targets and pathways for individualized and precise interventions to delay the progression of MCI to AD.

IPSC-Derived Neuronal Cultures Carrying the Alzheimer's Disease Associated TREM2 R47H Variant Enables the Construction of an Aβ-Induced Gene Regulatory Network

Genes associated with immune response and inflammation have been identified as genetic risk factors for late-onset Alzheimer´s disease (LOAD). The rare R47H variant within triggering receptor expressed on myeloid cells 2 (TREM2) has been shown to increase the risk for developing Alzheimer’s disease (AD) 2–3-fold. Here, we report the generation and characterization of a model of late-onset Alzheimer’s disease (LOAD) using lymphoblast-derived induced pluripotent stem cells (iPSCs) from patients carrying the TREM2 R47H mutation, as well as from control individuals without dementia. All iPSCs efficiently differentiated into mature neuronal cultures, however AD neuronal cultures showed a distinct gene expression profile. Furthermore, manipulation of the iPSC-derived neuronal cultures with an Aβ-S8C dimer highlighted metabolic pathways, phagosome and immune response as the most perturbed pathways in AD neuronal cultures. Through the construction of an Aβ-induced gene regulatory network, we were able to identify an Aβ signature linked to protein processing in the endoplasmic reticulum (ER), which emphasized ER-stress, as a potential causal role in LOAD. Overall, this study has shown that our AD-iPSC based model can be used for in-depth studies to better understand the molecular mechanisms underlying the etiology of LOAD and provides new opportunities for screening of potential therapeutic targets.

Analysis of risk factors for depression in Alzheimer's disease patients

Purpose: Depression, which affects about 52% of Alzheimer's disease (AD) patients, can worsen cognitive impairment and increase mortality and suicide rates. We hope to provide clinical evidence for the prevention and treatment of depression in AD patients by investigating related risk factors of depression in AD patients.Methods: 158 AD inpatients of the Department of Neurology, Daping Hospital from September 2017 to March 2019 were enrolled. General information, laboratory tests, cognitive and emotional function assessments of the inpatients were collected. Logistic regression was used to analyze the risk factors of depression in AD patients, and the relationship between 17 Hamilton depression scale scores and HbA1c levels in AD patients was further analyzed.Results: The prevalence of age, gender, hypertension, hyperlipidemia, Type 2 diabetes mellitus (T2DM), and white matter lesions (WML) in the AD with depression group was significantly different from without depression group. Hypertension, T2DM, and WML are independent risk factors for depression in AD patients. The depression scores of AD patients with HbA1c>6.5% were significantly higher than AD patients with HbA1c ≤ 6.5%, and there were significant difference in depression scale scores between using anti-diabetes drugs group and not using anti-diabetes drugs group whose HbA1c level is >6.5%, while no difference in depression scores between using anti-diabetes drugs group and not using anti-diabetes drugs group whose HbA1c level is ≤6.5%.Conclusion: T2DM is an independent risk factor for AD patients with depression. Increased HbA1c levels aggravate depression in AD patients, and controlling HbA1c levels and anti-diabetes drugs can reduce the severity of depression in AD patients.

Mitochondrial dysfunction in Alzheimer's disease: Role in pathogenesis and novel therapeutic opportunities

Dysfunction of cell bioenergetics is a common feature of neurodegenerative diseases, the most common of which is Alzheimer's disease (AD). Disrupted energy utilization implicates mitochondria at its nexus. This review summarizes some of the evidence that points to faulty mitochondrial function in AD and highlights past and current therapeutic development efforts. Classical neuropathological hallmarks of disease (β-amyloid and τ) and sporadic AD risk genes (APOE) may trigger mitochondrial disturbance, yet mitochondrial dysfunction may incite pathology. Preclinical and clinical efforts have overwhelmingly centred on the amyloid pathway, but clinical trials have yet to reveal clear-cut benefits. AD therapies aimed at mitochondrial dysfunction are few and concentrate on reversing oxidative stress and cell death pathways. Novel research efforts aimed at boosting mitochondrial and bioenergetic function offer an alternative treatment strategy. Enhancing cell bioenergetics in preclinical models may yield widespread favourable effects that could benefit persons with AD. LINKED ARTICLES: This article is part of a themed section on Therapeutics for Dementia and Alzheimer's Disease: New Directions for Precision Medicine. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v176.18/issuetoc.

Combination of Insulin with a GLP1 Agonist Is Associated with Better Memory and Normal Expression of Insulin Receptor Pathway Genes in a Mouse Model of Alzheimer's Disease

Disruption of brain insulin signaling may explain the higher Alzheimer's disease (AD) risk among type 2 diabetic (T2D) patients. There is evidence from in vitro and human postmortem studies that combination of insulin with hypoglycemic medications is neuroprotective and associated with less amyloid aggregation. We examined the effect of 8-month intranasal administration of insulin, exenatide (a GLP-1 agonist), combination therapy (insulin + exenatide) or saline, in wild-type (WT) and an AD-like mouse model (Tg2576). Mice were assessed for learning, gene expression of key mediators and effectors of the insulin receptor signaling pathway (IRSP-IRS1, AKT1, CTNNB1, INSR, IRS2, GSK3B, IGF1R, AKT3), and brain Amyloid Beta (Aβ) levels. In Tg2576 mice, combination therapy reduced expression of IRSP genes which was accompanied by better learning. Cortical Aβ levels were decreased by 15-30% in all groups compared to saline but this difference did not reach statistical significance. WT mice groups, with or without treatment, did not differ in any comparison. Disentangling the mechanisms underlying the potential beneficial effects of combination therapy on the IR pathway and AD-like behavior is warranted.