Role of RAGE in Alzheimer’s Disease

Receptor for advanced glycation end products (RAGE) is a receptor of the immunoglobulin super family that plays various important roles under physiological and pathological conditions. Compelling evidence suggests that RAGE acts as both an inflammatory intermediary and a critical inducer of oxidative stress, underlying RAGE-induced Alzheimer-like pathophysiological changes that drive the process of Alzheimer’s disease (AD). A critical role of RAGE in AD includes beta-amyloid (Aβ) production and accumulation, the formation of neurofibrillary tangles, failure of synaptic transmission, and neuronal degeneration. The steady-state level of Aβ depends on the balance between production and clearance. RAGE plays an important role in the Aβ clearance. RAGE acts as an important transporter via regulating influx of circulating Aβ into brain, whereas the efflux of brain-derived Aβ into the circulation via BBB is implemented by LRP1. RAGE could be an important contributor to Aβ generation via enhancing the activity of β- and/or γ-secretases and activating inflammatory response and oxidative stress. However, sRAGE–Aβ interactions could inhibit Aβ neurotoxicity and promote Aβ clearance from brain. Meanwhile, RAGE could be a promoting factor for the synaptic dysfunction and neuronal circuit dysfunction which are both the material structure of cognition, and the physiological and pathological basis of cognition. In addition, RAGE could be a trigger for the pathogenesis of Aβ and tau hyper-phosphorylation which both participate in the process of cognitive impairment. Preclinical and clinical studies have supported that RAGE inhibitors could be useful in the treatment of AD. Thus, an effective measure to inhibit RAGE may be a novel drug target in AD.     

The Central Role of AMP-Kinase and Energy Homeostasis Impairment in Alzheimer’s Disease: A Multifactor Network Analysis

Alzheimer’s disease is the most common cause of dementia worldwide, affecting the elderly population. It is characterized by the hallmark pathology of amyloid-β deposition, neurofibrillary tangle formation, and extensive neuronal degeneration in the brain. Wealth of data related to Alzheimer’s disease has been generated to date, nevertheless, the molecular mechanism underlying the etiology and pathophysiology of the disease is still unknown. Here we described a method for the combined analysis of multiple types of genome-wide data aimed at revealing convergent evidence interest that would not be captured by a standard molecular approach. Lists of Alzheimer-related genes (seed genes) were obtained from different sets of data on gene expression, SNPs, and molecular targets of drugs. Network analysis was applied for identifying the regions of the human protein-protein interaction network showing a significant enrichment in seed genes, and ultimately, in genes associated to Alzheimer’s disease, due to the cumulative effect of different combinations of the starting data sets. The functional properties of these enriched modules were characterized, effectively considering the role of both Alzheimer-related seed genes and genes that closely interact with them. This approach allowed us to present evidence in favor of one of the competing theories about AD underlying processes, specifically evidence supporting a predominant role of metabolism-associated biological process terms, including autophagy, insulin and fatty acid metabolic processes in Alzheimer, with a focus on AMP-activated protein kinase. This central regulator of cellular energy homeostasis regulates a series of brain functions altered in Alzheimer’s disease and could link genetic perturbation with neuronal transmission and energy regulation, representing a potential candidate to be targeted by therapy.     

The Emerging Therapeutic Role of NGF in Alzheimer’s Disease

Alzheimer’s disease (AD) is the most common type of neurodegenerative dementia that affects the elderly population. Nerve growth factor (NGF) contributes to the survival, regeneration and death of neurons during aging and in neurodegenerative diseases. Recently, research has shown that NGF is related to the pathology, mechanisms and symptoms of AD. Therefore, there is a need to summarize the new advancements in NGF research and its potential therapeutic implications in AD. In this review, we will focus on NGF distribution, production, and function; the interaction of Aβ and NGF; and the effect of different therapy methods on AD. In summary, we hope to describe the experimental and clinical data demonstrating the important roles of NGF for AD treatment.     

Structural Interactions within the Default Mode Network Identified by Bayesian Network Analysis in Alzheimer’s Disease

Alzheimer’s disease (AD) is a well-known neurodegenerative disease that is associated with dramatic morphological abnormalities. The default mode network (DMN) is one of the most frequently studied resting-state networks. However, less is known about specific structural dependency or interactions among brain regions within the DMN in AD. In this study, we performed a Bayesian network (BN) analysis based on regional grey matter volumes to identify differences in structural interactions among core DMN regions in structural MRI data from 80 AD patients and 101 normal controls (NC). Compared to NC, the structural interactions between the medial prefrontal cortex (mPFC) and other brain regions, including the left inferior parietal cortex (IPC), the left inferior temporal cortex (ITC) and the right hippocampus (HP), were significantly reduced in the AD group. In addition, the AD group showed prominent increases in structural interactions from the left ITC to the left HP, the left HP to the right ITC, the right HP to the right ITC, and the right IPC to the posterior cingulate cortex (PCC). The BN models significantly distinguished AD patients from NC with 87.12% specificity and 81.25% sensitivity. We then used the derived BN models to examine the replicability and stability of AD-associated BN models in an independent dataset and the results indicated discriminability with 83.64% specificity and 80.49% sensitivity. The results revealed that the BN analysis was effective for characterising regional structure interactions and the AD-related BN models could be considered as valid and predictive structural brain biomarker models for AD. Therefore, our study can assist in further understanding the pathological mechanism of AD, based on the view of the structural network, and may provide new insights into classification and clinical application in the study of AD in the future.     

Targeting the mTOR Signaling Network for Alzheimer’s Disease Therapy

The mammalian target of rapamycin (mTOR) is a highly conserved serine/threonine kinase that can sense environmental stimuli such as growth factors, energy state, and nutrients. It is essential for cell growth, proliferation, and metabolism, but dysregulation of mTOR signaling pathway is also associated with a number of human diseases. Encouraging data from experiments have provided sufficient evidence for the relationship between the mTOR signaling pathway and Alzheimer’s disease (AD). Upregulation of mTOR signaling pathway is thought to play an important role in major pathological processes of AD. The mTOR inhibitors such as rapamycin have been proven to ameliorate the AD-like pathology and cognitive deficits effectively in a broad range of animal models. Application of mTOR inhibitors indicates the potential value of reducing mTOR activity as an innovative therapeutic strategy for AD. In this review, we will focus on the recent process in understanding mTOR signaling pathway and the vital involvement of this signaling pathway in the pathology of AD, and discuss the application of mTOR inhibitors as potential therapeutic agents for the treatment of AD.     

Cluster Analysis of Risk Factor Genetic Polymorphisms in Alzheimer’s Disease

Multiple genetic variants may contribute to the risk of developing Alzheimer’s disease. We have analyzed polymorphisms in 9 genes to determine whether particular combinations would contribute to this risk. The genes were APOE, LDLr, CST3, CTSD, TNF, BACE1, MAPT, STH, eNOS, and TFCP2. Three risk groups for the disease were identified. Risk group I was younger, was heterozygous for the CST3 (GA), CTSD2936 (AG), TNF -308 (AG) genetic variants. Risk group II was older, was homozygous for the −427 APOE promoter polymorphism (TT), and heterozygous for the MAPT deletion and for the STH variant (QR). Group III had both the youngest and oldest subjects, were heterozygous for the −863 (AC) and −1031 (CT) TNF promoter polymorphisms. All three groups carried the APOE 4 allele and were heterozygous for both BACE1 polymorphisms. The control groups were carriers of the APOE 3 allele and were homozygous for the BACE1 genetic variants. C. N. Randall, S. N. Morris, A. D. Winkie and G. R. Parker—STAR students. C. N. Randall, D. Strasburger, J. Prozonic, S. N. Morris, A. D. Winkie, G. R. Parker, D. Cheng and E. M. Fennell contributed equally to this study. Special issue article in honor of Dr. George DeVries.     

Tau Overexpression Impacts a Neuroinflammation Gene Expression Network Perturbed in Alzheimer’s Disease

Filamentous inclusions of the microtubule-associated protein, tau, define a variety of neurodegenerative diseases known as tauopathies, including Alzheimer’s disease (AD). To better understand the role of tau-mediated effects on pathophysiology and global central nervous system function, we extensively characterized gene expression, pathology and behavior of the rTg4510 mouse model, which overexpresses a mutant form of human tau that causes Frontotemporal dementia and parkinsonism linked to chromosome 17 (FTDP-17). We found that the most predominantly altered gene expression pathways in rTg4510 mice were in inflammatory processes. These results closely matched the causal immune function and microglial gene-regulatory network recently identified in AD. We identified additional gene expression changes by laser microdissecting specific regions of the hippocampus, which highlighted alterations in neuronal network activity. Expression of inflammatory genes and markers of neuronal activity changed as a function of age in rTg4510 mice and coincided with behavioral deficits. Inflammatory changes were tau-dependent, as they were reversed by suppression of the tau transgene. Our results suggest that the alterations in microglial phenotypes that appear to contribute to the pathogenesis of Alzheimer’s disease may be driven by tau dysfunction, in addition to the direct effects of beta-amyloid.     

REST and Neural Gene Network Dysregulation in iPSC Models of Alzheimer’s Disease

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Expression of Novel Alzheimer’s Disease Risk Genes in Control and Alzheimer’s Disease Brains

Late onset Alzheimer’s disease (LOAD) etiology is influenced by complex interactions between genetic and environmental risk factors. Large-scale genome wide association studies (GWAS) for LOAD have identified 10 novel risk genes: ABCA7, BIN1, CD2AP, CD33, CLU, CR1, EPHA1, MS4A6A, MS4A6E, and PICALM. We sought to measure the influence of GWAS single nucleotide polymorphisms (SNPs) and gene expression levels on clinical and pathological measures of AD in brain tissue from the parietal lobe of AD cases and age-matched, cognitively normal controls. We found that ABCA7, CD33, and CR1 expression levels were associated with clinical dementia rating (CDR), with higher expression being associated with more advanced cognitive decline. BIN1 expression levels were associated with disease progression, where higher expression was associated with a delayed age at onset. CD33, CLU, and CR1 expression levels were associated with disease status, where elevated expression levels were associated with AD. Additionally, MS4A6A expression levels were associated with Braak tangle and Braak plaque scores, with elevated expression levels being associated with more advanced brain pathology. We failed to detect an association between GWAS SNPs and gene expression levels in our brain series. The minor allele of rs3764650 in ABCA7 is associated with age at onset and disease duration, and the minor allele of rs670139 in MS4A6E was associated with Braak tangle and Braak plaque score. These findings suggest that expression of some GWAS genes, namely ABCA7, BIN1, CD33, CLU, CR1 and the MS4A family, are altered in AD brains.     

High Resolution Discovery Proteomics Reveals Candidate Disease Progression Markers of Alzheimer’s Disease in Human Cerebrospinal Fluid

Disease modifying treatments for Alzheimer’s disease (AD) constitute a major goal in medicine. Current trends suggest that biomarkers reflective of AD neuropathology and modifiable by treatment would provide supportive evidence for disease modification. Nevertheless, a lack of quantitative tools to assess disease modifying treatment effects remains a major hurdle. Cerebrospinal fluid (CSF) biochemical markers such as total tau, p-tau and Ab42 are well established markers of AD; however, global quantitative biochemical changes in CSF in AD disease progression remain largely uncharacterized. Here we applied a high resolution open discovery platform, dMS, to profile a cross-sectional cohort of lumbar CSF from post-mortem diagnosed AD patients versus those from non-AD/non-demented (control) patients. Multiple markers were identified to be statistically significant in the cohort tested. We selected two markers SME-1 (p<0.0001) and SME-2 (p = 0.0004) for evaluation in a second independent longitudinal cohort of human CSF from post-mortem diagnosed AD patients and age-matched and case-matched control patients. In cohort-2, SME-1, identified as neuronal secretory protein VGF, and SME-2, identified as neuronal pentraxin receptor-1 (NPTXR), in AD were 21% (p = 0.039) and 17% (p = 0.026) lower, at baseline, respectively, than in controls. Linear mixed model analysis in the longitudinal cohort estimate a decrease in the levels of VGF and NPTXR at the rate of 10.9% and 6.9% per year in the AD patients, whereas both markers increased in controls. Because these markers are detected by mass spectrometry without the need for antibody reagents, targeted MS based assays provide a clear translation path for evaluating selected AD disease-progression markers with high analytical precision in the clinic.     

Directed Network Motifs in Alzheimer’s Disease and Mild Cognitive Impairment

Directed network motifs are the building blocks of complex networks, such as human brain networks, and capture deep connectivity information that is not contained in standard network measures. In this paper we present the first application of directed network motifs in vivo to human brain networks, utilizing recently developed directed progression networks which are built upon rates of cortical thickness changes between brain regions. This is in contrast to previous studies which have relied on simulations and in vitro analysis of non-human brains. We show that frequencies of specific directed network motifs can be used to distinguish between patients with Alzheimer’s disease (AD) and normal control (NC) subjects. Especially interesting from a clinical standpoint, these motif frequencies can also distinguish between subjects with mild cognitive impairment who remained stable over three years (MCI) and those who converted to AD (CONV). Furthermore, we find that the entropy of the distribution of directed network motifs increased from MCI to CONV to AD, implying that the distribution of pathology is more structured in MCI but becomes less so as it progresses to CONV and further to AD. Thus, directed network motifs frequencies and distributional properties provide new insights into the progression of Alzheimer’s disease as well as new imaging markers for distinguishing between normal controls, stable mild cognitive impairment, MCI converters and Alzheimer’s disease.     

Role of Cholesterol in APP Metabolism and Its Significance in Alzheimer’s Disease Pathogenesis

Alzheimer’s disease (AD) is a complex multifactorial neurodegenerative disorder believed to be initiated by accumulation of amyloid β (Aβ)-related peptides derived from proteolytic processing of amyloid precursor protein (APP). Research over the past two decades provided a mechanistic link between cholesterol and AD pathogenesis. Genetic polymorphisms in genes regulating the pivotal points in cholesterol metabolism have been suggested to enhance the risk of developing AD. Altered neuronal membrane cholesterol level and/or subcellular distribution have been implicated in aberrant formation, aggregation, toxicity, and degradation of Aβ-related peptides. However, the results are somewhat contradictory and we still do not have a complete understanding on how cholesterol can influence AD pathogenesis. In this review, we summarize our current understanding on the role of cholesterol in regulating the production/function of Aβ-related peptides and also examine the therapeutic potential of regulating cholesterol homeostasis in the treatment of AD pathology.