Genetics of Alzheimer's disease: recent advances

CoQ10 and Mitochondrial Dysfunction in Alzheimer's Disease

The progress in understanding the pathogenesis and treatment of Alzheimer's disease (AD) is based on the recognition of the primary causes of the disease, which can be deduced from the knowledge of risk factors and biomarkers measurable in the early stages of the disease. Insights into the risk factors and the time course of biomarker abnormalities point to a role for the connection of amyloid beta (Aβ) pathology, tau pathology, mitochondrial dysfunction, and oxidative stress in the onset and development of AD. Coenzyme Q10 (CoQ10) is a lipid antioxidant and electron transporter in the mitochondrial electron transport system. The availability and activity of CoQ10 is crucial for proper mitochondrial function and cellular bioenergetics. Based on the mitochondrial hypothesis of AD and the hypothesis of oxidative stress, the regulation of the efficiency of the oxidative phosphorylation system by means of CoQ10 can be considered promising in restoring the mitochondrial function impaired in AD, or in preventing the onset of mitochondrial dysfunction and the development of amyloid and tau pathology in AD. This review summarizes the knowledge on the pathophysiology of AD, in which CoQ10 may play a significant role, with the aim of evaluating the perspective of the pharmacotherapy of AD with CoQ10 and its analogues.

The Inflammation-Induced Dysregulation of Reelin Homeostasis Hypothesis of Alzheimer's Disease

Alzheimer's disease (AD) accounts for most dementia cases, but we lack a complete understanding of the mechanisms responsible for the core pathology associated with the disease (e.g., amyloid plaque and neurofibrillary tangles). Inflammation has been identified as a key contributor of AD pathology, with recent evidence pointing towards Reelin dysregulation as being associated with inflammation. Here we describe Reelin signaling and outline existing research involving Reelin signaling in AD and inflammation. Research is described pertaining to the inflammatory and immunological functions of Reelin before we propose a mechanism through which inflammation renders Reelin susceptible to dysregulation resulting in the induction and exacerbation of AD pathology. Based on this hypothesis, it is predicted that disorders of both inflammation (including peripheral inflammation and neuroinflammation) and Reelin dysregulation (including disorders associated with upregulated Reelin expression and disorders of Reelin downregulation) have elevated risk of developing AD. We conclude with a description of AD risk in various disorders involving Reelin dysregulation and inflammation.

Use of Albumin for Drug Delivery as a Diagnostic and Therapeutic Tool

Drug delivery is an important topic that has attracted the attention of researchers in recent years. Albumin nanoparticles play a significant role in drug delivery as a carrier due to their unique characteristics. Albumin is non-toxic, biocompatible, and biodegradable. Its structure is such that it can interact with different drugs, which makes the treatment of the disease faster and also reduces the side effects of the drug. Albumin nanoparticles can be used in the diagnosis and treatment of many diseases, including cancer, diabetes, Alzheimer's, etc. These nanoparticles can connect to some compounds, such as metal nanoparticles, antibodies, folate, etc. and create a powerful nanostructure for drug delivery. In this paper, we aim to investigate albumin nanoparticles in carrier format for drug delivery application. In the beginning, different types of albumin and their preparation methods were discussed, and then albumin nanoparticles were discussed in detail in diagnosing and treating various diseases.

Contextualizing the Role of Osteopontin in the Inflammatory Responses of Alzheimer's Disease

Alzheimer's disease (AD) is characterized by progressive accumulations of extracellular amyloid-beta (Aβ) aggregates from soluble oligomers to insoluble plaques and hyperphosphorylated intraneuronal tau, also from soluble oligomers to insoluble neurofibrillary tangles (NFTs). Tau and Aβ complexes spread from the entorhinal cortex of the brain to interconnected regions, where they bind pattern recognition receptors on microglia and astroglia to trigger inflammation and neurotoxicity that ultimately lead to neurodegeneration and clinical AD. Systemic inflammation is initiated by Aβ's egress into the circulation, which may be secondary to microglial activation and can confer both destructive and reparative actions. Microglial activation pathways and downstream drivers of Aβ/NFT neurotoxicity, including inflammatory regulators, are primary targets for AD therapy. Osteopontin (OPN), an inflammatory cytokine and biomarker of AD, is implicated in Aβ clearance and toxicity, microglial activation, and inflammation, and is considered to be a potential therapeutic target. Here, using the most relevant works from the literature, we review and contextualize the evidence for a central role of OPN and associated inflammation in AD.

Fluorescence detection of apolipoprotein E gene polymorphisms based on oligonucleotide ligation and magnetic separation

Alzheimer's disease is a progressive neurodegenerative condition that causes brain cell death and is the leading cause of dementia. Most patients with Alzheimer's disease are diagnosed with late-onset Alzheimer's disease (LOAD), with apolipoprotein E (APOE) genotypes being highly associated with the frequency of LOAD risk. A fluorescence detection system coupled with oligonucleotide ligation and magnetic separation was developed to identify two single-nucleotide polymorphisms (SNPs) for the APOE gene and recognize APOE alleles for LOAD. The system utilized a fluorescence probe with one base-discriminating nucleoside for SNP (F probe) and a perfectly complementary biotin-modified sequence against the target DNA (P probe). When the F and P probes matched the target DNA sequences, DNA ligation occurred, and ligation products were produced. Streptavidin magnetic beads were subsequently employed to remove the ligation products, and a decrease in fluorescence intensity was observed in the supernatant compared to when there was no target DNA. This system detected two SNPs of APOE alleles, namely rs429358 and rs7412. The results indicated that the R-values ((F0 - F1)/F0) for rs429358 were 0.92 ± 0.002 for the T/T target, 0.47 ± 0.004 for the T/C target and 0.11 ± 0.004 for the C/C target, respectively. The R-values for rs7412 were 0.73 ± 0.009 for the C/C target, 0.42 ± 0.001 for the C/T target and 0.16 ± 0.007 for the T/T target, respectively. F0 and F1 represent the fluorescence intensity of the F probe without and with target DNA, respectively. Based on fluorescence intensity, the fluorescence detection system was able to identify the genotypes of the APOE gene accurately to evaluate the risk of Alzheimer's disease.

A meta-analysis of microarray datasets to identify biological regulatory networks in Alzheimer's disease

Background: Alzheimer's Disease (AD) is an age-related progressive neurodegenerative disorder characterized by mental deterioration, memory deficit, and multiple cognitive abnormalities, with an overall prevalence of ∼2% among industrialized countries. Although a proper diagnosis is not yet available, identification of miRNAs and mRNAs could offer valuable insights into the molecular pathways underlying AD's prognosis. Method: This study aims to utilize microarray bioinformatic analysis to identify potential biomarkers of AD, by analyzing six microarray datasets (GSE4757, GSE5281, GSE16759, GSE28146, GSE12685, and GSE1297) of AD patients, and control groups. Furthermore, this study conducted gene ontology, pathways analysis, and protein-protein interaction network to reveal major pathways linked to probable biological events. The datasets were meta-analyzed using bioinformatics tools, to identify significant differentially expressed genes (DEGs) and hub genes and their targeted miRNAs'. Results: According to the findings, CXCR4, TGFB1, ITGB1, MYH11, and SELE genes were identified as hub genes in this study. The analysis of DEGs using GO (gene ontology) revealed that these genes were significantly enriched in actin cytoskeleton regulation, ECM-receptor interaction, and hypertrophic cardiomyopathy. Eventually, hsa-mir-122-5p, hsa-mir-106a-5p, hsa-mir-27a-3p, hsa-mir16-5p, hsa-mir-145-5p, hsa-mir-12-5p, hsa-mir-128-3p, hsa-mir 3200-3p, hsa-mir-103a-3p, and hsa-mir-9-3p exhibited significant interactions with most of the hub genes. Conclusion: Overall, these genes can be considered as pivotal biomarkers for diagnosing the pathogenesis and molecular functions of AD.

A novel regulator in Alzheimer's disease progression: The astrocyte-derived extracellular vesicles

Alzheimer's disease (AD) is known as an age-related irreversible neurodegenerative disease. AD seriously endangers the health of the elderly, but there is still no effective treatment. In the past several decades, the significant role of astrocytes in the process of AD has been universally acknowledged. In addition, extracellular vesicles (EVs) have been recognized as an essential mediator in intercellular communication and participate in various pathophysiological processes by carrying and transporting diverse cargoes. Moreover, specific conditions and stimuli can modulate the amount and properties of astrocyte-derived EVs (ADEVs) to affect AD progression. Thus, recent studies focused on the involvement of ADEVs in the pathogenesis of AD and the potential application of ADEVs in the diagnosis and treatment of AD, which provides a new direction and possibility for revealing the mystery of AD. Interestingly, it can be concluded that ADEVs have both pathogenic and protective effects in the process of AD through a comprehensive generalization. In this review, we aim to summarize the multi-faces of ADEVs effects on AD development, which can provide a novel strategy to investigate the underlying mechanism in AD. We also summarize the current ADEVs clinically relevant studies to raise the potential use of ADEVs in the discovery of novel biomarkers for diagnosis and therapeutic targets for AD.

Linking the Amyloid, Tau, and Mitochondrial Hypotheses of Alzheimer's Disease and Identifying Promising Drug Targets

Damage or loss of brain cells and impaired neurochemistry, neurogenesis, and synaptic and nonsynaptic plasticity of the brain lead to dementia in neurodegenerative diseases, such as Alzheimer's disease (AD). Injury to synapses and neurons and accumulation of extracellular amyloid plaques and intracellular neurofibrillary tangles are considered the main morphological and neuropathological features of AD. Age, genetic and epigenetic factors, environmental stressors, and lifestyle contribute to the risk of AD onset and progression. These risk factors are associated with structural and functional changes in the brain, leading to cognitive decline. Biomarkers of AD reflect or cause specific changes in brain function, especially changes in pathways associated with neurotransmission, neuroinflammation, bioenergetics, apoptosis, and oxidative and nitrosative stress. Even in the initial stages, AD is associated with Aβ neurotoxicity, mitochondrial dysfunction, and tau neurotoxicity. The integrative amyloid-tau-mitochondrial hypothesis assumes that the primary cause of AD is the neurotoxicity of Aβ oligomers and tau oligomers, mitochondrial dysfunction, and their mutual synergy. For the development of new efficient AD drugs, targeting the elimination of neurotoxicity, mutual potentiation of effects, and unwanted protein interactions of risk factors and biomarkers (mainly Aβ oligomers, tau oligomers, and mitochondrial dysfunction) in the early stage of the disease seems promising.

Neuroinflammation represents a common theme amongst genetic and environmental risk factors for Alzheimer and Parkinson diseases

Multifactorial diseases are characterized by inter-individual variation in etiology, age of onset, and penetrance. These diseases tend to be relatively common and arise from the combined action of genetic and environmental factors; however, parsing the convoluted mechanisms underlying these gene-by-environment interactions presents a significant challenge to their study and management. For neurodegenerative disorders, resolving this challenge is imperative, given the enormous health and societal burdens they impose. The mechanisms by which genetic and environmental effects may act in concert to destabilize homeostasis and elevate risk has become a major research focus in the study of common disease. Emphasis is further being placed on determining the extent to which a unifying biological principle may account for the progressively diminishing capacity of a system to buffer disease phenotypes, as risk for disease increases. Data emerging from studies of common, neurodegenerative diseases are providing insights to pragmatically connect mechanisms of genetic and environmental risk that previously seemed disparate. In this review, we discuss evidence positing inflammation as a unifying biological principle of homeostatic destabilization affecting the risk, onset, and progression of neurodegenerative diseases. Specifically, we discuss how genetic variation associated with Alzheimer disease and Parkinson disease may contribute to pro-inflammatory responses, how such underlying predisposition may be exacerbated by environmental insults, and how this common theme is being leveraged in the ongoing search for effective therapeutic interventions.

Exploring the Involvement of the Amyloid Precursor Protein A673T Mutation against Amyloid Pathology and Alzheimer's Disease in Relation to Therapeutic Editing Tools

Alzheimer's disease (AD) is biologically defined as a complex neurodegenerative condition with a multilayered nature that leads to a progressive decline in cognitive function and irreversible neuronal loss. It is one of the primary diseases among elderly individuals. With an increasing incidence and a high failure rate for pharmaceutical options that are merely symptom-targeting and supportive with many side effects, there is an urgent need for alternative strategies. Despite extensive knowledge on the molecular basis of AD, progress concerning effective disease-modifying therapies has proven to be a challenge. The ability of the CRISPR-Cas9 gene editing system to help identify target molecules or to generate new preclinical disease models could shed light on the pathogenesis of AD and provide promising therapeutic possibilities. Here, we sought to highlight the current understanding of the involvement of the A673T mutation in amyloid pathology, focusing on its roles in protective mechanisms against AD, in relation to the recent status of available therapeutic editing tools.

Utility of Polygenic Risk Scoring to Predict Cognitive Impairment as Measured by Preclinical Alzheimer Cognitive Composite Score

Background

The utility of Polygenic Risk Scores (PRS) is gaining increasing attention for generating an individual genetic risk profile to predict subsequent likelihood of future onset of Alzheimer's disease (AD), especially those carry two copies of the APOE E3 allele, currently considered at neutral risk in all populations studied.

Objectives

To access the performance of PRS in predicting individuals whilst pre-symptomatic or with mild cognitive impairment who are at greatest risk of progression of cognitive impairment due to Alzheimer's Disease from the Alzheimer's Disease Neuroimaging Initiative (ADNI) as measured by the Preclinical Alzheimer Cognitive Composite (PACC) score profile. Design: A longitudinal analysis of data from the ADNI study conducted across over 50 sites in the US and Canada.

Setting

Multi-centre genetics study.

Participants

594 subjects either APOE E3 homozygotes or APOE E3/E4 heterozygotes who upon entry to the study were diagnosed as cognitively normal or with mild cognitive impairment.

Measurements

Use of genotyping and/or whole genome sequencing data to calculate polygenic risk scores and assess its ability to predict subsequent cognitive decline as measured by PACC over 5 years. Results: Assessing both cognitively normal and mild cognitive impaired subjects using a PRS threshold of greater than 0.6, the high genetic risk participant group declined more than the low risk group over 5 years as measured by PACC score (PACC score reduced by time).

Conclusions

Our findings have shown that polygenic risk score provides a promising tool to identify those with higher risk to decline over 5 years regardless of their APOE alleles according to modified PACC profile, especially its ability to identify APOE3/E3 cognitively normal individuals who are at most risk for early cognitive decline. This genotype accounts for approximately 60% of the general population and 35% of the AD population but currently would not be considered at higher risk without access to expensive or invasive biomarker testing.

Is the Exposome Involved in Brain Disorders through the Serotoninergic System?

Serotonin (5-hydroxytryptamine, 5-HT) is a biogenic monoamine acting as a neurotransmitter in the central nervous system (CNS), local mediator in the gut, and vasoactive agent in the blood. It has been linked to a variety of CNS functions and is implicated in many CNS and psychiatric disorders. The high comorbidity between some neuropathies can be partially understood by the fact that these diseases share a common etiology involving the serotoninergic system. In addition to its well-known functions, serotonin has been shown to be a mitogenic factor for a wide range of normal and tumor cells, including glioma cells, in vitro. The developing CNS of fetus and newborn is particularly susceptible to the deleterious effects of neurotoxic substances in our environment, and perinatal exposure could result in the later development of diseases, a hypothesis known as the developmental origin of health and disease. Some of these substances affect the serotoninergic system and could therefore be the source of a silent pandemic of neurodevelopmental toxicity. This review presents the available data that are contributing to the appreciation of the effects of the exposome on the serotoninergic system and their potential link with brain pathologies (neurodevelopmental, neurodegenerative, neurobehavioral disorders, and glioblastoma).

Interacting Models of Amyloid-β and Tau Proteins: An Approach to Identify Drug Targets in Alzheimer's Disease

Alzheimer's disease (AD) is the primary cause of dementia affecting millions each year across the world, though still remains incurable. This might be attributed to the lack of knowledge about the associated proteins, their cellular and molecular mechanisms, and the genesis of the disease. The discovery of drugs that earlier revolved around targeting the amyloid-β cascade has now been reformed with the upgraded knowledge of the cross-seeding ability of tau protein which opens new gateways for therapeutic targets. This article provides a comprehensive review of various direct and indirect connecting pathways between the two main proteins involved in development and progression of AD, enabling us to further expand our repertoire of information regarding the etiology of AD. The current review indicates the need for extensive research in this niche, thus considerable advances can be made in understanding AD which eventually helps to improve the current therapeutics against AD.

Mitochondrial dysfunction in neurodegenerative diseases: A focus on iPSC-derived neuronal models

Progressive neuronal loss is a hallmark of many neurodegenerative diseases, including Alzheimer's and Parkinson's disease. These pathologies exhibit clear signs of inflammation, mitochondrial dysfunction, calcium deregulation, and accumulation of aggregated or misfolded proteins. Over the last decades, a tremendous research effort has contributed to define some of the pathological mechanisms underlying neurodegenerative processes in these complex brain neurodegenerative disorders. To better understand molecular mechanisms responsible for neurodegenerative processes and find potential interventions and pharmacological treatments, it is important to have robust in vitro and pre-clinical animal models that can recapitulate both the early biological events undermining the maintenance of the nervous system and early pathological events. In this regard, it would be informative to determine how different inherited pathogenic mutations can compromise mitochondrial function, calcium signaling, and neuronal survival. Since post-mortem analyses cannot provide relevant information about the disease progression, it is crucial to develop model systems that enable the investigation of early molecular changes, which may be relevant as targets for novel therapeutic options. Thus, the use of human induced pluripotent stem cells (iPSCs) represents an exceptional complementary tool for the investigation of degenerative processes. In this review, we will focus on two neurodegenerative diseases, Alzheimer's and Parkinson's disease. We will provide examples of iPSC-derived neuronal models and how they have been used to study calcium and mitochondrial alterations during neurodegeneration.

Role of environmental pollutants in Alzheimer's disease: a review

Neurodegenerative disorders are commonly erratic influenced by various factors including lifestyle, environmental, and genetic factors. In recent observations, it has been hypothesized that exposure to various environmental factors enhances the risk of Alzheimer's disease (AD). The exact etiology of Alzheimer's disease is still unclear; however, the contribution of environmental factors in the pathology of AD is widely acknowledged. Based on the available literature, the review aims to culminate in the prospective correlation between the various environmental factors and AD. The prolonged exposure to the various well-known environmental factors including heavy metals, air pollutants (particulate matter), pesticides, nanoparticles containing metals, industrial chemicals results in accelerating the progression of AD. Common mechanisms have been documented in the field of environmental contaminants for enhancing amyloid-β (Aβ) peptide along with tau phosphorylation, resulting in the initiation of senile plaques and neurofibrillary tangles, which results in the death of neurons. This review offers a compilation of available data to support the long-suspected correlation between environmental risk factors and AD pathology. Graphical abstract .

Changes in Expression Profiles Revealed by Transcriptomic Analysis in Peripheral Blood Mononuclear Cells of Alzheimer's Disease Patients

Alzheimer's disease (AD) is an age-related neurodegenerative pathology associated with accumulation of DNA damage. Inflammation and cell cycle alterations seem to be implicated in the pathogenesis of AD, although the molecular mechanisms have not been thoroughly elucidated to date. The aim of the present study was to evaluate whether peripheral blood mononuclear cells (PBMCs) of AD patients display alterations in gene expression profiles, focusing on finding markers that might improve the diagnosis of AD. Blood samples were collected from 22 AD patients and 13 healthy individuals to perform genome-wide mRNA expression. We found 593 differentially expressed genes in AD compared to controls, from which 428 were upregulated, and 165 were downregulated. By performing a gene set enrichment analysis, we observed pathways involved in inflammation, DNA damage response, cell cycle, and neuronal processes. Moreover, functional annotation analyses indicated that differentially expressed genes are strongly related to pathways associated with the cell cycle and the immune system. The results were compared with those of an independent study on hippocampus samples, and a number of genes in common between both studies were identified as potential peripheral biomarkers for AD, including DUSP1, FOS, SLC7A2, RGS1, GFAP, CCL2, ANGPTL4, and SSPN. Taken together, our results demonstrate that PBMCs of AD patients do present alterations in gene expression profiles, and these results are comparable to those previously reported in the literature for AD neurons, supporting the hypothesis that blood peripheral mononuclear cells express molecular changes that occur in the neurons of AD patients.

Knowledge domain and emerging trends in Alzheimer's disease: a scientometric review based on CiteSpace analysis

Alzheimer's disease is the most common cause of dementia. It is an increasingly serious global health problem and has a significant impact on individuals and society. However, the precise cause of Alzheimer's disease is still unknown. In this study, 11,748 Web-of-Science-indexed manuscripts regarding Alzheimer's disease, all published from 2015 to 2019, and their 693,938 references were analyzed. A document co-citation network map was drawn using CiteSpace software. Research frontiers and development trends were determined by retrieving subject headings with apparent changing word frequency trends, which can be used to forecast future research developments in Alzheimer's disease.

Genome-wide association analysis of dementia and its clinical endophenotypes reveal novel loci associated with Alzheimer's disease and three causality networks: The GR@ACE project

INTRODUCTION

Large variability among Alzheimer's disease (AD) cases might impact genetic discoveries and complicate dissection of underlying biological pathways.

METHODS

Genome Research at Fundacio ACE (GR@ACE) is a genome-wide study of dementia and its clinical endophenotypes, defined based on AD's clinical certainty and vascular burden. We assessed the impact of known AD loci across endophenotypes to generate loci categories. We incorporated gene coexpression data and conducted pathway analysis per category. Finally, to evaluate the effect of heterogeneity in genetic studies, GR@ACE series were meta-analyzed with additional genome-wide association study data sets.

RESULTS

We classified known AD loci into three categories, which might reflect the disease clinical heterogeneity. Vascular processes were only detected as a causal mechanism in probable AD. The meta-analysis strategy revealed the ANKRD31-rs4704171 and NDUFAF6-rs10098778 and confirmed SCIMP-rs7225151 and CD33-rs3865444.

DISCUSSION

The regulation of vasculature is a prominent causal component of probable AD. GR@ACE meta-analysis revealed novel AD genetic signals, strongly driven by the presence of clinical heterogeneity in the AD series.

Effects of in vivo conditions on amyloid aggregation

One of the grand challenges of biophysical chemistry is to understand the principles that govern protein misfolding and aggregation, which is a highly complex process that is sensitive to initial conditions, operates on a huge range of length- and timescales, and has products that range from protein dimers to macroscopic amyloid fibrils. Aberrant aggregation is associated with more than 25 diseases, which include Alzheimer's, Parkinson's, Huntington's, and type II diabetes. Amyloid aggregation has been extensively studied in the test tube, therefore under conditions that are far from physiological relevance. Hence, there is dire need to extend these investigations to in vivo conditions where amyloid formation is affected by a myriad of biochemical interactions. As a hallmark of neurodegenerative diseases, these interactions need to be understood in detail to develop novel therapeutic interventions, as millions of people globally suffer from neurodegenerative disorders and type II diabetes. The aim of this review is to document the progress in the research on amyloid formation from a physicochemical perspective with a special focus on the physiological factors influencing the aggregation of the amyloid-β peptide, the islet amyloid polypeptide, α-synuclein, and the hungingtin protein.

Identifying Imaging Markers for Predicting Cognitive Assessments Using Wasserstein Distances Based Matrix Regression

Alzheimer's disease (AD) is a severe type of neurodegeneration which worsens human memory, thinking and cognition along a temporal continuum. How to identify the informative phenotypic neuroimaging markers and accurately predict cognitive assessment are crucial for early detection and diagnosis Alzheimer's disease. Regression models are widely used to predict the relationship between imaging biomarkers and cognitive assessment, and identify discriminative neuroimaging markers. Most existing methods use different matrix norms as the similarity measures of the empirical loss or regularization to improve the prediction performance, but ignore the inherent geometry of the cognitive data. To tackle this issue, in this paper we propose a novel robust matrix regression model with imposing Wasserstein distances on both loss function and regularization. It successfully integrate Wasserstein distance into the regression model, which can excavate the latent geometry of cognitive data. We introduce an efficient algorithm to solve the proposed new model with convergence analysis. Empirical results on cognitive data of the ADNI cohort demonstrate the great effectiveness of the proposed method for clinical cognitive predication.

Important advances in Alzheimer's disease from the use of induced pluripotent stem cells

Among the various types of dementia, Alzheimer’s disease (AD) is the most prevalent and is clinically defined as the appearance of progressive deficits in cognition and memory. Considering that AD is a central nervous system disease, getting tissue from the patient to study the disease before death is challenging. The discovery of the technique called induced pluripotent stem cells (iPSCs) allows to reprogram the patient’s somatic cells to a pluripotent state by the forced expression of a defined set of transcription factors. Many studies have shown promising results and made important conclusions beyond AD using iPSCs approach. Due to the accumulating knowledge related to this topic and the important advances obtained until now, we review, using PubMed, and present an update of all publications related to AD from the use of iPSCs. The first iPSCs generated for AD were carried out in 2011 by Yahata et al. (PLoS One 6:e25788, 2011) and Yaqi et al. (Hum Mol Genet 20:4530–9, 2011). Like other authors, both authors used iPSCs as a pre-clinical tool for screening therapeutic compounds. This approach is also essential to model AD, testing early toxicity and efficacy, and developing a platform for drug development. Considering that the iPSCs technique is relatively recent, we can consider that the AD field received valuable contributions from iPSCs models, contributing to our understanding and the treatment of this devastating disorder.

Long-Term Exposure to Ambient Hydrocarbons Increases Dementia Risk in People Aged 50 Years and above in Taiwan

BACKGROUND

Alzheimer's disease, the most common cause of dementia among the elderly, is a progressive and irreversible neurodegenerative disease. Exposure to air pollutants is known to have adverse effects on human health, however, little is known about hydrocarbons in the air that can trigger a dementia event.

OBJECTIVE

We aimed to investigate whether long-term exposure to airborne hydrocarbons increases the risk of developing dementia.

METHOD

The present cohort study included 178,085 people aged 50 years and older in Taiwan. Cox proportional hazards regression analysis was used to fit the multiple pollutant models for two targeted pollutants, including total hydrocarbons and non-methane hydrocarbons, and estimated the risk of dementia.

RESULTS

Before controlling for multiple pollutants, hazard ratios with 95% confidence intervals for the overall population were 7.63 (7.28-7.99, p <0.001) at a 0.51-ppm increases in total hydrocarbons, and 2.94 (2.82-3.05, p <0.001) at a 0.32-ppm increases in non-methane hydrocarbons. The highest adjusted hazard ratios for different multiple-pollutant models of each targeted pollutant were statistically significant (p <0.001) for all patients: 11.52 (10.86-12.24) for total hydrocarbons and 9.73 (9.18-10.32) for non-methane hydrocarbons.

CONCLUSION

Our findings suggest that total hydrocarbons and non-methane hydrocarbons may be contributing to dementia development.

Quantitative trait loci identification for brain endophenotypes via new additive model with random networks

Motivation

The identification of quantitative trait loci (QTL) is critical to the study of causal relationships between genetic variations and disease abnormalities. We focus on identifying the QTLs associated to the brain endophenotypes in imaging genomics study for Alzheimer's Disease (AD). Existing research works mainly depict the association between single nucleotide polymorphisms (SNPs) and the brain endophenotypes via the linear methods, which may introduce high bias due to the simplicity of the models. Since the influence of QTLs on brain endophenotypes is quite complex, it is desired to design the appropriate non-linear models to investigate the associations of genotypes and endophenotypes.

Results

In this paper, we propose a new additive model to learn the non-linear associations between SNPs and brain endophenotypes in Alzheimer's disease. Our model can be flexibly employed to explain the non-linear influence of QTLs, thus is more adaptive for the complex distribution of the high-throughput biological data. Meanwhile, as an important computational learning theory contribution, we provide the generalization error analysis for the proposed approach. Unlike most previous theoretical analysis under independent and identically distributed samples assumption, our error bound is based on m-dependent observations, which is more appropriate for the high-throughput and noisy biological data. Experiments on the data from Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort demonstrate the promising performance of our approach for identifying biological meaningful SNPs.

Availability and implementation

An executable is available at https://github.com/littleq1991/additive_FNNRW.

Stabilizing the Retromer Complex in a Human Stem Cell Model of Alzheimer's Disease Reduces TAU Phosphorylation Independently of Amyloid Precursor Protein

Developing effective therapeutics for complex diseases such as late-onset, sporadic Alzheimer’s disease (SAD) is difficult due to genetic and environmental heterogeneity in the human population and the limitations of existing animal models. Here, we used hiPSC-derived neurons to test a compound that stabilizes the retromer, a highly conserved multiprotein assembly that plays a pivotal role in trafficking molecules through the endosomal network. Using this human-specific system, we have confirmed previous data generated in murine models and show that retromer stabilization has a potentially beneficial effect on amyloid beta generation from human stem cell-derived neurons. We further demonstrate that manipulation of retromer complex levels within neurons affects pathogenic TAU phosphorylation in an amyloid-independent manner. Taken together, our work demonstrates that retromer stabilization is a promising candidate for therapeutic development in AD and highlights the advantages of testing novel compounds in a human-specific, neuronal system.

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A retromer stabilizing molecule reduces Aβ and phospho-TAU levels in human neurons

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The molecule reduces Aβ and pTau in both SAD and FAD cell lines

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Retromer stabilization reduces tau phosphorylation in an APP-independent manner

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Confirms studies in mice and highlights hiPSCs as a preclinical model

Human Induced Pluripotent Stem Cells and the Modelling of Alzheimer's Disease: The Human Brain Outside the Dish

BACKGROUND

Neurodegenerative diseases like Alzheimer's Disease (AD) are a global health issue primarily in the elderly. Although AD has been investigated using primary cultures, animal models and post-mortem human brain tissues, there are currently no effective treatments.

SUMMARY

With the advent of induced pluripotent stem cells (iPSCs) reprogrammed from fully differentiated adult cells such as skin fibroblasts, newer opportunities have arisen to study the pathophysiology of many diseases in more depth. It is envisioned that iPSCs could be used as a powerful tool for neurodegenerative disease modelling and eventually be an unlimited source for cell replacement therapy. This paper provides an overview of; the contribution of iPSCs towards modeling and understanding AD pathogenesis, the novel human/mouse chimeric models in elucidating current AD pathogenesis hypotheses, the possible use of iPSCs in drug screening, and perspectives on possible future directions.

KEY MESSAGES

Human/mouse chimeric models using iPSCs to study AD offer much promise in better replicating AD pathology and can be further exploited to elucidate disease pathogenesis with regards to the neuroinflammation hypothesis of AD.

Amyloid beta: structure, biology and structure-based therapeutic development

Amyloid beta peptide (Aβ) is produced through the proteolytic processing of a transmembrane protein, amyloid precursor protein (APP), by β- and γ-secretases. Aβ accumulation in the brain is proposed to be an early toxic event in the pathogenesis of Alzheimer's disease, which is the most common form of dementia associated with plaques and tangles in the brain. Currently, it is unclear what the physiological and pathological forms of Aβ are and by what mechanism Aβ causes dementia. Moreover, there are no efficient drugs to stop or reverse the progression of Alzheimer's disease. In this paper, we review the structures, biological functions, and neurotoxicity role of Aβ. We also discuss the potential receptors that interact with Aβ and mediate Aβ intake, clearance, and metabolism. Additionally, we summarize the therapeutic developments and recent advances of different strategies for treating Alzheimer's disease. Finally, we will report on the progress in searching for novel, potentially effective agents as well as selected promising strategies for the treatment of Alzheimer's disease. These prospects include agents acting on Aβ, its receptors and tau protein, such as small molecules, vaccines and antibodies against Aβ; inhibitors or modulators of β- and γ-secretase; Aβ-degrading proteases; tau protein inhibitors and vaccines; amyloid dyes and microRNAs.

Identification and description of three families with familial Alzheimer disease that segregate variants in the SORL1 gene

Alzheimer disease (AD) is a progressive neurodegenerative disorder and the most common form of dementia. The majority of AD cases are sporadic, while up to 5% are families with an early onset AD (EOAD). Mutations in one of the three genes: amyloid beta precursor protein (APP), presenilin 1 (PSEN1) or presenilin 2 (PSEN2) can be disease causing. However, most EOAD families do not carry mutations in any of these three genes, and candidate genes, such as the sortilin-related receptor 1 (SORL1), have been suggested to be potentially causative. To identify AD causative variants, we performed whole-exome sequencing on five individuals from a family with EOAD and a missense variant, p.Arg1303Cys (c.3907C > T) was identified in SORL1 which segregated with disease and was further characterized with immunohistochemistry on two post mortem autopsy cases from the same family. In a targeted re-sequencing effort on independent index patients from 35 EOAD-families, a second SORL1 variant, c.3050-2A > G, was found which segregated with the disease in 3 affected and was absent in one unaffected family member. The c.3050-2A > G variant is located two nucleotides upstream of exon 22 and was shown to cause exon 22 skipping, resulting in a deletion of amino acids Gly1017- Glu1074 of SORL1. Furthermore, a third SORL1 variant, c.5195G > C, recently identified in a Swedish case control cohort included in the European Early-Onset Dementia (EU EOD) consortium study, was detected in two affected siblings in a third family with familial EOAD. The finding of three SORL1-variants that segregate with disease in three separate families with EOAD supports the involvement of SORL1 in AD pathology. The cause of these rare monogenic forms of EOAD has proven difficult to find and the use of exome and genome sequencing may be a successful route to target them.

Genomic variants, genes, and pathways of Alzheimer's disease: An overview

Alzheimer's disease (AD) (MIM: 104300) is a highly heritable disease with great complexity in its genetic contributors, and represents the most common form of dementia. With the gradual aging of the world's population, leading to increased prevalence of AD, and the substantial cost of care for those afflicted, identifying the genetic causes of disease represents a critical effort in identifying therapeutic targets. Here we provide a comprehensive review of genomic studies of AD, from the earliest linkage studies identifying monogenic contributors to early-onset forms of AD to the genome-wide and rare variant association studies of recent years that are being used to characterize the mosaic of genetic contributors to late-onset AD (LOAD), and which have identified approximately ∼20 genes with common variants contributing to LOAD risk. In addition, we explore studies employing alternative approaches to identify genetic contributors to AD, including studies of AD-related phenotypes and multi-variant association studies such as pathway analyses. Finally, we introduce studies of next-generation sequencing, which have recently helped identify multiple low-frequency and rare variant contributors to AD, and discuss on-going efforts with next-generation sequencing studies to develop statistically well- powered and comprehensive genomic studies of AD. Through this review, we help uncover the many insights the genetics of AD have provided into the pathways and pathophysiology of AD. © 2016 Wiley Periodicals, Inc.

Environmental Enrichment Modified Epigenetic Mechanisms in SAMP8 Mouse Hippocampus by Reducing Oxidative Stress and Inflammaging and Achieving Neuroprotection

With the increase in life expectancy, aging and age-related cognitive impairments are becoming one of the most important issues for human health. At the same time, it has been shown that epigenetic mechanisms are emerging as universally important factors in life expectancy. The Senescence Accelerated Mouse P8 (SAMP8) strain exhibits age-related deterioration evidenced in learning and memory abilities and is a useful model of neurodegenerative disease. In SAMP8, Environmental Enrichment (EE) increased DNA-methylation levels (5-mC) and reduced hydroxymethylation levels (5-hmC), as well as increased histone H3 and H4 acetylation levels. Likewise, we found changes in the hippocampal gene expression of some chromatin-modifying enzyme genes, such as Dnmt3b. Hdac1. Hdac2. Sirt2, and Sirt6. Subsequently, we assessed the effects of EE on neuroprotection-related transcription factors, such as the Nuclear regulatory factor 2 (Nrf2)-Antioxidant Response Element pathway and Nuclear Factor kappa Beta (NF-κB), which play critical roles in inflammation. We found that EE produces an increased expression of antioxidant genes, such as Hmox1. Aox1, and Cox2, and reduced the expression of inflammatory genes such as IL-6 and Cxcl10, all of this within the epigenetic context modified by EE. In conclusion, EE prevents epigenetic changes that promote or drive oxidative stress and inflammaging.

Biomarkers in Sporadic and Familial Alzheimer's Disease

Most forms of Alzheimer's disease (AD) are sporadic (sAD) or inherited in a non-Mendelian fashion, and less than 1% of cases are autosomal-dominant. Forms of sAD do not exhibit familial aggregation and are characterized by complex genetic and environmental interactions. Recently, the expansion of genomic methodologies, in association with substantially larger combined cohorts, has resulted in various genome-wide association studies that have identified several novel genetic associations of AD. Currently, the most effective methods for establishing the diagnosis of AD are defined by multi-modal pathways, starting with clinical and neuropsychological assessment, cerebrospinal fluid (CSF) analysis, and brain-imaging procedures, all of which have significant cost- and access-to-care barriers. Consequently, research efforts have focused on the development and validation of non-invasive and generalizable blood-based biomarkers. Among the modalities conceptualized by the systems biology paradigm and utilized in the "exploratory biomarker discovery arena", proteome analysis has received the most attention. However, metabolomics, lipidomics, transcriptomics, and epigenomics have recently become key modalities in the search for AD biomarkers. Interestingly, biomarker changes for familial AD (fAD), in many but not all cases, seem similar to those for sAD. The integration of neurogenetics with systems biology/physiology-based strategies and high-throughput technologies for molecular profiling is expected to help identify the causes, mechanisms, and biomarkers associated with the various forms of AD. Moreover, in order to hypothesize the dynamic trajectories of biomarkers through disease stages and elucidate the mechanisms of biomarker alterations, updated and more sophisticated theoretical models have been proposed for both sAD and fAD.

Genome research in pre-dementia stages of Alzheimer's disease

Genetic characterization of individuals at risk of Alzheimer's disease (AD), i.e. people having amyloid deposits in the brain without symptoms, people suffering from subjective cognitive decline (SCD) or mild cognitive impairment (MCI), has spurred the interests of researchers. However, their pre-dementia genetic profile remains mostly unexplored. In this study, we reviewed the loci related to phenotypes of AD, MCI and SCD from literature and performed the first meta-analyses evaluating the role of apolipoprotein E (APOE) in the risk of conversion from a healthy status to MCI and SCD. For AD dementia risk, an increased number of loci have been identified; to date, 28 genes have been associated with Late Onset AD. In MCI syndrome, APOE is confirmed as a pheno-conversion factor leading from MCI to AD, and clusterin is a promising candidate. Additionally, our meta-analyses revealed APOE as genetic risk factor to convert from a healthy status to MCI [OR = 1.849 (1.587-2.153); P = 2.80  × 10-15] and to a lesser extent from healthy status to SCD [OR = 1.151 (1.015-1.304); P = 0.028]. Thus, we believe that genetic studies in longitudinal SCD and MCI series may provide new therapeutic targets and improve the existing knowledge of AD. This type of studies must be completed on healthy subjects to better understand the natural disease resistance to brain insults and neurodegeneration.

Epigenetic mechanisms underlying cognitive impairment and Alzheimer disease hallmarks in 5XFAD mice

5XFAD is an early-onset mouse transgenic model of Alzheimer disease (AD). Up to now there are no studies that focus on the epigenetic changes produced as a result of Aβ-42 accumulation and the possible involvement in the different expression of related AD-genes. Under several behavioral and cognition test, we found impairment in memory and psychoemotional changes in female 5XFAD mice in reference to wild type that worsens with age. Cognitive changes correlated with alterations on protein level analysis and gene expression of markers related with tau aberrant phosphorylation, amyloidogenic pathway (APP, BACE1), Oxidative Stress (iNOS, Aldh2) and inflammation (astrogliosis, TNF-α and IL-6); no changes were found in non-amyloidogenic pathway indicators such as ADAM10. Epigenetics changes as higher CpG methylation and transcriptional changes in DNA methyltransferases (DNMTs) family were found. Dnmt1 increases in younger 5XFAD and Dnmt3a and b high levels in the oldest transgenic mice. Similar pattern was found with histone methyltransferases such as Jarid1a andG9a. Histone deacetylase 2 (Hdac2) or Sirt6, both related with cognition and memory, presented a similar pattern. Taken together, these hallmarks presented by the 5XFAD model prompted its use in assessing different potential therapeutic interventions based on epigenetic targets after earlier amyloid deposition.

Focus on Extracellular Vesicles: Physiological Role and Signalling Properties of Extracellular Membrane Vesicles

Extracellular vesicles (EVs) are a heterogeneous population of secreted membrane vesicles, with distinct biogenesis routes, biophysical properties and different functions both in physiological conditions and in disease. The release of EVs is a widespread biological process, which is conserved across species. In recent years, numerous studies have demonstrated that several bioactive molecules are trafficked with(in) EVs, such as microRNAs, mRNAs, proteins and lipids. The understanding of their final impact on the biology of specific target cells remains matter of intense debate in the field. Also, EVs have attracted great interest as potential novel cell-free therapeutics. Here we describe the proposed physiological and pathological functions of EVs, with a particular focus on their molecular content. Also, we discuss the advances in the knowledge of the mechanisms regulating the secretion of EV-associated molecules and the specific pathways activated upon interaction with the target cell, highlighting the role of EVs in the context of the immune system and as mediators of the intercellular signalling in the brain.

Genetic Factors Affecting Late-Onset Alzheimer's Disease Susceptibility

Alzheimer's disease is considered a progressive brain disease in the older population. Late-onset Alzheimer's disease (LOAD) as a multifactorial dementia has a polygenic inheritance. Age, environment, and lifestyle along with a growing number of genetic factors have been reported as risk factors for LOAD. Our aim was to present results of LOAD association studies that have been done in northwestern Iran, and we also explored possible interactions with apolipoprotein E (APOE) status. We re-evaluated the association of these markers in dominant, recessive, and additive models. In all, 160 LOAD and 163 healthy control subjects of Azeri Turkish ethnicity were studied. The Chi-square test with Yates' correction and Fisher's exact test were used for statistical analysis. A Bonferroni-corrected p value, based on the number of statistical tests, was considered significant. Our results confirmed that chemokine receptor type 2 (CCR2), estrogen receptor 1 (ESR1), toll-like receptor 2 (TLR2), tumor necrosis factor alpha (TNF α), APOE, bridging integrator 1 (BIN1), and phosphatidylinositol-binding clathrin assembly protein (PICALM) are LOAD susceptibility loci in Azeri Turk ancestry populations. Among them, variants of CCR2, ESR1, TNF α, and APOE revealed associations in three different genetic models. After adjusting for APOE, the association (both allelic and genotypic) with CCR2, BIN1, and ESRα (PvuII) was evident only among subjects without the APOE ε4, whereas the association with CCR5, without Bonferroni correction, was significant only among subjects carrying the APOE ε4 allele. This result is an evidence of a synergistic and antagonistic effect of APOE on variant associations with LOAD.

Inflammation in Alzheimer's Disease and Molecular Genetics: Recent Update

Alzheimer's disease (AD) is a complex age-related neurodegenerative disorder of the central nervous system. Since the first description of AD in 1907, many hypotheses have been established to explain its causes. The inflammation theory is one of them. Pathological and biochemical studies of brains from AD individuals have provided solid evidence of the activation of inflammatory pathways. Furthermore, people with long-term medication of anti-inflammatory drugs have shown a reduced risk to develop the disease. After three decades of genetic study in AD, dozens of loci harboring genetic variants influencing inflammatory pathways in AD patients has been identified through genome-wide association studies (GWAS). The most well-known GWAS risk factor that is responsible for immune response and inflammation in AD development should be APOE ε4 allele. However, a growing number of other GWAS risk AD candidate genes in inflammation have recently been discovered. In the present study, we try to review the inflammation in AD and immunity-associated GWAS risk genes like HLA-DRB5/DRB1, INPP5D, MEF2C, CR1, CLU and TREM2.

Decision tree analysis of genetic risk for clinically heterogeneous Alzheimer's disease

BACKGROUND

Heritability of Alzheimer's disease (AD) is estimated at 74% and genetic contributors have been widely sought. The ε4 allele of apolipoprotein E (APOE) remains the strongest common risk factor for AD, with numerous other common variants contributing only modest risk for disease. Variability in clinical presentation of AD, which is typically amnestic (AmnAD) but can less commonly involve visuospatial, language and/or dysexecutive syndromes (atypical or AtAD), further complicates genetic analyses. Taking a multi-locus approach may increase the ability to identify individuals at highest risk for any AD syndrome. In this study, we sought to develop and investigate the utility of a multi-variant genetic risk assessment on a cohort of phenotypically heterogeneous patients with sporadic AD clinical diagnoses.

METHODS

We genotyped 75 variants in our cohort and, using a two-staged study design, we developed a 17-marker AD risk score in a Discovery cohort (n = 59 cases, n = 133 controls) then assessed its utility in a second Validation cohort (n = 126 cases, n = 150 controls). We also performed a data-driven decision tree analysis to identify genetic and/or demographic criteria that are most useful for accurately differentiating all AD cases from controls.

RESULTS

We confirmed APOE ε4 as a strong risk factor for AD. A 17-marker risk panel predicted AD significantly better than APOE genotype alone (P < 0.00001) in the Discovery cohort, but not in the Validation cohort. In decision tree analyses, we found that APOE best differentiated cases from controls only in AmnAD but not AtAD. In AtAD, HFE SNP rs1799945 was the strongest predictor of disease; variation in HFE has previously been implicated in AD risk in non-ε4 carriers.

CONCLUSIONS

Our study suggests that APOE ε4 remains the best predictor of broad AD risk when compared to multiple other genetic factors with modest effects, that phenotypic heterogeneity in broad AD can complicate simple polygenic risk modeling, and supports the association between HFE and AD risk in individuals without APOE ε4.

Alzheimer's disease is associated with low density of the long CR1 isoform

The long complement receptor type 1 (CR1) isoform, CR1*2 (S), has been identified as being associated with Alzheimer's disease (AD) risk. We aimed to analyze the phenotypic structural and expression aspects (length and density) of CR1 in erythrocytes of 135 Caucasian subjects (100 AD and 35 controls). CR1 length polymorphism was assessed at protein and gene levels using Western blot and high-resolution melting, respectively. CR1 sites on erythrocytes were enumerated by flow cytometry. CR1 gene analysis, spotting the rs6656401 and rs3818361 polymorphisms, was performed by pyrosequencing. The CR1 density was significantly lower in AD patients expressing the CR1*2 isoform compared with the controls (p = 0.001), demonstrating lower expression of CR1 in CR1*2 carriers. Our data suggested the existence of silent CR1 alleles. Finally, rs6656401 and rs3818361 were strongly associated with CR1 length polymorphism (p < 0.0001). These observations indicate that AD susceptibility is associated with the long CR1 isoform (CR1*2), albeit at a lower density, suggesting that AD results from insufficient clearance of plaque deposits rather than increased inflammation.

An Association Study on IL16 Gene Polymorphisms with the Risk of Sporadic Alzheimer's Disease

BACKGROUND

Interleukin-16 (IL-16) is an important regulator of T cell activation and was reported to act as a chemoattractant agent. There are evidences that IL16 can control the neuroinflammatory processes in Alzheimer's Disease (AD). This study was performed to investigate the role or association of IL16 polymorphisms, rs11556218 and rs4778889 with the risk of late-onset Alzheimer's disease (LOAD) in Iranian population.

METHODS

Totally, 148 AD patients and 137 nondemented and age-matched subjects were recruited in this study. Genotyping of rs11556218 T/G and rs4778889 T/C polymorphisms was performed by PCR-RFLP method using the NdeI and AhdI restriction enzymes, respectively.

RESULTS

Statistical analysis of rs11556218 genotypes showed a protective effect against AD in the heterozygote genotype (p=0.001, OR=0.16) as well as rs4778889 (p=0.001, OR=0.23). Frequency of rs11556218 allele T was higher in controls than patients (p=0.001, OR=0.32). However, there was no significant difference in the frequencies of rs4778889 alleles between the AD patients and controls.

CONCLUSION

Our results indicate that the rs11556218 and rs4778889 polymorphisms have a protective role in the development of sporadic AD in Iranian population.

Role of environmental contaminants in the etiology of Alzheimer's disease: a review

Alzheimer's dis ease (AD) is a leading cause of mortality in the developed world with 70% risk attributable to genetics. The remaining 30% of AD risk is hypothesized to include environmental factors and human lifestyle patterns. Environmental factors possibly include inorganic and organic hazards, exposure to toxic metals (aluminium, copper), pesticides (organochlorine and organophosphate insecticides), industrial chemicals (flame retardants) and air pollutants (particulate matter). Long term exposures to these environmental contaminants together with bioaccumulation over an individual's life-time are speculated to induce neuroinflammation and neuropathology paving the way for developing AD. Epidemiologic associations between environmental contaminant exposures and AD are still limited. However, many in vitro and animal studies have identified toxic effects of environmental contaminants at the cellular level, revealing alterations of pathways and metabolisms associated with AD that warrant further investigations. This review provides an overview of in vitro, animal and epidemiological studies on the etiology of AD, highlighting available data supportive of the long hypothesized link between toxic environmental exposures and development of AD pathology.

Identifying genetic interactions associated with late-onset Alzheimer's disease

Background

Identifying genetic interactions in data obtained from genome-wide association studies (GWASs) can help in understanding the genetic basis of complex diseases. The large number of single nucleotide polymorphisms (SNPs) in GWASs however makes the identification of genetic interactions computationally challenging. We developed the Bayesian Combinatorial Method (BCM) that can identify pairs of SNPs that in combination have high statistical association with disease.

Results

We applied BCM to two late-onset Alzheimer’s disease (LOAD) GWAS datasets to identify SNPs that interact with known Alzheimer associated SNPs. We also compared BCM with logistic regression that is implemented in PLINK. Gene Ontology analysis of genes from the top 200 dataset SNPs for both GWAS datasets showed overrepresentation of LOAD-related terms. Four genes were common to both datasets: APOE and APOC1, which have well established associations with LOAD, and CAMK1D and FBXL13, not previously linked to LOAD but having evidence of involvement in LOAD. Supporting evidence was also found for additional genes from the top 30 dataset SNPs.

Conclusion

BCM performed well in identifying several SNPs having evidence of involvement in the pathogenesis of LOAD that would not have been identified by univariate analysis due to small main effect. These results provide support for applying BCM to identify potential genetic variants such as SNPs from high dimensional GWAS datasets.

Electronic supplementary material

The online version of this article (doi:10.1186/s13040-014-0035-z) contains supplementary material, which is available to authorized users.

Cumulative effects of the ApoE genotype and gender on the synaptic proteome and oxidative stress in the mouse brain

Elderly females, particularly those carrying the apolipoprotein E (ApoE)-ε4 allele, have a higher risk of developing Alzheimer's disease (AD). However, the underlying mechanism for this increased susceptibility remains unclear. In this study, we investigated the effects of the ApoE genotype and gender on the proteome of synaptosomes. We isolated synaptosomes and used label-free quantitative proteomics, to report, for the first time, that the synaptosomal proteomic profiles in the cortex of female human-ApoE4 mice exhibited significantly reduced expression of proteins related to energy metabolism, which was accompanied by increased levels of oxidative stress. In addition, we also first demonstrated that the proteomic response in synaptic termini was more susceptible than that in the soma to the adverse effects induced by genders and genotypes. This suggests that synaptic mitochondria might be 'older' than mitochondria in the soma of neurons; therefore, they might contain increased cumulative damage from oxidative stress. Furthermore, female human-ApoE4 mice had much lower oestrogen levels in the cortex and treatment with oestrogen protected ApoE3 stable transfected C6 neurons from oxidative stress. Overall, this study reveals complex ApoE- and gender-dependent effects on synaptic function and also provides a basis for future studies of candidates based on specific pathways involved in the pathogenesis of AD. The lack of oestrogen-mediated protection regulated by the ApoE genotype led to synaptic mitochondrial dysfunction and increased oxidative stress, which might make older females more susceptible to AD.

MACOED: a multi-objective ant colony optimization algorithm for SNP epistasis detection in genome-wide association studies

MOTIVATION

The existing methods for genetic-interaction detection in genome-wide association studies are designed from different paradigms, and their performances vary considerably for different disease models. One important reason for this variability is that their construction is based on a single-correlation model between SNPs and disease. Due to potential model preference and disease complexity, a single-objective method will therefore not work well in general, resulting in low power and a high false-positive rate.

METHOD

In this work, we present a multi-objective heuristic optimization methodology named MACOED for detecting genetic interactions. In MACOED, we combine both logistical regression and Bayesian network methods, which are from opposing schools of statistics. The combination of these two evaluation objectives proved to be complementary, resulting in higher power with a lower false-positive rate than observed for optimizing either objective independently. To solve the space and time complexity for high-dimension problems, a memory-based multi-objective ant colony optimization algorithm is designed in MACOED that is able to retain non-dominated solutions found in past iterations.

RESULTS

We compared MACOED with other recent algorithms using both simulated and real datasets. The experimental results demonstrate that our method outperforms others in both detection power and computational feasibility for large datasets.

AVAILABILITY AND IMPLEMENTATION

Codes and datasets are available at: www.csbio.sjtu.edu.cn/bioinf/MACOED/.

The Role of PICALM in Alzheimer's Disease

Alzheimer's disease (AD) is a highly heritable disease (with heritability up to 76%) with a complex genetic profile of susceptibility, among which large genome-wide association studies (GWASs) pointed to the phosphatidylinositol-binding clathrin assembly protein (PICALM) gene as a susceptibility locus for late-onset Alzheimer's disease (LOAD) incidence. Here, we summarize the known functions of PICALM and discuss its genetic polymorphisms and their potential physiological effects associated with LOAD. Compelling data indicated that PICALM affects AD risk primarily by modulating production, transportation, and clearance of β-amyloid (Aβ) peptide, but other Aβ-independent pathways are discussed, including tauopathy, synaptic dysfunction, disorganized lipid metabolism, immune disorder, and disrupted iron homeostasis. Finally, given the potential involvement of PICALM in facilitating AD occurrence in multiple ways, it might be possible that targeting PICALM might provide promising and novel avenues for AD therapy.

The application of network label propagation to rank biomarkers in genome-wide Alzheimer's data

Background

Ranking and identifying biomarkers that are associated with disease from genome-wide measurements holds significant promise for understanding the genetic basis of common diseases. The large number of single nucleotide polymorphisms (SNPs) in genome-wide studies (GWAS), however, makes this task computationally challenging when the ranking is to be done in a multivariate fashion. This paper evaluates the performance of a multivariate graph-based method called label propagation (LP) that efficiently ranks SNPs in genome-wide data.

Results

The performance of LP was evaluated on a synthetic dataset and two late onset Alzheimer’s disease (LOAD) genome-wide datasets, and the performance was compared to that of three control methods. The control methods included chi squared, which is a commonly used univariate method, as well as a Relief method called SWRF and a sparse logistic regression (SLR) method, which are both multivariate ranking methods. Performance was measured by evaluating the top-ranked SNPs in terms of classification performance, reproducibility between the two datasets, and prior evidence of being associated with LOAD.

On the synthetic data LP performed comparably to the control methods. On GWAS data, LP performed significantly better than chi squared and SWRF in classification performance in the range from 10 to 1000 top-ranked SNPs for both datasets, and not significantly different from SLR. LP also had greater ranking reproducibility than chi squared, SWRF, and SLR. Among the 25 top-ranked SNPs that were identified by LP, there were 14 SNPs in one dataset that had evidence in the literature of being associated with LOAD, and 10 SNPs in the other, which was higher than for the other methods.

Conclusion

LP performed considerably better in ranking SNPs in two high-dimensional genome-wide datasets when compared to three control methods. It had better performance in the evaluation measures we used, and is computationally efficient to be applied practically to data from genome-wide studies. These results provide support for including LP in the methods that are used to rank SNPs in genome-wide datasets.

Exosomes as mediators of neuroinflammation

Exosomes are membrane-bound nanovesicles that are shed by cells of various lineages under normal as well as pathological conditions. Previously thought to be ‘extracellular debris’, exosomes have recently generated immense interest following their discovery as mediators of intercellular communication by delivering functional proteins, mRNA transcripts as well as miRNAs to recipient cells. Although suggested to primarily serve as signaling organelles which also remove unwanted cellular components in the brain, accumulating evidence suggests that exosomes can also significantly contribute to the development of several neuropathologies. Toxic forms of aggregated proteins such as α-synuclein, amyloid β and prions, that are responsible for the development of Parkinson’s disease, Alzheimer’s disease and Creutzfeldt-Jacob disease (CJD) respectively, have been shown to get effectively packaged into exosomes and spread from one cell to another, initiating an inflammatory cascade. In addition, exosomes secreted by resident brain cells in response to pathogenic stimuli such as viral proteins can also influence bystander cells by the transfer of dysregulated miRNAs that suppress the expression of essential genes in the recipient cells. Given the relevance of exosomes in brain communication and neuropathogenesis, novel therapeutic strategies are now being developed that exploit the biology of these vesicles to deliver anti-inflammatory molecules to the CNS. Exosomes may alter the way we think about brain disorders and their treatments.