AlzBase: an Integrative Database for Gene Dysregulation in Alzheimer's Disease

Ubiquitin-mediated mitochondrial regulation by MITOL/MARCHF5 at a glance

Mitochondria are involved in various cellular processes, such as energy production, inflammatory responses and cell death. Mitochondrial dysfunction is associated with many age-related diseases, including neurological disorders and heart failure. Mitochondrial quality is strictly maintained by mitochondrial dynamics linked to an adequate supply of phospholipids and other substances from the endoplasmic reticulum (ER). The outer mitochondrial membrane-localized E3 ubiquitin ligase MITOL/MARCHF5 is responsible for mitochondrial quality control through the regulation of mitochondrial dynamics, formation of mitochondria-ER contacts and mitophagy. MITOL deficiency has been shown to impair mitochondrial function, cause an excessive inflammatory response and increase vulnerability to stress, resulting in the exacerbation of the disease. In this study, we overview the ubiquitin-mediated regulation of mitochondrial function by MITOL and the relationship between MITOL and diseases.

An integrated brain-specific network identifies genes associated with neuropathologic and clinical traits of Alzheimer’s disease

Alzheimer’s disease (AD) has a strong genetic predisposition. However, its risk genes remain incompletely identified. We developed an Alzheimer’s brain gene network-based approach to predict AD-associated genes by leveraging the functional pattern of known AD-associated genes. Our constructed network outperformed existing networks in predicting AD genes. We then systematically validated the predictions using independent genetic, transcriptomic, proteomic data, neuropathological and clinical data. First, top-ranked genes were enriched in AD-associated pathways. Second, using external gene expression data from the Mount Sinai Brain Bank study, we found that the top-ranked genes were significantly associated with neuropathological and clinical traits, including the Consortium to Establish a Registry for Alzheimer’s Disease score, Braak stage score and clinical dementia rating. The analysis of Alzheimer’s brain single-cell RNA-seq data revealed cell-type-specific association of predicted genes with early pathology of AD. Third, by interrogating proteomic data in the Religious Orders Study and Memory and Aging Project and Baltimore Longitudinal Study of Aging studies, we observed a significant association of protein expression level with cognitive function and AD clinical severity. The network, method and predictions could become a valuable resource to advance the identification of risk genes for AD.

Role of Oxidative Damage in Alzheimer's Disease and Neurodegeneration: From Pathogenic Mechanisms to Biomarker Discovery

Alzheimer’s disease (AD) is a neurodegenerative disorder accounting for over 50% of all dementia patients and representing a leading cause of death worldwide for the global ageing population. The lack of effective treatments for overt AD urges the discovery of biomarkers for early diagnosis, i.e., in subjects with mild cognitive impairment (MCI) or prodromal AD. The brain is exposed to oxidative stress as levels of reactive oxygen species (ROS) are increased, whereas cellular antioxidant defenses are decreased. Increased ROS levels can damage cellular structures or molecules, leading to protein, lipid, DNA, or RNA oxidation. Oxidative damage is involved in the molecular mechanisms which link the accumulation of amyloid-β and neurofibrillary tangles, containing hyperphosphorylated tau, to microglia response. In this scenario, microglia are thought to play a crucial role not only in the early events of AD pathogenesis but also in the progression of the disease. This review will focus on oxidative damage products as possible peripheral biomarkers in AD and in the preclinical phases of the disease. Particular attention will be paid to biological fluids such as blood, CSF, urine, and saliva, and potential future use of molecules contained in such body fluids for early differential diagnosis and monitoring the disease course. We will also review the role of oxidative damage and microglia in the pathogenesis of AD and, more broadly, in neurodegeneration.

Defining early changes in Alzheimer's disease from RNA sequencing of brain regions differentially affected by pathology

Tau pathology in Alzheimer’s disease (AD) spreads in a predictable pattern that corresponds with disease symptoms and severity. At post-mortem there are cortical regions that range from mildly to severely affected by tau pathology and neuronal loss. A comparison of the molecular signatures of these differentially affected areas within cases and between cases and controls may allow the temporal modelling of disease progression. Here we used RNA sequencing to explore differential gene expression in the mildly affected primary visual cortex and moderately affected precuneus of ten age-, gender- and RNA quality-matched post-mortem brains from AD patients and healthy controls. The two regions in AD cases had similar transcriptomic signatures but there were broader abnormalities in the precuneus consistent with the greater tau load. Both regions were characterised by upregulation of immune-related genes such as those encoding triggering receptor expressed on myeloid cells 2 and membrane spanning 4-domains A6A and milder changes in insulin/IGF1 signalling. The precuneus in AD was also characterised by changes in vesicle secretion and downregulation of the interneuronal subtype marker, somatostatin. The ‘early’ AD transcriptome is characterised by perturbations in synaptic vesicle secretion on a background of neuroimmune dysfunction. In particular, the synaptic deficits that characterise AD may begin with the somatostatin division of inhibitory neurotransmission.

Mitochondrial ubiquitin ligase alleviates Alzheimer's disease pathology via blocking the toxic amyloid-β oligomer generation

Mitochondrial pathophysiology is implicated in the development of Alzheimer's disease (AD). An integrative database of gene dysregulation suggests that the mitochondrial ubiquitin ligase MITOL/MARCH5, a fine-tuner of mitochondrial dynamics and functions, is downregulated in patients with AD. Here, we report that the perturbation of mitochondrial dynamics by MITOL deletion triggers mitochondrial impairments and exacerbates cognitive decline in a mouse model with AD-related Aβ pathology. Notably, MITOL deletion in the brain enhanced the seeding effect of Aβ fibrils, but not the spontaneous formation of Aβ fibrils and plaques, leading to excessive secondary generation of toxic and dispersible Aβ oligomers. Consistent with this, MITOL-deficient mice with Aβ etiology exhibited worsening cognitive decline depending on Aβ oligomers rather than Aβ plaques themselves. Our findings suggest that alteration in mitochondrial morphology might be a key factor in AD due to directing the production of Aβ form, oligomers or plaques, responsible for disease development.

Interdisciplinary Research in Alzheimer's Disease and the Roles International Societies Can Play

An ever-increasing ageing population has elevated Alzheimer's disease to be one of the biggest challenges in modern medicine. Alzheimer's disease is highly complex, and we are still no closer to understanding the causes, let alone an effective treatment. The lack of good experimental models and lack of critical understanding has led to high failure rates of clinical trials with high associated costs, as well as difficulties in implementing treatments. The multifaceted nature of this disease highlights the need for an interdisciplinary approach to address these concerns. In this essay, we suggest how collaborative work can be useful in addressing some of the above issues. We then propose that international organisations and publishers need to support interdisciplinary research by creating platforms, lobbying funders, and pushing for interdisciplinary publications. We further highlight some of the issues involved in implementing these suggestions and argue that willpower of the research community, together with a re-evaluation of evaluation metrics and incentive systems, are needed in order to foster interdisciplinary research. Overall, we emphasise the need for interdisciplinary research in Alzheimer's disease and suggest that international societies should play a huge role in this endeavour.

Prenatal exposure to bisphenol A alters the transcriptome-interactome profiles of genes associated with Alzheimer's disease in the offspring hippocampus

Our recent study revealed that prenatal exposure to bisphenol A (BPA) disrupted the transcriptome profiles of genes in the offspring hippocampus. In addition to genes linked to autism, several genes associated with Alzheimer’s disease (AD) were found to be differentially expressed, although the association between BPA-responsive genes and AD-related genes has not been thoroughly investigated. Here, we demonstrated that in utero BPA exposure also disrupted the transcriptome profiles of genes associated with neuroinflammation and AD in the hippocampus. The level of NF-κB protein and its AD-related target gene Bace1 were significantly increased in the offspring hippocampus in a sex-dependent manner. Quantitative RT-PCR analysis also showed an increase in the expression of Tnf gene. Moreover, the reanalysis of transcriptome profiling data from several previously published BPA studies consistently showed that BPA-responsive genes were significantly associated with top AD candidate genes. The findings from this study suggest that maternal BPA exposure may increase AD risk in offspring by dysregulating genes associated with AD neuropathology and inflammation and reveal a possible relationship between AD and autism, which are linked to the same environmental factor. Sex-specific effects of prenatal BPA exposure on the susceptibility of AD deserve further investigation.

Comparative functional genomic analysis of Alzheimer's affected and naturally aging brains

Background

Alzheimer’s disease (AD) is a prevalent progressive neurodegenerative human disease whose cause remains unclear. Numerous initially highly hopeful anti-AD drugs based on the amyloid-β (Aβ) hypothesis of AD have failed recent late-phase tests. Natural aging (AG) is a high-risk factor for AD. Here, we aim to gain insights in AD that may lead to its novel therapeutic treatment through conducting meta-analyses of gene expression microarray data from AG and AD-affected brain.

Methods

Five sets of gene expression microarray data from different regions of AD (hereafter, ALZ when referring to data)-affected brain, and one set from AG, were analyzed by means of the application of the methods of differentially expressed genes and differentially co-expressed gene pairs for the identification of putatively disrupted biological pathways and associated abnormal molecular contents.

Results

Brain-region specificity among ALZ cases and AG-ALZ differences in gene expression and in KEGG pathway disruption were identified. Strong heterogeneity in AD signatures among the five brain regions was observed: HC/PC/SFG showed clear and pronounced AD signatures, MTG moderately so, and EC showed essentially none. There were stark differences between ALZ and AG. OXPHOS and Proteasome were the most disrupted pathways in HC/PC/SFG, while AG showed no OXPHOS disruption and relatively weak Proteasome disruption in AG. Metabolic related pathways including TCA cycle and Pyruvate metabolism were disrupted in ALZ but not in AG. Three pathogenic infection related pathways were disrupted in ALZ. Many cancer and signaling related pathways were shown to be disrupted AG but far less so in ALZ, and not at all in HC. We identified 54 “ALZ-only” differentially expressed genes, all down-regulated and which, when used to augment the gene list of the KEGG AD pathway, made it significantly more AD-specific.

Candidate Genes and MiRNAs Linked to the Inverse Relationship Between Cancer and Alzheimer's Disease: Insights From Data Mining and Enrichment Analysis

The incidence of cancer and Alzheimer’s disease (AD) increases exponentially with age. A growing body of epidemiological evidence and molecular investigations inspired the hypothesis of an inverse relationship between these two pathologies. It has been proposed that the two diseases might utilize the same proteins and pathways that are, however, modulated differently and sometimes in opposite directions. Investigation of the common processes underlying these diseases may enhance the understanding of their pathogenesis and may also guide novel therapeutic strategies. Starting from a text-mining approach, our in silico study integrated the dispersed biological evidence by combining data mining, gene set enrichment, and protein-protein interaction (PPI) analyses while searching for common biological hallmarks linked to AD and cancer. We retrieved 138 genes (ALZCAN gene set), computed a significant number of enriched gene ontology clusters, and identified four PPI modules. The investigation confirmed the relevance of autophagy, ubiquitin proteasome system, and cell death as common biological hallmarks shared by cancer and AD. Then, from a closer investigation of the PPI modules and of the miRNAs enrichment data, several genes (SQSTM1, UCHL1, STUB1, BECN1, CDKN2A, TP53, EGFR, GSK3B, and HSPA9) and miRNAs (miR-146a-5p, MiR-34a-5p, miR-21-5p, miR-9-5p, and miR-16-5p) emerged as promising candidates. The integrative approach uncovered novel miRNA-gene networks (e.g., miR-146 and miR-34 regulating p62 and Beclin1 in autophagy) that might give new insights into the complex regulatory mechanisms of gene expression in AD and cancer.

miRDRN-miRNA disease regulatory network: a tool for exploring disease and tissue-specific microRNA regulatory networks

BACKGROUND

MicroRNA (miRNA) regulates cellular processes by acting on specific target genes, and cellular processes proceed through multiple interactions often organized into pathways among genes and gene products. Hundreds of miRNAs and their target genes have been identified, as are many miRNA-disease associations. These, together with huge amounts of data on gene annotation, biological pathways, and protein-protein interactions are available in public databases. Here, using such data we built a database and web service platform, miRNA disease regulatory network (miRDRN), for users to construct disease and tissue-specific miRNA-protein regulatory networks, with which they may explore disease related molecular and pathway associations, or find new ones, and possibly discover new modes of drug action.

METHODS

Data on disease-miRNA association, miRNA-target association and validation, gene-tissue association, gene-tumor association, biological pathways, human protein interaction, gene ID, gene ontology, gene annotation, and product were collected from publicly available databases and integrated. A large set of miRNA target-specific regulatory sub-pathways (RSPs) having the form (T, G 1, G 2) was built from the integrated data and stored, where T is a miRNA-associated target gene, G 1 (G 2) is a gene/protein interacting with T (G 1). Each sequence (T, G 1, G 2) was assigned a p-value weighted by the participation of the three genes in molecular interactions and reaction pathways.

RESULTS

A web service platform, miRDRN (http://mirdrn.ncu.edu.tw/mirdrn/), was built. The database part of miRDRN currently stores 6,973,875 p-valued RSPs associated with 116 diseases in 78 tissue types built from 207 diseases-associated miRNA regulating 389 genes. miRDRN also provides facilities for the user to construct disease and tissue-specific miRNA regulatory networks from RSPs it stores, and to download and/or visualize parts or all of the product. User may use miRDRN to explore a single disease, or a disease-pair to gain insights on comorbidity. As demonstrations, miRDRN was applied: to explore the single disease colorectal cancer (CRC), in which 26 novel potential CRC target genes were identified; to study the comorbidity of the disease-pair Alzheimer's disease-Type 2 diabetes, in which 18 novel potential comorbid genes were identified; and, to explore possible causes that may shed light on recent failures of late-phase trials of anti-AD, BACE1 inhibitor drugs, in which genes downstream to BACE1 whose suppression may affect signal transduction were identified.

Genetic meta-analysis of diagnosed Alzheimer's disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing

Risk for late-onset Alzheimer's disease (LOAD), the most prevalent dementia, is partially driven by genetics. To identify LOAD risk loci, we performed a large genome-wide association meta-analysis of clinically diagnosed LOAD (94,437 individuals). We confirm 20 previous LOAD risk loci and identify five new genome-wide loci (IQCK, ACE, ADAM10, ADAMTS1, and WWOX), two of which (ADAM10, ACE) were identified in a recent genome-wide association (GWAS)-by-familial-proxy of Alzheimer's or dementia. Fine-mapping of the human leukocyte antigen (HLA) region confirms the neurological and immune-mediated disease haplotype HLA-DR15 as a risk factor for LOAD. Pathway analysis implicates immunity, lipid metabolism, tau binding proteins, and amyloid precursor protein (APP) metabolism, showing that genetic variants affecting APP and Aβ processing are associated not only with early-onset autosomal dominant Alzheimer's disease but also with LOAD. Analyses of risk genes and pathways show enrichment for rare variants (P = 1.32 × 10-7), indicating that additional rare variants remain to be identified. We also identify important genetic correlations between LOAD and traits such as family history of dementia and education.

A Network-Based Perspective in Alzheimer's Disease: Current State and an Integrative Framework

A major rise in the prevalence and impact of Alzheimer's disease (AD) is projected in the coming decades, resulting from increasing life expectancy, thus leading to substantially increased healthcare costs. While brain disfunctions at the time of diagnosis are irreversible, it is widely accepted that AD pathology develops decades before clinical symptoms onset. If incipient processes can be detected early in the disease progression, prospective intervention for preventing or slowing the disease can be designed. Currently, there is no noninvasive biomarker available to detect and monitor early stages of disease progression. The complex etiology of AD warrants a systems-based approach supporting the integration of multimodal and multilevel data, while network-based modeling provides the scaffolding for methods revealing complex systems-level disruptions initiated by the disease. In this work, we review current state-of-the-art, focusing on network-based biomarkers at molecular and brain functional connectivity levels. Particular emphasis is placed on outlining recent trends, which highlight the functional importance of modular substructures in molecular and connectivity networks and their potential biomarker value. Our perspective is rooted in network medicine and summarizes the pipelines for identifying network-based biomarkers, as well as the benefits of integrating genotype and brain phenotype information for a comprehensively noninvasive approach in the early diagnosis of AD. Finally, we propose a framework for integrating knowledge from molecular and brain connectivity levels, which has the potential to enable noninvasive diagnosis, provide support for monitoring therapies, and help understand heretofore unexamined deep level relations between genotype and brain phenotype.

Autophagy and Alzheimer's Disease: From Molecular Mechanisms to Therapeutic Implications

Alzheimer’s disease (AD) is the most common cause of progressive dementia in the elderly. It is characterized by a progressive and irreversible loss of cognitive abilities and formation of senile plaques, composed mainly of amyloid β (Aβ), and neurofibrillary tangles (NFTs), composed of tau protein, in the hippocampus and cortex of afflicted humans. In brains of AD patients the metabolism of Aβ is dysregulated, which leads to the accumulation and aggregation of Aβ. Metabolism of Aβ and tau proteins is crucially influenced by autophagy. Autophagy is a lysosome-dependent, homeostatic process, in which organelles and proteins are degraded and recycled into energy. Thus, dysfunction of autophagy is suggested to lead to the accretion of noxious proteins in the AD brain. In the present review, we describe the process of autophagy and its importance in AD. Additionally, we discuss mechanisms and genes linking autophagy and AD, i.e., the mTOR pathway, neuroinflammation, endocannabinoid system, ATG7, BCL2, BECN1, CDK5, CLU, CTSD, FOXO1, GFAP, ITPR1, MAPT, PSEN1, SNCA, UBQLN1, and UCHL1. We also present pharmacological agents acting via modulation of autophagy that may show promise in AD therapy. This review updates our knowledge on autophagy mechanisms proposing novel therapeutic targets for the treatment of AD.

Knowledge-driven computational modeling in Alzheimer's disease research: Current state and future trends

Neurodegenerative diseases such as Alzheimer's disease (AD) follow a slowly progressing dysfunctional trajectory, with a large presymptomatic component and many comorbidities. Using preclinical models and large-scale omics studies ranging from genetics to imaging, a large number of processes that might be involved in AD pathology at different stages and levels have been identified. The sheer number of putative hypotheses makes it almost impossible to estimate their contribution to the clinical outcome and to develop a comprehensive view on the pathological processes driving the clinical phenotype. Traditionally, bioinformatics approaches have provided correlations and associations between processes and phenotypes. Focusing on causality, a new breed of advanced and more quantitative modeling approaches that use formalized domain expertise offer new opportunities to integrate these different modalities and outline possible paths toward new therapeutic interventions. This article reviews three different computational approaches and their possible complementarities. Process algebras, implemented using declarative programming languages such as Maude, facilitate simulation and analysis of complicated biological processes on a comprehensive but coarse-grained level. A model-driven Integration of Data and Knowledge, based on the OpenBEL platform and using reverse causative reasoning and network jump analysis, can generate mechanistic knowledge and a new, mechanism-based taxonomy of disease. Finally, Quantitative Systems Pharmacology is based on formalized implementation of domain expertise in a more fine-grained, mechanism-driven, quantitative, and predictive humanized computer model. We propose a strategy to combine the strengths of these individual approaches for developing powerful modeling methodologies that can provide actionable knowledge for rational development of preventive and therapeutic interventions. Development of these computational approaches is likely to be required for further progress in understanding and treating AD.

Analyzing the genes related to Alzheimer's disease via a network and pathway-based approach

Background

Our understanding of the molecular mechanisms underlying Alzheimer’s disease (AD) remains incomplete. Previous studies have revealed that genetic factors provide a significant contribution to the pathogenesis and development of AD. In the past years, numerous genes implicated in this disease have been identified via genetic association studies on candidate genes or at the genome-wide level. However, in many cases, the roles of these genes and their interactions in AD are still unclear. A comprehensive and systematic analysis focusing on the biological function and interactions of these genes in the context of AD will therefore provide valuable insights to understand the molecular features of the disease.

Method

In this study, we collected genes potentially associated with AD by screening publications on genetic association studies deposited in PubMed. The major biological themes linked with these genes were then revealed by function and biochemical pathway enrichment analysis, and the relation between the pathways was explored by pathway crosstalk analysis. Furthermore, the network features of these AD-related genes were analyzed in the context of human interactome and an AD-specific network was inferred using the Steiner minimal tree algorithm.

Results

We compiled 430 human genes reported to be associated with AD from 823 publications. Biological theme analysis indicated that the biological processes and biochemical pathways related to neurodevelopment, metabolism, cell growth and/or survival, and immunology were enriched in these genes. Pathway crosstalk analysis then revealed that the significantly enriched pathways could be grouped into three interlinked modules—neuronal and metabolic module, cell growth/survival and neuroendocrine pathway module, and immune response-related module—indicating an AD-specific immune-endocrine-neuronal regulatory network. Furthermore, an AD-specific protein network was inferred and novel genes potentially associated with AD were identified.

Conclusion

By means of network and pathway-based methodology, we explored the pathogenetic mechanism underlying AD at a systems biology level. Results from our work could provide valuable clues for understanding the molecular mechanism underlying AD. In addition, the framework proposed in this study could be used to investigate the pathological molecular network and genes relevant to other complex diseases or phenotypes.

Electronic supplementary material

The online version of this article (doi:10.1186/s13195-017-0252-z) contains supplementary material, which is available to authorized users.

THD-Module Extractor: An Application for CEN Module Extraction and Interesting Gene Identification for Alzheimer's Disease

There exist many tools and methods for construction of co-expression network from gene expression data and for extraction of densely connected gene modules. In this paper, a method is introduced to construct co-expression network and to extract co-expressed modules having high biological significance. The proposed method has been validated on several well known microarray datasets extracted from a diverse set of species, using statistical measures, such as p and q values. The modules obtained in these studies are found to be biologically significant based on Gene Ontology enrichment analysis, pathway analysis, and KEGG enrichment analysis. Further, the method was applied on an Alzheimer’s disease dataset and some interesting genes are found, which have high semantic similarity among them, but are not significantly correlated in terms of expression similarity. Some of these interesting genes, such as MAPT, CASP2, and PSEN2, are linked with important aspects of Alzheimer’s disease, such as dementia, increase cell death, and deposition of amyloid-beta proteins in Alzheimer’s disease brains. The biological pathways associated with Alzheimer’s disease, such as, Wnt signaling, Apoptosis, p53 signaling, and Notch signaling, incorporate these interesting genes. The proposed method is evaluated in regard to existing literature.

Common Aging Signature in the Peripheral Blood of Vascular Dementia and Alzheimer's Disease

Alzheimer's disease (AD) and vascular dementia (VaD) are the two most dominant forms of dementia in elderly people. Due to the large overlap between AD and VaD in clinical observations, great controversies exist regarding the distinction and connection between these two types of senile dementia. Here for the first time, we resort to the gene expression pattern of the peripheral blood to compare AD and VaD objectively. In our previous work, we have demonstrated that the dysregulation of gene expression in AD is unique among the examined diseases including neurological diseases, cancer, and metabolic diseases. In this study, we found that the dysregulation of gene expression in AD and VaD is quite similar to each other at both functional and gene levels. Interestingly, the dysregulation started at the early stages of the diseases, namely mild cognitive impairment (MCI) and vascular cognitive impairment (VCI). We have also shown that this signature is distinctive from that of peripheral vascular diseases. Comparison with aging studies revealed that the most profound change in AD and VaD, namely ribosome, is consistent with the accelerated aging scenario. This study may have implications to the common mechanism between AD and VaD.

Biological databases for human research

The completion of the Human Genome Project lays a foundation for systematically studying the human genome from evolutionary history to precision medicine against diseases. With the explosive growth of biological data, there is an increasing number of biological databases that have been developed in aid of human-related research. Here we present a collection of human-related biological databases and provide a mini-review by classifying them into different categories according to their data types. As human-related databases continue to grow not only in count but also in volume, challenges are ahead in big data storage, processing, exchange and curation.