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

Bai, Zhouxian; Han, Guangchun; Xie, Bin; Wang, Jiajia; Song, Fuhai; Xing, Peng; Lei, Hongxing

doi:10.1007/s12035-014-9011-3

Cited by 30 publications

(19 citation statements)

References 65 publications

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“…There have been several available datasets or projects focused on the curation of AD-related genes, including AlzGene [77], Alzheimer’s Disease Neuroimaging Initiative (ADNI) [78], the Alzheimer Disease & Frontotemporal Dementia Mutation Database (AD&FTDMDB) [79], and AlzBase [80]. While AlzGene maintains a comprehensive catalog of genetic association studies on AD and also includes results from meta-analysis of polymorphisms with genotype data available in several GWAS projects on AD, AD&FTDMDB is dedicated to the known mutations of genes associated with AD and frontotemporal dementias from the published reports or presentations at scientific meetings.…”

Section: Discussionmentioning

confidence: 99%

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

Xin

Ying

et al. 2017

Alz Res Therapy

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

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Section: Discussionmentioning

confidence: 99%

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

Xin

Ying

et al. 2017

Alz Res Therapy

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“…To further illustrate the relationship among the critical genes, we provided several types of networks including coexpression network, PPI network, mutual information network, and cocitation network. The first version of AlzBase (http://alz.big.ac.cn/alzBase/) is available online and we plan to update the database to keep up with the development in this field (Bai et al, 2015).…”

Section: Integrating Multiomics Information For Admentioning

confidence: 99%

Alzheimer's Disease

Song

Han

Bai

et al. 2015

International Review of Neurobiology

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“…Analysis of such network modules facilitates the study of molecular differences across different stages of a disease6. Methods presented in refs 7, 8, 9, 10, 11 suggest the application of CEN module extraction techniques in the analysis of genes related to diseases, such as Alzheimer’s Disease (AD). These studies consider the co-expressed genes in network modules based on expression similarity.…”

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confidence: 99%

“…Existing methods911131415, use CEN module extraction techniques that prioritize the genes and study them at molecular level during progression of AD and other neurodegenerative diseases. Alzbase11 is an integrated approach, which reveals links between upstream genetic variations and downstream endo-features and prioritizes genes in relation to AD.…”

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confidence: 99%

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

Kakati

Kashyap

Bhattacharyya

2016

Sci Rep

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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.The volume of data obtained by microarray or other new high throughput technologies have been increasing enormously, and as a result, the biological databases are growing enormously. The key challenge is to analyze these large amount of data and extract meaningful information. Therefore, it is an interesting and challenging task to represent these data in an easy way, so that researchers can communicate and interpret data efficiently. A biological network graph allows interactive visual representation and analysis of data. In a biological network, nodes represent bio-entities (genes or proteins) and edges represent associations between the bio-entities. The biological networks can be categorized broadly based on their constituent bio-entities, such as, protein-protein interaction network, gene co-expression network (CEN), and metabolic network. These biological networks encode the relationships, such as, correlation, co-expression, and co-regulation, among the bio-entities.A gene CEN is defined as an undirected graph, where two genes are connected to each other if their expression levels are similar across conditions. Information related to physical-interaction, genetic interaction, shared protein domains, co-localization, pathway, and predicted functions can be inferred from a gene CEN 1 . A gene CEN primarily shows correlation or association in a pair of genes in terms of standard correlation measures and mutual information. These networks encode the relationships of each entity with its neighbors, which helps in geometrical interpretations for extraction of functionally related genes or network modules.There are many established methods for construction of CEN based on various approaches and cor...

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

Cited by 30 publications

References 65 publications

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

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

Alzheimer's Disease

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

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