A METHODOLOGY BASED ON MOLECULAR INTERACTIONS AND PATHWAYS TO FIND CANDIDATE GENES ASSOCIATED TO DISEASES: ITS APPLICATION TO SCHIZOPHRENIA AND ALZHEIMER'S DISEASE

2011 ◽  
Vol 09 (04) ◽  
pp. 541-557 ◽  
Author(s):  
MARÍA ELENA OCHAGAVÍA ◽  
JAMILET MIRANDA ◽  
MARCELO NAZÁBAL ◽  
ALEXANDER MARTIN ◽  
LIDIA INÉS NOVOA ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Candidate Genes ◽  
Reference Genes ◽  
Enrichment Analysis ◽  
Second Step ◽  
Proof Of Concept ◽  
Molecular Interaction Networks ◽  
Gene Enrichment ◽  
Single List

Experimental techniques for the identification of genes associated with diseases are expensive and have certain limitations. In this scenario, computational methods are useful tools to identify lists of promising genes for further experimental verification. This paper describes a flexible methodology for the in silico prediction of genes associated with diseases combining the use of available tools for gene enrichment analysis, gene network generation and gene prioritization. A set of reference genes, with a known association to a disease, is used as bait to extract candidate genes from molecular interaction networks and enriched pathways. In a second step, prioritization methods are applied to evaluate the similarities between previously selected candidates and the set of reference genes. The top genes obtained by these programs are grouped into a single list sorted by the number of methods that have selected each gene. As a proof of concept, top genes reported a few years ago in SzGene and AlzGene databases were used as references to predict genes associated to schizophrenia and Alzheimer's disease, respectively. In both cases, we were able to predict a statistically significant amount of genes belonging to the updated lists.

scholarly journals Co-expression Network Analysis Reveals Novel Genes Underlying Alzheimer’s Disease Pathogenesis

2020 ◽  
Vol 12 ◽  
Author(s):  
Rui-ting Hu ◽  
Qian Yu ◽  
Shao-dan Zhou ◽  
Yi-xin Yin ◽  
Rui-guang Hu ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Enrichment Analysis ◽  
Hub Genes ◽  
Novel Genes ◽  
Independent Dataset ◽  
Gene Enrichment Analysis ◽  
Gene Enrichment ◽  
Functional Pathways ◽  
Independent Cohort

Background: The pathogenesis of Alzheimer’s disease (AD) remains to be elucidated. This study aimed to identify the hub genes in AD pathogenesis and determine their functions and pathways.Methods: A co-expression network for an AD gene dataset with 401 samples was constructed, and the AD status-related genes were screened. The hub genes of the network were identified and validated by an independent cohort. The functional pathways of hub genes were analyzed.Results: The co-expression network revealed a module that related to the AD status, and 101 status-related genes were screened from the trait-related module. Gene enrichment analysis indicated that these status-related genes are involved in synaptic processes and pathways. Four hub genes (ENO2, ELAVL4, SNAP91, and NEFM) were identified from the module, and these hub genes all participated in AD-related pathways, but the associations of each gene with clinical features were variable. An independent dataset confirmed the different expression of hub genes between AD and controls.Conclusions: Four novel genes associated with AD pathogenesis were identified and validated, which provided novel therapeutic targets for AD.

scholarly journals Decreased MEF2A Expression Regulated by Its Enhancer Methylation Inhibits Autophagy and May Play an Important Role in the Progression of Alzheimer’s Disease

2021 ◽  
Vol 15 ◽  
Author(s):  
Hui Li ◽  
Feng Wang ◽  
Xuqi Guo ◽  
Yugang Jiang
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Transcription Factor ◽  
Methylation Level ◽  
Life Quality ◽  
Enrichment Analysis ◽  
Amyloid Plaques ◽  
Sequencing Data ◽  
Single Cell Sequencing ◽  
Enhancer Factor

Alzheimer’s disease (AD) is a neurodegenerative disease characterized by amyloid plaques and neurofibrillary tangles which significantly affects people’s life quality. Recently, AD has been found to be closely related to autophagy. The aim of this study was to identify autophagy-related genes associated with the pathogenesis of AD from multiple types of microarray and sequencing datasets using bioinformatics methods and to investigate their role in the pathogenesis of AD in order to identify novel strategies to prevent and treat AD. Our results showed that the autophagy-related genes were significantly downregulated in AD and correlated with the pathological progression. Furthermore, enrichment analysis showed that these autophagy-related genes were regulated by the transcription factor myocyte enhancer factor 2A (MEF2A), which had been confirmed using si-MEF2A. Moreover, the single-cell sequencing data suggested that MEF2A was highly expressed in microglia. Methylation microarray analysis showed that the methylation level of the enhancer region of MEF2A in AD was significantly increased. In conclusion, our results suggest that AD related to the increased methylation level of MEF2A enhancer reduces the expression of MEF2A and downregulates the expression of autophagy-related genes which are closely associated with AD pathogenesis, thereby inhibiting autophagy.

scholarly journals Systems Pharmacological Approach to Investigate the Mechanism of Acori Tatarinowii Rhizoma for Alzheimer’s Disease

2018 ◽  
Vol 2018 ◽  
pp. 1-20 ◽  
Author(s):  
Zhenyan Song ◽  
Fang Yin ◽  
Biao Xiang ◽  
Bin Lan ◽  
Shaowu Cheng
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Therapeutic Effects ◽  
Biological Processes ◽  
Pathway Enrichment ◽  
Study Results ◽  
Target Network ◽  
Anti Inflammatory

In traditional Chinese medicine (TCM), Acori Tatarinowii Rhizoma (ATR) is widely used to treat memory and cognition dysfunction. This study aimed to confirm evidence regarding the potential therapeutic effect of ATR on Alzheimer’s disease (AD) using a system network level based in silico approach. Study results showed that the compounds in ATR are highly connected to AD-related signaling pathways, biological processes, and organs. These findings were confirmed by compound-target network, target-organ location network, gene ontology analysis, and KEGG pathway enrichment analysis. Most compounds in ATR have been reported to have antifibrillar amyloid plaques, anti-tau phosphorylation, and anti-inflammatory effects. Our results indicated that compounds in ATR interact with multiple targets in a synergetic way. Furthermore, the mRNA expressions of genes targeted by ATR are elevated significantly in heart, brain, and liver. Our results suggest that the anti-inflammatory and immune system enhancing effects of ATR might contribute to its major therapeutic effects on Alzheimer’s disease.

scholarly journals Epigenome-wide meta-analysis of DNA methylation differences in prefrontal cortex implicates the immune processes in Alzheimer’s disease

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Lanyu Zhang ◽  
Tiago C. Silva ◽  
Juan I. Young ◽  
Lissette Gomez ◽  
Michael A. Schmidt ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Dna Methylation ◽  
Prefrontal Cortex ◽  
Biomarker Discovery ◽  
Meta Analysis ◽  
Enrichment Analysis ◽  
Braak Stage ◽  
Polycomb Repressive Complex 2 ◽  
Differentially Methylated Genes

AbstractDNA methylation differences in Alzheimer’s disease (AD) have been reported. Here, we conducted a meta-analysis of more than 1000 prefrontal cortex brain samples to prioritize the most consistent methylation differences in multiple cohorts. Using a uniform analysis pipeline, we identified 3751 CpGs and 119 differentially methylated regions (DMRs) significantly associated with Braak stage. Our analysis identified differentially methylated genes such as MAMSTR, AGAP2, and AZU1. The most significant DMR identified is located on the MAMSTR gene, which encodes a cofactor that stimulates MEF2C. Notably, MEF2C cooperates with another transcription factor, PU.1, a central hub in the AD gene network. Our enrichment analysis highlighted the potential roles of the immune system and polycomb repressive complex 2 in pathological AD. These results may help facilitate future mechanistic and biomarker discovery studies in AD.

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