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Journals / Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi / 2026 / Cilt: 24 Sayı: 4

In Silico Analysis of Alzheimer's Disease Mechanism Through DNA Methylation and Gene Expression Data

Alzheimer Hastalığı Mekanizmasının DNA Metilasyonu ve Gen Ekspresyon Verileri Üzerinden İn Silico Analizi

Fatih Özen(Tobio Pharmaceuticals Drug Industry and Trade Limited Company)0000-0001-9235-4524
Tuba Sevimoğlu(Sağlık Bilimleri Üniversitesi)0000-0003-4563-3154
Pages
1019–1026
Publication Date
2024-08-20
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

This study integrated DNA methylation and gene expression data to further our knowledge of the AD disease mechanism.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Alzheimer's Disease (AD) is a debilitating disease impairing memory and thought process with currently no cure.
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Key Findings & Data:In the current study, GEO2R, an integrated tool in the GEO database, was used to analyze DNA methylation and gene expression datasets associated with AD.
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Conclusion & Impact:This study integrated DNA methylation and gene expression data to further our knowledge of the AD disease mechanism.
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:Alzheimer Hastalığı · Gen İfadesi · DNA Metilasyonu

Abstract

Alzheimer's Disease (AD) is a debilitating disease impairing memory and thought process with currently no cure. In the current study, GEO2R, an integrated tool in the GEO database, was used to analyze DNA methylation and gene expression datasets associated with AD. Data from the BioGRID Database were used to create a PPI network of differentially methylation and expressed AD genes (DEMEGs). Cytoscape was used to image and analyze the PPI network topologically. The DAVID bioinformatics program was utilized to do enrichment analysis in order to uncover disease associations and signaling pathways. Furthermore, small molecules were predicted using Connectivity Map 2 (Cmap 2) as potential therapeutic agents that might be exploited as pharmacological targets for the study's DEMEGs. As a result, 502 mutual DEMEGs and several hubs that may be researched further as new biomarker candidates for AD such as SMURF1 and UBE2D2 were identified. The link between AD and the MAPK signaling pathway, as well as addiction and brain diseases such as ADHD and epilepsy has been established. Additionally, candidate small molecules that can be used as therapeutics such as flucloxacillin, butamben, and acetohexamide were proposed. This study integrated DNA methylation and gene expression data to further our knowledge of the AD disease mechanism.

Özet

Alzheimer Hastalığı (AD), şu anda tedavisi olmayan, hafızayı ve düşünce sürecini bozan, zayıflatıcı bir hastalıktır. Mevcut çalışmada, GEO veritabanında entegre bir araç olan GEO2R, AD ile ilişkili DNA metilasyonunu ve gen ekspresyonu veri kümelerini analiz etmek için kullanıldı. Diferansiyel olarak metillenmiş ve eksprese edilmiş AD genlerinden (DEMEG'ler) oluşan PPI ağı oluşturmak için BioGRID Veri Tabanından elde edilen veriler kullanıldı. PPI ağını topolojik olarak görüntülemek ve analiz etmek için Cytoscape kullanıldı. Hastalık ilişkilerini ve sinyal yolaklarını ortaya çıkarmak amacıyla zenginleştirme analizi yapmak için DAVID biyoinformatik programından yararlanıldı. Ayrıca, Connectivity Map 2 (Cmap 2) kullanılarak çalışmanın DEMEG'leri için farmakolojik hedefler olarak kullanılabilecek potansiyel terapötik ajanlar olarak küçük moleküller ortaya konuldu. Sonuç olarak, SMURF1 ve UBE2D2 gibi AD için yeni biyobelirteç adayları olarak daha fazla araştırılabilecek 502 ortak DEMEG ve çeşitli merkezi proteinler belirlendi. Alzheimer ile MAPK sinyal yolağının yanı sıra bağımlılık ve DEHB ve epilepsi gibi beyin hastalıkları arasındaki bağlantı da belirlendi. Ayrıca flukloksasilin, butamben, asetoheksamid gibi tedavi edici olarak kullanılabilecek aday küçük moleküller de önerilmiştir. Bu çalışma, AD hastalığı mekanizması hakkındaki bilgimizi ilerletmek için DNA metilasyonu ve gen ekspresyonu verilerini birleştirmiştir.

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Cite This Article

Özen, F., Sevimoğlu, T. (2024). In Silico Analysis of Alzheimer's Disease Mechanism Through DNA Methylation and Gene Expression Data. Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi, Cilt: 24 Sayı: 4, 1019–1026. https://doi.org/10.35414/akufemubid.1332018

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