Identification of telomere-related genes associated with aging-related molecular clusters and the construction of a diagnostic model in Alzheimer's disease based on a bioinformatic analysis

Ruan, Yijun; Lv, Weichao; Li, Shuaiyu; Cheng, Yuzhong; Wang, Duanyang; Zhang, Chaofeng; Shimizu, Kuniyoshi

doi:10.1016/j.compbiomed.2023.106922

Cited by 2 publications

(1 citation statement)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Telomere-related genes have been proposed to play a role in the pathogenesis of AD. Ruan et al (2023) identified telomere-related genes associated with aging clusters in AD patients and explored their immunological characteristics. Furthermore, they established prediction models for AD and AD subtypes based on TRGs and validated them using artificial neural network analysis and nomogram models.…”

Section: Identification Of Candidate Biomarkers Associated With the B...mentioning

confidence: 99%

A review and analysis of key biomarkers in Alzheimer’s disease

Zhang,

Liu,

Zhang

et al. 2024

Front. Neurosci.

View full text Add to dashboard Cite

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects over 50 million elderly individuals worldwide. Although the pathogenesis of AD is not fully understood, based on current research, researchers are able to identify potential biomarker genes and proteins that may serve as effective targets against AD. This article aims to present a comprehensive overview of recent advances in AD biomarker identification, with highlights on the use of various algorithms, the exploration of relevant biological processes, and the investigation of shared biomarkers with co-occurring diseases. Additionally, this article includes a statistical analysis of key genes reported in the research literature, and identifies the intersection with AD-related gene sets from databases such as AlzGen, GeneCard, and DisGeNet. For these gene sets, besides enrichment analysis, protein–protein interaction (PPI) networks utilized to identify central genes among the overlapping genes. Enrichment analysis, protein interaction network analysis, and tissue-specific connectedness analysis based on GTEx database performed on multiple groups of overlapping genes. Our work has laid the foundation for a better understanding of the molecular mechanisms of AD and more accurate identification of key AD markers.

show abstract

Section: Identification Of Candidate Biomarkers Associated With the B...mentioning

confidence: 99%