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Updated: May 23, 2026

Biomarker Identification for Gender Specificity of Alzheimer's Disease Based on the Glial Transcriptome Profiles
Published on: May 20, 2024
Analyzing microarray data of Alzheimer's using cluster analysis to identify the biomarker genes
Satya Vani Guttula1, Apparao Allam, R Sridhar Gumpeny
1Department of Biotechnology, Al-Ameer College of Engineering & IT, Andhra Pradesh, Visakhapatnam 531173, India.
Abstract:
Alzheimer is characterized by the presence of senile plaques and neurofibrillary tangles in cortical regions of the brain. The experimental data is taken from Gene Expression Omnibus. A hierarchical Cluster analysis and TreeView were performed to group genes on the basis of the expression pattern. The dynamic change of expression over time and diverse patterns of expression support the concept of a complex local milieu. TreeView allows the organized data to be visualized. List of 24 genes were obtained which showed high expression levels. Three genes, SORL1, APP, and APOE, are suspected to cause Alzheimer's whereas the other 21 genes are related to other diseases but may also be found to be associated with Alzheimer's, and these are TMEM59, CCT4, IGF2R, SFPQ, PRDX3, RNF14, IDS, SSBP1, SYNE2, TXNL4A, STXBP3, SMARCB1, ULK2, AGTPBP1, FABP7, CALB1, H2AFY, COPA, SAP18, ATIC and SYNCRIP.
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