The Footprint of CHASERR as a Potential Culprit in Alzheimer's Disease Patients: An In-Silico-Experimental Study.

Abstract

Objectives: Dementia has become a major global cause of death, posing significant health and economic challenges. Alzheimer's disease (AD) is the most common type of dementia. Recent studies have shown that long noncoding RNAs (lncRNAs) play a role in AD development. In this context, the current study conducted a comprehensive meta-analysis of high-throughput Gene Expression Omnibus (GEO) datasets to identify significant lncRNAs that could play a crucial role in the pathogenesis of AD.

Methods: Three microarray expression profiles of human subjects diagnosed with AD and corresponding healthy controls were obtained from the GEO database. Afterward, the expression profiles from the chosen microarray datasets were combined. A network of differentially expressed genes (DEGs) was visualized, identifying key hub genes. Subsequently, the two significant lncRNAs, identified as LINC01003 and CHASERR, were chosen based on the number of interactions between hubs and lncRNAs. Blood samples were collected from AD patients as well as from healthy control individuals. Ultimately, the expression levels of CHASERR and LINC01003 were quantitatively assessed in the blood samples of 50 AD patients and 50 healthy controls using the quantitative Real-Time PCR (q-PCR) technique.

Results: Experimental validation showed that CHASERR was differentially expressed in Alzheimer's disease (AD) patients compared to the control group. In contrast, LINC01003 revealed no significant difference between the AD patients and the control group.

Conclusion: This study thoroughly examined the molecular landscape of AD, identifying key differentially expressed genes and highlighting candidate CHASERR as a potential molecular biomarker for AD patients.