A meta-analysis of bulk RNA-seq datasets identifies potential biomarkers and repurposable therapeutics against Alzheimer’s disease

Abstract

AbstractAlzheimer’s disease (AD) poses a major challenge due to its impact on the elderly population and the lack of effective early diagnosis and treatment options. In an effort to address this issue, a study focused on identifying potential biomarkers and therapeutic agents for AD was carried out. Using RNA-Seq data from AD patients and healthy individuals, 12 differentially expressed genes (DEGs) were identified, with 9 expressing upregulation (ISG15, HRNR, MTATP8P1, MTCO3P12, DTHD1, DCX, ST8SIA2, NNAT,andPCDH11Y) and 3 expressing downregulation (LTF, XIST,andTTR). Among them,TTRexhibited the lowest gene expression profile. Interestingly, functional analysis tiedTTRto amyloid fiber formation and neutrophil degranulation through enrichment analysis. These findings suggested the potential ofTTRas a diagnostic biomarker for AD. Additionally, druggability analysis revealed that the FDA-approved drug Levothyroxine might be effective against the Transthyretin protein encoded by theTTRgene. Molecular docking and dynamics simulation studies of Levothyroxine and Transthyretin suggested that this drug could be repurposed to treat AD. However, additional studies using in vitro and in vivo models are necessary before these findings can be applied in clinical applications.