Introduction: Alzheimer's Disease (AD) is the most common neurodegenerative disease, and timely and effective diagnosis is essential for the prevention and treatment of AD. Peripheral blood is readily available, inexpensive, and non-invasive, making it an ideal substrate for screening diagnostic biomarkers.
Method: The Notch signaling pathway is closely related to AD, so genes related to the Notch signaling pathway may be candidate diagnostic biomarkers for AD. Here, we have performed an integrated analysis of peripheral blood cells transcriptomics from two AD cohorts (GSE63060: Ctrl = 104, MCI = 80, AD = 145; GSE63061: Ctrl = 134, MCI = 109, AD = 139) to reveal the expression levels of 16 Notch signals involving 100 genes.
Result: The results have shown the changes in Notch signaling-related genes to be highly consistent in both AD cohorts. Bioinformatics analysis has found Differentially Expressed Genes (DEGs) related to Notch signaling to mainly play important roles in Alzheimer's disease, the Notch signaling pathway, and the C-type lectin receptor signaling pathway. Multiple machine learning analyses have revealed IKBKB, HDAC2, and PIK3R1 to exhibit good diagnostic value in both AD cohorts and that they may be ideal biomarkers for early diagnosis of AD.
Conclusion: This study has provided a comprehensive description of the molecular signatures of the Notch signaling pathway in AD peripheral blood and a potential diagnostic model for AD clinical screening.
Keywords: Alzheimer's disease; Notch signaling.; biomarkers; machine learning; peripheral blood; transcriptomics.
Copyright© Bentham Science Publishers; For any queries, please email at [email protected].