Blood transcriptome analysis for Alzheimer' disease in Hong Kong Chinese population. (1st February 2022)

• Record Type: Journal Article
• Authors: Zhong, Huan; Zhou, Xiaopu; Jiang, Yuanbing; Chen, Yu; Lai, Nicole Chit Hang; Tong, Estella Pui‐Sze; Lo, Ronnie M.N.; Kwok, Timothy CY; Mok, Vincent C.T.; Ip, Fanny C. F.; Mok, Kin Y; Hardy, John; Fu, Amy K.Y.; Ip, Nancy Y.
• Is Part Of: Alzheimer's & dementia. Volume 17(2021)Supplement 3
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-02-01
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.056643
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Although blood transcriptome has emerged as a powerful resource for studying human diseases, the changes in the blood transcriptome of Alzheimer's disease (AD) patients are poorly understood. Method: We conducted transcriptome profiling of 422 participants (208 normal controls and 214 patients with AD) from the Hong Kong Chinese population. WGCNA (weighted correlation network analysis) was performed to construct a co‐expression network to identify modules associated with AD and AD‐associated biomarkers. Result: Co‐expression modules exerting significant association with AD and AD plasma biomarkers (e.g., Aβ and NFL) were identified. Pathway enrichment analysis suggested their possible involvement in specific biological pathways. Motif analysis further revealed the potential mechanisms that driving the observed blood transcriptomic changes observed in AD. Conclusion: The co‐expression network analysis of the AD blood transcriptome changes may facilitate a better understanding of AD progression, as well as the identification of potential targets for disease intervention and monitoring.