Prediction of disease progression in individuals with subjective cognitive decline using brain network analysis
- PMID: 39009557
- PMCID: PMC11250750
- DOI: 10.1111/cns.14859
Prediction of disease progression in individuals with subjective cognitive decline using brain network analysis
Abstract
Objective: The objective of this study is to explore potential differences in brain functional networks at baseline between individuals with progressive subjective cognitive decline (P-SCD) and stable subjective cognitive decline (S-SCD), as well as to identify potential indicators that can effectively distinguish between P-SCD and S-SCD.
Methods: Alzheimer's Disease Neuroimaging Initiative (ADNI) database was utilized to enroll SCD individuals with a follow-up period of over 3 years. This study included 39 individuals with S-SCD, 15 individuals with P-SCD, and 45 cognitively normal (CN) individuals. Brain functional networks were constructed based on the AAL template, and graph theory analysis was performed to determine the topological properties.
Results: For global metric, the S-SCD group exhibited stronger small-worldness with reduced connectivity among nearby nodes and accelerated compensatory information transfer capacity. For nodal efficiency, the S-SCD group showed increased connectivity in bilateral posterior cingulate gyri (PCG). However, for nodal local efficiency, the P-SCD group exhibited significantly reduced connectivity in the right cerebellar Crus I compared with the S-SCD group.
Conclusion: There are differences in brain functional networks at baseline between P-SCD and S-SCD groups. Furthermore, the right cerebellar Crus I region may be a potentially useful brain area to distinguish between P-SCD and S-SCD.
Keywords: SCD; brain functional networks; early identification; graph theory.
© 2024 The Author(s). CNS Neuroscience & Therapeutics published by John Wiley & Sons Ltd.
Conflict of interest statement
The author reports no conflicts of interest in this work.
Figures
References
-
- Abbott A. Conquering Alzheimer's: a look at the therapies of the future. Nature. 2023;616(7955):26‐28. - PubMed
-
- 2023 Alzheimer's disease facts and figures. Alzheimers Dement. 2023;19(4):1598‐1695. - PubMed
-
- Self WK, Holtzman DM. Emerging diagnostics and therapeutics for Alzheimer disease. Nat Med. 2023;29(9):2187‐2199. - PubMed
-
- Jessen F, Wolfsgruber S, Kleineindam L, et al. Subjective cognitive decline and stage 2 of Alzheimer disease in patients from memory centers. Alzheimers Dement. 2023;19(2):487‐497. - PubMed
Publication types
MeSH terms
Grants and funding
LinkOut - more resources
Full Text Sources
Medical
