{"doi":"10.1111/cns.14859","title":"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.","journal":"CNS Neuroscience & Therapeutics","year":2024,"id":475936,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":3,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.6872,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1313232,"name":"Si Tan","orcid":null,"position":1,"is_corresponding":false},{"id":1312827,"name":"Xiaojing Song","orcid":"0000-0001-9462-0056","position":2,"is_corresponding":false},{"id":1313233,"name":"Xinyun Lin","orcid":null,"position":3,"is_corresponding":false},{"id":1313234,"name":"Kaize Yang","orcid":null,"position":4,"is_corresponding":false},{"id":1269694,"name":"Xiuhong Li","orcid":"0000-0001-8084-9706","position":5,"is_corresponding":false},{"id":300139,"name":"for the Alzheimer's Disease Neuroimaging Initiative","orcid":null,"position":6,"is_corresponding":false},{"id":1312826,"name":"Simin Deng","orcid":"0009-0009-5747-2205","position":0,"is_corresponding":true}],"reference_count":56,"raw_metadata":null,"created_at":"2026-07-19T02:06:21.071690Z","pmid":"39009557","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}