{"doi":"10.3233/jad-230027","title":"Uncovering the System Vulnerability and Criticality of Human Brain Under Dynamical Neuropathological Events in Alzheimer’s Disease","abstract":"BACKGROUND: Despite the striking efforts in investigating neurobiological factors behind the acquisition of amyloid-β (A), protein tau (T), and neurodegeneration ([N]) biomarkers, the mechanistic pathways of how AT[N] biomarkers spreading throughout the brain remain elusive. OBJECTIVE: To disentangle the massive heterogeneities in Alzheimer's disease (AD) progressions and identify vulnerable/critical brain regions to AD pathology. METHODS: In this work, we characterized the interaction of AT[N] biomarkers and their propagation across brain networks using a novel bistable reaction-diffusion model, which allows us to establish a new systems biology underpinning of AD progression. We applied our model to large-scale longitudinal neuroimages from the ADNI database and studied the systematic vulnerability and criticality of brains. RESULTS: Our model yields long term prediction that is statistically significant linear correlated with temporal imaging data, produces clinically consistent risk prediction, and captures the Braak-like spreading pattern of AT[N] biomarkers in AD development. CONCLUSIONS: Our major findings include (i) tau is a stronger indicator of regional risk compared to amyloid, (ii) temporal lobe exhibits higher vulnerability to AD-related pathologies, (iii) proposed critical brain regions outperform hub nodes in transmitting disease factors across the brain, and (iv) comparing the spread of neuropathological burdens caused by amyloid-β and tau diffusions, disruption of metabolic balance is the most determinant factor contributing to the initiation and progression of AD.","journal":"Journal of Alzheimer s Disease","year":2023,"id":367358,"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":5,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9545,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":384819,"name":"Qing Liu","orcid":"0000-0001-5286-4423","position":1,"is_corresponding":false},{"id":1046365,"name":"Haorui Zhang","orcid":"0009-0004-0445-2810","position":2,"is_corresponding":false},{"id":1124510,"name":"Michelle Dai","orcid":"0000-0001-5490-9242","position":3,"is_corresponding":false},{"id":288146,"name":"Qianqian Song","orcid":"0000-0002-4455-5302","position":4,"is_corresponding":false},{"id":397222,"name":"Defu Yang","orcid":"0000-0002-0212-9882","position":5,"is_corresponding":false},{"id":397224,"name":"Guorong Wu","orcid":"0000-0002-0550-6145","position":6,"is_corresponding":false},{"id":872308,"name":"Minghan Chen","orcid":"0000-0002-7321-8962","position":7,"is_corresponding":false},{"id":346022,"name":"Jingwen Zhang","orcid":"0000-0003-3568-6017","position":0,"is_corresponding":true}],"reference_count":72,"raw_metadata":null,"created_at":"2026-07-19T01:15:12.215513Z","pmid":"37661878","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":[]}