{"doi":"10.1002/dad2.70006","title":"Assessing Alzheimer's disease via plasma extracellular vesicle–derived mRNA","abstract":"INTRODUCTION: Alzheimer's disease (AD), the most prevalent neurodegenerative disorder globally, has emerged as a significant health concern. Recently it has been revealed that extracellular vesicles (EVs) play a critical role in AD pathogenesis and progression. Their stability and presence in various biofluids, such as blood, offer a minimally invasive window for monitoring AD-related changes. METHODS: We analyzed plasma EV-derived messenger RNA (mRNA) from 82 human subjects, including individuals with AD, mild cognitive impairment (MCI), and healthy controls. With next-generation sequencing, we profiled differentially expressed genes (DEGs), identifying those associated with AD. RESULTS: Based on DEGs identified in both the MCI and AD groups, a diagnostic model was established based on machine learning, demonstrating an average diagnostic accuracy of over 98% and showed a strong correlation with different AD stages. DISCUSSION: mRNA derived from plasma EVs shows significant promise as a non-invasive biomarker for the early detection and continuous monitoring of AD. Highlights: The study conducted next-generation sequencing (NGS) of mRNA derived from human plasma extracellular vesicles (EVs) to assess Alzheimer's disease (AD).Profiling of plasma EV-derived mRNA shows a significantly enriched AD pathway, indicating its potential for AD-related studies.The AD-prediction model achieved a receiver-operating characteristic area under the curve (ROC-AUC) of more than 0.98, with strong correlation to the established Clinical Dementia Rating (CDR).","journal":"Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring","year":2024,"id":447479,"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":6,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9311,"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":737041,"name":"Ching‐Fang Chang","orcid":"0000-0001-6754-2769","position":1,"is_corresponding":false},{"id":1168772,"name":"Katherine Tuchez","orcid":null,"position":2,"is_corresponding":false},{"id":1265546,"name":"Fei Liu","orcid":"0000-0002-9814-4226","position":3,"is_corresponding":false},{"id":807960,"name":"Yuchao Chen","orcid":"0009-0008-9676-7770","position":4,"is_corresponding":false},{"id":1063150,"name":"Le Hoang Phu Pham","orcid":null,"position":0,"is_corresponding":true}],"reference_count":22,"raw_metadata":null,"created_at":"2026-07-19T02:02:03.354708Z","pmid":"39279994","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":[]}