{"doi":"10.9758/cpn.25.1360","title":"Cellular Senescence of Patient-derived Fibroblasts Reveals the Mid-old Stage as a Critical Window for Transcriptomic Signatures Linked to Alzheimer㉾s Disease Biomarkers and Classification","abstract":"Objective: Alzheimer's disease (AD) is strongly associated with aging, yet the interactions remain unclear. This study modeled replicative senescence in patient-derived fibroblasts to compare gene expression between AD dementia and controls across senescence stages and to evaluate whether stage-specific alterations reflect disease characteristics with diagnostic implications. Methods: Dermal fibroblasts from 13 AD dementia patients and 13 healthy controls were repeatedly passaged to induce replicative senescence and classified into young (passage 7), mid-old (passage 18), and old stages (passage 25-28). Transcriptomic profiling was performed by RNA sequencing, followed by stepwise gene extraction, machine learning-based classification, and correlation analyses with AD biomarkers. Results: Fibroblasts were successfully driven into replicative senescence, validated by SA-β-gal staining, increased expression of CDKN1A and CDKN2A, and transcriptomic age acceleration. From transcriptome data, 605 senescence-associated genes were identified, enriched in extracellular matrix remodeling, chromatin organization, and immune-related pathways. Machine learning classifiers trained on these genes achieved the highest accuracy at the mid-old stage above 0.9, markedly outperforming the young and old stages. In addition, among the most consistently selected mid-old genes, H2AC18, H1-2, and LTBP1 showed significant correlations with cortical amyloid burden and plasma pTau217, linking cellular transcriptomic changes to established AD biomarkers. Conclusion: In summary, replicative senescence models of patient-derived fibroblasts revealed that transcriptomic differences between AD dementia and controls peak at the mid-old stage. This transitional window represents the most informative point for capturing disease-related alterations with strong biomarker relevance.","journal":"Clinical Psychopharmacology and Neuroscience","year":2025,"id":585331,"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":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9558,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1498688,"name":"Sunwoo Yoon","orcid":"0000-0001-7501-1781","position":1,"is_corresponding":false},{"id":1498689,"name":"Yeojin Kim","orcid":"0000-0003-0877-7415","position":2,"is_corresponding":false},{"id":1498690,"name":"Hong Song","orcid":"0009-0008-6804-8680","position":3,"is_corresponding":false},{"id":1249949,"name":"You Jin Nam","orcid":"0000-0002-6603-5586","position":4,"is_corresponding":false},{"id":1485769,"name":"Sang Hyuk Lee","orcid":"0000-0002-4414-8176","position":5,"is_corresponding":false},{"id":1498691,"name":"Sehee Lee","orcid":"0009-0006-1659-3017","position":6,"is_corresponding":false},{"id":1498692,"name":"Daekyo Shin","orcid":"0009-0000-4958-5036","position":7,"is_corresponding":false},{"id":1498693,"name":"Sun Min Lee","orcid":"0000-0001-5917-015X","position":8,"is_corresponding":false},{"id":226620,"name":"So Young Moon","orcid":"0000-0002-1025-1968","position":9,"is_corresponding":false},{"id":411325,"name":"Eun‐Joo Kim","orcid":"0000-0002-8460-1377","position":10,"is_corresponding":false},{"id":393062,"name":"Soo Hyun Cho","orcid":"0000-0002-4262-1468","position":11,"is_corresponding":false},{"id":355748,"name":"Byeong C. Kim","orcid":"0000-0001-6827-6730","position":12,"is_corresponding":false},{"id":686613,"name":"Seong Hye Choi","orcid":"0000-0002-0680-8364","position":13,"is_corresponding":false},{"id":300908,"name":"Sang Won Seo","orcid":"0000-0002-8747-0122","position":14,"is_corresponding":false},{"id":1498694,"name":"Jin Cheol Kim","orcid":"0000-0003-3820-8811","position":15,"is_corresponding":false},{"id":1498695,"name":"Young Joon Park","orcid":"0000-0003-0723-4136","position":16,"is_corresponding":false},{"id":1498696,"name":"Hee Young Kang","orcid":"0000-0001-8697-4292","position":17,"is_corresponding":false},{"id":1498697,"name":"Sang‐Rae Lee","orcid":"0000-0001-8400-5973","position":18,"is_corresponding":false},{"id":1249948,"name":"Sunhwa Hong","orcid":"0000-0003-0268-6360","position":19,"is_corresponding":false},{"id":662356,"name":"Sang Joon Son","orcid":"0000-0001-7434-7996","position":20,"is_corresponding":false},{"id":226610,"name":"Chang Hyung Hong","orcid":"0000-0003-3258-7611","position":21,"is_corresponding":false},{"id":998661,"name":"Hyun Woong Roh","orcid":"0000-0002-1333-358X","position":22,"is_corresponding":false},{"id":1498687,"name":"Y.-J. Cho","orcid":"0009-0000-6474-3231","position":0,"is_corresponding":true}],"reference_count":0,"raw_metadata":null,"created_at":"2026-07-19T02:59:20.067334Z","pmid":"42036745","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":[]}