{"doi":"10.1007/s11357-025-02027-4","title":"Your brain doesn’t look a day past 70! Cross-sectional associations with brain-predicted age in the cognitively-intact oldest-old","abstract":"The cognitively-intact oldest-old (85 +) may be the most-resilient members of their birth cohort; due to survivorship effects (e.g., depletion of susceptibles), risk factors associated with brain aging biomarkers in younger samples may not generalize to the cognitively-intact oldest-old. We evaluated associations between established aging-related risk factors and brain-predicted age difference (brainPAD) in a cross-sectional cognitively-intact oldest-old sample. Additionally, we evaluated brainPAD-cognition associations to characterize brain maintenance vs. cognitive reserve in our sample. Oldest-old adults (N = 206; 85-99 years; Montreal Cognitive Assessment > 22 or neurologist evaluation) underwent T1-weighted MRI; brainPAD was generated with brainageR, such that more-positive brainPAD reflected more-advanced brain aging. Sex, education, alcohol and smoking history, exercise history, BMI, cardiovascular and metabolic disease history, and anticholinergic medication burden were self-reported. Global cognitive z-score and coefficient of variation were derived from the UDS 3.0 cognitive battery; crystallized-fluid discrepancy was derived from the NIH Toolbox Cognitive Battery. Mean brainPAD was -7.99 (SD: 5.37; range: -24.50, 6.03). Women showed more-delayed brain aging than men (B = -2.9, 95% CI = -4.6, -1.1, p = 0.002). No other exposures were significantly associated with brainPAD. BrainPAD was not associated with any cognitive variable. These findings suggest that cognitively-intact oldest-old adults may be atypically-resistant to risk factors associated with aging in younger samples, consistent with survivorship effects in aging. Furthermore, brainPAD may have limited explanatory value for cognitive performance in cognitively-intact oldest-old adults, potentially due to high cognitive reserve. Overall, our findings highlight the impact of survivorship effects on brain aging research.","journal":"GeroScience","year":2025,"id":584951,"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":0.9515,"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":1458095,"name":"Hannah Hoogerwoerd","orcid":"0009-0002-8087-7314","position":1,"is_corresponding":false},{"id":1458566,"name":"Joshua Juhasz","orcid":null,"position":2,"is_corresponding":false},{"id":980911,"name":"Keyanni Joy Johnson","orcid":null,"position":3,"is_corresponding":false},{"id":1458096,"name":"Paul D. Stewart","orcid":"0000-0001-7176-900X","position":4,"is_corresponding":false},{"id":279955,"name":"Pradyumna K. Bharadwaj","orcid":null,"position":5,"is_corresponding":false},{"id":906716,"name":"Stacy Merritt","orcid":null,"position":6,"is_corresponding":false},{"id":906719,"name":"Cortney J. Jessup","orcid":null,"position":7,"is_corresponding":false},{"id":295981,"name":"Clinton B. Wright","orcid":"0000-0002-9797-6215","position":8,"is_corresponding":false},{"id":279956,"name":"Georg A. Hishaw","orcid":null,"position":9,"is_corresponding":false},{"id":615563,"name":"David A. Raichlen","orcid":"0000-0002-4940-7886","position":10,"is_corresponding":false},{"id":953316,"name":"Victor A. Del Bene","orcid":"0000-0002-8562-5071","position":11,"is_corresponding":false},{"id":246149,"name":"Virginia G. Wadley","orcid":"0000-0003-4524-8395","position":12,"is_corresponding":false},{"id":390754,"name":"Theodore P. Trouard","orcid":"0000-0001-9461-2283","position":13,"is_corresponding":false},{"id":446739,"name":"Noam Alperin","orcid":"0000-0002-3828-2950","position":14,"is_corresponding":false},{"id":328215,"name":"Bonnie Levin","orcid":"0000-0003-0931-296X","position":15,"is_corresponding":false},{"id":310714,"name":"Tatjana Rundek","orcid":"0000-0002-7115-9815","position":16,"is_corresponding":false},{"id":576042,"name":"Kristina Visscher","orcid":"0000-0003-0737-4024","position":17,"is_corresponding":false},{"id":277891,"name":"Gene E. Alexander","orcid":"0000-0002-6476-5606","position":18,"is_corresponding":false},{"id":109360,"name":"Ronald A. Cohen","orcid":"0000-0002-8863-8847","position":19,"is_corresponding":false},{"id":277889,"name":"Eric C. Porges","orcid":"0000-0003-3885-5859","position":20,"is_corresponding":false},{"id":336598,"name":"Joseph M. Gullett","orcid":"0000-0002-8184-7187","position":21,"is_corresponding":false},{"id":528283,"name":"Mark K. Britton","orcid":"0000-0003-4261-1806","position":0,"is_corresponding":true}],"reference_count":110,"raw_metadata":null,"created_at":"2026-07-19T02:59:16.166424Z","pmid":"41381972","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":[]}