{"doi":"10.1093/gerona/glaf128","title":"Longitudinal associations between medication use and phenotypic aging: insights from the Baltimore longitudinal study of aging","abstract":"BACKGROUND: Limited population-based data exist on the association between medication use and changes in phenotypic aging. This study investigated these associations using data from the Baltimore Longitudinal Study of Aging. METHODS: Phenotypic aging (PA) markers were constructed using the Klemera-Doubal method across four domains: body composition (structural and metabolic changes), energetics (energy generation and utilization capacity), homeostatic mechanisms (internal stability maintenance), and neuroplasticity/neurodegeneration (nervous system function and decline). Associations between 27 common drug categories and changes in these PA markers were analyzed using conditional generalized estimating equations (cGEE), focusing on within-individual variation to control for genetics and early-life factors, with additional adjustments for time-varying covariates. RESULTS: Five drug categories were associated with significant reductions in PA markers. Vitamin D, bisphosphonates, and proton pump inhibitors were linked to decreases in body composition (Beta = -0.73 years, 95% CI: -1.35 to -0.10), energetics (Beta = -2.05, 95% CI: -3.98 to -0.13), and neuroplasticity/neurodegeneration (Beta = -1.00, 95% CI: -2.02 to -0.03), respectively. Thyroid hormones showed reductions in body composition (Beta = -1.75, 95% CI: -3.24 to -0.26) and neuroplasticity/neurodegeneration (Beta = -1.04, 95% CI: -1.96 to -0.12). Thiazides were associated with decreases across body composition (Beta = -1.55, 95% CI: -2.94 to -0.16), energetics (Beta = -2.36, 95% CI: -4.30 to -0.42), and homeostatic mechanisms (Beta = -3.83, 95% CI: -6.71 to -0.96). CONCLUSIONS: These findings suggest potential protective effects of certain medications on phenotypic aging. Further research is needed to validate these results, particularly with data from other populations.","journal":"The Journals of Gerontology Series A","year":2025,"id":567940,"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":0.0,"corpus_rank":10062,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.5855,"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":1443022,"name":"Perry Kuo","orcid":null,"position":1,"is_corresponding":false},{"id":243007,"name":"Ann Zenobia Moore","orcid":"0000-0002-1471-4253","position":2,"is_corresponding":false},{"id":107085,"name":"Madhav Thambisetty","orcid":"0000-0002-2200-2299","position":3,"is_corresponding":false},{"id":21956,"name":"Luigi Ferrucci","orcid":"0000-0002-6273-1613","position":4,"is_corresponding":false},{"id":228610,"name":"Sara Hägg","orcid":"0000-0002-2452-1500","position":5,"is_corresponding":false},{"id":1040588,"name":"Bowen Tang","orcid":"0000-0002-1391-2522","position":0,"is_corresponding":true}],"reference_count":49,"raw_metadata":null,"created_at":"2026-07-19T02:56:48.183032Z","pmid":"40498559","pmcid":"PMC12756985","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":[]}