{"doi":"10.1016/j.semcdb.2021.01.003","title":"Aging biomarkers and the brain","abstract":null,"journal":"Seminars in Cell & Developmental Biology","year":2021,"id":591917,"datarank":2.3060322093609273,"base_score":4.442651256490317,"endowment":4.442651256490317,"self_citation_contribution":0.6663976884735476,"citation_network_contribution":1.6396345208873797,"self_endowment_contribution":0.6663976884735476,"citer_contribution":1.6396345208873797,"corpus_percentile":null,"corpus_rank":null,"citation_count":84,"citer_count":78,"citers_with_citation_signal":57,"citers_with_endowment":57,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1514542,"name":"Kyra L. Thrush","orcid":null,"position":1,"is_corresponding":false},{"id":218505,"name":"Morgan E. Levine","orcid":"0000-0001-9890-9324","position":2,"is_corresponding":false},{"id":1514541,"name":"Albert T. Higgins-Chen","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Aging biomarkers and the brain","abstract":"Quantifying biological aging is critical for understanding why aging is the primary driver of morbidity and mortality and for assessing novel therapies to counter pathological aging. In the past decade, many biomarkers relevant to brain aging have been developed using various data types and modeling techniques. Aging involves numerous interconnected processes, and thus many complementary biomarkers are needed, each capturing a different slice of aging biology. Here we present a hierarchical framework highlighting how these biomarkers are related to each other and the underlying biological processes. We review those measures most studied in the context of brain aging: epigenetic clocks, proteomic clocks, and neuroimaging age predictors. Many studies have linked these biomarkers to cognition, mental health, brain structure, and pathology during aging. We also delve into the challenges and complexities in interpreting these biomarkers and suggest areas for further innovation. Ultimately, a robust mechanistic understanding of these biomarkers will be needed to effectively intervene in the aging process to prevent and treat age-related disease.","is_dataset_classified":null,"base_score":4.442651256490317,"endowment":4.442651256490317,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"33509689","pmcid":"PMC8292153","openalex_id":"https://openalex.org/W3121529995","authors":[],"funders":[{"funder_name":"NIMH NIH HHS","grant_id":"T32 MH019961","title":null},{"funder_name":"NIA NIH HHS","grant_id":"P30 AG066508","title":null},{"funder_name":"NIA NIH HHS","grant_id":"R01 AG065403","title":null},{"funder_name":"NIA NIH HHS","grant_id":"R01 AG068285","title":null},{"funder_name":"NIA NIH HHS","grant_id":"R01 AG057912","title":null},{"funder_name":"National Institute of Mental Health","grant_id":"","title":null},{"funder_name":"National Institute on Aging","grant_id":"","title":null}],"total_grants":7,"fwci":7.6538,"citation_percentile":0.98298422,"influential_citations":0,"citation_trend":[{"year":2021,"count":2},{"year":2022,"count":12},{"year":2023,"count":18},{"year":2024,"count":20},{"year":2025,"count":18},{"year":2026,"count":14}],"oa_status":"green","license":"https://doi.org/10.15223/policy-004","oa_locations":[{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8292153","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8292153","host_type":"repository"},{"url":"https://api.elsevier.com/content/article/PII:S1084952121000094?httpAccept=text/xml","host_type":"publisher"},{"url":"https://api.elsevier.com/content/article/PII:S1084952121000094?httpAccept=text/plain","host_type":"publisher"},{"url":"https://doi.org/10.1016/j.semcdb.2021.01.003","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/33509689","host_type":"repository"}],"fields_of_study":["Dementia and Cognitive Impairment Research","Functional Brain Connectivity Studies","Epigenetics and DNA Methylation","Aged","Aged, 80 and over","Aging","Biomarkers","Brain","Humans"],"mesh_terms":["Aged","Aged, 80 and over","Aging","Brain","Humans","Biomarkers"],"keywords":["Brain aging","Cognitive aging","Healthy aging","Neuroimaging","Context (archaeology)","Aging brain","Neuroscience","Biological age","Disease","Cognition","Psychology","Medicine","Biology","Gerontology","Pathology","Aging","Proteomics","Biomarker","Neurodegeneration","Epigenetic Clock"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-07-26T11:22:25.964051Z","pmid":null,"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":[]}