{"doi":"10.1101/2022.11.01.514719","title":"A generalizable epigenetic clock captures aging in two nonhuman primates","abstract":"<jats:title>ABSTRACT</jats:title>\n                <jats:p>Epigenetic clocks generated from DNA methylation array data provide important insights into biological aging, disease susceptibility, and mortality risk. However, these clocks cannot be applied to high-throughput, sequence-based datasets more commonly used to study nonhuman animals. Here, we built a generalizable epigenetic clock using genome-wide DNA methylation data from 493 free-ranging rhesus macaques. Using a sliding-window approach that maximizes generalizability across datasets and species, this model predicted age with high accuracy (± 1.42 years) in held-out test samples, as well as in two independent test sets: rhesus macaques from a captive population (n=43) and wild baboons in Kenya (n=271). Our model can also be used to generate insight into the factors hypothesized to alter epigenetic aging, including social status and exposure to traumatic events. Our results thus provide a flexible tool for predicting age in other populations and species and illustrate how connecting behavioral data with the epigenetic clock can uncover social influences on biological age.</jats:p>","journal":null,"year":null,"id":647063,"datarank":0.24141568686511508,"base_score":1.6094379124341003,"endowment":1.6094379124341003,"self_citation_contribution":0.24141568686511508,"citation_network_contribution":0.0,"self_endowment_contribution":0.24141568686511508,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":4,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"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":267895,"name":"Kenneth L. Chiou","orcid":"0000-0001-7247-4107","position":1,"is_corresponding":false},{"id":267898,"name":"Marina M. Watowich","orcid":"0000-0003-4144-4225","position":2,"is_corresponding":false},{"id":556515,"name":"Arianne Mercer","orcid":null,"position":3,"is_corresponding":false},{"id":1685610,"name":"Sierra N. Sams","orcid":null,"position":4,"is_corresponding":false},{"id":267899,"name":"Julie E. Horvath","orcid":"0000-0002-6426-035X","position":5,"is_corresponding":false},{"id":497291,"name":"Jordan A. Anderson","orcid":"0000-0002-8109-7136","position":6,"is_corresponding":false},{"id":109258,"name":"Jenny Tung","orcid":"0000-0003-0416-2958","position":8,"is_corresponding":false},{"id":250515,"name":"James P. Higham","orcid":"0000-0002-1133-2030","position":9,"is_corresponding":false},{"id":267903,"name":"Lauren J. N. Brent","orcid":"0000-0002-1202-1939","position":10,"is_corresponding":false},{"id":267902,"name":"Melween I. Martínez","orcid":"0000-0003-1030-9506","position":11,"is_corresponding":false},{"id":267896,"name":"Michael J. Montague","orcid":"0000-0003-0253-4404","position":12,"is_corresponding":false},{"id":246475,"name":"Michael L. Platt","orcid":"0000-0003-3912-8821","position":13,"is_corresponding":false},{"id":267900,"name":"Kirstin N. Sterner","orcid":"0000-0001-8429-4533","position":14,"is_corresponding":false},{"id":109246,"name":"Noah Snyder‐Mackler","orcid":"0000-0003-3026-6160","position":15,"is_corresponding":false},{"id":267897,"name":"Elisabeth A. Goldman","orcid":"0000-0003-1562-0010","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"A generalizable epigenetic clock captures aging in two nonhuman primates","abstract":"<jats:title>ABSTRACT</jats:title>\n                <jats:p>Epigenetic clocks generated from DNA methylation array data provide important insights into biological aging, disease susceptibility, and mortality risk. However, these clocks cannot be applied to high-throughput, sequence-based datasets more commonly used to study nonhuman animals. Here, we built a generalizable epigenetic clock using genome-wide DNA methylation data from 493 free-ranging rhesus macaques. Using a sliding-window approach that maximizes generalizability across datasets and species, this model predicted age with high accuracy (± 1.42 years) in held-out test samples, as well as in two independent test sets: rhesus macaques from a captive population (n=43) and wild baboons in Kenya (n=271). Our model can also be used to generate insight into the factors hypothesized to alter epigenetic aging, including social status and exposure to traumatic events. Our results thus provide a flexible tool for predicting age in other populations and species and illustrate how connecting behavioral data with the epigenetic clock can uncover social influences on biological age.</jats:p>","is_dataset_classified":null,"base_score":1.3862943611198906,"endowment":1.3862943611198906,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"19910364","pmcid":null,"openalex_id":"https://openalex.org/W4307981475","authors":[],"funders":[{"funder_name":"National Institutes of Health","grant_id":"1R01GM102562-01","title":"Stress and the Genome: Testing the Impact of Social Effects on Gene Regulation"},{"funder_name":"National Institutes of Health","grant_id":"9R01AG057235-06","title":"Stress and the Genome: Testing the Impact of Social Effects on Gene Regulation"},{"funder_name":"National Institutes of Health","grant_id":"5P40OD012217-28","title":"CARIBBEAN PRIMATE RESEARCH CENTER"},{"funder_name":"National Institutes of Health","grant_id":"3R01AG060931-02S1","title":"Social modifiers of the pace of aging across multiple domains and tissues"},{"funder_name":"National Institutes of Health","grant_id":"1R01MH089484-01","title":"Neurogenetic Model of Social Behavior Heterogeneity in Autism Spectrum Disorders"},{"funder_name":"National Institutes of Health","grant_id":"5R21AG075648-02","title":"Development and comparison of multi-tissue and liver-specific epigenetic clock models to measure variation in biological aging in the rhesus macaque."},{"funder_name":"National Science Foundation","grant_id":"1800558","title":"RAPID: Preservation of the Cayo Santiago macaque colony and post-storm behavioral and biological data in the aftermath of Hurricane Maria"},{"funder_name":"National Science Foundation","grant_id":"1920350","title":"Doctoral Dissertation Research: Investigating the relationship between diet and biological age with a primate epigenetic clock"},{"funder_name":"National Institutes of Health","grant_id":"5T32AG000057-34","title":"Genetic Approaches to Aging"},{"funder_name":"National Institutes of Health","grant_id":"5R01MH118203-03","title":"Neurogenomics of Vulnerability and Resilience to Mental Health Syndromes in Response to Extreme Life Events"},{"funder_name":"National Institutes of Health","grant_id":"4R00AG051764-03","title":"Gene regulatory analysis of social integration and resilience during aging"},{"funder_name":"National Institutes of Health","grant_id":"1F31AG072787-01A1","title":"Effects of an extreme natural disaster on immunity and aging"}],"total_grants":12,"fwci":null,"citation_percentile":null,"influential_citations":0,"citation_trend":[{"year":2023,"count":1},{"year":2024,"count":2}],"oa_status":"green","license":"cc-by","oa_locations":[{"url":"https://www.biorxiv.org/content/biorxiv/early/2022/11/02/2022.11.01.514719.full.pdf","host_type":"repository"},{"url":"https://www.biorxiv.org/content/biorxiv/early/2022/11/02/2022.11.01.514719.full.pdf","host_type":"repository"},{"url":"https://syndication.highwire.org/content/doi/10.1101/2022.11.01.514719","host_type":"publisher"},{"url":"https://doi.org/10.1101/2022.11.01.514719","host_type":"repository"}],"fields_of_study":["Epigenetics and DNA Methylation","Children's Rights and Participation","Genetics and Neurodevelopmental Disorders","0301 basic medicine","03 medical and health sciences"],"mesh_terms":[],"keywords":["Epigenetics","Biology","DNA methylation","Generalizability theory","Evolutionary biology","Population","Computational biology","Genetics","Psychology","Developmental psychology","Gene","Demography"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Good health and well-being"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-09T16:31:44.976908Z","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":[]}