Lieke M Kuiper, Harmke A Polinder-Bos, Daniele Bizzarri, Dina Vojinovic, Costanza L Vallerga, Marian Beekman, E T Dollé, Mohsen Ghanbari, Trudy Voortman, Marcel J T Reinders, W M Monique Verschuren, P Eline Slagboom, Erik B van den Akker, Joyce B J van Meurs
{"title":"生物年龄的表观遗传学和代谢组学生物标志物:死亡率和虚弱风险的比较分析。","authors":"Lieke M Kuiper, Harmke A Polinder-Bos, Daniele Bizzarri, Dina Vojinovic, Costanza L Vallerga, Marian Beekman, E T Dollé, Mohsen Ghanbari, Trudy Voortman, Marcel J T Reinders, W M Monique Verschuren, P Eline Slagboom, Erik B van den Akker, Joyce B J van Meurs","doi":"10.1093/gerona/glad137","DOIUrl":null,"url":null,"abstract":"<p><p>Biological age captures a person's age-related risk of unfavorable outcomes using biophysiological information. Multivariate biological age measures include frailty scores and molecular biomarkers. These measures are often studied in isolation, but here we present a large-scale study comparing them. In 2 prospective cohorts (n = 3 222), we compared epigenetic (DNAm Horvath, DNAm Hannum, DNAm Lin, DNAm epiTOC, DNAm PhenoAge, DNAm DunedinPoAm, DNAm GrimAge, and DNAm Zhang) and metabolomic-based (MetaboAge and MetaboHealth) biomarkers in reflection of biological age, as represented by 5 frailty measures and overall mortality. Biomarkers trained on outcomes with biophysiological and/or mortality information outperformed age-trained biomarkers in frailty reflection and mortality prediction. DNAm GrimAge and MetaboHealth, trained on mortality, showed the strongest association with these outcomes. The associations of DNAm GrimAge and MetaboHealth with frailty and mortality were independent of each other and of the frailty score mimicking clinical geriatric assessment. Epigenetic, metabolomic, and clinical biological age markers seem to capture different aspects of aging. These findings suggest that mortality-trained molecular markers may provide novel phenotype reflecting biological age and strengthen current clinical geriatric health and well-being assessment.</p>","PeriodicalId":49953,"journal":{"name":"Journals of Gerontology Series A-Biological Sciences and Medical Sciences","volume":" ","pages":"1753-1762"},"PeriodicalIF":4.3000,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/8e/8e/glad137.PMC10562890.pdf","citationCount":"0","resultStr":"{\"title\":\"Epigenetic and Metabolomic Biomarkers for Biological Age: A Comparative Analysis of Mortality and Frailty Risk.\",\"authors\":\"Lieke M Kuiper, Harmke A Polinder-Bos, Daniele Bizzarri, Dina Vojinovic, Costanza L Vallerga, Marian Beekman, E T Dollé, Mohsen Ghanbari, Trudy Voortman, Marcel J T Reinders, W M Monique Verschuren, P Eline Slagboom, Erik B van den Akker, Joyce B J van Meurs\",\"doi\":\"10.1093/gerona/glad137\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Biological age captures a person's age-related risk of unfavorable outcomes using biophysiological information. Multivariate biological age measures include frailty scores and molecular biomarkers. These measures are often studied in isolation, but here we present a large-scale study comparing them. In 2 prospective cohorts (n = 3 222), we compared epigenetic (DNAm Horvath, DNAm Hannum, DNAm Lin, DNAm epiTOC, DNAm PhenoAge, DNAm DunedinPoAm, DNAm GrimAge, and DNAm Zhang) and metabolomic-based (MetaboAge and MetaboHealth) biomarkers in reflection of biological age, as represented by 5 frailty measures and overall mortality. Biomarkers trained on outcomes with biophysiological and/or mortality information outperformed age-trained biomarkers in frailty reflection and mortality prediction. DNAm GrimAge and MetaboHealth, trained on mortality, showed the strongest association with these outcomes. The associations of DNAm GrimAge and MetaboHealth with frailty and mortality were independent of each other and of the frailty score mimicking clinical geriatric assessment. Epigenetic, metabolomic, and clinical biological age markers seem to capture different aspects of aging. These findings suggest that mortality-trained molecular markers may provide novel phenotype reflecting biological age and strengthen current clinical geriatric health and well-being assessment.</p>\",\"PeriodicalId\":49953,\"journal\":{\"name\":\"Journals of Gerontology Series A-Biological Sciences and Medical Sciences\",\"volume\":\" \",\"pages\":\"1753-1762\"},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2023-10-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/8e/8e/glad137.PMC10562890.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journals of Gerontology Series A-Biological Sciences and Medical Sciences\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1093/gerona/glad137\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GERIATRICS & GERONTOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journals of Gerontology Series A-Biological Sciences and Medical Sciences","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/gerona/glad137","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GERIATRICS & GERONTOLOGY","Score":null,"Total":0}
Epigenetic and Metabolomic Biomarkers for Biological Age: A Comparative Analysis of Mortality and Frailty Risk.
Biological age captures a person's age-related risk of unfavorable outcomes using biophysiological information. Multivariate biological age measures include frailty scores and molecular biomarkers. These measures are often studied in isolation, but here we present a large-scale study comparing them. In 2 prospective cohorts (n = 3 222), we compared epigenetic (DNAm Horvath, DNAm Hannum, DNAm Lin, DNAm epiTOC, DNAm PhenoAge, DNAm DunedinPoAm, DNAm GrimAge, and DNAm Zhang) and metabolomic-based (MetaboAge and MetaboHealth) biomarkers in reflection of biological age, as represented by 5 frailty measures and overall mortality. Biomarkers trained on outcomes with biophysiological and/or mortality information outperformed age-trained biomarkers in frailty reflection and mortality prediction. DNAm GrimAge and MetaboHealth, trained on mortality, showed the strongest association with these outcomes. The associations of DNAm GrimAge and MetaboHealth with frailty and mortality were independent of each other and of the frailty score mimicking clinical geriatric assessment. Epigenetic, metabolomic, and clinical biological age markers seem to capture different aspects of aging. These findings suggest that mortality-trained molecular markers may provide novel phenotype reflecting biological age and strengthen current clinical geriatric health and well-being assessment.
期刊介绍:
Publishes articles representing the full range of medical sciences pertaining to aging. Appropriate areas include, but are not limited to, basic medical science, clinical epidemiology, clinical research, and health services research for professions such as medicine, dentistry, allied health sciences, and nursing. It publishes articles on research pertinent to human biology and disease.