Biological age estimation using circulating blood biomarkers

被引：16
作者：
Bortz J. [1 ,2 ]
Guariglia A. [1 ,2 ]
Klaric L. [1 ]
Tang D. [2 ]
Ward P. [1 ]
Geer M. [1 ]
Chadeau-Hyam M. [2 ,3 ,4 ]
Vuckovic D. [2 ,4 ]
Joshi P.K. [1 ,5 ]
机构：
[1] Humanity Inc, Humanity, 177 Huntington Ave, Ste 1700, Humanity Inc - 91556, Boston, 02115, MA
[2] Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, London
[3] MRC Centre for Environment and Health, School of Public Health, Imperial College London, London
[4] NIHR-HPRU, Health Protection Research Unit in Chemical and Radiation Threats and Hazards, Public Health England and Imperial College London, London
[5] Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh
来源：
Communications Biology | / 6卷 / 1期
关键词：
D O I：
10.1038/s42003-023-05456-z
中图分类号：
学科分类号：
摘要：
Biological age captures physiological deterioration better than chronological age and is amenable to interventions. Blood-based biomarkers have been identified as suitable candidates for biological age estimation. This study aims to improve biological age estimation using machine learning models and a feature-set of 60 circulating biomarkers available from the UK Biobank (n = 306,116). We implement an Elastic-Net derived Cox model with 25 selected biomarkers to predict mortality risk (C-Index = 0.778; 95% CI [0.767–0.788]), which outperforms the well-known blood-biomarker based PhenoAge model (C-Index = 0.750; 95% CI [0.739–0.761]), providing a C-Index lift of 0.028 representing an 11% relative increase in predictive value. Importantly, we then show that using common clinical assay panels, with few biomarkers, alongside imputation and the model derived on the full set of biomarkers, does not substantially degrade predictive accuracy from the theoretical maximum achievable for the available biomarkers. Biological age is estimated as the equivalent age within the same-sex population which corresponds to an individual’s mortality risk. Values ranged between 20-years younger and 20-years older than individuals’ chronological age, exposing the magnitude of ageing signals contained in blood markers. Thus, we demonstrate a practical and cost-efficient method of estimating an improved measure of Biological Age, available to the general population. © 2023, The Author(s).
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  • [1] Baker G.T., Sprott R.L., Biomarkers of aging, Exp. Gerontol., 23, pp. 223-239, (1988)
  • [2] Moqri M., Et al., Biomarkers of aging for the identification and evaluation of longevity interventions, Cell, 186, pp. 3758-3775, (2023)
  • [3] Jylhava J., Pedersen N.L., Hagg S., Biological age predictors, EBioMedicine, 21, pp. 29-36, (2023)
  • [4] Horvath S., Raj K., DNA methylation-based biomarkers and the epigenetic clock theory of ageing, Nat. Rev. Genet., 19, pp. 371-384, (2018)
  • [5] Frenck R.W., Blackburn E.H., Shannon K.M., The rate of telomere sequence loss in human leukocytes varies with age, Proc. Natl Acad. Sci. USA, 95, pp. 5607-5610, (1998)
  • [6] Macdonald-Dunlop E., Et al., A catalogue of omics biological ageing clocks reveals substantial commonality and associations with disease risk, Aging (Albany NY), 14, (2022)
  • [7] Kristic J., Et al., Glycans are a novel biomarker of chronological and biological ages, J. Gerontol. Ser. A: Biomed. Sci. Med. Sci., 69, pp. 779-789, (2014)
  • [8] Pyrkov T.V., Sokolov I.S., Fedichev P.O., Deep longitudinal phenotyping of wearable sensor data reveals independent markers of longevity, stress, and resilience, Aging (Albany NY), 13, (2021)
  • [9] Belsky D.W., Et al., Quantification of biological aging in young adults, Proc. Natl Acad. Sci. USA, 112, pp. E4104-E4110, (2015)
  • [10] Vidal-Bralo L., Lopez-Golan Y., Gonzalez A., Simplified assay for epigenetic age estimation in whole blood of adults, Front. Genet., 7, (2016)
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