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Introduction

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Part of the book series: Healthy Ageing and Longevity ((HAL,volume 10))

Abstract

In laboratory studies, potential geroprotective interventions have been created: more than 400 geroprotectors, several gene and cell therapies. Their translation into medical practice is restricted, in part, due to the inability to assess clinical efficacy. Human biomarker panels are needed. Based on them, it will be able to predict the accelerated or delayed aging of an individual, track the effectiveness of procedures aimed at preventing aging, such as changing diets, lifestyles, increasing physical activity, geroprotective drugs. Aging biomarkers are an integrative qualitative and quantitative indicator of the functional state of a person and this is their key difference from the risk factors of specific age-related pathologies (type 2 diabetes, cardiovascular diseases, Alzheimer’s or Parkinson’s). In other words, aging biomarkers are indicators of a preclinical stage of father aging-related pathologies. Interventions should reverse these biomarkers to a younger state or slow down their changes with aging.

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References

  • Butler RN et al (2004) Biomarkers of aging: from primitive organisms to humans. J Gerontol A Biol Sci Med Sci 59:B560

    Article  Google Scholar 

  • Craig T et al (2015) The Digital Ageing Atlas: integrating the diversity of age-related changes into a unified resource. Nucleic Acids Res 43:D873

    Article  CAS  Google Scholar 

  • Fedintsev A et al (2017) Markers of arterial health could serve as accurate non-invasive predictors of human biological and chronological age. Aging 9:1280

    Article  CAS  Google Scholar 

  • Putin E et al (2016) Deep biomarkers of human aging: application of deep neural networks to biomarker development. Aging 8:1021

    Article  CAS  Google Scholar 

  • Quach A et al (2017) Epigenetic clock analysis of diet, exercise, education, and lifestyle factors. Aging 9:419

    Article  CAS  Google Scholar 

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Correspondence to Alexey Moskalev .

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Moskalev, A. (2019). Introduction. In: Moskalev, A. (eds) Biomarkers of Human Aging. Healthy Ageing and Longevity, vol 10. Springer, Cham. https://doi.org/10.1007/978-3-030-24970-0_1

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