Anastasia A Kobelyatskaya, Fedor I Isaev, Anna V Kudryavtseva, Zulfiya G Guvatova, Alexey A Moskalev
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引用次数: 0
Abstract
Organic acids reflect the course of all important metabolic processes and the effects of diet, nutrient deficiency, lifestyle, and microbiota composition. In present work, we focused on identifying age-related changes in organic acids in urine, and creating a neural network model based on them to determine biological age. The investigation involves data on concentrations of 60 organic acids in urine of 863 samples. Due to data analysis we found these acids could be used to determine human biological age. Two models were created for calculating biological age: a comprehensive AcidAGE model and a concise AcidAGE model based on 10 indicators. Both models demonstrate high accuracy. The presented models are useful for dynamically assessing the impact of medical interventions, lifestyle and diet amendments, and taking nutraceuticals on overall health and the risk of disease occurrence or progression. Their advantage lies in their ability to quickly update estimates as the corresponding biological processes change.
期刊介绍：
The journal Biogerontology offers a platform for research which aims primarily at achieving healthy old age accompanied by improved longevity. The focus is on efforts to understand, prevent, cure or minimize age-related impairments.
Biogerontology provides a peer-reviewed forum for publishing original research data, new ideas and discussions on modulating the aging process by physical, chemical and biological means, including transgenic and knockout organisms; cell culture systems to develop new approaches and health care products for maintaining or recovering the lost biochemical functions; immunology, autoimmunity and infection in aging; vertebrates, invertebrates, micro-organisms and plants for experimental studies on genetic determinants of aging and longevity; biodemography and theoretical models linking aging and survival kinetics.
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