Introduction. Biomarkers of biological age (BA) are essential for anti-aging research and practice because of their prediction of life expectancy, detection of premature aging, and estimation of anti-ageing programs' effectiveness. The purpose of this study is a clinical validation of the method of biological age estimation based on the analysis of heart rate variability (HRV), artificial intelligence technologies, and biometric monitoring. Methods. In 51 patients who received wellness and rehabilitation services in the medical center "Edem Medical", biological age was determined based on the analysis of HRV and machine learning algorithms. A comparison was made between the proposed method and other known methods of biological age estimation. Biological age estimation by physicians which is based on the Frailty Index was chosen as a reference method. The second method was DNA methylation age (DNAm PhenoAge). This method predicts biological age based on nine parameters of blood (albumin, creatinine, glucose, C-reactive protein, lymphocytes [%], mean corpuscular volume [MCV], red cell distribution width [RDW], alkaline phosphatase, WBC count). Using the «leave one out» technique, an additional algorithm was created for approximating biological age in view of blood test parameters and ECG signals as input data. Morning HRV assessment was performed on empty stomach and after 10-minute rest in horizontal position. ECG was recorded using Mawi Vital multisensor device. The following statistical tests were used to reveal associations between different methods of biological age estimation: 1. bivariate correlation, 2. mean absolute error (MAE), 3. qualitative binary age estimation. Results. All tested methods of BA evaluation were strongly correlated with the reference method (physician-determined age). HRV based approach was superior in comparison with other methods. In 9 out of 10 cases, the qualitative binary age assessment using HRV coincided with the reference method. The HRV method was the most accurate for biological age estimation (3.62 vs 12.62) based on MAE. Conclusion. The method based on HRV is an affordable and convenient approach to biological age estimation. This method offers opportunities for early stratification of individuals at risk of accelerated aging. It combines well with the paradigm of 3 P medicine which is based on Prevention, Prediction, and Personalized approach to each patient
RELATIONSHIP OF HEART RATE VARIABILITY AND BIOLOGICAL AGE IN STUDENTS
