Difference between the biologic and chronologic age as an individualized indicator for the skin care intensity selection: skin topography and immune system state studies, parameter correlations with age difference

• Main Authors: Yurij Sukhovei, Elena Kostolomova, Irina Unger, Andrey Koptyug, Denis Kaigorodov
• Format: Article
• Language: English
• Published: BMC 2020-01-01
• Series: Biomedical Dermatology
• Subjects: Skin aging; Biologic and chronologic age; Skin topography; Immune status; Individualized treatment
• Online Access: https://doi.org/10.1186/s41702-019-0050-2

Abstract Background Present research addresses the issue of skin aging and corresponding skin treatment individualization. Particular research question was on the developing of simplified criterion supporting patient-specific decision on the necessity and intensity of skin treatment. Basing on the published results and a wide pool of experimental data, we have formulated a hypothesis that a difference between biologic and chronologic age can be used as an express criterion of skin aging. Methods In present paper, we report the results of studies with 80 volunteers between 15 and 65 years of age, linking parameters reflecting immune state, skin state, and topography to the difference between biologic and chronologic age. Facial skin topography, skin moisture, sebum level, and skin elasticity were studied using commercial devices. Blood immunology studies were performed using venous blood samples. Correlations between all measured parameters and age difference were calculated. Also, cross correlations between skin cell profile and blood immune profile parameters, and skin roughness parameters were calculated. Results Age dependencies of the blood immunological parameters on the biologic and chronologic age difference are less pronounced as compared to the changes in skin cell profile parameters. However, the changes in the tendencies when biologic age becomes equal to chronologic one are visible for all studied parameters. All measured skin roughness parameters show correlations with age difference, but average skin roughness and depth of the deepest profile valley have the largest correlation coefficient values. Many of the measured skin cell profile and blood immunology parameters show strong correlations with average skin roughness and deepest profile valley, with some of the coefficients exceeding 0.5–0.6. Conclusions Basing on own experiments and published research results, it is possible to suggest using the difference between calculated biologic age and chronologic age as an individualized criterion supporting decisions on skin treatment strategy. Further research involving larger numbers of participants and aiming on optimizing the expressions for calculating biologic age could lead to reliable and easily available express criterion supporting the decision making for an individualized skin treatment.