We conducted a research study to create the groundwork for personalized solutions within a skin aging segment. This test utilizes genetic and general laboratory data to predict individual susceptibility to weak skin characteristics, leveraging the research on genetic polymorphisms related to skin functional properties. A cross-sectional study was conducted in a collaboration between the Private Clinic Medicina Practica Laboratory (Vilnius, Lithuania) and the Public Institution Lithuanian University of Health Sciences (Kaunas, Lithuania). A total of 370 participants agreed to participate in the project. The median age of the respondents was 40, with a range of 19 to 74 years. After the literature search, we selected 15 polymorphisms of the genes related to skin aging, which were subsequently categorized in terms of different skin functions: SOD2 (rs4880), GPX1 (rs1050450), NQO1 (rs1800566), CAT (rs1001179), TYR (rs1126809), SLC45A2 (rs26722), SLC45A2 (rs16891982), MMP1 (rs1799750), ELN (rs7787362), COL1A1 (rs1800012), AHR (rs2066853), IL6 (rs1800795), IL1Beta (rs1143634), TNF-α (rs1800629), and AQP3 (rs17553719). RT genotyping, blood count, and immunochemistry results were analyzed using statistical methods. The obtained results show significant associations between genotyping models and routine blood screens. These findings demonstrate the personalized medicine approach for the aging segment and further add to the growing literature. Further investigation is warranted to fully understand the complex interplay between genetic factors, environmental influences, and skin aging.

We conducted a research study to create groundwork for personalized solutions within skin aging segment. This test utilises genetic and general laboratory data to predict individual susceptibility of weak skin characteristics, leveraging on the research on genetic polymorphisms related to skin functional properties. A cross-sectional study was conducted in collaboration between the Private Clinic Medicina Practica Laboratory (Vilnius, Lithuania) and the Public Institution Lithuanian University of Health Sciences (Kaunas, Lithuania). 370 participants agreed to participate in the project. The median age of respondents was 40, with a range of 19 to 74 years. After the literature search, we selected 15 polymorphisms of the genes related to skin aging subsequently distributed for different skin functions: SOD2(rs4880), GPX1(rs1050450), NQO1(rs1800566), CAT (rs1001179), TYR (rs1126809), SLC45A2 (rs26722), SLC45A2 (rs16891982), MMP1(rs1799750), ELN (rs7787362), COL1A1(rs1800012), AHR (rs2066853), IL6 (rs1800795), IL1Beta (rs1143634), TNF-α (rs1800629), AQP3(rs17553719). RT genotyping, blood count and immunochemistry results have been analysed using statistical methods. Obtained results showed significant associations among genotyping models and routine blood screens. These findings demonstrate the personalized medicine approach for aging segment and further add onto the growing field of literature. Further investigation is warranted to fully understand the complex interplay between genetic factors, environmental influences, and skin aging.