Personalized Epigenetic Study to Prevent Non-communicable Diseases and Predict Biological Age in Adults in Kazakhstan

What this Trial Is About

Researchers are exploring ways to improve personalized and preventive care for non-communicable diseases such as cardiovascular diseases, type 2 diabetes, chronic respiratory diseases, obesity, and chronic kidney diseases in Kazakhstan. This observational study focuses on understanding epigenetic factors and uses machine learning models to predict biological age and reproductive function, aiming to tailor health recommendations for individuals. The study involves one cohort divided into four age groups 18-29 years, 30-44 years, 45-59 years, and 60-69 years, with an equal number of men and women in each group. Participants will undergo genetic investigations including DNA analysis to examine telomere length and DNA methylation levels. Data collection and model predictions will take place within ten months from the start of the study. Participants will be residents of Kazakhstan aged 18 to 69 years who consent to participate. The study will monitor the accuracy of machine learning models in predicting biological age and reproductive function. All data collection will be observational, with no treatments administered. The total participation timeline includes data collection and assessment periods within the planned study duration ending in 2026.

Epigenetics and NCD Prevention in Kazakhstan: Personalized Approaches and Biological Age Prediction