Metabolic Diseases Predictor Analysis Based on Single Nucleotide Polymorphisms and Lifestyle Factors: Preliminary Study in Indonesia

Type 2 Diabetes Mellitus (T2DM) and cardiovascular disease (CVD) emerged as a cause of high mortality rates in low-middle-income countries, including Indonesia. Understanding predictor variables to the commonly used biomarkers, including lipid profiles and blood glucose levels, can thus be beneficial in disease prevention strategies. To support that, this study aims to analyze the genetic, lifestyle, and disease history variables as predictors towards lipid and blood glucose profiles. The respondent’s data were collected from clinical data, food recall, health history, and genetic profiling. From the results, APOA5 rs662799 is positively correlated with triglyceride (TG) levels. Sugar, fat, fiber, and calorie intake also significantly affect lipid and blood glucose profiles. Exercise conditions such as aerobic and flexibility exercise duration significantly correlated with low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C) profiles. Disease history in individuals and families emerged as additional variables associated with the response variables. These findings can serve as a preliminary study for understanding health predictors that can be used to predict incident of metabolic diseases in the Indonesian population.