Development of a Platform for Metabolic Predictions of a Stroke for the Elderly Population

In this study, Glucose level, HDL-C, Age will be used as biomarkers for the prediction of a stroke in the elderly population. Using big data, additional biomarker lists can be obtained. Glucose level, lipid, blood pressure (BP), and diabetic control data will be obtained. Moreover, genomic information will be collected to identify population association in stroke susceptibility. I will collect stroke-related data such as diet information, smoke, age, blood tests and medical histories for as many as 30 thousand elderly patients in Seoul KOREA. For the analysis of data, the commonly used tool is ADMIXTURE, which performs maximum likelihood estimation of correlation among datasets.