Metabolomics and partial least square discriminant analysis to predict history of myocardial infarction of self-claimed healthy subjects: validity and feasibility for clinical practice

The dynamics of metabolomics in establishing a prediction model using partial least square discriminant analysis have enabled better disease diagnosis; with emphasis on early detection of diseases. We attempted to translate the metabolomics model to predict the health status of the Orang Asli community whom we have little information. The metabolite expressions of the healthy vs. diseased patients (cardiovascular) were compared. A metabotype model was developed and validated using partial least square discriminant analysis (PLSDA). Cardiovascular risks of the Orang Asli were predicted and confirmed by biochemistry profiles conducted concurrently.