The "Integrated modeLs for Early Risk-prediction in Africa (ILERA) study (Ilera in Yoruba means health) aims to investigate the potential for improving the prediction of 13 cardio-metabolic disease (CMD) indicator levels (and thereby of CMDs) by integrating diverse streams of data into the risk prediction models. Starting with the currently best representative/performing PRSs, we plan to progressively add layers of data such as predicted transcriptomes, environment and lifestyle information and assess whether this additional data, either independently or in combination with others could improve prediction. To allow for complex and non-linear interactions between these factors, data-driven approaches will be employed for integrating these variables with the genomic data. In-depth evaluation of the predictivity of these models will be performed in independent cohorts from South, East and West Africa and also in longitudinal data from the same cohort. The potential for an early warning system aimed at public health intervention will be investigated using the combination of best predictive models and traits