Incorporating local ancestry information to predict genetically associated DNA methylation in admixed populations.

Abstract

Methylome-wide association studies (MWASs) have identified many 5'-cytosine-phosphate-guanine-3' (CpG) sites associated with complex traits. Several methods have been developed to predict CpG methylation levels from genotypes when the direct measurements of methylation are unavailable. To date, the published methods have mostly used datasets from populations of European ancestry to train prediction models for methylations, which limits the generalizability of methylome-wide association study to non-European populations. To address this gap, we proposed a new model by incorporating local ancestry (LA) information, called LA Methylation Predictor with Preselection (LAMPP), to improve the prediction accuracy of DNA methylation in admixed populations. We showed that LAMPP outperformed the conventional model and other LA models in prediction accuracy using an admixed African American population. We further applied our model to identify significant CpG sites for seven complex traits. Together, our LAMPP model is a valuable tool to reveal epigenetic underpinnings of complex traits in the admixed populations.