We present metabolite pathway enrichment analysis (MPEA) for the visualization and biological interpretation of metabolite data at the system level. Our tool follows the concept of gene set enrichment analysis (GSEA) and tests whether metabolites involved in some predefined pathway occur towards the top (or bottom) of a ranked query compound list. In particular, MPEA is designed to handle many-to-many relationships that may occur between the query compounds and metabolite annotations. For a demonstration, we analysed metabolite profiles of 14 twin pairs with differing body weights. MPEA found significant pathways from data that had no significant individual query compounds, its results were congruent with those discovered from transcriptomics data and it detected more pathways than the competing metabolic pathway method did.