10.17608/k6.auckland.8116097.v1 Tayaza Fadason Tayaza Fadason William Schierding William Schierding Jiamou Liu Jiamou Liu Justin O'Sullivan Justin O'Sullivan Supplementary_tables_metabolites.xlsx The University of Auckland 2019 blood metabolite levels gene regulation eQTL chromatin interactions Bioinformatics Cell Metabolism Molecular Biology Quantitative Genetics (incl. Disease and Trait Mapping Genetics) 2019-05-22 03:48:35 Dataset https://auckland.figshare.com/articles/dataset/Supplementary_tables_metabolites_xlsx/8116097 We identified proximal and distal target genes for 145 genome-wide significant metabolite-associated SNPs by the systematic integration of chromatin interaction (Hi-C), expression quantitative trait loci (eQTL), gene ontology (KEGG), protein classification (The Human Protein Atlas), drug-gene interaction (DGIdb), and literature text mining (PubMed) data. Our approach revealed that ~90% of the metabolite-associated SNPs are eQTLs. These SNPs form 612 distinct eSNP-eGene interactions via chromatin looping across 48 human tissues.