BMI-genome interactions regulate global gene expression with emphasis in brain and gut.

Genome-wide association studies identify single-nucleotide polymorphisms (SNPs) associated with disease in a population but do not reliably account for individual environmental effects, despite evidence that environment mediates SNP functional regulatory capacity. Body mass index (BMI) is associated with physiologic processes across disorders but hasn't been modeled as an environment for disease-associated SNPs. We use an interaction approach to identify SNPs that contextually regulate gene expression across the BMI spectrum, called BMI-dynamic expression quantitative trait loci (BMI-eQTL). We found BMI-eQTL across tissues, including brain and gut, while the main effects of BMI were confined to endocrine tissues. We demonstrate that cell type, putative enhancers, and/or inflammatory cytokines underlie BMI-eQTL. We develop models to predict gene expression using BMI-by-SNP interactions and identify more replicating disease-associated genes than SNP-only models. While neither genetics nor BMI is sufficient as a standalone measure to capture the complexity of downstream cellular consequences, including environment helps power disease gene discovery.