medRxivGenetic & Genomic MedicinePreprint
BMI Interacts with the Genome to Regulate Gene Expression Globally, with Emphasis in the Brain and Gut
Rebecca H. SigneriD, Carina SeahiD, Hannah Young, Kayla G. TownsleyiD, Agathe M. de PinsiD, Alanna C. CoteiD, S. H. LeeiD, Meng Jia, Jessica JohnsoniD, Keira J.A. JohnstoniD, Jiayi XuiD, Kristen BrennandiD, Laura M. HuckinsiD
Abstract
Genome-wide association studies identify common genomic variants associated with disease across a population. Individual environmental effects are often not included, despite evidence that environment mediates genomic regulation of higher order biology. Body mass index (BMI) is associated with complex disorders across clinical specialties, yet has not been modeled as a genomic environment. Here, we tested for expression quantitative trait (eQTL) loci that contextually regulate gene expression across the BMI spectrum using an interaction approach. We parsed the impact of cell type, enhancer interactions, and created novel BMI-dynamic gene expression predictor models. We found that BMI main effects associated with endocrine gene expression, while interactive variant-by-BMI effects impacted gene expression in the brain and gut. Cortical BMI-dynamic loci were experimentally dysregulated by inflammatory cytokines in an in vitro system. Using BMI-dynamic models, we identify novel genes in nitric oxide signaling pathways in the nucleus accumbens significantly associated with depression and smoking. While neither genetics nor BMI are sufficient as standalone measures to capture the complexity of downstream cellular consequences, including environment powers disease gene discovery.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 3
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Exploring the molecular basis of the genetic correlation between body mass index and brain morphological traits
Daniela Fusco, Camilla Marinelli, … Paolo Provero·PLoS GeneticsPeer-reviewed·Apr 10, 2025
- Leveraging phenotypic variability to identify genetic interactions in human phenotypes
Andrew R. Marderstein, Emily Davenport, … Andrew G. Clark·The American Journal of Human GeneticsPeer-reviewed·Dec 15, 2020
- Multifaceted genome-wide study identifies novel regulatory loci for body mass index in Indians
INDICO, Anil Kumar Giri, … Dwaipayan Bharadwaj·Molecular Genetics and GenomicsPeer-reviewed·May 3, 2020
- Gene-environment interactions using a Bayesian whole genome regression model
Matthew Kerin, Jonathan Marchini·The American Journal of Human GeneticsPeer-reviewed·Sep 3, 2020
- Variance-quantitative trait loci enable systematic discovery of gene-environment interactions for cardiometabolic serum biomarkers
Kenneth E. Westerman, Timothy D. Majarian, … Joanne B. Cole·Nature CommunicationsPeer-reviewed·Jul 9, 2022
- Distinguishing between interaction and dispersion effects in the analysis of gene-environment interaction
Benjamin W. Domingue, Klint Kanopka, … Elliot M. Tucker–Drob·bioRxiv·Sep 8, 2020