2006-LB: Polygenic Scores for Metabolic Diseases Are Associated with Gene Expression Networks across Tissues

Genetic risk for type 2 diabetes (T2D), coronary artery disease (CAD), and obesity can be estimated with global extended polygenic scores (gePS), which capture risk across thousands of genetic variants. Nevertheless, knowledge of underlying disease pathways remains limited. Expression Quantitative Trait Scores (eQTS) connecting gePS to gene expression could help prioritize disease-causing genes and pathways in specific tissues. We generated gePS for T2D, CAD, and body mass index (BMI) in the Genotype-Tissue Expression (GTEx) database of 838 individuals and 49 tissues. eQTS were calculated using a linear model of association between gePS and tissue transcript expression level, adjusting for age, sex, 5 genetic PCs, and 20 gene expression PCs. Gene set enrichment was performed using Enrichr with Gene Ontology pathway sets and Fisher’s Exact Test (Q < 0.05). T2D, CAD, and BMI gePS were each associated with > 500 transcript expression levels (eQTS) across multiple tissues at p < 0.05. In multiple tissues, both T2D and BMI eQTS were significantly enriched for pathways related to mitochondrial function (Q<10^-7), with the most significant T2D signal found in the heart atrial appendage and BMI signals in subcutaneous (SC) and visceral adipose. For T2D, pancreas eQTS were enriched for pancreatic beta cell development and mature onset diabetes of the young (MODY) (Q<10^-3). For CAD, cholesterol metabolism pathways were enriched in the coronary artery (Q<10^-7). In summary, T2D and BMI eQTS share mitochondrial and metabolic transcription mechanisms across several tissues, including SC adipose. Cholesterol metabolism was enriched in the coronary artery in CAD eQTS. This study provides novel insight into the shared genetic and transcriptomic architecture of T2D, CAD, and obesity.