Functional Characterization of Lipid Regulatory Effects of Three Genes Using Knockout Mouse Models

Abstract Integrative analysis that combines genome-wide association data with expression quantitative trait analysis and network representation may illuminate causal relationships between genes and diseases. To identify causal lipid genes, we utilized genotype, gene expression, protein-protein interaction networks, and phenotype data from 5,257 Framingham Heart Study participants and performed Mendelian randomization to investigate possible mechanistic explanations for observed associations. We selected three putatively causal candidate genes (ABCA6, ALDH2, and SIDT2) for lipid traits (LDL cholesterol, HDL cholesterol and triglycerides) in humans and conducted mouse knockout studies for each gene to confirm its causal effect on the corresponding lipid trait. We conducted the RNA-seq from mouse livers to explore transcriptome-wide alterations after knocking out the target genes. Our work builds upon a lipid-related gene network and expands upon it by including protein-protein interactions. These resources, along with the innovative combination of emerging analytical techniques, provide a groundwork upon which future studies can be designed to more fully understand genetic contributions to cardiovascular diseases.