Search

Background: Genome-wide association (GWAS) have identified hundreds of loci that are robustly associated with the risk of cardiometabolic risk factors and diseases. With few exceptions, the causal genes through which these loci influence disease risk remain uncharacterized. Since murine model systems are not suitable for systematic characterization of candidate genes in hundreds of loci, novel in vivo model systems are desirable. Methods: My group has developed and validated zebrafish model systems that make optimal use of: 1) the zebrafish’ well-annotated genome, with orthologues of at least 71.4% of human genes; 2) recent developments in multiplex CRISPR-Cas9-based mutagenesis; 3) advances in automated positioning of non-embedded zebrafish larvae; 4) fluorescent transgenes and dyes; and 5) custom-written image-quantification pipelines. Results: Five days of overfeeding, dietary cholesterol supplementation and/or exposure to glucose induce atherogenic and insulin resistant phenotypes (higher/more whole-body LDL cholesterol (LDLc) and triglyceride levels; vascular foam cell formation and inflammation; beta-cell number and volume; subcutaneous and hepatic accumulation of fat) that can largely be prevented by concomitant treatment with lipid-lowering or diabetes medication (N>4000). In line with recent results in humans, treatment with atorvastatin and ezetimibe results in higher whole-body glucose levels (N~835). Each additional mutated allele in zebrafish orthologues of APOE results in higher LDLc levels, while mutations in LDLR affect vascular infiltration by lipids and macrophages (N~330). Ongoing characterization of 37 prioritized genes in GWAS-identified loci for triglyceride levels identified genes that influence triglycerides, LDLc, and/or vascular inflammatory and atherogenic traits, while characterizing prioritized genes in loci associated with heart rate variability yielded genes that influence cardiac rate and rhythm. Conclusions: Systematic characterization of candidate genes for cardiometabolic traits in zebrafish model systems will help increase our understanding of human disease and identify novel targets that can be translated into efficient therapeutics.