den Hoed M, Emmanouilidou A, Bandaru M, von der Heyde B, Wählby C, Ranefall P, Allalou A, Larsson A, Ingelsson E
ASHG 2017 Annual Meeting - The American Society of Human Genetics - (-) - [2017-10-17; online 2017-10-17]
Background: Genome-wide association, exome array and whole-exome sequencing efforts have identified hundreds of loci that are robustly associated with the risk of cardiometabolic diseases and risk factors. With few exceptions, the causal genes through which these loci influence the risk of disease remain uncharacterized. While in silico genomic annotation using results from e.g. the ENCODE and RoadMap Epigenomics projects provides valuable insights, novel model systems that enable systematic, in vivo characterization of candidate genes 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 ≥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) levels; vascular foam cell formation and inflammation; β-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). Proof-of-principle studies show that each additional mutated allele in the zebrafish’ orthologues of APOE (apoea, apoeb) results in higher LDLc levels and more vascular foam cell formation and inflammation (N~384). In line with recent results in humans, treatment with LDLc-lowering drugs (N~400) and mutations in pcsk9 (N~384) both result in higher whole-body glucose levels. Finally, characterization of candidate genes in loci identified in a recent GWAS for heart rate variability helped identify genes that influence early-stage cardiac development, cardiac rate, and/or cardiac rhythm. Conclusions: Systematic, largely image-based characterization of candidate genes for cardiometabolic traits in zebrafish model systems will increase our understanding of human disease, and will likely identify novel targets that can be translated into efficient therapeutics. In addition, undesirable side effects can be quantified in vivo at an early stage, thereby preventing costly and time-consuming experiments for targets that would otherwise likely fail on the road towards clinical trials.
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