Leveraging large-scale CRISPR mutagenesis in zebrafish to understand fat distribution and obesity-associated disease

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Obesity affects approximately 25% of all UK adults and is a primary risk factor for atherosclerotic cardiovascular disease, diabetes, cancer and severe COVID-19 symptoms. Among obese patients, there is large inter-individual variation in risk for developing obesity-associated diseases. Therefore, predicting and stratifying obese patients according to disease risk, and understanding the causal mechanisms driving this disease risk, are essential prerequisites for developing effective obesity treatments.Body fat distribution is a key determinant of obesity-associated disease risk. In similarly obese individuals, increased accumulation of visceral adipose tissue is associated with cardiometabolic disorders, whereas increased levels of subcutaneous adipose is associated with more metabolically healthy obesity. Indeed, fat distribution is a more accurate predictor of disease risk than obesity alone. Body fat distribution is highly heritable, suggesting a strong genetic basis, and over 96 genome-wide association studies (GWAS) have identified >9,000 genetic associations with waist-hip ratio (a proxy for fat distribution). Mechanistically understanding how these genetic associations impact fat distribution and cardiometabolic disease risk represents a significant hurdle, but will inform patient complexity in obesity and enable more targeted and effective strategies for obesity-associated disease prevention and treatment. The overall aim of this project is to translate findings from GWAS into molecular, cellular and physiological fat distribution phenotypes. By doing so, I aim to inform personalized risk prediction for cardiometabolic disease and identify new therapeutic targets for obesity-associated disease.