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

利用斑马鱼大规模 CRISPR 诱变来了解脂肪分布和肥胖相关疾病

• 批准号: 2744483
• 金额: --
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2744483
• 关键词: Leveraging; large; scale; CRISPR; mutagenesis

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.

肥胖影响着大约25%的英国成年人，是动脉粥样硬化性心血管疾病、糖尿病、癌症和严重新冠肺炎症状的主要风险因素。在肥胖患者中，患肥胖症相关疾病的风险存在很大的个体差异。因此，根据疾病风险对肥胖患者进行预测和分层，并了解导致这种疾病风险的原因机制，是开发有效的肥胖治疗的必要前提。体脂分布是肥胖相关疾病风险的关键决定因素。在类似的肥胖者中，内脏脂肪组织的增加与心脏代谢障碍有关，而皮下脂肪水平的增加与代谢更健康的肥胖有关。事实上，脂肪分布比单纯肥胖更能准确地预测疾病风险。身体脂肪分布是高度可遗传的，这表明有很强的遗传基础，超过96项全基因组关联研究(GWAS)已经确定了9,000个与腰臀比(脂肪分布的替代指标)的遗传关联。机械地了解这些遗传关联如何影响脂肪分布和心脏代谢性疾病风险是一个重大障碍，但将了解肥胖患者的复杂性，并为肥胖相关疾病的预防和治疗制定更有针对性和更有效的战略。该项目的总体目标是将GWAS的研究结果转化为分子、细胞和生理脂肪分布表型。通过这样做，我的目标是为心脏代谢性疾病的个性化风险预测提供信息，并确定肥胖相关疾病的新治疗目标。