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首页> 外文期刊>The lancet. Diabetes & endocrinology. >Genetics of obesity: what genetic association studies have taught us about the biology of obesity and its complications
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Genetics of obesity: what genetic association studies have taught us about the biology of obesity and its complications

机译:肥胖的遗传学:什么遗传关联研究教导了我们肥胖的生物学及其并发症

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Genome-wide association studies (GWAS) for BMI, waist-to-hip ratio, and other adiposity traits have identified more than 300 single-nucleotide polymorphisms (SNPs). Although there is reason to hope that these discoveries will eventually lead to new preventive and therapeutic agents for obesity, this will take time because such developments require detailed mechanistic understanding of how an SNP influences phenotype (and this information is largely unavailable). Fortunately, absence of functional information has not prevented GWAS findings from providing insights into the biology of obesity. Genes near loci regulating total body mass are enriched for expression in the CNS, whereas genes for fat distribution are enriched in adipose tissue itself. Gene by environment and lifestyle interaction analyses have revealed that our increasingly obesogenic environment might be amplifying genetic risk for obesity, yet those at highest risk could mitigate this risk by increasing physical activity and possibly by avoiding specific dietary components. GWAS findings have also been used in mendelian randomisation analyses probing the causal association between obesity and its many putative complications. In supporting a causal association of obesity with diabetes, coronary heart disease, specific cancers, and other conditions, these analyses have clinical relevance in identifying which outcomes could be preventable through weight loss interventions.
机译:基因组 - 宽协会研究(GWAS)对于BMI,腰部比率和其他肥胖性状具有鉴定了​​300多种单核苷酸多态性(SNP)。虽然有理由希望这些发现最终会导致肥胖的新预防和治疗剂,但这将需要时间,因为这种发展需要详细的机制理解SNP如何影响表型(并且这些信息在很大程度上不可用)。幸运的是,缺乏功能信息并没有阻止GWAS发现提供肥胖生物学的见解。在CNS中富集Loci调节总体质量附近的基因富集,而脂肪分布的基因富含脂肪组织本身。环境和生活方式互动分析的基因透露,我们越来越富含肥胖的环境可能会扩大肥胖症的遗传风险,但最高风险的人可能通过避免特定的膳食成分来减轻这种风险。 GWAS发现还用于孟德尔随机化分析探测肥胖与许多推定并发症之间的因果关系。在支持肥胖与糖尿病的因果关系,冠心病,特异性癌症和其他条件方面,这些分析具有临床相关性,即通过减肥干预识别哪些结果可以预防到哪些结果。

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