MRC-GSK pilot programme to identify new targets and biomarkers from genetic association studies

肥胖症和相关代谢性疾病日益流行是一个重大的公共卫生问题，需要采取广泛的方法来加强预防和治疗。其中一个因素是人们对我们的基因构成和生活方式如何相互作用导致这些疾病有了更好的理解。此前，我们试图了解肥胖和2型糖尿病等常见疾病的遗传基础的方法限制了这一领域的进展。然而，最近已经超越了以前研究单基因变异与疾病的关联的方法，这些单基因变异是基于对可能的生物途径的先验知识而确定的。由于人类基因组计划之后的技术进步，基于一次研究数十万种变异的新方法成为可能。然而，遗传信息规模的这种增长的不利之处是，研究不得不涉及更多的参与者，因为如果研究太小，仅仅是偶然发现关联的可能性很大。因此，在这项研究中，我们将在研究小组之间建立一个协作网络，结合来自大规模基于人群的队列研究的现有遗传数据，以研究5个常见代谢性状的遗传基础。在这个初步的分析阶段之后，我们将确认其他大型研究中的发现，以减少错误发现的可能性，然后进行进一步的工作，以准确地确定遗传信号来自基因组中的哪里。通过这种方式，我们将有助于发现这些共同代谢特征分布的新变异，这反过来将有助于开发新的预防和治疗策略。

The rising prevalence of obesity and related metabolic diseases is a major public health problem requiring a broad spectrum of approaches to enhanced prevention and treatment. One element of this is the generation of greater understanding about how our genetic make up and lifestyles interact to bring about these disorders. Previously progress in this area had been limited by our approaches to trying to understand the genetic basis of common disorders like obesity and type 2 diabetes. However, recently it has become possible beyond the former approach of studying the association with disease of single gene variants identified on the basis of prior knowledge of possible biological pathways. New approaches based on studying many hundreds of thousands of variants at once have become possible because of technological advances following the human genome project. However, the downside of this increase in the scale of genetic information is that studies have had to involve many more participants since the chance of an association being found simply by chance is considerable if studies are too small. Therefore, in this study, we will create a collaborative network between research groups to combine existing genetic data from large population-based cohort studies in order to study the genetic basis of 5 common metabolic traits. Following this initial analytical stage, we will confirm the findings in other large studies to reduce the possibility of false discovery and then undertake further work to pinpoint exactly where in the genome the genetic signal is coming from. In this way, we will contribute to discovering new variants underlying the distribution of these common metabolic traits which in turn will contribute to the development of novel preventive and therapeutic strategies.