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

肥胖症和相关代谢疾病的流行率不断上升，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。其中一个因素是对我们的遗传组成和生活方式如何相互作用导致这些疾病有了更深入的了解。以前在这一领域的进展一直受到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的限制。然而，最近，它已经成为可能超越了以前的方法，研究与疾病的基础上确定的可能的生物学途径的先验知识的单基因变异的关联。由于人类基因组计划之后的技术进步，基于同时研究数十万种变异的新方法已经成为可能。然而，这种遗传信息规模的增加的不利之处在于，研究不得不涉及更多的参与者，因为如果研究太小，仅仅偶然发现关联的机会就相当大。因此，在这项研究中，我们将在研究小组之间建立一个合作网络，以联合收割机结合来自大型人群队列研究的现有遗传数据，以研究5种常见代谢性状的遗传基础。在这个初步分析阶段之后，我们将在其他大型研究中确认这些发现，以减少错误发现的可能性，然后进行进一步的工作，以准确地确定基因组中遗传信号的来源。通过这种方式，我们将有助于发现这些常见代谢特征分布的新变体，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.