Personal omics profiling of the progression to diabetes mellitus type 2

描述（由申请人提供）：2型糖尿病影响全球超过2亿人。虽然DM2有很强的家族性成分，但对个体致病基因的研究只取得了轻微的成果，DM2的发展被认为取决于许多遗传和环境因素的结合。随着个体全基因组测序成本的提高以及可定量测量数万个生物分子的技术的成熟，存在着巨大的机会来了解DM2进展背后的遗传和双分子因素。我们的实验室最近开发了一种新的管道，称为综合个人组学分析（iPOP），它将基因组学、转录组学、蛋白质组学和代谢组学与计算工具相结合，全面研究疾病发生和进展过程中变化的分子和途径。我们建议对发展为DM2的高风险或低风险超重个体进行全基因组测序和纵向iPOP分析。对于这个队列，我们将分析研究开始时、体重适度增加后和体重明显减轻一段时间后的血液样本。我们假设，通过iPOP分析，我们可以阐明新的分子因素和途径，这些因素和途径在体重增加和减少的反应中发生变化，并且在高风险和低风险个体之间存在差异。通过这一分析，我们将为获得性胰岛素抵抗背后不断变化的分子景观提供前所未有的视角。

DESCRIPTION (provided by applicant): Diabetes Mellitus type 2 affects over 200 million individuals worldwide. While DM2 has a strong familial component, the search for individual causative genes has been only mildly fruitful and development of DM2 is thought to depend on the combination of a number of genetic and environmental factors. With the cost for whole- genome sequencing of individuals in reach as well as the maturation of technologies for quantifiably measuring tens of thousands of biomolecules, there exists a tremendous opportunity to understand the genetic and bimolecular factors which underlie the progression to DM2. Our lab has recently developed a novel pipeline termed integrative personal omics profiling (iPOP) which combines genomic, transcriptomic, proteomic and metabolomics profiles with computational tools to comprehensively investigate the molecules and pathways that change during disease onset and progression. We propose to perform whole-genome sequencing and longitudinal iPOP analysis on a cohort of overweight individuals either high-risk or low-risk for progression to DM2. For this cohort, we will analyze blood samples at the onset of the study, after a moderate weight gain and after a period of significant weight loss. We hypothesize that through iPOP analysis we can elucidate novel molecular factors and pathways which change in response to weight gain and loss and which differ between high- and low-risk individuals. Through this analysis we will offer an unprecedented view of the changing molecular landscape underlying acquired insulin resistance.