Search for obesity-associated genes with protective effects on metabolic health

肥胖是许多代谢和心血管并发症的主要危险因素。然而，a 相当大比例的肥胖者免受心脏代谢并发症的影响，尽管他们 过度肥胖(所谓的代谢性健康肥胖，MHO)。相反，并不是所有的正常体重 个人的新陈代谢是健康的，尽管很瘦(代谢性肥胖的正常体重，MONW)。这个 决定为什么一些肥胖个体受到保护，以及为什么一些正常个体 体重个体处于危险之中，人们对此知之甚少，因为临床研究往往太小和方法太多 测试所涉及的假定路径太具侵入性。识别基因及其存在的途径 牵连为阐明MHO和MONW的生物学基础提供了另一种策略。 全基因组关联研究到目前为止已经确定了300个肥胖特征的基因座。然而，这些 对于肥胖及其并发症之间的联系，基因座只能提供有限的洞察力，因为 Gwas孤立地检查了每种特征，忽略了肥胖是一种不同的临床状况这一事实。 因此，我们建议[1]对肥胖增加的基因座进行多性状全基因组搜索 对心脏代谢特征的保护作用，反之亦然，[2]优先考虑已识别基因座内的候选基因， 以及[3]在模型系统中对优先的候选基因进行功能表征。 具体地说，我们应用了两种互补的发现方法。在第一种方法(目标1a)中，我们执行 结合肥胖症和心脏代谢性GWA汇总统计的多因素相关荟萃分析 来自大型遗传财团和英国生物库(NTotal~840,000)。我们的目标是识别SNPs 同时与肥胖增加和有利的心脏代谢风险相关， 反过来说。在第二种方法(目标1b)中，我们使用来自英国生物库(N~500,000)的个人级别数据来 对心脏代谢性和肥胖性特征之间的差异得出的新结果进行GWA。 接下来，我们优先考虑已识别的基因座中最可能的候选基因和最相关的组织 基于CRISPR-CAS9的转基因技术中的功能注释管道(AIM 2a)和高通量筛选 斑马鱼模型系统(目标2b)。最后，我们研究了优先基因的功能影响。 人诱导多能干细胞分化为相关细胞类型的CRISPR-Cas9(目标3a) 以及转基因斑马鱼模型系统中的组织特异性转录分析(目标3b)。 我们专注于肥胖相关基因对健康的保护作用(反之亦然)是独一无二的，也是有针对性的 这是一种还没有用单一性状的GWAs获得的生物学。我们使用模型系统的方法 确定基因的优先顺序和特征是创新的，并将提供深入跟踪所需的关键见解- 在小鼠模型和临床研究中。一些已识别的基因可能指向可操作的靶点 预防和治疗肥胖及其并发症，对普通人群具有临床影响。

Obesity is a major risk factor for a number of metabolic and cardiovascular complications. However, a substantial proportion of obese individuals are protected from cardiometabolic complications, despite their excess adiposity (the so-called metabolically healthy obese, MHO). Conversely, not all normal weight individuals are metabolically healthy, despite being lean (the metabolically obese normal weight, MONW). The physiological mechanisms that determine why some obese individuals are protected, and why some normal weight individuals are at risk, are poorly understood, because clinical studies are often too small and methods to test presumed pathways involved are too invasive. Identifying genes and the pathways in which they are implicated provides an alternative strategy to elucidate the biology that underlies the MHO and MONW. Genome-wide association studies (GWAS) have so far identified >300 loci for obesity traits. However, these loci have provided only limited insight into the mechanisms that link obesity and its complications, because the GWAS examine each trait in isolation and ignore the fact that obesity is a heterogeneous clinical condition. Therefore, we propose to [1] perform a multi-trait genome-wide search for obesity-increasing loci with protective effects on cardiometabolic traits and vice versa, [2] prioritize candidate genes within identified loci, and [3] functionally characterize prioritized candidate genes in model systems. Specifically, we apply two complementary discovery approaches. In the first approach (Aim 1a), we perform multi-trait correlated meta-analyses that combine summary statistics of adiposity and cardiometabolic GWAS from large-scale genetic consortia and the UK Biobank (Ntotal~840,000). We aim to identify SNPs simultaneously associated with increased adiposity and a favorable cardiometabolic risk profile, and vice versa. In the second approach (Aim 1b), we use individual-level data from the UKBiobank (N~500,000) to perform GWAS on new outcomes derived from the difference between a cardiometabolic and an adiposity trait. Next, we prioritize the most likely candidate genes in identified loci and the most relevant tissues using functional annotation pipelines (Aim 2a) and high-throughput screens in transgenic CRISPR-Cas9-based zebrafish model systems (Aim 2b). Lastly, we investigate the functional impact of prioritized genes using CRISPR-Cas9 in human-induced pluripotent stem cells (hiPSCs) differentiated into relevant cell types (Aim 3a) and tissue-specific transcriptomic analyses in transgenic zebrafish model systems (Aim 3b). Our focus on obesity-associated loci with protective effects on health (and vice versa) is unique and targets a biology that has not been accessed with single-trait GWAS. Our approaches that use model systems to prioritize and characterize genes are innovative and will provide the critical insights needed for in-depth follow- up in murine models and clinical studies. Some identified genes may point towards actionable targets for the prevention and treatment of obesity and its complications with clinical impact for the general population.