Variant to Gene Mapping for Type 2 Diabetes

摘要 2型糖尿病是一种严重且昂贵的疾病，在美国影响至少2000万人， 慢性并发症包括心血管和微血管疾病的加速发展。 近年来，全基因组关联研究（GWAS）已经彻底改变了复杂疾病遗传学领域 多年来，在那里，密集的努力已经成功地发现了关键的遗传变异， 2型糖尿病然而，GWAS仅报告与给定性状相关的基因组信号，而不报告与给定性状相关的基因组信号。 这就需要精确定位罪魁祸首基因。因此，在过去的十年里，GWAS并没有严格地 代表了基因靶点发现的十年，而不仅仅是信号发现的十年。 这方面的一个明显的例子是最近在表征FTO基因座的相关基因中的进展所强调的。 肥胖症的特征事实上，最近已经证明，位于FTO内含子区域内的GWAS信号 主要影响附近IRX 3和IRX 5基因的表达而不是“宿主”基因本身， 这表明该变体位于嵌入一个基因的增强子中，但影响其他基因的表达。 因此，一个关键问题是：这种情况与2型糖尿病相关信号的频率有多高？ 事实上，我们已经讨论了迄今为止报道的2型糖尿病中最重要的GWAS发现， 即转录因子7样2（TCF 7 L2）基因内的遗传变异，P.I. on this 2006年首次提出申请。鉴于2型糖尿病遗传学社区广泛认为T TCF 7 L2内内含子单核苷酸多态性（SNP）的等位基因rs7903146是致病变异体 在这个位点，我们利用染色质构象捕获和CRISPR/Cas9基因组编辑技术， 靶向这个特定的基因组区域。因此，我们有令人信服的证据证明真正的罪犯 该基因座上的基因实际上是“酰基辅酶A合成酶长链家族成员5”（ACSL 5）。 鉴于我们已经有了由费城儿童医院资助的专用基础设施， 进行这样的“变异基因图谱”的努力，我们的团队准备确定如何额外的最近 未发现的2型糖尿病GWAS相关基因座通过以下途径影响特定基因的表达和功能： 使用关键的尖端分子生物学方法。基于“3D基因组学”技术的应用 将有助于在10个2型糖尿病GWAS信号中精确定位致病基因，其中“可信的 SNP的“集合"不超过十个变体，即已经通过 广泛的基因图谱工作，以一个可管理的候选变体短名单，其中一个必须是 因果关系因此，这些最近公布的SNP列表代表了可行数量的变体，以便 两者都确定了每个位点的致病基因，并证明了我们方法的普遍性。只 通过揭示这些遗传变异的正确功能背景并了解它们的运作方式， 我们真正将这些高价值的GWAS报告转化为对患者护理有意义的益处。

ABSTRACT Type 2 diabetes is a serious and costly disease that impacts at least 20 million people in the United States, with chronic complications including accelerated development of cardiovascular and microvascular disease. Genome wide association studies (GWAS) have revolutionized the field of complex disease genetics in recent years, where intense efforts have been successful in discovering key genetic variants robustly associated with type 2 diabetes. However, GWAS only reports genomic signals associated with a given trait and not necessarily the precise localization of culprit genes. As such, over the past ten years, GWAS did not strictly represent a decade of gene target discovery, rather it was simply a decade of signal discovery. One clear example of this is highlighted by the recent progress in characterizing the FTO locus in the related trait of obesity. The GWAS signal that resides within an intronic region of FTO has in fact been recently shown to primarily influence the expression of the IRX3 and IRX5 genes nearby rather than the ‘host’ gene itself, suggesting that this variant is in an enhancer embedded in one gene but influencing the expression of others. So a key question is: how often is this the case with type 2 diabetes association signals? Indeed, we have already addressed the most significant GWAS finding in type 2 diabetes reported to date, namely genetic variation within the transcription factor 7–like 2 (TCF7L2) gene, which the P.I. on this application first described in 2006. Given that the type 2 diabetes genetics community widely consider the T allele of the intronic single nucleotide polymorphism (SNP), rs7903146, within TCF7L2 to be the causal variant at this locus, we utilized chromatin conformation capture and CRISPR/Cas9 genome editing techniques to target this specific genomic region. As a consequence, we have compelling evidence that the actual culprit gene at this locus is in fact ‘acyl-CoA synthetase long chain family, member 5’ (ACSL5). Given we already have a dedicated infrastructure in place funded by the Children’s Hospital of Philadelphia to conduct such ‘variant to gene mapping’ efforts, our team is poised to determine how additional recently uncovered type 2 diabetes GWAS-implicated loci affect the expression and function of specific genes through the use key cutting-edge molecular biology approaches. The application of ‘3D Genomics’ based techniques will aid in the pinpointing of the causal gene(s) at ten of the type 2 diabetes GWAS signals, where the ‘credible set’ of SNPs is no more than ten variants i.e. a number of loci have already been distilled down through extensive genetic mapping efforts to a manageable shortlist of candidate variants, of which one must be causal. As such, these recently published lists of SNPs represent a workable number of variants in order to both determine the causal gene(s) at each locus and to demonstrate the generalizability of our approach. Only by uncovering the correct functional context of these genetic variants and understanding how they operate can we truly translate these high value GWAS reports in to meaningful benefits for patient care.