Variant to Gene Mapping for Type 2 Diabetes

摘要 2型糖尿病是一种严重且代价高昂的疾病，在美国至少有2000万人受到影响， 有慢性并发症，包括心血管和微血管疾病的加速发展。 全基因组关联研究近年来给复杂疾病遗传学领域带来了革命性的变化 多年来，密集的努力成功地发现了与疾病密切相关的关键基因变异 2型糖尿病。然而，GWAS只报告了与给定性状相关的基因组信号，而不是 必须对罪犯基因进行精确定位。因此，在过去的十年里，GWAS并没有严格地 代表了十年的基因靶标发现，而不是仅仅是信号发现的十年。 一个明显的例子是最近在表征相关的FTO基因座方面取得的进展 肥胖的特征。事实上，最近已经显示了位于FTO内含子区域内的Gwas信号 为了主要影响附近的IRX3和IRX5基因的表达，而不是“宿主”基因本身， 这表明这种变异存在于嵌入在一个基因中的增强子中，但会影响其他基因的表达。 因此，一个关键的问题是：2型糖尿病关联信号的出现频率是多少？ 事实上，我们已经解决了迄今为止报告的在2型糖尿病中最重要的GWAS发现， 即转录因子7-样2(TCF7L2)基因内的遗传变异，P.I. 应用程序于2006年首次描述。鉴于2型糖尿病遗传学社区普遍认为T细胞 TCF7L2内含子单核苷酸多态(SNP)的等位基因rs7903146为因果变异 在这个基因座上，我们利用染色质构象捕捉和CRISPR/Cas9基因组编辑技术 瞄准这个特定的基因组区域。因此，我们有令人信服的证据表明真正的罪魁祸首 该基因实际上是‘酰辅酶A合成酶长链家族成员5’(ACSL5)。 鉴于我们已经有了由费城儿童医院资助的专用基础设施 进行这种“基因图谱变异”的工作，我们的团队准备确定最近如何增加 未发现的2型糖尿病GWAS相关基因通过以下途径影响特定基因的表达和功能 使用关键的前沿分子生物学方法。基于“3D基因组学”技术的应用 将有助于精确定位致病基因(S)在10个2型糖尿病GWAs信号，在那里 SNPs的集合不超过10个变异，即许多基因座已经通过 对候选变异的可管理的短名单进行广泛的基因图谱绘制工作，其中一个必须是 因果关系。因此，这些最近公布的SNPs列表代表了许多可行的变体，以便 这两个方法都确定了每个基因座上的因果基因(S)，并证明了我们方法的普遍性。仅限 通过揭示这些基因变体的正确功能背景并了解它们是如何工作的，可以 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好处。

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.