Metabolic syndrome is a cluster of symptoms including excessive body fat and insulin resistance which may lead to obesity and type 2 diabetes (T2D). The physiological and pathological cross-talk between T2D and obesity is crucial and complex, meanwhile, the genetic connection between T2D and obesity is largely unknown. The purpose of this study is to identify pleiotropic SNPs and genes between these two associated conditions by applying genetic analysis incorporating pleiotropy and annotation (GPA) on two large genome-wide association studies (GWAS) data sets: a body mass index (BMI) data set containing 339,224 subjects and a T2D data set containing 110,452 subjects. In all, 5182 SNPs showed pleiotropy in both T2D and obesity. After further prioritization based on suggested local false discovery rates (FDR) by the GPA model, 2146 SNPs corresponding to 217 unique genes are significantly associated with both traits (FDR < 0.2), among which 187 are newly identified pleiotropic genes compare with original GWAS in individual traits. Subsequently, gene enrichment and pathway analyses highlighted several pleiotropic SNPs including rs849135 (FDR = 0.0002), rs2119812 (FDR = 0.0018), rs4506565 (FDR = 1.23E−08), rs1558902 (7.23E−10) and corresponding genes JAZF1, SYN2, TCF7L2, FTO which may play crucial rol5es in the etiology of both T2D and obesity. Additional evidences from expression data analysis of pleiotropic genes strongly supports that the pleiotropic genes including JAZF1 (p = 1.39E−05 and p = 2.13E−05), SYN2 (p = 5.49E−03 and p = 5.27E−04), CDKN2C (p = 1.99E−12 and p = 6.27E−11), RABGAP1 (p = 3.08E−03 and p = 7.46E−03), and UBE2E2 (p = 1.83E−04 and p = 8.22E−03) play crucial roles in both obesity and T2D pathogenesis. Pleiotropic analysis integrated with functional network identified several novel and causal SNPs and genes involved in both BMI and T2D which may be ignored in single GWAS.

代谢综合征是一系列症状，包括体脂过多和胰岛素抵抗，可能导致肥胖和 2 型糖尿病 (T2D)。T2D 与肥胖之间的生理和病理交叉至关重要且复杂，同时，T2D 与肥胖之间的遗传联系在很大程度上是未知的。本研究的目的是通过在两个大型全基因组关联研究 (GWAS) 数据集上应用结合多效性和注释 (GPA) 的遗传分析来识别这两种相关疾病之间的多效性 SNP 和基因：体重指数 (BMI) 数据包含 339,224 名受试者的数据集和包含 110,452 名受试者的 T2D 数据集。总共有 5182 个 SNP 在 T2D 和肥胖症中均表现出多效性。在 GPA 模型根据建议的局部错误发现率 (FDR) 进一步确定优先级之后，对应于217个独特基因的2146个SNP与两个性状均显着相关（FDR < 0.2），其中187个是新发现的多效性基因，与原始GWAS相比，单个性状。随后，基因富集和通路分析突出了几个多效性 SNP，包括 rs849135 (FDR = 0.0002)、rs2119812 (FDR = 0.0018)、rs4506565 (FDR = 1.23E−08)、rs155829302 (FDR = 0.0002) 和相应的基因 (JAZF1、SYN2、TCF7L2、FTO可能在 T2D 和肥胖症的病因学中起关键作用。多效基因表达数据分析的其他证据强烈支持多效基因包括 JAZF1（p  = 1.39E-05 和p  = 2.13E-05）、SYN2（p  = 5.49E-03 和p  = 5.27E-04）， CDKN2C（p  = 1.99E-12 和p  = 6.27E-11）、RABGAP1（p  = 3.08E-03 和p  = 7.46E-03）和 UBE2E2（p  = 1.83E-04 和p = 8.22E-03) 在肥胖和 T2D 发病机制中都起着至关重要的作用。与功能网络相结合的多向性分析确定了几个新的和因果的 SNP 和基因，这些 SNP 和基因涉及 BMI 和 T2D，这些在单个 GWAS 中可能会被忽略。