GWA-based pleiotropic analysis identified potential SNPs and genes related to type 2 diabetes and obesity

• Published in: Journal of human genetics Vol. 66; no. 3; pp. 297 - 306
• Main Authors: Zeng, Yong, He, Hao, Zhang, Lan, Zhu, Wei, Shen, Hui, Yan, Yu-Jie, Deng, Hong-Wen
• Format: Journal Article
• Language: English
• Published: England Nature Publishing Group 01.03.2021
• Subjects: Alpha-Ketoglutarate-Dependent Dioxygenase FTO - genetics; Body fat; Body Mass Index; Comorbidity; Datasets as Topic - statistics & numerical data; Diabetes; Diabetes mellitus (non-insulin dependent); Diabetes Mellitus, Type 2 - epidemiology; Diabetes Mellitus, Type 2 - genetics; Etiology; Gene Expression; Gene Regulatory Networks; Genetic analysis; Genetic Association Studies; Genetic Pleiotropy; Genetic Predisposition to Disease; Genome-wide association studies; Genome-Wide Association Study; Genomes; Humans; Insulin; Insulin resistance; Meta-Analysis as Topic; Metabolic syndrome; Metabolic Syndrome - epidemiology; Metabolic Syndrome - genetics; Molecular Sequence Annotation; Obesity; Obesity - epidemiology; Obesity - genetics; Pleiotropy; Polymorphism, Single Nucleotide; Prevalence; Single-nucleotide polymorphism; Transcription Factor 7-Like 2 Protein - genetics
• ISSN: 1434-5161; 1435-232X
• DOI: 10.1038/s10038-020-00843-4

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.