Liang Xiao, He Awen, Wang Wenyu, Liu Li, Du Yanan, Fan Qianrui, Li Ping, Wen Yan, Hao Jingcan, Guo Xiong, Zhang Feng
Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China.
Biomed Res Int. 2017;2017:1758636. doi: 10.1155/2017/1758636. Epub 2017 Jun 28.
To identify novel candidate genes and gene sets for diabetes.
We performed an integrative analysis of genome-wide association studies (GWAS) and expression quantitative trait loci (eQTLs) data for diabetes. Summary data was driven from a large-scale GWAS of diabetes, totally involving 58,070 individuals. eQTLs dataset included 923,021 cis-eQTL for 14,329 genes and 4,732 trans-eQTL for 2,612 genes. Integrative analysis of GWAS and eQTLs data was conducted by summary data-based Mendelian randomization (SMR). To identify the gene sets associated with diabetes, the SMR single gene analysis results were further subjected to gene set enrichment analysis (GSEA). A total of 13,311 annotated gene sets were analyzed in this study.
SMR analysis identified 6 genes significantly associated with fasting glucose, such as C11ORF10 ( = 6.04 × 10), MRPL33 ( = 1.24 × 10), and FADS1 ( = 2.39 × 10). Gene set analysis identified HUANG_FOXA2_TARGETS_UP (false discovery rate = 0.047) associated with fasting glucose.
Our study provides novel clues for clarifying the genetic mechanism of diabetes. This study also illustrated the good performance of SMR approach and extended it to gene set association analysis for complex diseases.
鉴定糖尿病的新型候选基因和基因集。
我们对糖尿病的全基因组关联研究（GWAS）和表达数量性状基因座（eQTL）数据进行了综合分析。汇总数据来自一项大规模的糖尿病GWAS，共涉及58,070名个体。eQTL数据集包括14,329个基因的923,021个顺式eQTL和2,612个基因的4,732个反式eQTL。通过基于汇总数据的孟德尔随机化（SMR）对GWAS和eQTL数据进行综合分析。为了鉴定与糖尿病相关的基因集，将SMR单基因分析结果进一步进行基因集富集分析（GSEA）。本研究共分析了13,311个注释基因集。
SMR分析鉴定出6个与空腹血糖显著相关的基因，如C11ORF10（= 6.04×10）、MRPL33（= 1.24×10）和FADS1（= 2.39×10）。基因集分析鉴定出与空腹血糖相关的HUANG_FOXA2_TARGETS_UP（错误发现率 = 0.047）。
我们的研究为阐明糖尿病的遗传机制提供了新线索。本研究还展示了SMR方法的良好性能，并将其扩展到复杂疾病的基因集关联分析。
