Olsson Anders H, Volkov Petr, Bacos Karl, Dayeh Tasnim, Hall Elin, Nilsson Emma A, Ladenvall Claes, Rönn Tina, Ling Charlotte
Department of Clinical Sciences, Epigenetics and Diabetes, Lund University Diabetes Centre, Clinical Research Centre, Malmö, Sweden.
Department of Clinical Sciences, Diabetes and Endocrinology, Lund University Diabetes Centre, Clinical Research Centre, Malmö, Sweden.
PLoS Genet. 2014 Nov 6;10(11):e1004735. doi: 10.1371/journal.pgen.1004735. eCollection 2014 Nov.
Genetic and epigenetic mechanisms may interact and together affect biological processes and disease development. However, most previous studies have investigated genetic and epigenetic mechanisms independently, and studies examining their interactions throughout the human genome are lacking. To identify genetic loci that interact with the epigenome, we performed the first genome-wide DNA methylation quantitative trait locus (mQTL) analysis in human pancreatic islets. We related 574,553 single nucleotide polymorphisms (SNPs) with genome-wide DNA methylation data of 468,787 CpG sites targeting 99% of RefSeq genes in islets from 89 donors. We identified 67,438 SNP-CpG pairs in cis, corresponding to 36,783 SNPs (6.4% of tested SNPs) and 11,735 CpG sites (2.5% of tested CpGs), and 2,562 significant SNP-CpG pairs in trans, corresponding to 1,465 SNPs (0.3% of tested SNPs) and 383 CpG sites (0.08% of tested CpGs), showing significant associations after correction for multiple testing. These include reported diabetes loci, e.g. ADCY5, KCNJ11, HLA-DQA1, INS, PDX1 and GRB10. CpGs of significant cis-mQTLs were overrepresented in the gene body and outside of CpG islands. Follow-up analyses further identified mQTLs associated with gene expression and insulin secretion in human islets. Causal inference test (CIT) identified SNP-CpG pairs where DNA methylation in human islets is the potential mediator of the genetic association with gene expression or insulin secretion. Functional analyses further demonstrated that identified candidate genes (GPX7, GSTT1 and SNX19) directly affect key biological processes such as proliferation and apoptosis in pancreatic β-cells. Finally, we found direct correlations between DNA methylation of 22,773 (4.9%) CpGs with mRNA expression of 4,876 genes, where 90% of the correlations were negative when CpGs were located in the region surrounding transcription start site. Our study demonstrates for the first time how genome-wide genetic and epigenetic variation interacts to influence gene expression, islet function and potential diabetes risk in humans.
遗传和表观遗传机制可能相互作用，并共同影响生物过程和疾病发展。然而，以往大多数研究都是独立研究遗传和表观遗传机制，缺乏在全人类基因组范围内研究它们相互作用的研究。为了确定与表观基因组相互作用的基因座，我们在人类胰岛中进行了首次全基因组DNA甲基化定量性状基因座（mQTL）分析。我们将574,553个单核苷酸多态性（SNP）与来自89名供体的胰岛中靶向99%的RefSeq基因的468,787个CpG位点的全基因组DNA甲基化数据相关联。我们在顺式中鉴定出67,438个SNP-CpG对，对应于36,783个SNP（占测试SNP的6.4%）和11,735个CpG位点（占测试CpG的2.5%），以及在反式中鉴定出2,562个显著的SNP-CpG对，对应于1,465个SNP（占测试SNP的0.3%）和383个CpG位点（占测试CpG的0.08%），在经过多重检验校正后显示出显著关联。这些包括已报道的糖尿病基因座，如ADCY5、KCNJ11、HLA-DQA1、INS、PDX1和GRB10。显著顺式mQTL的CpG在基因体和CpG岛外的比例过高。后续分析进一步确定了与人类胰岛中基因表达和胰岛素分泌相关的mQTL。因果推断测试（CIT）确定了SNP-CpG对，其中人类胰岛中的DNA甲基化是与基因表达或胰岛素分泌的遗传关联的潜在介导因素。功能分析进一步证明，鉴定出的候选基因（GPX7、GSTT1和SNX19）直接影响胰腺β细胞中的增殖和凋亡等关键生物过程。最后，我们发现22,773个（4.9%）CpG的DNA甲基化与4,876个基因的mRNA表达之间存在直接相关性，当CpG位于转录起始位点周围区域时，90%的相关性为负相关。我们的研究首次证明了全基因组遗传和表观遗传变异如何相互作用以影响人类的基因表达、胰岛功能和潜在的糖尿病风险。
