Cis-methylation Quantitative Loci Research Articles

Integration of Mendelian randomisation and systems biology models to identify novel blood-based biomarkers for stroke

Stroke is the second largest cause of mortality in the world. Genome-wide association studies (GWAS) have identified some genetic variants associated with stroke risk, but their putative functional causal genes are unknown. Hence, we aimed to identify putative functional causal gene biomarkers of stroke risk. We used a summary-based Mendelian randomisation (SMR) approach to identify the pleiotropic associations of genetically regulated traits (i.e., gene expression and DNA methylation) with stroke risk. Using SMR approach, we integrated cis-expression quantitative loci (cis-eQTLs) and cis-methylation quantitative loci (cis-mQTLs) data with GWAS summary statistics of stroke. We also utilised heterogeneity in dependent instruments (HEIDI) test to distinguish pleiotropy from linkage from the observed associations identified through SMR analysis. Our integrative SMR analyses and HEIDI test revealed 45 candidate biomarker genes (FDR < 0.05; PHEIDI > 0.01) that were pleiotropically or potentially causally associated with stroke risk. Of those candidate biomarker genes, 10 genes (HTRA1, PMF1, FBN2, C9orf84, COL4A1, BAG4, NEK6, SH2B3, SH3PXD2A, ACAD10) were differentially expressed in genome-wide blood transcriptomics data from stroke and healthy individuals (FDR < 0.05). Functional enrichment analysis of the identified candidate biomarker genes revealed gene ontologies and pathways involved in stroke, including “cell aging”, “metal ion binding” and “oxidative damage”. Based on the evidence of genetically regulated expression of genes through SMR and directly measured expression of genes in blood, our integrative analysis suggests ten genes as blood biomarkers of stroke risk. Furthermore, our study provides a better understanding of the influence of DNA methylation on the expression of genes linked to stroke risk.

Obesity-related CpG Methylation (cg07814318) of Kruppel-like Factor-13 (KLF13) Gene with Childhood Obesity and its cis-Methylation Quantitative Loci

The cg07814318 hypermethylation of Kruppel-like factor 13 (KLF13) gene has been reported for its relevancy with Body Mass Index (BMI) from European origin. We explored the cg07814318 methylation and its cis-meQTL (cis-methylation quantitative loci) of KLF13 from a childhood obesity cohort. The cg07814318 methylation in blood was significantly associated with obesity and correlated with several obesity-related physical and biochemical traits. We examined the same loci from purified three human cell types (n = 47), i.e., pre-adipocytes, adipocytes and islets. The cg07814318 methylation pattern in pre-adipocytes and islets were significant higher in cells from subjects with a higher BMI compared with control subjects. By exome sequencing of KLF13 gene in blood with the same cohort, we found nine SNPs (single nucleotide polymorphisms) within its gene body, and two SNPs (rs11537749 and rs12595641) were as cis-meQTL of cg07814318. There was the 2.01% methylation change of cg07814318 between homozygous dominant and recessive genotypes, especially, in rs12595641. The sequencing variations within KLF13 genes could drive dynamic modifications of obesity-related CpG methylation. Differential DNA methylation patterns in the KLF13 gene determined from separate blood samples showed that this criterion could be used as a surrogate for representing overall epigenetic changes in cells related to obesity.