Mouse ADIPOQ peptide

The extent to which genetic influences on cardiovascular disease risk are mediated by changes in DNA methylation levels has not been systematically explored. We developed an analytical framework that integrates genetic fine mapping and Mendelian randomization with epigenome-wide association studies to evaluate the causal relationships between methylation levels and 14 cardiovascular disease traits. We identified ten genetic loci known to influence proximal DNA methylation which were also associated with cardiovascular traits after multiple-testing correction. Bivariate fine mapping provided evidence that the individual variants responsible for the observed effects on cardiovascular traits at the ADCY3 and ADIPOQ loci were potentially mediated through changes in DNA methylation, although we highlight that we are unable to reliably separate causality from horizontal pleiotropy. Estimates of causal effects were replicated with results from large-scale consortia. Genetic variants and CpG sites identified in this study were enriched for histone mark peaks in relevant tissue types and gene promoter regions. Integrating our results with expression quantitative trait loci data, we provide evidence that variation at these regulatory regions is likely to also influence gene expression levels at these loci.

Background and aims At present obesity and metabolic syndrome (MetS) in India are the most challenging health problems. It is also well accepted that obesity is a significant risk factor for the development of metabolic syndrome and other degenerative diseases. Many studies have reported that single-nucleotide polymorphisms (SNPs) of the adiponectin (ADIPOQ) gene have been associated with obesity and its related disorders. Here, we aimed to investigate the association of two intronic variants in ADIPOQ gene, -3971A>G (rs822396) and +276G>T (rs1501299) with obesity and metabolic syndrome. Methods Biochemical and anthropometric measurements were obtained from a total of 550 unrelated subjects (obese = 250 and non-obese = 300) of North Indian Punjabi population. Genotyping for the intron variants were performed by polymerase chain reaction based restriction fragment length polymorphism (PCR-RFLP) methods. After genotyping, as a quality control measure 10% of the samples for each polymorphism were confirmed by Sanger Sequencing method. The distributions of genotypic and allelic frequencies among obese and non-obese groups were compared by chi-square test and the corresponding risk was calculated using binary logistic regression. The effects of multiple testing were controlled by applying Bonferroni corrections. Results All the anthropometric and biochemical parameters except triglycerides (TG) and very low-density lipoproteins cholesterol (VLDL-C) have shown significant association with both GG and TT genotypes of -3971A>G (rs822396) and +276G>T (rs1501299) polymorphisms respectively. The frequencies of GG (-3971A>G) and TT (+276G>T) genotypes were higher among obese cases (p = 0.008 and p = 0.035 respectively). However, no significant association was found between allelic frequencies of ADIPOQ rs822396 and obesity, whereas the 16 association of ADIPOQ rs1501299 attenuated and became marginally significant after Bonferroni correction (p>0.025). Both the variant genotypes of ADIPOQ gene polymorphisms (-3971GG and +276TT) significantly increased the risk of development of obesity (OR: 1.52, p = 0.03; OR: 1.58, p = 0.04 respectively) and MetS (OR: 1.42, p = 0.03; OR: 1.57, p = 0.01 respectively) in the present population, after adjusting the various covariates. The G-T haplotype model (possessing -3971G and +276T alleles) was shown to provide similar to 3 fold risk towards the obesity susceptibility (OR: 2.69, p = 0.009) and MetS risk (OR: 2.73, p = 0.009) and the association persisted after adjusting for different confounding variables. Conclusion The present study has confirmed that ADIPOQ -3971A>G (rs822396) and +276G>T (rs1501299) polymorphism may be clinically helpful to estimate obesity and MetS risk in North Indian Punjabi population.