Body mass index (BMI) serves as an important measurement of obesity and adiposity which are highly correlated with cardiometabolic disease. Many genetic variants have been identified in genetic association studies but with small proportion of BMI variation explained. Meanwhile little is known due to epigenetic changes and few studies that focus on BMI use whole genome bisulfite sequencing data. Taking advantage of monozygotic twins being genetic identical, we aim to explore the association between DNA methylation profile and BMI and seek to detangle the environmental influence on BMI, using discordant twin design for controlling the genetic effect.
Thirty Monozygotic twin pairs are included for this study with 11% minimum and 38% maximum BMI difference. There are 15 male pairs and 15 female pairs with age ranging from 39 to 72 years old. Methylation data from whole blood sample is collected using reduced representation bisulfite sequencing (RRBS). Approximately 4 million CpGs coverage in this platform means that data processing and analysis is extremely challenging. Preliminary analysis suggests no significant association between BMI and age or sex.
RRBS is a cost-effective approach for genome-wide methylation pattern profiling and RRBS data require many preprocessing procedures to obtain methylation data for whole CpG sites. Reads will be mapped to reference genome using mapping software that specialized for bisulfite sequencing. Methylation levels for each CpG will be extracted afterwards for data analysis. We will apply the model we previously proposed that regress intra-pair methylation difference on phenotype with adjustment of other factors such as age and sex on need. We will examine the whole genome for differential methylated CpGs and report those who are significantly associated with BMI for further pathway analysis.
|Period||26. Apr 2017|
|Event title||Åben forskerdag: Region Syddanmark|