Considerable interpersonal variability in weight loss exists in diet interventions, likely due to individuals' inherent factors such as genomic and epigenomic variations; however our currently knowledge on these factors is extremely poor. The proposed systems study aims to fill this significant research gap. In three independent, comprehensive comparator trials on weight-loss diets ? POUNDS LOST, DIRECT and MACRO, we propose to perform thus far the most comprehensive epigenome-wide association study (EWAS) using state-of-the-art capture-based bisulfite sequencing approach (targeting ~5M dynamic CpGs) to identify DNA methylation (DNAm) associated with long-term (up to 2 years) weight loss in response to diet interventions (Aim 1a and 1b), and assess the dietary effects on dynamic changes in DNAm (Aim 1c). We will develop joint DNAm Scores (MeS) integrating methylation information across CpG sites, and analyze their associations with weight loss (Aim 2). We will also examine the relations between DNAm and markers of energy balance (Aim 3). In addition, we will apply newly-developed multi-omics algorithm to predict weight loss, by integrating DNAm with genomics, metabolomics, biochemical and clinical measures (Aim 4). We believe that our study will provide novel insights into the roles of epigenomics and multi-omics in determining weight loss in response to diet interventions, and contribute significantly to improve efficiency of precision obesity management.
In three independent, long-term (up to 2 years) weight-loss diet intervention trials, the study propose to perform thus far the most comprehensive epigenome-wide association study (targeting ~5M dynamic CpGs) to detect DNA methylation (DNAm) associated with weight loss in response to diet interventions, and assess the dietary effects on dynamic changes in DNAm. We will also examine the relations between DNAm and energy balance regulation, and develop multi-omics algorithm to predict weight loss by integrating DNAm with genomics, metabolomics, biochemical and clinical measures. Our study would lead to identification of novel determinants for weight loss in diet interventions, and improve efficiency of precision obesity management.
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