Genome-wide association studies (GWAS) have uncovered multiple single nucleotide polymorphisms (SNPs) that are associated with height[1], adiposity[2, 3], cardiometabolic diseases[4] and intermediate cardiometabolic phenotypes.[5, 6] However, most GWAS have been carried out in caucasian adults, and the association between the SNPs and phenotypes in different ethnic groups and at different stages of the life course remains uncertain.

Within epidemiology, observational data are often used to assess the association between an exposure and a health outcome of interest in situations where a randomized controlled trial (which provides stronger evidence of causality) is not possible or not ethical. These studies are, however, plagued with difficulties due to bias and confounding.[7, 8] Mendelian Randomization[9] (MR) is a technique that uses genetic variants related to an exposure of interest to obtain an estimate of the exposure-outcome association that is not affected by confounding or reverse causality.

This PhD proposal will 1) further understanding of the genetic architecture of anthropometry and cardiometabolic traits, and 2) use MR to advance understanding of the causal relationships between anthropometry and cardiometabolic health.