Abstract
PURPOSE OF THE REVIEW: Increasing access to large-scale genetic datasets in population-based studies allows for genetic association studies as a means to examine previously known and novel relationships among complex traits. In this review, we discuss two widely used approaches to leverage genetic data to study the links between traits: Genome-wide genetic correlation and Mendelian Randomization (MR) studies. RECENT FINDINGS: Both genetic correlation and MR studies have provided important novel insights. However, although they are less sensitive to many sources of bias present in traditional, observational epidemiology, they still rely on assumptions that in practice might be difficult to assess. To overcome this, development of novel methods less sensitive to these assumptions is an active area of research. SUMMARY: We believe that as population-based genetic datasets grow larger and novel methods allowing for weaker forms of current assumptions become available, genetic correlation and MR studies will become an integral part of genetic epidemiology studies.