Complex trait genetics: mapping, correlation and causation

Abstract

Efforts to understand the genetic aetiology of complex traits have gained a lot of momentum in the last decade. Advancement of next generation sequencing and the ever-decreasing price of genotyping platforms have allowed us to carry out a vast number of genome wide association studies (GWAS). Until relatively recently, GWAS was guided by the common disease -common genetic variation paradigm.However, recent findings and developments have made us look at the bigger picture, including rare genetic variation. In addition, methodological developments are guiding the translation of GWAS findings. For instance, diverse statistical methods can be applied on genetically informative data to estimate the genetic correlation between complex diseases. The latter can have important medical implications, as genetically correlated diseases might be responsive to the same treatments. Also, approaches such as Mendelian randomization (MR) can help investigations of causal factors in disease when is unfeasible to carry out randomized control trials.My focus is on the application of statistical methods in complex trait genetics -I cover a range of phenotypes, ranging from eye disease to cancer.