Evolutionary modeling of genetically complex traits and diseases
Approved Research ID: Evolutionary modeling of genetically complex traits and diseases
Approval date: February 1st 2022
Human beings differ from one another in many ways: in our physical traits like our height and weight; in metabolic traits like our cholesterol or triglyceride levels; and in our risk of developing severe medical conditions like schizophrenia or diabetes. A subset of these differences in our traits can be traced to differences in our genes, and the way in which these genetic differences are distributed among individuals is a result of our evolutionary history.
Natural selection is one evolutionary forces that is known to have shaped these patterns of genetic variation. Human geneticists have clearly observed that genetic variants with large effects on a given trait will tend to be less common in the population than those with smaller effects, a pattern that is expected only if variants with larger effects tend to have more severe consequences for evolutionary fitness than those with small effects. However, human biology is quite complicated, and a single genetic variant will often influence multiple different traits. This "pleiotropy" means that patterns of genetic variation for any particular trait will depend not only how natural selection has impacted that trait, but also on how natural selection has impacted all the other traits to which it is pleiotropically connected.
While it is clear that natural selection has played an important role in shaping patterns of genetic variation within populations, natural selection may also have caused the evolution of differences among populations, and such among population differences could be medically relevant if they impact traits that are associated with variation in disease risk. However, non-genetic factors are also known to have a substantial impact on among group differences, and these non-genetic effects can often be difficult to distinguish from genetic ones.
Our research aims to characterize the the impact of natural selection on patterns of genetic variation for human traits. We are particularly interested in understanding the relative importance of natural selection acting directly on a trait vs on pleiotropically associated traits, and in accurately identifying cases where natural selection has driven differences between populations. We are actively developing statistical methods to accomplish these two aims, and plan to apply them broadly to traits measured in the UK Biobank dataset. We anticipate that the knowledge gained from our work will be broadly useful to other researchers seeking to better understand the genetics of complex human traits. The anticipated timeline for our project is 3 years.