Principal Investigator: Dr Hilary Martin
Wellcome Trust Sanger Institute, Cambridge, UKTags: 44165, autozygosity, constraint, loss-of-function, Modifiers, penetrance, Polygenic
Ms Eva van Walree – VU University Amsterdam, Amsterdam, Netherlands
Professor George Kirov – Cardiff University, Cardiff, UK
Human genetics research has typically been divided into research into common diseases, which are due to a combination of many common genetic variants of small effect and environmental factors, and rare diseases, which are thought to be due largely to rare genetic variants. These two fields are starting to converge, with multiple studies showing that rare variation contributes to common diseases and evidence emerging for a role of common variants in rare disorders. We will investigate the interplay between these different types of genetic variation and their contribution to various traits in the UK Biobank. Specifically, we will look at how common genetic variation modifies the “penetrance” of rare variants (meaning the probability that a person has a particular disease, given they have the variant).
Some genes have been shown to be very intolerant of variation (i.e. genetic variants in them damage normal functioning and are thus removed from the population by natural selection). Previous work focused on identifying genes in which loss of one of the two copies is very damaging. In contrast, other genes are recessive, meaning both copies have to be lost in order to affect normal functioning. We will use the Biobank data to infer which genes act recessively, which will inform the discovery of new genes for rare diseases and increase our understanding of fundamental biology (i.e. how many copies of each human gene are essential to have). To understand the impact of disrupting these variation-intolerant genes, we will test for associations between different classes of variants in these genes and various traits.
Demographic processes such as population growth, migration and endogamy (marriage within groups or between family members) impact the distribution of genetic variants within the genome, and can contribute to differences in disease risk. In particular, it is well known that having parents who are related increases risk of rare, early-onset conditions because it increases the chance of inheriting the same damaging variant from each parent in a recessive gene. However, the effects of parental relatedness on later-onset diseases have not been quantified. We will investigate patterns of genetic variation in people of different ancestries from UK Biobank and other cohorts enriched for parental relatedness.
Our research will increase fundamental understanding of how genetics contribute to human disease risk, which will lead to better risk prediction, as well as potential diagnoses and treatment. The project duration will be three years.
We are interested in a variety of questions regarding the influence of different classes of genetic variation on phenotypes, and the forces that give rise to patterns of genetic variation. Some of these questions will require the exome sequence data when they become available, and others can be addressed with the imputed genotype data.
– What are the phenotypic consequences of rare variants in known Mendelian disease genes (e.g. heterozygous carriers in recessive genes) and genes under strong purifying selection against loss-of-function and missense variants?
– How penetrant are such variants? Do common variants affect penetrance, either in aggregate (e.g. polygenic risk scores) or by affecting expression of individual genes?
– Which genes or regions of genes are under different types of selective constraint e.g. purifying selection against monoallelic (heterozygous) versus biallelic (homozygous or compound heterozygous) loss-of-function or missense variants? What are the phenotypic consequences of variants in these genes?
– What are the phenotypic consequences of higher levels of autozygosity (homozygosity due to recent consanguinity), and what classes of variants are these manifested through?
– How has population history, including patterns of endogamy, influenced the distribution of deleterious variation?
Extension: Where relevant, we will meta-analyse UK Biobank with the INTERVAL cohort, with a focus on rare and common variants affecting cognition. For this, we will need to identify relatives between the cohorts using the genetic data so we can exclude them from one.
Last updated Jun 10, 2019