Both common and rare genetic variants contribute to the heritability of complex traits. However, usually they are analysed separately using different analytical techniques, such as single variant regression versus burden methods. This fails to fully utilise the information contained in genomes. Here, we aim to apply computational methods we have developed which combine information from common and rare variants and which can utilise information about the predicted effects of the variants to identify genes influencing complex traits. We will use our results to assess how natural selection has shaped the genetic architecture of complex traits in modern humans. We will particularly focus on non-communicable diseases, such as cardiovascular disease, neurological disorders and cancer, and disease-related traits, such as obesity and cholesterol levels, as well as the susceptibility to infectious diseases. Differences in environments, natural selection and drift may have distinctly shaped the genetic architectures in some populations. Therefore, we will compare results for different ancestry groups.
|Return ID||App ID||Description||Archive Date|
|3787||51119||Analysis of 50,000 exome-sequenced UK Biobank subjects fails to identify genes influencing probability of developing a mood disorder resulting in psychiatric referral||6 Sep 2021|
|3614||51119||Analysis of exome-sequenced UK Biobank subjects implicates genes affecting risk of hyperlipidaemia||30 Jun 2021|
|4003||51119||Investigation of Association of Rare, Functional Genetic Variants With Heavy Drinking and Problem Drinking in Exome Sequenced UK Biobank Participants||14 Oct 2021|
|3788||Analysis of 50,000 exome-sequenced UK Biobank subjects fails to identify genes influencing probability of developing a mood disorder resulting in psychiatric referral||Curtis et al.,||2021||Journal of Affective Disorders (2021)|
|3615||Analysis of exome-sequenced UK Biobank subjects implicates genes affecting risk of hyperlipidaemia||Curtis||2021||Molecular Genetics and Metabolism|