Aims: The study aimed to identify specific genes and functional genetic variants affecting susceptibility to two alcohol-related phenotypes: heavy drinking and problem drinking.
Methods: Phenotypic and exome sequence data were downloaded from the UK Biobank. Reported drinks in the last 24 hours were used to define heavy drinking, while responses to a mental health questionnaire defined problem drinking. Gene-wise weighted burden analysis was applied, with genetic variants which were rarer and/or had a more severe functional effect being weighted more highly. Additionally, previously reported variants of interest were analysed inidividually.
Results: Of exome sequenced subjects, for heavy drinking, there were 8166 cases and 84,461 controls, while for problem drinking, there were 7811 cases and 59,606 controls. No gene was formally significant after correction for multiple testing, but three genes possibly related to autism were significant at P < 0.001, FOXP1, ARHGAP33 and CDH9, along with VGF which may also be of psychiatric interest. Well established associations with rs1229984 in ADH1B and rs671 in ALDH2 were confirmed, but previously reported variants in ALDH1B1 and GRM3 were not associated with either phenotype.
Conclusions: This large study fails to conclusively implicate any novel genes or variants. It is possible that more definitive results will be obtained when sequence data for the remaining UK Biobank participants become available and/or if data can be obtained for a more extreme phenotype such as alcohol dependence disorder. This research has been conducted using the UK Biobank Resource.
Study of effects of common and rare genetic variants on health-related phenotypes
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.
|Lead investigator:||Professor David Curtis|
|Lead institution:||University College London|
2 related Returns
|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|