PT  - JOURNAL ARTICLE
AU  - David Curtis
TI  - Analysis of 200 000 exome-sequenced UK Biobank subjects illustrates the contribution of rare genetic variants to hyperlipidaemia
AID  - 10.1136/jmedgenet-2021-107752
DP  - 2021 Apr 28
TA  - Journal of Medical Genetics
PG  - jmedgenet-2021-107752
4099  - http://jmg.bmj.com/content/early/2021/04/27/jmedgenet-2021-107752.short
4100  - http://jmg.bmj.com/content/early/2021/04/27/jmedgenet-2021-107752.full
AB  - BackgroundA few genes have previously been identified in which very rare variants can have major effects on lipid levels.MethodsWeighted burden analysis of rare variants was applied to exome sequenced UK Biobank subjects with hyperlipidaemia as the phenotype, of whom 44 054 were designated cases and 156 578 controls, with the strength of association characterised by the signed log 10 p value (SLP).ResultsWith principal components included as covariates there was a tendency for genes on the X chromosome to produce strongly negative SLPs, and this was found to be due to the fact that rare X chromosome variants were identified less frequently in men than women. The test performed well when both principal components and sex were included as covariates and strongly implicated LDLR (SLP=50.08) and PCSK9 (SLP=−10.42) while also highlighting other genes previously found to be associated with lipid levels. Variants classified by SIFT as deleterious have on average a twofold effect and their cumulative frequency is such that they are present in approximately 1.5% of the population.ConclusionThese analyses shed further light on the way that genetic variation contributes to risk of hyperlipidaemia and in particular that there are very many protein-altering variants which have on average moderate effects and whose effects can be detected when large samples of exome-sequenced subjects are available. This research has been conducted using the UK Biobank Resource.Data may be obtained from a third party and are not publicly available. The raw data are available on application to UK Biobank. Detailed results with variant counts cannot be made available because they might be used for subject identification. Relevant derived variables including principal components and variant annotations will be deposited in UK Biobank. Scripts and software used to carry out the analyses are available at: https://github.com/davenomiddlenamecurtis.