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Abstract
Background
A few genes have previously been identified in which very rare variants can have major effects on lipid levels.
Methods
Weighted 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).
Results
With 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.
Conclusion
These 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.
- human genetics
- point mutation
- sequence analysis
- DNA
Data availability statement
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.
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Data availability statement
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.
Footnotes
Twitter @davecurtis314
Contributors Conceived study, carried out analysis, wrote paper.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.
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