Exploration of weighting schemes based on allele frequency and annotation for weighted burden association analysis of complex phenotypes

Curtis, David

doi:10.1016/j.gene.2021.146039

Cited by 6 publications

(8 citation statements)

References 26 publications

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“…For most genes LOF variants have the largest effect size but this is not the case for ABCG5 in which LOF variants do not clearly have any effect and the signal is instead driven by specific splice region variants. This inconsistency of effects of different annotations across genes was noted in a previous study and seems to imply that there is no universal system for weighting variants which would perform optimally for all genes (Curtis, 2022).…”

Section: Discussionmentioning

confidence: 78%

Weighted burden analysis of rare coding variants in 470,000 exome-sequenced UK Biobank subject characterises effects on hyperlipidaemia risk

Curtis

2023

Preprint

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A previous study of 200,000 exome-sequenced UK Biobank participants investigating the association between rare coding variants and hyperlipidaemia had implicated four genes, LDLR, PCSK9, APOC3 and IFITM5, at exome-wide significance. In addition, a further 43 protein-coding genes were significant with an uncorrected p value of <0.001. Exome sequence data has become available for a further 270,000 participants and weighted burden analysis to test for association with hyperlipidaemia was carried out in this sample for the 47 genes highlighted by the previous study. There was no evidence to implicate IFITM5 but LDLR, PCSK9, APOC3, ANGPLT3, ABCG5 and NPC1L1 were all statistically significant after correction for multiple testing. These six genes were also all exome-wide significant in the combined sample of 470,000 participants. Variants impairing function of LDLR and ABCG5 were associated with increased risk whereas variants in the other genes were protective. Variant categories associated with large effect sizes are cumulatively very rare and the main benefit of this kind of study seems to be to throw light on the molecular mechanisms impacting hyperlipidaemia risk, hopefully supporting attempts to develop improved therapies.

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Section: Discussionmentioning

confidence: 78%

Weighted burden analysis of rare coding variants in 470,000 exome-sequenced UK Biobank subject characterises effects on hyperlipidaemia risk

Curtis

2023

Preprint

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“…Additionally, we assign higher weights to variants which are rarer, under the assumption that variants which are extremely rare may have larger effect sizes. Work on real world data confirms that weighting on variant annotation and allele frequency in this way does indeed yield increased power (10).…”

Section: Introductionmentioning

confidence: 73%

“…The weights allocated are to some extent arbitrary but took account of the analysis of the effects of different categories of variant in LDLR on hyperlipidaemia risk (7). A systematic exploration of different weighting schemes has shown than no one scheme is optimal in all circumstances but that the one used here has reasonable performance (10). Variants predicted to cause complete loss of function (LOF) of the gene were assigned a weight of 100.…”

Section: Methodsmentioning

confidence: 99%

Weighted burden analysis in 200,000 exome-sequenced subjects characterises rare variant effects on BMI

Curtis

2022

Int J Obes

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IntroductionA number of genes have been identified in which rare variants can cause obesity. Here we analyse a sample of exome sequenced subjects from UK Biobank using BMI as a phenotype with the aim of identifying genes in which rare, functional variants influence BMI and characterising the effects of different categories of variant. MethodsThere were 199,807 exome sequenced subjects for whom BMI was recorded. Weighted burden analysis of rare, functional variants was carried out, incorporating population principal components and sex as covariates. For selected genes, additional analyses were carried out to clarify the contribution of different categories of variant. Statistical significance was summarised as the signed log 10 of the p value (SLP), given a positive sign if the weighted burden score was positively correlated with BMI. ResultsTwo genes were exome-wide significant, MC4R (SLP = 15.79) and PCSK1 (SLP = 6.61). In MC4R, disruptive variants were associated with an increase in BMI of 2.72 units and probably damaging nonsynonymous variants with an increase of 2.02 units. In PCSK1, disruptive variants were associated with a BMI increase of 2.29 and protein-altering variants with an increase of 0.34. Results for other genes were not formally significant after correction for multiple testing, although SIRT1, ZBED6 and NPC2 were noted to be of potential interest. ConclusionBecause the UK Biobank consists of a self-selected sample of relatively healthy volunteers, the effect sizes noted may be underestimates. The results demonstrate the effects of very rare variants on BMI and suggest that other genes and variants will be definitively implicated when the sequence data for additional subjects becomes available. This research has been conducted using the UK Biobank Resource.

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“…The methods used closely followed those described in the previous study exploring different annotation and weighting schemes, and the description is partly repeated here for the convenience of the reader (Curtis, 2022).…”

Section: Methodsmentioning

confidence: 99%

“…A large number of methods are available to carry out such secondary annotations and we have recently assessed their relative performance (Curtis, 2022). Since then a new method, AlphaMissense, has been released with the aim of recognising whether a nonsynonymous variant observed in a patient is or is not likely to be pathogenic (Cheng et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

Assessment of ability of AlphaMissense to identify variants affecting susceptibility to common disease

Curtis

2023

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An important issue pertinent to the analysis of sequence data to detect association between rare variants in a gene and a given phenotype is the ability to annotate nonsynonymous variants in terms of their likely importance as affecting protein function. While a number of software tools attempt to do this, AlphaMissense was recently released and was shown to have good performance using benchmarks based on variants causing severe disease and on functional assays. Here, we assess the performance of AlphaMissense across 18 genes which had previously demonstrated association between rare coding variants and hyperlipidaemia, hypertension or type 2 diabetes. Ability to detect association, expressed as the signed log p value (SLP) was compared between AlphaMissense and 43 other annotation methods. The results demonstrated marked variability between genes regarding the extent to which nonsynonymous variants contributed to evidence for association and also between the performance of different methods of annotating the nonsynonymous variants. Although AlphaMissense produced the highest SLP on average across genes, it produced the maximum SLP for only 4 genes. For some genes, other methods produced a considerably higher SLP and there were examples of genes where AlphaMissense produced no evidence for association while another method performed well. The marked inconsistency across genes means that it is difficult to decide on an optimal method of analysis of sequence data. The fact that different methods perform well for different genes suggests that if one wished to use sequence data for individual risk prediction then gene-specific annotation methods should be used. It would be desirable to have the ability to recognise characteristics of a gene which could facilitate the selection of an annotation method which would best discriminate variants of interest within that gene.This research has been conducted using the UK Biobank Resource.

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Exploration of weighting schemes based on allele frequency and annotation for weighted burden association analysis of complex phenotypes

Cited by 6 publications

References 26 publications

Weighted burden analysis of rare coding variants in 470,000 exome-sequenced UK Biobank subject characterises effects on hyperlipidaemia risk

Weighted burden analysis of rare coding variants in 470,000 exome-sequenced UK Biobank subject characterises effects on hyperlipidaemia risk

Weighted burden analysis in 200,000 exome-sequenced subjects characterises rare variant effects on BMI

Assessment of ability of AlphaMissense to identify variants affecting susceptibility to common disease

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