scholarly journals Analysis of exome-sequenced UK Biobank subjects implicates genes affecting risk of hyperlipidaemia

2020 ◽  
Author(s):  
David Curtis
Keyword(s):  
Rare Variants ◽  
Sequence Data ◽  
Lipid Lowering ◽  
P Value ◽  
Data Sets ◽  
Uk Biobank ◽  
Functional Studies ◽  
Exome Sequence Data ◽  
Rare Genetic Variants ◽  
The Uk

Rare genetic variants in LDLR, APOB and PCSK9 are known causes of familial hypercholesterolaemia and it is expected that rare variants in other genes will also have effects on hyperlipidaemia risk although such genes remain to be identified. The UK Biobank consists of a sample of 500,000 volunteers and exome sequence data is available for 50,000 of them. 11,490 of these were classified as hyperlipidaemia cases on the basis of having a relevant diagnosis recorded and/or taking lipid-lowering medication while the remaining 38,463 were treated as controls. Variants in each gene were assigned weights according to rarity and predicted impact and overall weighted burden scores were compared between cases and controls, including population principal components as covariates. One biologically plausible gene, HUWE1, produced statistically significant evidence for association after correction for testing 22,028 genes with a signed log10 p value (SLP) of -6.15, suggesting a protective effect of variants in this gene. Other genes with uncorrected p<0.001 are arguably also of interest, including LDLR (SLP=3.67), RBP2 (SLP=3.14), NPFFR1 (SLP=3.02) and ACOT9 (SLP=-3.19). Gene set analysis indicated that rare variants in genes involved in metabolism and energy can influence hyperlipidaemia risk. Overall, the results provide some leads which might be followed up with functional studies and which could be tested in additional data sets as these become available. This research has been conducted using the UK Biobank Resource.

scholarly journals Weighted burden analysis in 200 000 exome-sequenced UK Biobank subjects characterises effects of rare genetic variants on BMI

2021 ◽  
Author(s):  
David Curtis
Keyword(s):  
Multiple Testing ◽  
Rare Variants ◽  
Sequence Data ◽  
Statistical Significance ◽  
Positive Sign ◽  
P Value ◽  
Uk Biobank ◽  
Functional Variants ◽  
Rare Genetic Variants ◽  
The Uk

AbstractIntroductionA 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.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.

scholarly journals Variants in ACE2 and TMPRSS2 genes are not major determinants of COVID-19 severity in UK Biobank subjects

2020 ◽  
Author(s):  
David Curtis
Keyword(s):  
Rare Variants ◽  
Sequence Data ◽  
Severe Disease ◽  
Major Effect ◽  
Uk Biobank ◽  
Exome Sequence Data ◽  
Dna Sequence Variants ◽  
The Uk ◽  
And Function ◽  
Exome Sequence

AbstractIt is plausible that variants in the ACE2 and TMPRSS2 genes might contribute to variation in COVID-19 severity and that these could explain why some people become very unwell whereas most do not. Exome sequence data was obtained for 49,953 UK Biobank subjects of whom 74 had tested positive for SARS-CoV-2 and could be presumed to have severe disease. A weighted burden analysis was carried out using SCOREASSOC to determine whether there were differences between these cases and the other sequenced subjects in the overall burden of rare, damaging variants in ACE2 or TMPRSS2. There were no statistically significant differences in weighted burden scores between cases and controls for either gene. There were no individual DNA sequence variants with a markedly different frequency between cases and controls. Whether there are small effects on severity, or whether there might be rare variants with major effect sizes, would require studies in much larger samples. Genetic variants affecting the structure and function of the ACE2 and TMPRSS2 proteins are not a major determinant of whether infection with SARS-CoV-2 results in severe symptoms. This research has been conducted using the UK Biobank Resource.

scholarly journals Variants in ACE2 and TMPRSS2 Genes Are Not Major Determinants of COVID-19 Severity in UK Biobank Subjects

2021 ◽  
pp. 1-3
Author(s):  
David Curtis
Keyword(s):  
Rare Variants ◽  
Sequence Data ◽  
Severe Disease ◽  
Major Effect ◽  
Uk Biobank ◽  
Exome Sequence Data ◽  
Dna Sequence Variants ◽  
The Uk ◽  
And Function ◽  
Exome Sequence

It is plausible that variants in the ACE2 and TMPRSS2 genes might contribute to variation in COVID-19 severity and that these could explain why some people become very unwell whereas most do not. Exome sequence data was obtained for 49,953 UK Biobank subjects, of whom 82 had tested positive for SARS-CoV-2 and could be presumed to have severe disease. A weighted burden analysis was carried out using SCOREASSOC to determine whether there were differences between these cases and the other sequenced subjects in the overall burden of rare, damaging variants in ACE2 or TMPRSS2. There were no statistically significant differences in weighted burden scores between cases and controls for either gene. There were no individual DNA sequence variants with a markedly different frequency between cases and controls. Whether there are small effects on severity, or whether there might be rare variants with major effect sizes, would require studies in much larger samples. Genetic variants affecting the structure and function of the ACE2 and TMPRSS2 proteins are not the main explanation for why some people develop severe symptoms in response to infection with SARS-CoV-2. This research was conducted using the UK Biobank Resource.

scholarly journals Analysis of 200 000 exome-sequenced UK Biobank subjects illustrates the contribution of rare genetic variants to hyperlipidaemia

2021 ◽  
pp. jmedgenet-2021-107752
Author(s):  
David Curtis
Keyword(s):  
X Chromosome ◽  
Principal Components ◽  
Rare Variants ◽  
P Value ◽  
Uk Biobank ◽  
Lipid Levels ◽  
Large Samples ◽  
Rare Genetic Variants ◽  
The Uk ◽  
Strength Of Association

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.

scholarly journals Investigation of association of rare, functional genetic variants with heavy drinking and problem drinking in exome sequenced UK Biobank participants

2021 ◽  
Author(s):  
David Curtis
Keyword(s):  
Genetic Variants ◽  
Multiple Testing ◽  
Sequence Data ◽  
Problem Drinking ◽  
Heavy Drinking ◽  
Uk Biobank ◽  
Exome Sequence Data ◽  
The Uk ◽  
Or Genes ◽  
Mental Health Questionnaire

AbstractAimsThe study aimed to identify specific genes and functional genetic variants affecting susceptibility to two alcohol related phenotypes: heavy drinking and problem drinking.MethodsPhenotypic and exome sequence data was downloaded from the UK Biobank. Reported drinks in the last 24 hours was 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.ResultsOf exome sequenced subjects, for heavy drinking there were 8,166 cases and 84,461 controls while for problem drinking there were 7,811 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.ConclusionsThis 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 becomes 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.Short summaryTests for association of rare, functional genetic variants with heavy drinking and problem drinking confirm the known effects of variants in ADH1B and ALDH2 but fail to implicate novel variants or genes. Results for three genes potentially related to autism suggest they might exert a protective effect.

scholarly journals Analysis of 50,000 exome-sequenced UK Biobank subjects fails to identify genes influencing probability of psychiatric referral

2020 ◽  
Author(s):  
David Curtis
Keyword(s):  
Multiple Testing ◽  
Rare Variants ◽  
Sequence Data ◽  
Statistical Significance ◽  
Major Effect ◽  
Self Report ◽  
Uk Biobank ◽  
Functional Variants ◽  
Exome Sequence Data ◽  
Exome Sequence

Background Depression is moderately heritable but there is no common genetic variant which has a major effect on susceptibility. It is possible that some very rare variants could have substantial effect sizes and these could be identified from exome sequence data. Methods Data from 50,000 exome-sequenced UK Biobank participants was analysed. Subjects were treated as cases if they had reported having seen a psychiatrist for "nerves, anxiety, tension or depression". Gene-wise weighted burden analysis was performed to see if there were any genes or sets of genes for which there was an excess of rare, functional variants in cases. Results There were 5,872 cases and 43,862 controls. There were 22,028 informative genes but none produced a statistically significant result after correction for multiple testing. Of the 25 genes individually significant at p<0.001 none appeared to be a biologically plausible candidate. No set of genes achieved statistical significance after correction for multiple testing and those with the lowest p values again did not appear to be biologically plausible candidates. Limitations The phenotype is based on self-report and the cases are likely to somewhat heterogeneous. The number of cases is on the low side for a study of exome sequence data. Conclusions The results conform exactly with the expectation under the null hypothesis. It seems unlikely that depression genetics research will produce findings that might have a substantial clinical impact until far larger samples become available.

scholarly journals Analysis of 200,000 exome-sequenced UK Biobank subjects illustrates the contribution of rare genetic variants to hyperlipidaemia

2021 ◽  
Author(s):  
David Curtis
Keyword(s):  
X Chromosome ◽  
Principal Components ◽  
Rare Variants ◽  
P Value ◽  
Uk Biobank ◽  
Loss Of Function ◽  
Lipid Levels ◽  
Large Samples ◽  
Rare Genetic Variants ◽  
Strength Of Association

AbstractA few genes have previously been identified in which very rare variants can have major effects on lipid levels. Weighted burden analysis of rare variants was applied to 200,000 exome sequenced UK Biobank subjects with hyperlipidaemia as the phenotype, with the strength of association characterised by the signed log 10 p value (SLP). 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 males than females. 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. Category-specific analyses of variants in these two genes revealed that, while there were loss of function variants with major effects, there were much larger numbers of protein-altering variants which had moderate effects on risk of hyperlipidaemia. Variants classified by SIFT as deleterious have on average a two-fold effect and their cumulative frequency is such that they are present in approximately 1.5% of the population. There was no evidence for association of HUWE1, which had produced statistically significant results in an earlier analysis of a subset of 50,000 exomes, and with hindsight this result had been caused by the excess of X gene variants in females. 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.

scholarly journals Predicting the effect of statins on cancer risk using genetic variants from a Mendelian randomization study in the UK Biobank

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Paul Carter ◽  
Mathew Vithayathil ◽  
Siddhartha Kar ◽  
Rahul Potluri ◽  
Amy M Mason ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Cancer Risk ◽  
Genetic Variants ◽  
Ldl Cholesterol ◽  
Human Genetics ◽  
Density Lipoprotein ◽  
Lipid Lowering ◽  
Uk Biobank ◽  
Standard Deviation Increase ◽  
The Uk

Laboratory studies have suggested oncogenic roles of lipids, as well as anticarcinogenic effects of statins. Here we assess the potential effect of statin therapy on cancer risk using evidence from human genetics. We obtained associations of lipid-related genetic variants with the risk of overall and 22 site-specific cancers for 367,703 individuals in the UK Biobank. In total, 75,037 individuals had a cancer event. Variants in the HMGCR gene region, which represent proxies for statin treatment, were associated with overall cancer risk (odds ratio [OR] per one standard deviation decrease in low-density lipoprotein [LDL] cholesterol 0.76, 95% confidence interval [CI] 0.65–0.88, p=0.0003) but variants in gene regions representing alternative lipid-lowering treatment targets (PCSK9, LDLR, NPC1L1, APOC3, LPL) were not. Genetically predicted LDL-cholesterol was not associated with overall cancer risk (OR per standard deviation increase 1.01, 95% CI 0.98–1.05, p=0.50). Our results predict that statins reduce cancer risk but other lipid-lowering treatments do not. This suggests that statins reduce cancer risk through a cholesterol independent pathway.

scholarly journals Assessing the contribution of rare-to-common protein-coding variants to circulating metabolic biomarker levels via 412,394 UK Biobank exome sequences

2021 ◽  
Author(s):  
Abhishek Nag ◽  
Lawrence Middleton ◽  
Ryan S Dhindsa ◽  
Dimitrios Vitsios ◽  
Eleanor M Wigmore ◽  
...  
Keyword(s):  
Gene Networks ◽  
Rare Variants ◽  
Association Studies ◽  
Low Frequency ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Protein Coding ◽  
The Uk ◽  
Metabolic Biomarkers ◽  
Coding Variants

Genome-wide association studies have established the contribution of common and low frequency variants to metabolic biomarkers in the UK Biobank (UKB); however, the role of rare variants remains to be assessed systematically. We evaluated rare coding variants for 198 metabolic biomarkers, including metabolites assayed by Nightingale Health, using exome sequencing in participants from four genetically diverse ancestries in the UKB (N=412,394). Gene-level collapsing analysis, that evaluated a range of genetic architectures, identified a total of 1,303 significant relationships between genes and metabolic biomarkers (p<1x10-8), encompassing 207 distinct genes. These include associations between rare non-synonymous variants in GIGYF1 and glucose and lipid biomarkers, SYT7 and creatinine, and others, which may provide insights into novel disease biology. Comparing to a previous microarray-based genotyping study in the same cohort, we observed that 40% of gene-biomarker relationships identified in the collapsing analysis were novel. Finally, we applied Gene-SCOUT, a novel tool that utilises the gene-biomarker association statistics from the collapsing analysis to identify genes having similar biomarker fingerprints and thus expand our understanding of gene networks.

scholarly journals Reproducibility in the UK Biobank of Genome-Wide Significant Signals Discovered in Earlier Genome-wide Association Studies

2020 ◽  
Author(s):  
Jack W. O’Sullivan ◽  
John P. A. Ioannidis
Keyword(s):  
Effect Size ◽  
Association Studies ◽  
Genome Wide Association ◽  
P Value ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Single Nucleotide ◽  
Genome Wide ◽  
The Uk ◽  
Open Question

AbstractWith the establishment of large biobanks, discovery of single nucleotide polymorphism (SNPs) that are associated with various phenotypes has been accelerated. An open question is whether SNPs identified with genome-wide significance in earlier genome-wide association studies (GWAS) are replicated also in later GWAS conducted in biobanks. To address this question, the authors examined a publicly available GWAS database and identified two, independent GWAS on the same phenotype (an earlier, “discovery” GWAS and a later, replication GWAS done in the UK biobank). The analysis evaluated 136,318,924 SNPs (of which 6,289 had reached p<5e-8 in the discovery GWAS) from 4,397,962 participants across nine phenotypes. The overall replication rate was 85.0% and it was lower for binary than for quantitative phenotypes (58.1% versus 94.8% respectively). There was a18.0% decrease in SNP effect size for binary phenotypes, but a 12.0% increase for quantitative phenotypes. Using the discovery SNP effect size, phenotype trait (binary or quantitative), and discovery p-value, we built and validated a model that predicted SNP replication with area under the Receiver Operator Curve = 0.90. While non-replication may often reflect lack of power rather than genuine false-positive findings, these results provide insights about which discovered associations are likely to be seen again across subsequent GWAS.

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