scholarly journals Genome-wide association analysis of 350,000 Caucasians from the UK Biobank identifies novel loci for asthma, hay fever and eczema

2017 ◽  
Author(s):  
Åsa Johansson ◽  
Mathias Rask-Andersen ◽  
Torgny Karlsson ◽  
Weronica E. Ek

AbstractEven though heritability estimates suggest that the risk of asthma, hay fever and eczema is largely due to genetic factors, previous studies have not explained a large part of the genetics behind these diseases. In this GWA study, we include 346,545 Caucasians from the UK Biobank to identify novel loci for asthma, hay fever and eczema. We further investigate if associated lead SNPs have a significantly larger effect for one disease compared to the other diseases, to highlight possible disease specific effects.We identified 141 loci, of which 41 are novel, to be associated (P≤3×10−8) with asthma, hay fever or eczema, analysed separately or as disease phenotypes that includes the presence of different combinations of these diseases. The largest number of loci were associated with the combined phenotype (asthma/hay fever/eczema). However, as many as 20 loci had a significantly larger effect on hay fever/eczema-only compared to their effects on asthma, while 26 loci exhibited larger effects on asthma compared with their effects on hay fever/eczema. At four of the novel loci, TNFRSF8, MYRF, TSPAN8, and BHMG1, the lead SNPs were in LD (> 0.8) with potentially casual missense variants.Our study shows that a large amount of the genetic contribution is shared between the diseases. Nonetheless, a number of SNPs have a significantly larger effect on one of the phenotypes suggesting that part of the genetic contribution is more phenotype specific. Identified loci and probable causal genes may in the future be used as targets for treatments of asthma, hay fever and eczema.

2019 ◽  
Vol 28 (23) ◽  
pp. 4022-4041 ◽  
Author(s):  
Åsa Johansson ◽  
Mathias Rask-Andersen ◽  
Torgny Karlsson ◽  
Weronica E Ek

Abstract Even though heritability estimates suggest that the risk of asthma, hay fever and eczema is largely due to genetic factors, previous studies have not explained a large part of the genetics behind these diseases. In this genome-wide association study, we include 346 545 Caucasians from the UK Biobank to identify novel loci for asthma, hay fever and eczema and replicate novel loci in three independent cohorts. We further investigate if associated lead single nucleotide polymorphisms (SNPs) have a significantly larger effect for one disease compared to the other diseases, to highlight possible disease-specific effects. We identified 141 loci, of which 41 are novel, to be associated (P ≤ 3 × 10−8) with asthma, hay fever or eczema, analyzed separately or as disease phenotypes that includes the presence of different combinations of these diseases. The largest number of loci was associated with the combined phenotype (asthma/hay fever/eczema). However, as many as 20 loci had a significantly larger effect on hay fever/eczema only compared to their effects on asthma, while 26 loci exhibited larger effects on asthma compared with their effects on hay fever/eczema. At four of the novel loci, TNFRSF8, MYRF, TSPAN8, and BHMG1, the lead SNPs were in Linkage Disequilibrium (LD) (>0.8) with potentially casual missense variants. Our study shows that a large amount of the genetic contribution is shared between the diseases. Nonetheless, a number of SNPs have a significantly larger effect on one of the phenotypes, suggesting that part of the genetic contribution is more phenotype specific.


2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Jianchang Hu ◽  
Cai Li ◽  
Shiying Wang ◽  
Ting Li ◽  
Heping Zhang

Abstract Background The severity of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is highly heterogeneous. Studies have reported that males and some ethnic groups are at increased risk of death from COVID-19, which implies that individual risk of death might be influenced by host genetic factors. Methods In this project, we consider the mortality as the trait of interest and perform a genome-wide association study (GWAS) of data for 1778 infected cases (445 deaths, 25.03%) distributed by the UK Biobank. Traditional GWAS fails to identify any genome-wide significant genetic variants from this dataset. To enhance the power of GWAS and account for possible multi-loci interactions, we adopt the concept of super variant for the detection of genetic factors. A discovery-validation procedure is used for verifying the potential associations. Results We find 8 super variants that are consistently identified across multiple replications as susceptibility loci for COVID-19 mortality. The identified risk factors on chromosomes 2, 6, 7, 8, 10, 16, and 17 contain genetic variants and genes related to cilia dysfunctions (DNAH7 and CLUAP1), cardiovascular diseases (DES and SPEG), thromboembolic disease (STXBP5), mitochondrial dysfunctions (TOMM7), and innate immune system (WSB1). It is noteworthy that DNAH7 has been reported recently as the most downregulated gene after infecting human bronchial epithelial cells with SARS-CoV-2. Conclusions Eight genetic variants are identified to significantly increase the risk of COVID-19 mortality among the patients with white British ancestry. These findings may provide timely clues and potential directions for better understanding the molecular pathogenesis of COVID-19 and the genetic basis of heterogeneous susceptibility, with potential impact on new therapeutic options.


2021 ◽  
Author(s):  
Duncan S Palmer ◽  
Wei Zhou ◽  
Liam Abbott ◽  
Nik Baya ◽  
Claire Churchhouse ◽  
...  

In classical statistical genetic theory, a dominance effect is defined as the deviation from a purely additive genetic effect for a biallelic variant. Dominance effects are well documented in model organisms. However, evidence in humans is limited to a handful of traits, particularly those with strong single locus effects such as hair color. We carried out the largest systematic evaluation of dominance effects on phenotypic variance in the UK Biobank. We curated and tested over 1,000 phenotypes for dominance effects through GWAS scans, identifying 175 loci at genome-wide significance correcting for multiple testing (P < 4.7 × 10-11). Power to detect non-additive loci is much lower than power to detect additive effects for complex traits: based on the relative effect sizes at genome-wide significant additive loci, we estimate a factor of 20-30 increase in sample size will be necessary to capture clear evidence of dominance similar to those currently observed for additive effects. However, these localised dominance hits do not extend to a significant aggregate contribution to phenotypic variance genome-wide. By deriving a version of LD-score regression to detect dominance effects tagged by common variation genome-wide (minor allele frequency > 0.05), we found no strong evidence of a contribution to phenotypic variance when accounting for multiple testing. Across the 267 continuous and 793 binary traits the median contribution was 5.73 × 10-4, with unbiased point estimates ranging from -0.261 to 0.131. Finally, we introduce dominance fine-mapping to explore whether the more rapid decay of dominance LD can be leveraged to find causal variants. These results provide the most comprehensive assessment of dominance trait variation in humans to date.


Author(s):  
Jack W. O’Sullivan ◽  
John P. A. Ioannidis

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.


Author(s):  
Mengyao Yu ◽  
Sergiy Kyryachenko ◽  
Stephanie Debette ◽  
Philippe Amouyel ◽  
Jean-Jacques Schott ◽  
...  

Background: Mitral valve prolapse (MVP) is a common cardiac valve disease, which affects 1 in 40 in the general population. Previous genome-wide association study have identified 6 risk loci for MVP. But these loci explained only partially the genetic risk for MVP. We aim to identify additional risk loci for MVP by adding data set from the UK Biobank. Methods: We reanalyzed 1007/479 cases from the MVP-France study, 1469/862 controls from the MVP-Nantes study for reimputation genotypes using HRC and TOPMed panels. We also incorporated 434 MVP cases and 4527 controls from the UK Biobank for discovery analyses. Genetic association was conducted using SNPTEST and meta-analyses using METAL. We used FUMA for post-genome-wide association study annotations and MAGMA for gene-based and gene-set analyses. Results: We found TOPMed imputation to perform better in terms of accuracy in the lower ranges of minor allele frequency below 0.1. Our updated meta-analysis included UK Biobank study for ≈8 million common single-nucleotide polymorphisms (minor allele frequency >0.01) and replicated the association on Chr2 as the top association signal near TNS1 . We identified an additional risk locus on Chr1 ( SYT2 ) and 2 suggestive risk loci on chr8 ( MSRA ) and chr19 ( FBXO46 ), all driven by common variants. Gene-based association using MAGMA revealed 6 risk genes for MVP with pronounced expression levels in cardiovascular tissues, especially the heart and globally part of enriched GO terms related to cardiac development. Conclusions: We report an updated meta-analysis genome-wide association study for MVP using dense imputation coverage and an improved case-control sample. We describe several loci and genes with MVP spanning biological mechanisms highly relevant to MVP, especially during valve and heart development.


2020 ◽  
Author(s):  
Ada Admin ◽  
Yann C. Klimentidis ◽  
Amit Arora ◽  
Michelle Newell ◽  
Jin Zhou ◽  
...  

Although hyperlipidemia is traditionally considered a risk factor for type-2 diabetes (T2D), evidence has emerged from statin trials and candidate gene investigations suggesting that lower LDL-C increases T2D risk. We thus sought to more comprehensively examine the phenotypic and genotypic relationships of LDL-C with T2D. Using data from the UK Biobank, we found that levels of circulating LDL-C were negatively associated with T2D prevalence (OR=0.41[0.39, 0.43] per mmol/L unit of LDL-C), despite positive associations of circulating LDL-C with HbA1c and BMI. We then performed the first genome-wide exploration of variants simultaneously associated with lower circulating LDL-C and increased T2D risk, using data on LDL-C from the UK Biobank (n=431,167) and the GLGC consortium (n=188,577), and T2D from the DIAGRAM consortium (n=898,130). We identified 31 loci associated with lower circulating LDL-C and increased T2D, capturing several potential mechanisms. Seven of these loci have previously been identified for this dual phenotype, and 9 have previously been implicated in non-alcoholic fatty liver disease. These findings extend our current understanding of the higher T2D risk among individuals with low circulating LDL-C, and of the underlying mechanisms, including those responsible for the diabetogenic effect of LDL-C-lowering medications.


2020 ◽  
Author(s):  
Dan Ju ◽  
Iain Mathieson

AbstractSkin pigmentation is a classic example of a polygenic trait that has experienced directional selection in humans. Genome-wide association studies have identified well over a hundred pigmentation-associated loci, and genomic scans in present-day and ancient populations have identified selective sweeps for a small number of light pigmentation-associated alleles in Europeans. It is unclear whether selection has operated on all the genetic variation associated with skin pigmentation as opposed to just a small number of large-effect variants. Here, we address this question using ancient DNA from 1158 individuals from West Eurasia covering a period of 40,000 years combined with genome-wide association summary statistics from the UK Biobank. We find a robust signal of directional selection in ancient West Eurasians on skin pigmentation variants ascertained in the UK Biobank, but find this signal is driven mostly by a limited number of large-effect variants. Consistent with this observation, we find that a polygenic selection test in present-day populations fails to detect selection with the full set of variants; rather, only the top five show strong evidence of selection. Our data allow us to disentangle the effects of admixture and selection. Most notably, a large-effect variant at SLC24A5 was introduced to Europe by migrations of Neolithic farming populations but continued to be under selection post-admixture. This study shows that the response to selection for light skin pigmentation in West Eurasia was driven by a relatively small proportion of the variants that are associated with present-day phenotypic variation.SignificanceSome of the genes responsible for the evolution of light skin pigmentation in Europeans show signals of positive selection in present-day populations. Recently, genome-wide association studies have highlighted the highly polygenic nature of skin pigmentation. It is unclear whether selection has operated on all of these genetic variants or just a subset. By studying variation in over a thousand ancient genomes from West Eurasia covering 40,000 years we are able to study both the aggregate behavior of pigmentation-associated variants and the evolutionary history of individual variants. We find that the evolution of light skin pigmentation in Europeans was driven by frequency changes in a relatively small fraction of the genetic variants that are associated with variation in the trait today.


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