scholarly journals Quantification of genetic components of population differentiation in UK Biobank traits reveals signals of polygenic selection

2018 ◽  
Author(s):  
Xuanyao Liu ◽  
Po-Ru Loh ◽  
Luke J. O’Connor ◽  
Steven Gazal ◽  
Armin Schoech ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Population Differentiation ◽  
Uk Biobank ◽  
Red Hair ◽  
Genetic Components ◽  
Total Correlation ◽  
Genome Wide ◽  
Selection For ◽  
Polygenic Selection ◽  
East West

AbstractThe genetic architecture of most human complex traits is highly polygenic, motivating efforts to detect polygenic selection involving a large number of loci. In contrast to previous work relying on top GWAS loci, we developed a method that uses genome-wide association statistics and linkage disequilibrium patterns to estimate the genome-wide genetic component of population differentiation of a complex trait along a continuous gradient, enabling powerful inference of polygenic selection. We analyzed 43 UK Biobank traits and focused on PC1 and North-South and East-West birth coordinates across 337K unrelated British-ancestry samples, for which our method produced close to unbiased estimates of genetic components of population differentiation and high power to detect polygenic selection in simulations across different trait architectures. For PC1, we identified signals of polygenic selection for height (74.5±16.7% of 9.3% total correlation with PC1 attributable to genome-wide genetic effects; P = 8.4×10−6) and red hair pigmentation (95.9±24.7% of total correlation with PC1 attributable to genome-wide genetic effects; P = 1.1×10−4); the bulk of the signal remained when removing genome-wide significant loci, even though red hair pigmentation includes loci of large effect. We also detected polygenic selection for height, systolic blood pressure, BMI and basal metabolic rate along North-South birth coordinate, and height and systolic blood pressure along East-West birth coordinate. Our method detects polygenic selection in modern human populations with very subtle population structure and elucidates the relative contributions of genetic and non-genetic components of trait population differences.

scholarly journals Population structure of UK Biobank and ancient Eurasians reveals adaptation at genes influencing blood pressure

2016 ◽  
Author(s):  
Kevin J. Galinsky ◽  
Po-Ru Loh ◽  
Mallick Swapan ◽  
Nick J. Patterson ◽  
Alkes L. Price
Keyword(s):  
Blood Pressure ◽  
Population Structure ◽  
Population Differentiation ◽  
Large Sample Size ◽  
Uk Biobank ◽  
Genome Wide ◽  
Combining Evidence ◽  
A Genome ◽  
The Uk ◽  
Fine Resolution

AbstractAnalyzing genetic differences between closely related populations can be a powerful way to detect recent adaptation. The very large sample size of the UK Biobank is ideal for detecting selection using population differentiation, and enables an analysis of UK population structure at fine resolution. In analyses of 113,851 UK Biobank samples, population structure in the UK is dominated by 5 principal components (PCs) spanning 6 clusters: Northern Ireland, Scotland, northern England, southern England, and two Welsh clusters. Analyses with ancient Eurasians show that populations in the northern UK have higher levels of Steppe ancestry, and that UK population structure cannot be explained as a simple mixture of Celts and Saxons. A scan for unusual population differentiation along top PCs identified a genome-wide significant signal of selection at the coding variant rs601338 in FUT2 (p = 9.16 × 10−9). In addition, by combining evidence of unusual differentiation within the UK with evidence from ancient Eurasians, we identified new genome-wide significant (p < 5 × 10−8) signals of recent selection at two additional loci: CYP1A2/CSK and F12. We detected strong associations to diastolic blood pressure in the UK Biobank for the variants with new selection signals at CYP1A2/CSK (p = 1.10 × 10−19)) and for variants with ancient Eurasian selection signals in the ATXN2/SH2B3 locus (p = 8.00 × 10−33), implicating recent adaptation related to blood pressure.

scholarly journals The consequences of adjustment, correction and selection in genome-wide association studies used for two-sample Mendelian randomization

2020 ◽  
Author(s):  
Venexia M Walker ◽  
Sean Harrison ◽  
Alice R Carter ◽  
Dipender Gill ◽  
Ioanna Tzoulaki ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Systolic Blood Pressure ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Medication Use ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Empirical Estimates ◽  
Genome Wide

Introduction: Genome-wide association studies (GWASs) often adjust for covariates, correct for medication use, or select on medication users. If these summary statistics are used in two-sample Mendelian randomization analyses, estimates may be biased. We used simulations to investigate how GWAS adjustment, correction and selection affects these estimates and performed an analysis in UK Biobank to provide an empirical example. Methods: We simulated six GWASs: no adjustment for a covariate, correction for medication use, or selection on medication users; adjustment only; selection only; correction only; both adjustment and selection; and both adjustment and correction. We then ran two-sample Mendelian randomization analyses using these GWASs to evaluate bias. We also performed equivalent GWASs using empirical data from 318,147 participants in UK Biobank with systolic blood pressure as the exposure and body mass index as the covariate and ran two-sample Mendelian randomization with coronary heart disease as the outcome. Results: The simulation showed that estimates from GWASs with selection can produce biased two-sample Mendelian randomization estimates. Yet, we observed relatively little difference between empirical estimates of the effect of systolic blood pressure on coronary artery disease across the six scenarios. Conclusions: Given the potential for bias from using GWASs with selection on Mendelian randomization estimates demonstrated in our simulation, and the reduced sample size of these GWAS, this approach should be deprioritized. However, based on our empirical results, using adjusted, corrected or selected GWASs is unlikely to make a large difference to two-sample Mendelian randomization estimates in practice.

scholarly journals The consequences of adjustment, correction and selection in genome-wide association studies used for two-sample Mendelian randomization

2021 ◽  
Vol 6 ◽  
pp. 103
Author(s):  
Venexia Walker ◽  
Sean Harrison ◽  
Alice Carter ◽  
Dipender Gill ◽  
Ioanna Tzoulaki ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Systolic Blood Pressure ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Medication Use ◽  
Careful Consideration ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Genome Wide

Introduction: Genome-wide association studies (GWASs) often adjust for covariates, correct for medication use, or select on medication users. If these summary statistics are used in two-sample Mendelian randomization analyses, estimates may be biased. We used simulations to investigate how GWAS adjustment, correction and selection affects these estimates and performed an analysis in UK Biobank to provide an empirical example. Methods: We simulated six GWASs: no adjustment for a covariate, correction for medication use, or selection on medication users; adjustment only; selection only; correction only; both adjustment and selection; and both adjustment and correction. We then ran two-sample Mendelian randomization analyses using these GWASs to evaluate bias. We also performed equivalent GWASs using empirical data from 306,560 participants in UK Biobank with systolic blood pressure as the exposure and body mass index as the covariate and ran two-sample Mendelian randomization with coronary heart disease as the outcome. Results: The simulation showed that estimates from GWASs with selection can produce biased two-sample Mendelian randomization estimates. Yet, we observed relatively little difference between empirical estimates of the effect of systolic blood pressure on coronary artery disease across the six scenarios. Conclusions: Given the potential for bias from using GWASs with selection on Mendelian randomization estimates demonstrated in our simulation, careful consideration before using this approach is warranted. However, based on our empirical results, using adjusted, corrected or selected GWASs is unlikely to make a large difference to two-sample Mendelian randomization estimates in practice.

scholarly journals GWAS identifies 10 loci for objectively-measured physical activity and sleep with causal roles in cardiometabolic disease.

2018 ◽  
Author(s):  
Aiden Doherty ◽  
Karl Smith-Bryne ◽  
Teresa Ferreira ◽  
Michael V Holmes ◽  
Chris Holmes ◽  
...  
Keyword(s):  
Physical Activity ◽  
Blood Pressure ◽  
Genome Wide Association Study ◽  
Moderate Intensity ◽  
Uk Biobank ◽  
Fat Percentage ◽  
Genome Wide ◽  
A Genome ◽  
Pathway Analyses ◽  
Objectively Measured

Physical activity and sleep disorders are established risk factors for many diseases, but their etiology is poorly understood, partly due to a reliance on self-reported evidence. Here we report a genome-wide association study (GWAS) of wearable-defined and machine-learned physical activity and sleep phenotypes in 91,112 UK Biobank participants, and self-reported physical activity in 351,154 UK Biobank participants. While the self-reported activity analysis resulted in no significant (p<5x10-9) loci, the analysis of objectively-measured traits identified 10 loci, 6 of which are novel. These 10 loci account for 0.05% of activity and 0.33% of sleep phenotype variation, but genome-wide estimates suggest that common variation accounts for ~12% of phenotypic variation, indicating high polygenicity. Heritability was higher in women than in men for overall activity (Δh2 = 4%, p=6.3x10-5), moderate intensity activity (6%, p=6.7x10-8), and walking (5%, p=2.6x10-6). Heritability partitioning, enrichment and pathway analyses all indicate the central nervous system plays a role in activity behaviours. Mendelian randomization in publicly available GWAS data and in 278,367 UK Biobank participants, who were not included in our discovery analyses, suggest that overall activity might be causally related to lowering body fat percentage (beta per SD higher overall activity: -0.44, SE=0.047, p=2.70x10-21) and systolic blood pressure (beta per SD: -0.71, SE=0.125, p=1.38x10-8). Our current results advocate the value of physical activity for the reduction of adiposity and blood pressure.

scholarly journals O21: GENOME-WIDE ASSOCIATION STUDY OF VARICOSE VEINS IN 810,625 INDIVIDUALS IDENTIFIES 45 GENETIC RISK LOCI

2021 ◽  
Vol 108 (Supplement_1) ◽  
Author(s):  
WUR Ahmed ◽  
A Wiberg ◽  
M Ng ◽  
D Furniss
Keyword(s):  
Association Study ◽  
Genetic Architecture ◽  
Genome Wide Association Study ◽  
Varicose Veins ◽  
Phenotypic Expression ◽  
Cell Activity ◽  
Genome Wide Association ◽  
Uk Biobank ◽  
Genetic Components ◽  
Genome Wide

Abstract Introduction Varicose veins (VV) impact a third of the UK adult population; 10% of patients develop lipodermatosclerosis and ulceration. VV often requires surgical management, however, there is a high-risk of recurrence. VV is a complex disease, where genetic and non-genetic components contribute to overall phenotypic expression. The genetic architecture of VV is poorly understood; we aimed to uncover its genetic basis. Method We conducted hitherto the largest genome-wide association study of VV. In stage one, using UK Biobank, we compared 22,473 VV patients and 379,183 controls. In stage two, replication and meta-analysis were performed in an independent cohort of 113,041 VV cases and 295,928 controls from 23&Me (California, USA). In-silico analysis was conducted in FUMA, MAGMA, and XGR. Result 109 genome-wide significant (P≤ 5×10-8) loci were identified in UK Biobank, 45 of which successfully replicated in the 23&Me cohort. Twenty-seven loci have not been previously reported. FUMA positionally-mapped 128 genes at the replicated loci, with 84 having a combined annotation-dependent depletion score (CADD) &gt;12.37, suggesting functional, deleterious variants. MAGMA analysis implicated pathways involved in cardiovascular system development (P=1.57×10-08) and tube morphogenesis (P=9.35×10-08). Furthermore, XGR revealed enriched pathways in downstream signalling in naive CD8+ T cells (P=0.0017), and encoding structural and core extracellular glycoproteins (both P=0.007). Conclusion We identified 45 variants conferring risk of VV, which provide insights into disease biology. Implicated genes are enriched in pathways involved in vascular development, immune cell activity and extracellular matrix function, and provide new targets for therapeutic development. Take-home message Unravelling the genetic architecture of varicose veins may facilitate our understanding of the disease and guide therapeutic approaches.

scholarly journals Analysing electrocardiographic traits and predicting cardiac risk in UK biobank

2021 ◽  
Vol 10 ◽  
pp. 204800402110236
Author(s):  
Julia Ramírez ◽  
Stefan van Duijvenboden ◽  
William J Young ◽  
Michele Orini ◽  
Aled R Jones ◽  
...  
Keyword(s):  
Genetic Information ◽  
Association Studies ◽  
Cardiac Risk ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Biological Mechanisms ◽  
Clinical Tool ◽  
Genome Wide ◽  
Response To Exercise ◽  
Electrocardiogram Ecg

The electrocardiogram (ECG) is a commonly used clinical tool that reflects cardiac excitability and disease. Many parameters are can be measured and with the improvement of methodology can now be quantified in an automated fashion, with accuracy and at scale. Furthermore, these measurements can be heritable and thus genome wide association studies inform the underpinning biological mechanisms. In this review we describe how we have used the resources in UK Biobank to undertake such work. In particular, we focus on a substudy uniquely describing the response to exercise performed at scale with accompanying genetic information.

scholarly journals Variation in VKORC1 Is Associated with Vascular Dementia

2021 ◽  
Vol 80 (3) ◽  
pp. 1329-1337
Author(s):  
Jure Mur ◽  
Daniel L. McCartney ◽  
Daniel I. Chasman ◽  
Peter M. Visscher ◽  
Graciela Muniz-Terrera ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Vascular Dementia ◽  
Genetic Variant ◽  
Warfarin Dose ◽  
Uk Biobank ◽  
Parental History ◽  
Genome Wide ◽  
History Of ◽  
First Time ◽  
The Relationship

Background: The genetic variant rs9923231 (VKORC1) is associated with differences in the coagulation of blood and consequentially with sensitivity to the drug warfarin. Variation in VKORC1 has been linked in a gene-based test to dementia/Alzheimer’s disease in the parents of participants, with suggestive evidence for an association for rs9923231 (p = 1.8×10–7), which was included in the genome-wide significant KAT8 locus. Objective: Our study aimed to investigate whether the relationship between rs9923231 and dementia persists only for certain dementia sub-types, and if those taking warfarin are at greater risk. Methods: We used logistic regression and data from 238,195 participants from UK Biobank to examine the relationship between VKORC1, risk of dementia, and the interplay with warfarin use. Results: Parental history of dementia, APOE variant, atrial fibrillation, diabetes, hypertension, and hypercholesterolemia all had strong associations with vascular dementia (p < 4.6×10–6). The T-allele in rs9923231 was linked to a lower warfarin dose (βperT - allele = –0.29, p < 2×10–16) and risk of vascular dementia (OR = 1.17, p = 0.010), but not other dementia sub-types. However, the risk of vascular dementia was not affected by warfarin use in carriers of the T-allele. Conclusion: Our study reports for the first time an association between rs9923231 and vascular dementia, but further research is warranted to explore potential mechanisms and specify the relationship between rs9923231 and features of vascular dementia.

scholarly journals SELECTION FOR BLOOD PRESSURE LEVELS IN MICE

Genetics ◽  
1974 ◽  
Vol 76 (3) ◽  
pp. 537-549
Author(s):  
Gunther Schlager
Keyword(s):  
Blood Pressure ◽  
Systolic Blood Pressure ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Population Bottleneck ◽  
Control Line ◽  
Selected Lines ◽  
High Line ◽  
Selection For ◽  
Random Control

ABSTRACT Response to two-way selection for systolic blood pressure was immediate and continuous for about eight generations. In the twelfth generation, the High males differed from the Low males by 38 mmHG; the females differed by 39 mmHg. There was little overlap between the two lines and they were statistically significant from each other and from the Random control line. There appeared to be no more additive genetic variance in the eleventh and twelfth generations. Causes for the cessation of response are explored. This is probably due to a combination of natural selection acting to reduce litter sizes in the Low line, a higher incidence of sudden deaths in the High line, and loss of favorable alleles as both selection lines went through a population bottleneck in the ninth generation.—In the eleventh generation, the selected lines were used to produce F1, F2, and backcross generations. A genetic analysis yielded significant additive and dominance components in the inheritance of systolic blood pressure.

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