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 Effects of blood lead on coronary artery disease and its risk factors: a Mendelian Randomization study

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
C. Mary Schooling ◽  
Glen D. Johnson ◽  
Jean Grassman
Keyword(s):  
Blood Pressure ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Mendelian Randomization ◽  
Blood Lead ◽  
Uk Biobank ◽  
1000 Genomes ◽  
A Genome ◽  
Artery Disease ◽  
The Uk

Abstract Lead is pervasive, although lead exposure has fallen in response to public health efforts. Observationally, lead is positively associated with cardiovascular disease and hypertension. We used separate-sample instrumental variable analysis with genetic instruments (Mendelian randomization) based on 13 single nucleotide polymorphisms (SNP), from a genome wide association study, strongly (p-value < 5 × 10−6) and independently associated with blood lead. These SNPs were applied to a large extensively genotyped coronary artery disease (CAD) study (cases = <76014, controls = <264785) largely based on CARDIoGRAPMplusC4D 1000 Genomes and the UK Biobank SOFT CAD, to the UK Biobank (n = 361,194) for blood pressure and to the DIAGRAM 1000 genomes diabetes case (n = 26,676)-control (n = 132,532) study. SNP-specific Wald estimates were combined using inverse variance weighting, MR-Egger and MR-PRESSO. Genetically instrumented blood lead was not associated with CAD (odds ratio (OR) 1.01 per effect size of log transformed blood lead, 95% confidence interval (CI) 0.97, 1.05), blood pressure (systolic −0.18 mmHg, 95% CI −0.44 to 0.08 and diastolic −0.03 mmHg, 95% CI −0.09 to 0.15) or diabetes (OR 0.98, 95% CI 0.92 to 1.03) using MR-PRESSO estimates corrected for an outlier SNP (rs550057) from the highly pleiotropic gene ABO. Exogenous lead may have different effects from endogenous lead; nevertheless, this study raises questions about the role of blood lead in CAD.

scholarly journals A novel variant in GLIS3 is associated with osteoarthritis

2018 ◽  
Vol 77 (4) ◽  
pp. 620-623 ◽  
Author(s):  
Elisabetta Casalone ◽  
Ioanna Tachmazidou ◽  
Eleni Zengini ◽  
Konstantinos Hatzikotoulas ◽  
Sophie Hackinger ◽  
...  
Keyword(s):  
Complex Disease ◽  
Genome Wide Association Study ◽  
Total Joint Replacement ◽  
Population Based ◽  
Uk Biobank ◽  
Proteomics Data ◽  
Glucose Levels ◽  
Genome Wide ◽  
A Genome ◽  
The Uk

ObjectivesOsteoarthritis (OA) is a complex disease, but its genetic aetiology remains poorly characterised. To identify novel susceptibility loci for OA, we carried out a genome-wide association study (GWAS) in individuals from the largest UK-based OA collections to date.MethodsWe carried out a discovery GWAS in 5414 OA individuals with knee and/or hip total joint replacement (TJR) and 9939 population-based controls. We followed-up prioritised variants in OA subjects from the interim release of the UK Biobank resource (up to 12 658 cases and 50 898 controls) and our lead finding in operated OA subjects from the full release of UK Biobank (17 894 cases and 89 470 controls). We investigated its functional implications in methylation, gene expression and proteomics data in primary chondrocytes from 12 pairs of intact and degraded cartilage samples from patients undergoing TJR.ResultsWe detect a genome-wide significant association at rs10116772 with TJR (P=3.7×10−8; for allele A: OR (95% CI) 0.97 (0.96 to 0.98)), an intronic variant in GLIS3, which is expressed in cartilage. Variants in strong correlation with rs10116772 have been associated with elevated plasma glucose levels and diabetes.ConclusionsWe identify a novel susceptibility locus for OA that has been previously implicated in diabetes and glycaemic traits.

scholarly journals A genome-wide association study finds genetic variants associated with neck or shoulder pain in UK Biobank

2020 ◽  
Vol 29 (8) ◽  
pp. 1396-1404 ◽  
Author(s):  
Weihua Meng ◽  
Brian W Chan ◽  
Cameron Harris ◽  
Maxim B Freidin ◽  
Harry L Hebert ◽  
...  
Keyword(s):  
Association Study ◽  
Shoulder Pain ◽  
Genetic Variants ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Uk Biobank ◽  
Genome Wide ◽  
A Genome ◽  
Significant Locus ◽  
The Uk

Abstract Background Common types of musculoskeletal conditions include pain in the neck and shoulder areas. This study seeks to identify the genetic variants associated with neck or shoulder pain based on a genome-wide association approach using 203 309 subjects from the UK Biobank cohort and look for replication evidence from the Generation Scotland: Scottish Family Health Study (GS:SFHS) and TwinsUK. Methods A genome-wide association study was performed adjusting for age, sex, BMI and nine population principal components. Significant and independent genetic variants were then sent to GS:SFHS and TwinsUK for replication. Results We identified three genetic loci that were associated with neck or shoulder pain in the UK Biobank samples. The most significant locus was in an intergenic region in chromosome 17, rs12453010, having P = 1.66 × 10−11. The second most significant locus was located in the FOXP2 gene in chromosome 7 with P = 2.38 × 10−10 for rs34291892. The third locus was located in the LINC01572 gene in chromosome 16 with P = 4.50 × 10−8 for rs62053992. In the replication stage, among four significant and independent genetic variants, rs2049604 in the FOXP2 gene and rs62053992 in the LINC01572 gene were weakly replicated in GS:SFHS (P = 0.0240 and P = 0.0202, respectively). Conclusions We have identified three loci associated with neck or shoulder pain in the UK Biobank cohort, two of which were weakly supported in a replication cohort. Further evidence is needed to confirm their roles in neck or shoulder pain.

scholarly journals Fine-scale population structure in the UK Biobank: implications for genome-wide association studies

2020 ◽  
Vol 29 (16) ◽  
pp. 2803-2811
Author(s):  
James P Cook ◽  
Anubha Mahajan ◽  
Andrew P Morris
Keyword(s):  
Population Structure ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Fine Scale ◽  
Uk Biobank ◽  
Genome Wide ◽  
Scale Population ◽  
The Uk ◽  
The Impact

Abstract The UK Biobank is a prospective study of more than 500 000 participants, which has aggregated data from questionnaires, physical measures, biomarkers, imaging and follow-up for a wide range of health-related outcomes, together with genome-wide genotyping supplemented with high-density imputation. Previous studies have highlighted fine-scale population structure in the UK on a North-West to South-East cline, but the impact of unmeasured geographical confounding on genome-wide association studies (GWAS) of complex human traits in the UK Biobank has not been investigated. We considered 368 325 white British individuals from the UK Biobank and performed GWAS of their birth location. We demonstrate that widely used approaches to adjust for population structure, including principal component analysis and mixed modelling with a random effect for a genetic relationship matrix, cannot fully account for the fine-scale geographical confounding in the UK Biobank. We observe significant genetic correlation of birth location with a range of lifestyle-related traits, including body-mass index and fat mass, hypertension and lung function, even after adjustment for population structure. Variants driving associations with birth location are also strongly associated with many of these lifestyle-related traits after correction for population structure, indicating that there could be environmental factors that are confounded with geography that have not been adequately accounted for. Our findings highlight the need for caution in the interpretation of lifestyle-related trait GWAS in UK Biobank, particularly in loci demonstrating strong residual association with birth location.

scholarly journals Genetic underpinnings of sociability in the UK Biobank

2019 ◽  
Author(s):  
J Bralten ◽  
CJHM Klemann ◽  
NR Mota ◽  
W De Witte ◽  
C Arango ◽  
...  
Keyword(s):  
Social Anxiety ◽  
Psychiatric Disorders ◽  
Genetic Correlation ◽  
Genome Wide Association Study ◽  
Autism Spectrum ◽  
Self Report ◽  
Uk Biobank ◽  
Genome Wide ◽  
A Genome ◽  
The Uk

ABSTRACTDifficulties with sociability include a tendency to avoid social contacts and activities, and to prefer being alone rather than being with others. While sociability is a continuously distributed trait in the population, decreased sociability represent a common early manifestation of multiple neuropsychiatric disorders such as Schizophrenia (SCZ), Bipolar Disorder (BP), Major Depressive Disorder (MDD), Autism Spectrum Disorders (ASDs), and Alzheimer’s disease (AD). We aimed to investigate the genetic underpinnings of sociability as a continuous trait in the general population. In this respect, we performed a genome-wide association study (GWAS) using a sociability score based on 4 social functioning-related self-report questions in the UK Biobank sample (n=342,461) to test the effect of individual genetic variants. This was followed by LD score analyses to investigate the genetic correlation with psychiatric disorders (SCZ, BP, MDD, ASDs) and a neurological disorder (AD) as well as related phenotypes (Loneliness and Social Anxiety). The phenotypic data indeed showed that the sociability score was decreased in individuals with ASD, (probable) MDD, BP and SCZ, but not in individuals with AD. Our GWAS showed 604 genome-wide significant SNPs, coming from 18 independent loci (SNP-based h2=0.06). Genetic correlation analyses showed significant correlations with SCZ (rg=0.15, p=9.8e-23), MDD (rg=0.68, p=6.6e-248) and ASDs (rg=0.27, p=4.5e-28), but no correlation with BP (rg=0.01, p=0.45) or AD (rg=0.04, p=0.55). Our sociability trait was also genetically correlated with Loneliness (rg=0.45, p=2.4e-8) and Social Anxiety (rg=0.48, p=0.002). Our study shows that there is a significant genetic component to variation in population levels of sociability, which is relevant to some psychiatric disorders (SCZ, MDD, ASDs), but not to BP and AD.

scholarly journals Genome-wide association study of liver fat, iron, and extracellular fluid fraction in the UK Biobank

2021 ◽  
Author(s):  
Colm O'Dushlaine ◽  
Mary Germino ◽  
Niek Verweij ◽  
Jonas B Nielsen ◽  
Ashish Yadav ◽  
...  
Keyword(s):  
Extracellular Fluid ◽  
Genome Wide Association ◽  
Liver Fat ◽  
Uk Biobank ◽  
Liver Iron ◽  
Invasive Approach ◽  
Genome Wide ◽  
A Genome ◽  
Fluid Fraction ◽  
The Uk

Abdominal magnetic resonance imaging (MRI) represents a non-invasive approach allowing the extraction of clinically informative phenotypes. We developed an automated pipeline to segment liver pixels from abdominal MRI images and apply published models to approximate fat fraction, extracellular fluid fraction and iron content in 40,058 MRIs from the UK Biobank. We then conducted a genome-wide association of these traits using imputed variants (N=37,250 individuals, 11,914,698 variants) and exome sequence data (N=35,274 individuals, 8,287,315 variants). For liver fat we identified 8 novel loci in or near genes MARC1, GCKR, ADH1B, MTTP, TRIB1, GPAM, PNPLA2 and APOH. For liver iron we identified 1 novel locus between the genes ASNSD1 and SLC40A1, an iron transporter involved in hemochromatosis. For extracellular fluid fraction we identified 6 novel loci in or near genes AGMAT, NAT2, MRPL4-S1PR2, FADS1, ABO and HFE, with almost all having prior associations to obesity, liver, iron, or lipid traits.

scholarly journals Genetic determinants of daytime napping and effects on cardiometabolic health

2020 ◽  
Author(s):  
Hassan S. Dashti ◽  
Iyas Daghlas ◽  
Jacqueline M. Lane ◽  
Yunru Huang ◽  
Miriam S. Udler ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Drug Targets ◽  
Genetic Basis ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Cardiometabolic Health ◽  
Genetic Determinants ◽  
Genome Wide ◽  
A Genome ◽  
The Uk

AbstractDaytime napping is a common, heritable behavior, but its genetic basis and causal relationship with cardiometabolic health remains unclear. Here, we performed a genome-wide association study of self-reported daytime napping in the UK Biobank (n=452,633) and identified 123 loci of which 60 replicated in 23andMe research participants (n=541,333). Findings included missense variants in established drug targets (HCRTR1, HCRTR2), genes with roles in arousal (TRPC6, PNOC), and genes suggesting an obesity-hypersomnolence pathway (PNOC, PATJ). Signals were concordant with accelerometer-measured daytime inactivity duration and 33 signals colocalized with signals for other sleep phenotypes. Cluster analysis identified 3 clusters suggesting distinct nap-promoting mechanisms with heterogeneous associations with cardiometabolic outcomes. Mendelian randomization showed potential causal links between more frequent daytime napping and higher systolic blood pressure, diastolic blood pressure, and waist circumference.

scholarly journals A genome-wide association study identifies that the GDF5 and COL27A1 genes are associated with knee pain in UK Biobank (N = 171, 516)

2019 ◽  
Author(s):  
Weihua Meng ◽  
Mark J Adams ◽  
Colin NA Palmer ◽  
Jingchunzi Shi ◽  
Adam Auton ◽  
...  
Keyword(s):  
Knee Pain ◽  
Genome Wide Association Study ◽  
Meta Analysis ◽  
Genome Wide Association ◽  
Uk Biobank ◽  
Narrow Sense ◽  
Narrow Sense Heritability ◽  
Genome Wide ◽  
A Genome ◽  
The Uk

SUMMARYObjectiveKnee pain is one of the most common musculoskeletal complaints that brings people to medical attention. We sought to identify the genetic variants associated with knee pain in 171,516 subjects from the UK Biobank cohort and replicate them using cohorts from 23andMe, the Osteoarthritis Initiative (OAI), and the Johnston County Osteoarthritis Study (JoCo).MethodsWe performed a genome-wide association study of knee pain in the UK Biobank, where knee pain was ascertained through self-report and defined as “knee pain in the last month interfering with usual activities”. A total of 22,204 cases and 149,312 controls were included in the discovery analysis. We tested our top and independent SNPs (P < 5 × 10−8) for replication in 23andMe, OAI, and JoCo, then performed a joint meta-analysis between discovery and replication cohorts using GWAMA. We calculated the narrow-sense heritability of knee pain using Genome-wide Complex Trait Analysis (GCTA).ResultsWe identified 2 loci that reached genome-wide significance, rs143384 located in the GDF5 (P = 1.32 × 10−12), a gene previously implicated in osteoarthritis, and rs2808772, located near COL27A1 (P = 1.49 × 10−8). These findings were subsequently replicated in independent cohorts and increased in significance in the joint meta-analysis (rs143384: P = 4.64 × 10−18; rs2808772: P −11 = 2.56 × 10−1’). The narrow sense heritability of knee pain was 0.08.ConclusionIn this first reported genome-wide association meta-analysis of knee pain, we identified and replicated two loci in or near GDF5 and COL27A1 that are associated with knee pain.

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.

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