scholarly journals HLA-B27 and not variation in MICA is responsible for genotype by sex interaction in risk of Ankylosing Spondylitis

2021 ◽  
Author(s):  
Zhixiu Li ◽  
Allan F McRae ◽  
Geng Wang ◽  
Jonathan J Ellis ◽  
Tony J Kenna ◽  
...  
Keyword(s):  
Ankylosing Spondylitis ◽  
Complex Traits ◽  
Hla B27 ◽  
Uk Biobank ◽  
Association Analyses ◽  
Genome Wide ◽  
Conditional Association ◽  
A Genome ◽  
Mhc Locus ◽  
The Uk

Ankylosing Spondylitis (AS) is a highly heritable inflammatory arthritis which occurs more frequently in men than women. In their recent publication examining sex differences in the genetic aetiology of common complex traits and diseases, Bernabeu et al. (2021) observe differences in heritability of AS between sexes, and a genome-wide significant genotype by sex interaction in risk of AS at the major histocompatability (MHC) locus. The authors then present evidence suggesting that this genotype by sex interaction arises primarily as a result of differential expression of the gene MICA across the sexes in skeletal muscle tissue. Through a series of conditional association analyses in the UK Biobank, reanalysis of the GTEx gene expression resource and RNASeq experiments on peripheral blood cells from AS cases and controls, we show that the genotype by sex interaction the authors' report is unlikely to be a result of variation in MICA, but probably reflects a known interaction between the HLA-B gene, sex and risk of AS. We demonstrate that the diagnostic accuracy of AS in the UK Biobank is low, particularly amongst women, likely explaining some of the observed differences in heritability across the sexes and the difficulty in precisely locating association signals in the cohort.

scholarly journals The molecular genetics of hand preference revisited

2018 ◽  
Author(s):  
Carolien G.F. de Kovel ◽  
Clyde Francks
Keyword(s):  
Complex Traits ◽  
Large Population ◽  
Enrichment Analysis ◽  
Hand Preference ◽  
Population Based ◽  
Gene Set Enrichment Analysis ◽  
Uk Biobank ◽  
Genome Wide ◽  
A Genome ◽  
The Uk

AbstractHand preference is a prominent behavioural trait linked to human brain asymmetry. A handful of genetic variants have been reported to associate with hand preference or quantitative measures related to it. Most of these reports were on the basis of limited sample sizes, by current standards for genetic analysis of complex traits. Here we performed a genome-wide association analysis of hand preference in the large, population-based UK Biobank cohort (N=331,037). We used gene-set enrichment analysis to investigate whether genes involved in visceral asymmetry are particularly relevant to hand preference, following one previous report. We found no evidence implicating any specific candidate variants previously reported. We also found no evidence that genes involved in visceral laterality play a role in hand preference. It remains possible that some of the previously reported genes or pathways are relevant to hand preference as assessed in other ways, or else are relevant within specific disorder populations. However, some or all of the earlier findings are likely to be false positives, and none of them appear relevant to hand preference as defined categorically in the general population. Within the UK Biobank itself, a significant association implicates the gene MAP2 in handedness.

scholarly journals Analysis of genetic dominance in the UK Biobank

2021 ◽  
Author(s):  
Duncan S Palmer ◽  
Wei Zhou ◽  
Liam Abbott ◽  
Nik Baya ◽  
Claire Churchhouse ◽  
...  
Keyword(s):  
Complex Traits ◽  
Multiple Testing ◽  
Model Organisms ◽  
Systematic Evaluation ◽  
Hair Color ◽  
Phenotypic Variance ◽  
Additive Effects ◽  
Uk Biobank ◽  
Genome Wide ◽  
The Uk

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.

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 Genome-wide haplotype association study in imaging genetics using whole-brain sulcal openings of 16,304 UK Biobank subjects

2021 ◽  
Author(s):  
Slim Karkar ◽  
Claire Dandine-Roulland ◽  
Jean-François Mangin ◽  
Yann Le Guen ◽  
Cathy Philippe ◽  
...  
Keyword(s):  
Brain Imaging ◽  
Complex Traits ◽  
Haplotype Analysis ◽  
Imaging Genetics ◽  
Genetic Maps ◽  
Imaging Features ◽  
Uk Biobank ◽  
Whole Brain ◽  
Genome Wide ◽  
A Genome

AbstractNeuroimaging-genetics cohorts gather two types of data: brain imaging and genetic data. They allow the discovery of associations between genetic variants and brain imaging features. They are invaluable resources to study the influence of genetics and environment in the brain features variance observed in normal and pathological populations. This study presents a genome-wide haplotype analysis for 123 brain sulcus opening value (a measure of sulcal width) across the whole brain that include 16,304 subjects from UK Biobank. Using genetic maps, we defined 119,548 blocks of low recombination rate distributed along the 22 autosomal chromosomes and analyzed 1,051,316 haplotypes. To test associations between haplotypes and complex traits, we designed three statistical approaches. Two of them use a model that includes all the haplotypes for a single block, while the last approach considers each haplotype independently. All the statistics produced were assessed as rigorously as possible. Thanks to the rich imaging dataset at hand, we used resampling techniques to assess False Positive Rate for each statistical approach in a genome-wide and brain-wide context. The results on real data show that genome-wide haplotype analyses are more sensitive than single-SNP approach and account for local complex Linkage Disequilibrium (LD) structure, which makes genome-wide haplotype analysis an interesting and statistically sound alternative to the single-SNP counterpart.

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 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 Genome-wide haplotype association study in imaging genetics using whole-brain sulcal openings of 16,304 UK Biobank subjects

2020 ◽  
Author(s):  
Slim Karkar ◽  
Claire Dandine-Roulland ◽  
Jean-François Mangin ◽  
Yann Le Guen ◽  
Cathy Philippe ◽  
...  
Keyword(s):  
Brain Imaging ◽  
Complex Traits ◽  
Haplotype Analysis ◽  
Imaging Genetics ◽  
Genetic Maps ◽  
Imaging Features ◽  
Uk Biobank ◽  
Whole Brain ◽  
Genome Wide ◽  
A Genome

AbstractNeuroimaging-genetics cohorts gather two types of data: brain imaging and genetic data. They allow the discovery of associations between genetic variants and brain imaging features. They are invaluable resources to study the influence of genetics and environment in the brain features variance observed in normal and pathological populations. This study presents a genome wide haplotype analysis for 123 brain sulcus opening value (a measure of sulcal width) across the whole brain that include 16,304 subjects from UK Biobank. Using genetic maps, we defined 119,548 blocks of low recombination rate distributed along the 22 autosomal chromosomes, and analyzed 1,051,316 haplotypes. To test associations between haplotypes and complex traits, we designed three statistical approaches. Two of them use a model that includes all the haplotypes for a sin gle block, while the last approach considers one model by haplotype. All the statistics produced were assessed as rigorously as possible. Thanks to the rich imaging dataset at hand, we used resampling techniques to assess False Positive Rate for each statistical approach in a genome-wide and brain-wide context. The results on real data show that genome-wide haplotype analyses are more sensitive than single-SNP approach and account for local complex Linkage Disequilibrium (LD) structure, which makes genome-wide haplotype analysis an interesting and statistically sound alternative to the single-SNP counterpart.

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