scholarly journals Physician-confirmed and administrative definitions of stroke in UK Biobank reflect the same underlying genetic trait.

2021 ◽  
Author(s):  
Kristiina Rannikmae ◽  
Konrad Rawlik ◽  
Amy C Ferguson ◽  
Nikos Avramidis ◽  
Muchen Jiang ◽  
...  
Keyword(s):  
Primary Care ◽  
Association Studies ◽  
Genetic Correlations ◽  
Self Report ◽  
Hospital Death ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Genetic Trait ◽  
Stroke Case ◽  
Code Type

Background: Stroke in UK Biobank (UKB) is ascertained via linkages to coded administrative datasets and self-report. We studied the accuracy of these codes using genetic validation. Methods: We compiled stroke-specific and broad cerebrovascular disease (CVD) code lists (Read V2/V3, ICD-9/-10) for medical settings (hospital, death record, primary care) and self-report. Among 408,210 UKB participants we identified all with a relevant code, creating 12 stroke definitions based on the code type and source. We performed genome-wide association studies (GWASs) for each definition, comparing summary results against the largest published stroke GWAS (MEGASTROKE), assessing genetic correlations, and replicating 32 stroke-associated loci. Results: Stroke case numbers identified varied widely from 3,976 (primary care stroke-specific codes) to 19,449 (all codes, all sources). All 12 UKB stroke definitions were significantly correlated with the MEGASTROKE summary GWAS results (rg 0.81-1) and each other (rg 0.4-1). However, Bonferroni-corrected confidence intervals were wide, suggesting limited precision of some results. Six previously reported stroke-associated loci were replicated using ≥1 UKB stroke definitions. Conclusions: Stroke case numbers in UKB depend on the code source and type used, with a 5-fold difference in the maximum case-sample size. All stroke definitions are significantly genetically correlated with the largest stroke GWAS to date.

scholarly journals Insights into the genetic basis of retinal detachment

2019 ◽  
Vol 29 (4) ◽  
pp. 689-702 ◽  
Author(s):  
Thibaud S Boutin ◽  
David G Charteris ◽  
Aman Chandra ◽  
Susan Campbell ◽  
Caroline Hayward ◽  
...  
Keyword(s):  
Retinal Detachment ◽  
Association Studies ◽  
Genetic Correlations ◽  
Self Report ◽  
Cataract Operation ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Genetic Associations ◽  
Data Set ◽  
Genome Wide

Abstract Retinal detachment (RD) is a serious and common condition, but genetic studies to date have been hampered by the small size of the assembled cohorts. In the UK Biobank data set, where RD was ascertained by self-report or hospital records, genetic correlations between RD and high myopia or cataract operation were, respectively, 0.46 (SE = 0.08) and 0.44 (SE = 0.07). These correlations are consistent with known epidemiological associations. Through meta-analysis of genome-wide association studies using UK Biobank RD cases (N = 3 977) and two cohorts, each comprising ~1 000 clinically ascertained rhegmatogenous RD patients, we uncovered 11 genome-wide significant association signals. These are near or within ZC3H11B, BMP3, COL22A1, DLG5, PLCE1, EFEMP2, TYR, FAT3, TRIM29, COL2A1 and LOXL1. Replication in the 23andMe data set, where RD is self-reported by participants, firmly establishes six RD risk loci: FAT3, COL22A1, TYR, BMP3, ZC3H11B and PLCE1. Based on the genetic associations with eye traits described to date, the first two specifically impact risk of a RD, whereas the last four point to shared aetiologies with macular condition, myopia and glaucoma. Fine-mapping prioritized the lead common missense variant (TYR S192Y) as causal variant at the TYR locus and a small set of credible causal variants at the FAT3 locus. The larger study size presented here, enabled by resources linked to health records or self-report, provides novel insights into RD aetiology and underlying pathological pathways.

scholarly journals Genetic stratification of depression by neuroticism: revisiting a diagnostic tradition

2019 ◽  
Vol 50 (15) ◽  
pp. 2526-2535 ◽  
Author(s):  
Mark J. Adams ◽  
David M. Howard ◽  
Michelle Luciano ◽  
Toni-Kim Clarke ◽  
Gail Davies ◽  
...  
Keyword(s):  
Association Studies ◽  
Genetic Correlations ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Genome Wide ◽  
Artery Disease ◽  
Specific Association ◽  
Genetic Stratification ◽  
Genomic Regions ◽  
Genetic Contributions

AbstractBackgroundMajor depressive disorder and neuroticism (Neu) share a large genetic basis. We sought to determine whether this shared basis could be decomposed to identify genetic factors that are specific to depression.MethodsWe analysed summary statistics from genome-wide association studies (GWAS) of depression (from the Psychiatric Genomics Consortium, 23andMe and UK Biobank) and compared them with GWAS of Neu (from UK Biobank). First, we used a pairwise GWAS analysis to classify variants as associated with only depression, with only Neu or with both. Second, we estimated partial genetic correlations to test whether the depression's genetic link with other phenotypes was explained by shared overlap with Neu.ResultsWe found evidence that most genomic regions (25/37) associated with depression are likely to be shared with Neu. The overlapping common genetic variance of depression and Neu was genetically correlated primarily with psychiatric disorders. We found that the genetic contributions to depression, that were not shared with Neu, were positively correlated with metabolic phenotypes and cardiovascular disease, and negatively correlated with the personality trait conscientiousness. After removing shared genetic overlap with Neu, depression still had a specific association with schizophrenia, bipolar disorder, coronary artery disease and age of first birth. Independent of depression, Neu had specific genetic correlates in ulcerative colitis, pubertal growth, anorexia and education.ConclusionOur findings demonstrate that, while genetic risk factors for depression are largely shared with Neu, there are also non-Neu-related features of depression that may be useful for further patient or phenotypic stratification.

scholarly journals Genome-wide analyses of behavioural traits are subject to bias by misreports and longitudinal changes

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Angli Xue ◽  
Longda Jiang ◽  
Zhihong Zhu ◽  
Naomi R. Wray ◽  
Peter M. Visscher ◽  
...  
Keyword(s):  
Alcohol Consumption ◽  
Association Studies ◽  
Genetic Correlations ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Longitudinal Changes ◽  
Genome Wide ◽  
The Uk ◽  
Almost All ◽  
Cardiovascular Traits

AbstractGenome-wide association studies (GWAS) have discovered numerous genetic variants associated with human behavioural traits. However, behavioural traits are subject to misreports and longitudinal changes (MLC) which can cause biases in GWAS and follow-up analyses. Here, we demonstrate that individuals with higher disease burden in the UK Biobank (n = 455,607) are more likely to misreport or reduce their alcohol consumption levels, and propose a correction procedure to mitigate the MLC-induced biases. The alcohol consumption GWAS signals removed by the MLC corrections are enriched in metabolic/cardiovascular traits. Almost all the previously reported negative estimates of genetic correlations between alcohol consumption and common diseases become positive/non-significant after the MLC corrections. We also observe MLC biases for smoking and physical activities in the UK Biobank. Our findings provide a plausible explanation of the controversy about the effects of alcohol consumption on health outcomes and a caution for future analyses of self-reported behavioural traits in biobank data.

scholarly journals Sexual differences in genetic architecture in UK Biobank

2020 ◽  
Author(s):  
Elena Bernabeu ◽  
Oriol Canela-Xandri ◽  
Konrad Rawlik ◽  
Andrea Talenti ◽  
James Prendergast ◽  
...  
Keyword(s):  
Sexual Dimorphism ◽  
Complex Traits ◽  
Genetic Architecture ◽  
Molecular Mechanisms ◽  
Association Studies ◽  
Mammalian Species ◽  
Genetic Correlations ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Uk Biobank

ABSTRACTSex is arguably the most important differentiating characteristic in most mammalian species, separating populations into different groups, with varying behaviors, morphologies, and physiologies based on their complement of sex chromosomes. In humans, despite males and females sharing nearly identical genomes, there are differences between the sexes in complex traits and in the risk of a wide array of diseases. Gene by sex interactions (GxS) are thought to account for some of this sexual dimorphism. However, the extent and basis of these interactions are poorly understood.Here we provide insights into both the scope and mechanism of GxS across the genome of circa 450,000 individuals of European ancestry and 530 complex traits in the UK Biobank. We found small yet widespread differences in genetic architecture across traits through the calculation of sex-specific heritability, genetic correlations, and sex-stratified genome-wide association studies (GWAS). We also found that, in some cases, sex-agnostic GWAS efforts might be missing loci of interest, and looked into possible improvements in the prediction of high-level phenotypes. Finally, we studied the potential functional role of the dimorphism observed through sex-biased eQTL and gene-level analyses.This study marks a broad examination of the genetics of sexual dimorphism. Our findings parallel previous reports, suggesting the presence of sexual genetic heterogeneity across complex traits of generally modest magnitude. Our results suggest the need to consider sex-stratified analyses for future studies in order to shed light into possible sex-specific molecular mechanisms.

scholarly journals Carotid intima-media thickness in UK Biobank: Identification of novel genome-wide loci, sex-specific effects and genetic correlations with obesity and glucometabolic traits

2019 ◽  
Author(s):  
Rona J. Strawbridge ◽  
Joey Ward ◽  
Mark E.S. Bailey ◽  
Breda Cullen ◽  
Amy Ferguson ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Association Studies ◽  
Genetic Correlations ◽  
Intima Media Thickness ◽  
Genome Wide Association ◽  
Ultra Sound ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Media Thickness ◽  
Genome Wide

AbstractObjectivesAtherosclerosis is the underlying cause of most cardiovascular disease, but mechanisms underlying atherosclerosis are incompletely understood. Ultra-sound measurement of the carotid artery intima-media thickness (cIMT) can be used to measure vascular remodelling, which is indicative of atherosclerosis. Genome-wide association studies have identified a number of genetic loci associated with cIMT, but heterogeneity of measurements collected by many small cohorts have been a major limitation in these efforts. Here we conducted genome-wide association analyses in UK Biobank (N=22,179), the largest single study with consistent cIMT measurements.Approach and resultsWe used BOLT-LMM to run linear regression of cIMT in UK Biobank, adjusted for age, sex, genotyping platform and population structure. In white British participants, we identified 4 novel loci associated with cIMT and replicated most previously reported loci. In the first sex-specific analyses of cIMT, we identified a female-specific locus on Chromosome 5, associated with cIMT in women only and highlight VCAN as a good candidate gene at this locus. Genetic correlations with body-mass index and glucometabolic traits were also observed.ConclusionThese findings replicate previously reported associations, highlight novel biology and provide new directions for investigating the sex differences observed in cardiovascular disease presentation and progression.

scholarly journals Insight into the genetic aetiology of retinal detachment by combining small clinical and large population-based datasets

2019 ◽  
Author(s):  
Thibaud S. Boutin ◽  
David G. Charteris ◽  
Aman Chandra ◽  
Susan Campbell ◽  
Caroline Hayward ◽  
...  
Keyword(s):  
Retinal Detachment ◽  
Genetic Risk ◽  
Association Studies ◽  
Population Based ◽  
Self Report ◽  
Cataract Operation ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Genome Wide ◽  
Independent Population

AbstractIdiopathic retinal detachment is a serious common condition, but genetic studies to date have been hampered by the small size of the assembled cohorts. Genetic correlations between retinal detachment and high myopia or cataract operation were high, respectively 0.46 (SE=0.08) and 0.44 (SE=0.07), in the UK Biobank dataset and in line with known epidemiological associations. Meta-analysis of genome-wide association studies using UK Biobank retinal detachment cases (N=3977) and two cohorts, each comprising ∼1000 rhegmatogenous retinal detachment patients, uncovered 11 genome-wide significant association signals, near or withinZC3H11B, BMP3, COL22A1, DLG5, PLCE1, EFEMP2, TYR, FAT3, TRIM29, COL2A1andLOXL1.Replication in the 23andMe dataset, where retinal detachment is self-reported by participants, firmly establishes association at six lociFAT3, COL22A1, TYR, BMP3, ZC3H11BandPLCE1.The former two seem to particularly impact on retinal detachment, the latter three shed light on shared aetiologies with cataract, myopia and glaucoma.Author SummaryRetinal detachments are common conditions that may lead to permanent severe sight reduction or blindness; they are a major cause of emergency eye surgery. The most common type of retinal detachment follows a break in the retina and is thought to be in part genetically determined but little is known about the contributing individual genetic risk variants. The condition prevalence increases with age and with common eye conditions such as myopia, cataract or glaucoma. We showed that the retinal detachment cases derived from self-report or hospitalisation records in the large UK Biobank dataset show very similar characteristics to samples of carefully clinically evaluated retinal detachment with break cases and therefore could be used to perform genetic analysis of the condition. Association studies require large sample of cases and by pooling Biobank and clinical cases, this study identifies 11 novel significant associations, six of which were further replicated in an independent population-based dataset (23andMe). Two of the replicated findings seem to specifically underline retinal detachment risk while three others highlight shared genetic risk with myopia, cataract and/or glaucoma, paving the way to better understanding of these conditions and of their overlap.

scholarly journals The genomic basis of mood instability: identification of 46 loci in 363,705 UK Biobank participants, genetic correlation with psychiatric disorders, and association with gene expression and function

2019 ◽  
Author(s):  
Joey Ward ◽  
Elizabeth M. Tunbridge ◽  
Cynthia Sandor ◽  
Laura M. Lyall ◽  
Amy Ferguson ◽  
...  
Keyword(s):  
Nervous System ◽  
Association Studies ◽  
Large Population ◽  
Genetic Correlations ◽  
Melatonin Receptors ◽  
Chromosome 17 ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Mood Instability ◽  
Gene Sets

AbstractGenome-wide association studies (GWAS) of psychiatric phenotypes have tended to focus on categorical diagnoses, but to understand the biology of mental illness it may be more useful to study traits which cut across traditional boundaries. Here we report the results of a GWAS of mood instability (MI) as a trait in a large population cohort (UK Biobank, n=363,705). We also assess the clinical and biological relevance of the findings, including whether genetic associations show enrichment for nervous system pathways. Forty six unique loci associated with MI were identified with a heritability estimate of 9%. Linkage Disequilibrium Score Regression (LDSR) analyses identified genetic correlations with Major Depressive Disorder (MDD), Bipolar Disorder (BD), Schizophrenia (SZ), anxiety and Post Traumatic Stress Disorder (PTSD). Gene-level and gene set analyses identified total 244 significant genes and 6 enriched gene sets. Tissue expression analysis from the SNP level data found enrichment in multiple brain regions, and eQTL analyses highlighted an inversion on chromosome 17 plus two brain-specific eQTLs. Additionally, we used a Phenotype Linkage Network (PLN) analysis and community analysis to assess for enrichment of nervous system gene sets using mouse orthologue databases. The PLN analysis found enrichment in nervous system PLNs for a community containing serotonin and melatonin receptors. In summary, this work has identified novel loci, tissues, and gene sets contributing to MI as a normal trait and will inform future work on the biology of mood and psychotic disorders, and to point the way towards potential for new stratified medicine approaches and the identification of novel trans-diagnostic drug targets.

scholarly journals Novel genetic variants associated with brain functional networks in 18,445 adults from the UK Biobank

2020 ◽  
Author(s):  
Heidi Foo ◽  
Anbupalam Thalamuthu ◽  
Jiyang Jiang ◽  
Forrest C. Koch ◽  
Karen A. Mather ◽  
...  
Keyword(s):  
Sleep Duration ◽  
Psychiatric Symptoms ◽  
Association Studies ◽  
Genetic Correlations ◽  
Functional Network ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Network Measures ◽  
Functional Brain Network ◽  
The Uk

AbstractThis is the first study investigating the genetics of weighted functional brain network graph theory measures from 18,445 participants of the UK Biobank (44-80 years). The eighteen measures studied showed low heritability (mean h2SNP =0.12) and were highly genetically correlated. Genome-wide association studies for these measures observed 14 significant variants associated with strength of somatomotor and limbic networks. These intergenic variants were located near the PAX8 gene on chromosome 2. Gene-based analyses identified five significantly associated genes for five of the network measures, which have been implicated in sleep duration, neuronal differentiation/development, cancer, and susceptibility to neurodegenerative diseases. Genetic correlations with other traits were examined and significant correlations were observed with sleep measures and psychiatric symptoms. Further analysis found that somatomotor network strength was phenotypically associated with sleep duration and insomnia. Single nucleotide polymorphism (SNP) and gene level associations with functional network measures were identified, which may help uncover novel biological pathways relevant to human brain functional network integrity and diseases that affect it.

scholarly journals A Large-Scale Genetic Correlation Scan Between Intelligence and Brain Imaging Phenotypes

2020 ◽  
Vol 30 (7) ◽  
pp. 4197-4203
Author(s):  
Shiqiang Cheng ◽  
Cuiyan Wu ◽  
Xin Qi ◽  
Li Liu ◽  
Mei Ma ◽  
...  
Keyword(s):  
Brain Imaging ◽  
Large Scale ◽  
Association Studies ◽  
Pearson Correlation ◽  
Genetic Correlations ◽  
Correlation Coefficients ◽  
Functional Brain Imaging ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Individual Level

Abstract Limited efforts have been paid to evaluate the potential relationships between structural and functional brain imaging and intelligence until now. We performed a two-stage analysis to systematically explore the relationships between 3144 brain image-derived phenotypes (IDPs) and intelligence. First, by integrating genome-wide association studies (GWAS) summaries data of brain IDPs and two GWAS summary datasets of intelligence, we systematically scanned the relationship between each of the 3144 brain IDPs and intelligence through linkage disequilibrium score regression (LDSC) analysis. Second, using the individual-level genotype and intelligence data of 160 124 subjects derived from UK Biobank datasets, polygenetic risk scoring (PRS) analysis was performed to replicate the common significant associations of the first stage. In the first stage, LDSC identified 6 and 2 significant brain IDPs significantly associated with intelligence dataset1 and dataset2, respectively. It is interesting that NET100_0624 showed genetic correlations with intelligence in the two datasets of intelligence. After adjusted for age and sex as the covariates, NET100_0624 (P = 5.26 × 10−20, Pearson correlation coefficients = −0.02) appeared to be associated with intelligence by PRS analysis of UK Biobank samples. Our findings may help to understand the genetic mechanisms of the effects of brain structure and function on the development of intelligence.

scholarly journals EPID-19. SHARED GENOMIC ARCHITECTURE OF GLIOMA AND NEURO-COGNITIVE AND NEURO-PSYCHIATRIC TRAITS REVEALED BY LD-SCORE REGRESSION

2019 ◽  
Vol 21 (Supplement_6) ◽  
pp. vi78-vi78
Author(s):  
Kyle Walsh ◽  
Quinn Ostrom ◽  
Chenan Zhang ◽  
Jacob Edelson ◽  
Erica Shen ◽  
...  
Keyword(s):  
Association Studies ◽  
Meta Analysis ◽  
Genetic Correlations ◽  
College Attendance ◽  
Case Control ◽  
Cognitive Test ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Genomic Architecture ◽  
Genome Wide

Abstract BACKGROUND Genome-wide analyses estimate glioma heritability at 25%, yet known risk loci account for just one-third of this risk and suggest that sporadic glioma is a highly polygenic disease with hitherto unaccounted for genomic architecture. LD-score regression leverages results from genome-wide association studies (GWAS) and known patterns of linkage disequilibrium (LD) to estimate correlation between the genetic architecture of multiple phenotypes. We applied LD-score regression to identify associations with neuro-cognitive and neuro-psychiatric traits not amenable to study in prior glioma case-control analyses. METHODS GWAS summary statistics were obtained from the Glioma International Case-Control Consortium (GICC) meta-analysis (Melin, et al. 2017) and for 64 neuro-cognitive and neuro-psychiatric traits primarily from the UK Biobank. Included SNPs had quality scores ≥0.70 and minor allele frequency ≥0.01. Pairwise genetic correlations between traits were estimated using the LDSC package. P-values < 7.8x10-4 (i.e. 0.05/64) were considered significant. RESULTS Significant negative correlations were identified between the genetic architectures of glioma and bipolar disorder (Rg=-0.41, P=1.4x10-9) and schizophrenia (Rg=-0.29, P=7.1x10-9), consistent in both GBM and LGG. Significant positive correlations were identified with measures of educational attainment, including age at educational completion (Rg=0.11, P=2.0x10-4), obtaining a college degree (Rg=0.086, P=4.9x10-4), college attendance (Rg=0.086, P=5.9x10-4), and years of education (Rg=0.081, P=7.7x10-4). These associations were notably stronger with LGG. A number of additional nominal associations were observed, including with anorexia (anti-correlated) and performance on a pair-matching cognitive test (positively correlated). Importantly, LD-score regression did not identify an association between glioma risk in GICC data and Townsend deprivation index in UK Biobank data. CONCLUSIONS These results implicate a shared genetic basis for glioma and several psychiatric and cognitive traits. Further research is needed to understand these associations and to explore underlying mechanisms, including the mediating effects of neuro-inflammation, developmental differences in neural‒glial cell circuitry, and inter-individual variation in myelination.

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