scholarly journals Genome-wide analysis of over 106 000 individuals identifies 9 neuroticism-associated loci

2016 ◽  
Vol 21 (6) ◽  
pp. 749-757 ◽  
Author(s):  
D J Smith ◽  
V Escott-Price ◽  
G Davies ◽  
M E S Bailey ◽  
L Colodro-Conde ◽  
...  
Keyword(s):  
Medical Research ◽  
Genetic Correlation ◽  
Meta Analysis ◽  
Small Sample ◽  
Chromosome 8 ◽  
Chromosome 17 ◽  
Chromosome 1 ◽  
Eysenck Personality Questionnaire ◽  
Uk Biobank ◽  
Genome Wide

Abstract Neuroticism is a personality trait of fundamental importance for psychological well-being and public health. It is strongly associated with major depressive disorder (MDD) and several other psychiatric conditions. Although neuroticism is heritable, attempts to identify the alleles involved in previous studies have been limited by relatively small sample sizes. Here we report a combined meta-analysis of genome-wide association study (GWAS) of neuroticism that includes 91 370 participants from the UK Biobank cohort, 6659 participants from the Generation Scotland: Scottish Family Health Study (GS:SFHS) and 8687 participants from a QIMR (Queensland Institute of Medical Research) Berghofer Medical Research Institute (QIMR) cohort. All participants were assessed using the same neuroticism instrument, the Eysenck Personality Questionnaire-Revised (EPQ-R-S) Short Form’s Neuroticism scale. We found a single-nucleotide polymorphism-based heritability estimate for neuroticism of ∼15% (s.e.=0.7%). Meta-analysis identified nine novel loci associated with neuroticism. The strongest evidence for association was at a locus on chromosome 8 (P=1.5 × 10−15) spanning 4 Mb and containing at least 36 genes. Other associated loci included interesting candidate genes on chromosome 1 (GRIK3 (glutamate receptor ionotropic kainate 3)), chromosome 4 (KLHL2 (Kelch-like protein 2)), chromosome 17 (CRHR1 (corticotropin-releasing hormone receptor 1) and MAPT (microtubule-associated protein Tau)) and on chromosome 18 (CELF4 (CUGBP elav-like family member 4)). We found no evidence for genetic differences in the common allelic architecture of neuroticism by sex. By comparing our findings with those of the Psychiatric Genetics Consortia, we identified a strong genetic correlation between neuroticism and MDD and a less strong but significant genetic correlation with schizophrenia, although not with bipolar disorder. Polygenic risk scores derived from the primary UK Biobank sample captured ∼1% of the variance in neuroticism in the GS:SFHS and QIMR samples, although most of the genome-wide significant alleles identified within a UK Biobank-only GWAS of neuroticism were not independently replicated within these cohorts. The identification of nine novel neuroticism-associated loci will drive forward future work on the neurobiology of neuroticism and related phenotypes.

scholarly journals Genome-wide analysis of over 106,000 individuals identifies 9 neuroticism-associated loci

2015 ◽  
Author(s):  
Daniel J Smith ◽  
Valentina Escott-Price ◽  
Gail Davies ◽  
Mark ES Bailey ◽  
Lucia Colodro Conde ◽  
...  
Keyword(s):  
Genetic Correlation ◽  
Meta Analysis ◽  
Small Sample ◽  
Chromosome 8 ◽  
Chromosome 17 ◽  
Chromosome 1 ◽  
Eysenck Personality Questionnaire ◽  
Uk Biobank ◽  
Genome Wide ◽  
A Genome

Neuroticism is a personality trait of fundamental importance for psychological wellbeing and public health. It is strongly associated with major depressive disorder (MDD) and several other psychiatric conditions. Although neuroticism is heritable, attempts to identify the alleles involved in previous studies have been limited by relatively small sample sizes and heterogeneity in the measurement of neuroticism. Here we report a genome-wide association study of neuroticism in 91,370 participants of the UK Biobank cohort and a combined meta-analysis which includes a further 6,659 participants from the Generation Scotland Scottish Family Health Study (GS:SFHS) and 8,687 participants from a QIMR Berghofer Medical Research Institute (QIMR) cohort. All participants were assessed using the same neuroticism instrument, the Eysenck Personality Questionnaire-Revised (EPQ-R-S) Short Form Neuroticism scale. We found a SNP-based heritability estimate for neuroticism of approximately 15% (SE = 0.7%). Meta-analysis identified 9 novel loci associated with neuroticism. The strongest evidence for association was at a locus on chromosome 8 (p = 1.5x10-15) spanning 4 Mb and containing at least 36 genes. Other associated loci included interesting candidate genes on chromosome 1 (GRIK3, glutamate receptor ionotropic kainate 3), chromosome 4 (KLHL2, Kelch-like protein 2), chromosome 17 (CRHR1, corticotropin-releasing hormone receptor 1 and MAPT, microtubule-associated protein Tau), and on chromosome 18 (CELF4, CUGBP elav-like family member 4). We found no evidence for genetic differences in the common allelic architecture of neuroticism by sex. By comparing our findings with those of the Psychiatric Genetics Consortia, we identified a strong genetic correlation between neuroticism and MDD (0.64) and a less strong but significant genetic correlation with schizophrenia (0.22), although not with bipolar disorder. Polygenic risk scores derived from the primary UK Biobank sample captured about 1% of the variance in neuroticism in independent samples. Overall, our findings confirm a polygenic basis for neuroticism and substantial shared genetic architecture between neuroticism and MDD. The identification of 9 new neuroticism-associated loci will drive forward future work on the neurobiology of neuroticism and related phenotypes.

scholarly journals EPCO-13. GENOME-WIDE ASSOCIATION STUDY IN INDIVIDUALS OF ASHKENAZI JEWISH ANCESTRY IDENTIFIES NOVEL RISK LOCI FOR GLIOMA

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii71-ii72
Author(s):  
Quinn Ostrom ◽  
Jinyoung Byun ◽  
Christopher Amos ◽  
Elizabeth Claus ◽  
Melissa Bondy
Keyword(s):  
Genetic Risk ◽  
Risk Allele ◽  
Meta Analysis ◽  
Small Sample ◽  
Genome Wide Association ◽  
Chromosome 17 ◽  
European Ancestry ◽  
Ashkenazi Jewish ◽  
Genome Wide ◽  
Glioma Risk

Abstract Population stratification, or systematic differences in allele frequencies between subpopulations, can distort the results from genome-wide association studies (GWAS). While GWAS are usually conducted within continental (e.g. European) ancestry groups, sub-groups may have specific population histories that result in enrichment for risk or protective alleles for complex disease. In this analysis, we examined genetic risk for glioma in a US population with predominantly Ashkenazi Jewish (AJ) ancestry. Genotyping data were obtained from three prior glioma case-control studies. Best-guess assignment to one of seven subcontinental European ancestry groups was performed using AIPS (https://github.com/biomedicaldatascience/AIPS). Out of a total of 6,416 cases and 7,441 controls across all three studies, 202 cases (3% of all cases, 63% GBM) and 403 controls (5% of all controls) were assigned to the AJ ancestry group. Unconditional logistic regression was performed for by study (adjusted for age and first two principal components) and then studies were combined using fixed effects meta-analysis. No associations reached genome-wide significance (p< 5x10-8), including those detected in prior pan-European GWAS. A nominally significant association was detected on chromosome 17 in ASPA (rs9904040, MAF=20%, p=2.61x10-6, Odds ratio=2.22 [95% confidence interval=1.59–3.09]) which is in linkage equilibrium (r2=0.0013) with the previously detected glioma risk SNP in TP53 (MAF=0.3% in this analysis, p=0.8801) in the European population. In our prior pan-European meta-analysis (Melin et al., 2017, this SNP was non-significant (p=0.0620). This study failed to replicate many previously identified glioma risk alleles, likely due to diminished power due to small sample size. We did identify a novel risk allele on chromosome 17 in ASPA, which encodes for aspartoacylase (which catalyzes deacylation of N-acetyl_L-aspartic acid). Larger sample sizes identified via targeted recruitment are necessary in order to fully characterize genetic risk for glioma in this population, including assessment of rare (MAF< 5%) risk allele associations.

scholarly journals Causal effect of renal function on venous thromboembolism: a two-sample Mendelian randomization investigation

2021 ◽  
Author(s):  
Shuai Yuan ◽  
Maria Bruzelius ◽  
Susanna C. Larsson
Keyword(s):  
Renal Function ◽  
Venous Thromboembolism ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Meta Analysis ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Genome Wide ◽  
Increased Risk ◽  
Mr Study

AbstractWhether renal function is causally associated with venous thromboembolism (VTE) is not yet fully elucidated. We conducted a two-sample Mendelian randomization (MR) study to determine the causal effect of renal function, measured as estimated glomerular filtration rate (eGFR), on VTE. Single-nucleotide polymorphisms associated with eGFR were selected as instrumental variables at the genome-wide significance level (p < 5 × 10−8) from a meta-analysis of 122 genome-wide association studies including up to 1,046,070 individuals. Summary-level data for VTE were obtained from the FinnGen consortium (6913 VTE cases and 169,986 non-cases) and UK Biobank study (4620 VTE cases and 356,574 non-cases). MR estimates were calculated using the random-effects inverse-variance weighted method and combined using fixed-effects meta-analysis. Genetically predicted decreased eGFR was significantly associated with an increased risk of VTE in both FinnGen and UK Biobank. For one-unit decrease in log-transformed eGFR, the odds ratios of VTE were 2.93 (95% confidence interval (CI) 1.25, 6.84) and 4.46 (95% CI 1.59, 12.5) when using data from FinnGen and UK Biobank, respectively. The combined odds ratio was 3.47 (95% CI 1.80, 6.68). Results were consistent in all sensitivity analyses and no horizontal pleiotropy was detected. This MR-study supported a casual role of impaired renal function in VTE.

scholarly journals Genome-Wide Association Meta-Analysis Supports Genes Involved in Valve and Cardiac Development to Associate With Mitral Valve Prolapse

2021 ◽  
Author(s):  
Mengyao Yu ◽  
Sergiy Kyryachenko ◽  
Stephanie Debette ◽  
Philippe Amouyel ◽  
Jean-Jacques Schott ◽  
...  
Keyword(s):  
Mitral Valve ◽  
Association Study ◽  
Genome Wide Association Study ◽  
Cardiac Development ◽  
Meta Analysis ◽  
Genome Wide Association ◽  
Uk Biobank ◽  
Additional Risk ◽  
Genome Wide ◽  
The Uk

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.

Abstract P260: Large-scale Meta-analysis of Diverse Ancestry Genome-wide Association Studies to Identify Pharmacogenomic Interactions of Sulfonylureas and ECG Phenotypes

Circulation ◽  
2016 ◽  
Vol 133 (suppl_1) ◽  
Author(s):  
James S Floyd ◽  
Colleen Sitlani ◽  
Christy L Avery ◽  
Eric A Whitsel ◽  
Leslie Lange ◽  
...  
Keyword(s):  
Repeated Measures ◽  
Qt Interval ◽  
Association Studies ◽  
Meta Analysis ◽  
Small Sample ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Meta Analyses

Introduction: Sulfonylureas are a commonly-used class of diabetes medication that can prolong the QT-interval, which is a leading cause of drug withdrawals from the market given the possible risk of life-threatening arrhythmias. Previously, we conducted a meta-analysis of genome-wide association studies of sulfonylurea-genetic interactions on QT interval among 9 European-ancestry (EA) cohorts using cross-sectional data, with null results. To improve our power to identify novel drug-gene interactions, we have included repeated measures of medication use and QT interval and expanded our study to include several additional cohorts, including African-American (AA) and Hispanic-ancestry (HA) cohorts with a high prevalence of sulfonylurea use. To identify potentially differential effects on cardiac depolarization and repolarization, we have also added two phenotypes - the JT and QRS intervals, which together comprise the QT interval. Hypothesis: The use of repeated measures and expansion of our meta-analysis to include diverse ancestry populations will allow us to identify novel pharmacogenomic interactions for sulfonylureas on the ECG phenotypes QT, JT, and QRS. Methods: Cohorts with unrelated individuals used generalized estimating equations to estimate interactions; cohorts with related individuals used mixed effect models clustered on family. For each ECG phenotype (QT, JT, QRS), we conducted ancestry-specific (EA, AA, HA) inverse variance weighted meta-analyses using standard errors based on the t-distribution to correct for small sample inflation in the test statistic. Ancestry-specific summary estimates were combined using MANTRA, an analytic method that accounts for differences in local linkage disequilibrium between ethnic groups. Results: Our study included 65,997 participants from 21 cohorts, including 4,020 (6%) sulfonylurea users, a substantial increase from the 26,986 participants and 846 sulfonylureas users in the previous meta-analysis. Preliminary ancestry-specific meta-analyses have identified genome-wide significant associations (P < 5х10–8) for each ECG phenotype, and analyses with MANTRA are in progress. Conclusions: In the setting of the largest collection of pharmacogenomic studies to date, we used repeated measurements and leveraged diverse ancestry populations to identify new pharmacogenomic loci for ECG traits associated with cardiovascular risk.

Abstract P147: Genome Wide Assessment of Shared Genetic Architecture Between Rheumatoid Arthritis and Cardiovascular Diseases Using the UK Biobank Data

Circulation ◽  
2020 ◽  
Vol 141 (Suppl_1) ◽  
Author(s):  
Yanjun Guo ◽  
Wonil Chung ◽  
Zhilei Shan ◽  
Liming Liang
Keyword(s):  
Cardiovascular Diseases ◽  
Genetic Correlation ◽  
Multiple Testing ◽  
Mendelian Randomization ◽  
Meta Analysis ◽  
Uk Biobank ◽  
Increased Risk ◽  
The Uk ◽  
Cardiovascular Traits ◽  
Shared Genetic

Background: Patients with RA have a 2-10 folds increased risk of cardiovascular diseases (CVD) and CVD accounts for almost 50% of the excess mortality in patients with RA when compared with general population, but the mechanisms underlying such associations are largely unknown. Methods: We examined the genetic correlation, causality, and shared genetic variants between RA (Ncase=6,756, Ncontrol=452,476) and CVD (Ncase=44,246, Ncontrol=414,986) using LD Score regression (LDSC), generalized summary-data-based Mendelian Randomization (GSMR), and cross-trait meta-analysis in the UK Biobank Data. Results: In the present study, RA was significantly genetically correlated with MI, angina, CHD, and CVD after correcting for multiple testing (Rg ranges from 0.40 to 0.43, P<0.05/5). Interestingly, when stratified by frequent usage of aspirin and paracetamol, we observed increased genetic correlation between RA and CVD for participants without aspirin usage ( Rg increased to 0.54 [95%CI: 0.54, 0.78] for angina; P value=6.69х10 -6 ), and for participants with usage of paracetamol ( Rg increased to 0.75 [95%CI: 0.20, 1.29] for MI; P value=8.90х10 -3 ). Cross-trait meta-analysis identified 9 independent loci that were shared between RA and at least one of the genetically correlated CVD traits including PTPN22 at chr1p13.2 , BCL2L11 at chr2q13 , and CCR3 at chr3p21.31 ( P single trait <1х10 -3 and P meta <5х10 -8 ) highlighting potential shared etiology between them which include accelerating atherosclerosis and upregulating oxidative stress and vascular permeability. Finally, Mendelian randomization analyses observed inconsistent instrumental effects and were unable to conclude the causality and directionality between RA and CVD. Conclusion: Our results supported positive genetic correlation between RA and multiple cardiovascular traits, and frequent usage of aspirin and paracetamol may modify their associations, but instrumental analyses were unable to conclude the causality and directionality between them.

scholarly journals Evidence of causal effect of major depression on alcohol dependence: findings from the psychiatric genomics consortium

2019 ◽  
Vol 49 (07) ◽  
pp. 1218-1226 ◽  
Author(s):  
Renato Polimanti ◽  
Roseann E. Peterson ◽  
Jue-Sheng Ong ◽  
Stuart MacGregor ◽  
Alexis C. Edwards ◽  
...  
Keyword(s):  
Major Depression ◽  
Alcohol Dependence ◽  
Genetic Correlation ◽  
Causal Relationship ◽  
Causal Effect ◽  
Uk Biobank ◽  
Genome Wide ◽  
Genome Wide Data ◽  
Genetic Mechanisms ◽  
Shared Genetic

AbstractBackgroundDespite established clinical associations among major depression (MD), alcohol dependence (AD), and alcohol consumption (AC), the nature of the causal relationship between them is not completely understood. We leveraged genome-wide data from the Psychiatric Genomics Consortium (PGC) and UK Biobank to test for the presence of shared genetic mechanisms and causal relationships among MD, AD, and AC.MethodsLinkage disequilibrium score regression and Mendelian randomization (MR) were performed using genome-wide data from the PGC (MD: 135 458 cases and 344 901 controls; AD: 10 206 cases and 28 480 controls) and UK Biobank (AC-frequency: 438 308 individuals; AC-quantity: 307 098 individuals).ResultsPositive genetic correlation was observed between MD and AD (rgMD−AD = + 0.47, P = 6.6 × 10−10). AC-quantity showed positive genetic correlation with both AD (rgAD−AC quantity = + 0.75, P = 1.8 × 10−14) and MD (rgMD−AC quantity = + 0.14, P = 2.9 × 10−7), while there was negative correlation of AC-frequency with MD (rgMD−AC frequency = −0.17, P = 1.5 × 10−10) and a non-significant result with AD. MR analyses confirmed the presence of pleiotropy among these four traits. However, the MD-AD results reflect a mediated-pleiotropy mechanism (i.e. causal relationship) with an effect of MD on AD (beta = 0.28, P = 1.29 × 10−6). There was no evidence for reverse causation.ConclusionThis study supports a causal role for genetic liability of MD on AD based on genetic datasets including thousands of individuals. Understanding mechanisms underlying MD-AD comorbidity addresses important public health concerns and has the potential to facilitate prevention and intervention efforts.

A GENOME-WIDE ASSOCIATION STUDY IN PROGRESSIVE SUPRANUCLEAR PALSY

2015 ◽  
Vol 86 (11) ◽  
pp. e4.68-e4
Author(s):  
Zhongbo Chen ◽  
Aleksey Shatunov ◽  
Gilbert Bensimon ◽  
Christine Payan ◽  
Albert Ludolph ◽  
...  
Keyword(s):  
Progressive Supranuclear Palsy ◽  
Genome Wide Association Study ◽  
Meta Analysis ◽  
Genome Wide Association ◽  
Chromosome 17 ◽  
Gene Variants ◽  
Genome Wide ◽  
Mapt Gene ◽  
Common Genetic Variants ◽  
A Genome

BackgroundProgressive supranuclear palsy (PSP) is a debilitating Parkinsonian movement disorder characterised by tau protein burden. We aimed to identify common genetic variants influencing PSP susceptibility through a genome-wide association analysis (GWAS) of a multi-centre European study, Neuroprotection and Natural History in Parkinson's Plus Syndromes (NNIPPS), recruiting clinically well-characterised patients. We combined this with a meta-analysis of previously-identified gene variants.MethodsWe genotyped 275,684 single nucleotide polymorphisms using Illumina microarrays in 212 PSP cases from the UK, Germany and France, and compared these with 4,707 matched controls. GWAS was performed using PLINK. Meta-analysis was performed with METAL. Genome-wide significance was defined as p<5×10^–8.ResultsWe observed multiple associations on chromosome 17 within or close to the MAPT gene, a well-established risk locus for PSP, confirming the sample and method validity. Of nine other previously reported associations, meta-analysis only confirmed that the MOBP variation (rs1768208) modified PSP risk (p=3.29×10^–13).ConclusionIn the GWAS and meta-analysis, we found the chromosome 17 inversion region to be associated with PSP susceptibility. Furthermore, we have shown that MOBP can modify the risk of PSP, possibly through influencing oligodendrocyte tau inclusions. These identified gene variants provide novel insights into the underlying genetics of sporadic PSP.

scholarly journals Genome-wide association studies for canine hip dysplasia in single and multiple populations – implications and potential novel risk loci

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Shizhi Wang ◽  
Erling Strandberg ◽  
Per Arvelius ◽  
Dylan N. Clements ◽  
Pamela Wiener ◽  
...  
Keyword(s):  
Hip Dysplasia ◽  
Association Studies ◽  
Meta Analysis ◽  
Small Sample ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Single Population ◽  
Positional Candidate ◽  
Genome Wide ◽  
Canine Hip Dysplasia

Abstract Background Association mapping studies of quantitative trait loci (QTL) for canine hip dysplasia (CHD) can contribute to the understanding of the genetic background of this common and debilitating disease and might contribute to its genetic improvement. The power of association studies for CHD is limited by relatively small sample numbers for CHD records within countries, suggesting potential benefits of joining data across countries. However, this is complicated due to the use of different scoring systems across countries. In this study, we incorporated routinely assessed CHD records and genotype data of German Shepherd dogs from two countries (UK and Sweden) to perform genome-wide association studies (GWAS) within populations using different variations of CHD phenotypes. As phenotypes, dogs were either classified into cases and controls based on the Fédération Cynologique Internationale (FCI) five-level grading of the worst hip or the FCI grade was treated as an ordinal trait. In a subsequent meta-analysis, we added publicly available data from a Finnish population and performed the GWAS across all populations. Genetic associations for the CHD phenotypes were evaluated in a linear mixed model using 62,089 SNPs. Results Multiple SNPs with genome-wide significant and suggestive associations were detected in single-population GWAS and the meta-analysis. Few of these SNPs overlapped between populations or between single-population GWAS and the meta-analysis, suggesting that many CHD-related QTL are population-specific. More significant or suggestive SNPs were identified when FCI grades were used as phenotypes in comparison to the case-control approach. MED13 (Chr 9) and PLEKHA7 (Chr 21) emerged as novel positional candidate genes associated with hip dysplasia. Conclusions Our findings confirm the complex genetic nature of hip dysplasia in dogs, with multiple loci associated with the trait, most of which are population-specific. Routinely assessed CHD information collected across countries provide an opportunity to increase sample sizes and statistical power for association studies. While the lack of standardisation of CHD assessment schemes across countries poses a challenge, we showed that conversion of traits can be utilised to overcome this obstacle.

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