ObjectiveThe objective of this study was to aggregate data for the first genomewide association study meta-analysis of cluster headache, to identify genetic risk variants, and gain biological... Show moreObjectiveThe objective of this study was to aggregate data for the first genomewide association study meta-analysis of cluster headache, to identify genetic risk variants, and gain biological insights.MethodsA total of 4,777 cases (3,348 men and 1,429 women) with clinically diagnosed cluster headache were recruited from 10 European and 1 East Asian cohorts. We first performed an inverse-variance genomewide association meta-analysis of 4,043 cases and 21,729 controls of European ancestry. In a secondary trans-ancestry meta-analysis, we included 734 cases and 9,846 controls of East Asian ancestry. Candidate causal genes were prioritized by 5 complementary methods: expression quantitative trait loci, transcriptome-wide association, fine-mapping of causal gene sets, genetically driven DNA methylation, and effects on protein structure. Gene set and tissue enrichment analyses, genetic correlation, genetic risk score analysis, and Mendelian randomization were part of the downstream analyses.ResultsThe estimated single nucleotide polymorphism (SNP)-based heritability of cluster headache was 14.5%. We identified 9 independent signals in 7 genomewide significant loci in the primary meta-analysis, and one additional locus in the trans-ethnic meta-analysis. Five of the loci were previously known. The 20 genes prioritized as potentially causal for cluster headache showed enrichment to artery and brain tissue. Cluster headache was genetically correlated with cigarette smoking, risk-taking behavior, attention deficit hyperactivity disorder (ADHD), depression, and musculoskeletal pain. Mendelian randomization analysis indicated a causal effect of cigarette smoking intensity on cluster headache. Three of the identified loci were shared with migraine. Show less
Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry(1,2). Here, in cross... Show morePrevious genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry(1,2). Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis(3), and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach(4), we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry(5). Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries. Show less
Background The proportion of venous thromboembolism (VTE) events that can be attributed to established prothrombotic genotypes has been scarcely investigated in the general population. We aimed to... Show moreBackground The proportion of venous thromboembolism (VTE) events that can be attributed to established prothrombotic genotypes has been scarcely investigated in the general population. We aimed to estimate the proportion of VTEs in the population that could be attributed to established prothrombotic genotypes using a population-based case-cohort. Methods Cases with incident VTE ( n = 1,493) and a randomly sampled subcohort ( n = 13,069) were derived from the Tromso Study (1994-2012) and the Nord-Trondelag Health (HUNT) study (1995-2008). DNA samples were genotyped for 17 single-nucleotide polymorphisms (SNPs) associated with VTE. Hazard ratios with 95% confidence intervals (CIs) were estimated in Cox regression models. Population-attributable fractions (PAFs) with 95% bias-corrected CIs (based on 10,000 bootstrap samples) were estimated using a cumulative model where SNPs significantly associated with VTE were added one by one in ranked order of the individual PAFs. Results Six SNPs were significantly associated with VTE (rs1799963 [Prothrombin], rs2066865 [FGG], rs6025 [FV Leiden], rs2289252 [F11], rs2036914 [F11], and rs8176719 [ABO]). The cumulative PAF for the six-SNP model was 45.3% (95% CI: 19.7-71.6) for total VTE and 61.7% (95% CI: 19.6-89.3) for unprovoked VTE. The PAF for prothrombotic genotypes was higher for deep vein thrombosis (DVT; 52.9%) than for PE (33.8%), and higher for those aged <70 years (66.1%) than for those aged >= 70 years (24.9%). Conclusion Our findings suggest that 45 to 62% of all VTE events in the population can be attributed to known prothrombotic genotypes. The PAF of established prothrombotic genotypes was higher in DVT than in PE, and higher in the young than in the elderly. Show less
Osteoarthritis affects over 300 million people worldwide. Here, we conduct a genome-wide association study meta-analysis across 826,690 individuals (177,517 with osteoarthritis) and identify 100... Show moreOsteoarthritis affects over 300 million people worldwide. Here, we conduct a genome-wide association study meta-analysis across 826,690 individuals (177,517 with osteoarthritis) and identify 100 independently associated risk variants across 11 osteoarthritis phenotypes, 52 of which have not been associated with the disease before. We report thumb and spine osteoarthritis risk variants and identify differences in genetic effects between weight-bearing and non-weight-bearing joints. We identify sex-specific and early age-at-onset osteoarthritis risk loci. We integrate functional genomics data from primary patient tissues (including articular cartilage, subchondral bone, and osteophytic cartilage) and identify high-confidence effector genes. We provide evidence for genetic correlation with phenotypes related to pain, the main disease symptom, and identify likely causal genes linked to neuronal processes. Our results provide insights into key molecular players in disease processes and highlight attractive drug targets to accelerate translation. Show less
Background The role of combined prothrombotic genotypes in cancer-related venous thromboembolism (VTE) is scarcely studied. We aimed to investigate the impact of a 5-single nucleotide polymorphism ... Show moreBackground The role of combined prothrombotic genotypes in cancer-related venous thromboembolism (VTE) is scarcely studied. We aimed to investigate the impact of a 5-single nucleotide polymorphism (SNP) score on the risk of VTE in patients with and without cancer using a population-based case-cohort. Methods Cases with a first VTE (n = 1493) and a subcohort (n = 13 072) were derived from the Tromso Study (1994-2012) and the Nord-Trondelag Health Study (1995-2008). Five SNPs previously reported as a risk score were genotyped: ABO (rs8176719), F5 (rs6025), F2 (rs1799963), FGG (rs2066865), and F11 (rs2036914). Hazard ratios (HRs) for VTE were estimated according to cancer status and the number of risk alleles in the 5-SNP score (0-1, 2-3, and >= 4 alleles). Results During a median follow-up of 12.3 years, 1496 individuals were diagnosed with cancer, of whom 232 experienced VTE. The VTE risk increased with the number of risk alleles in the 5-SNP score among subjects without and with cancer. In cancer-free subjects, the HR was 2.17 (95% confidence interval [CI] 1.79-2.62) for >= 4 versus 0-1 risk alleles. In cancer patients, the corresponding HR was 1.93 (95% CI 1.28-2.91). The combination of cancer and >= 4 risk alleles yielded a 17-fold (HR 17.1, 95% CI 12.5-23.4) higher risk of VTE compared with cancer-free subjects with 0-1 risk alleles. Conclusion The risk of VTE increases with the number of prothrombotic risk alleles in subjects with and without cancer, and the combination of prothrombotic risk alleles and cancer leads to a highly elevated risk of VTE. Show less
Venous thromboembolism (VTE) is a frequent complication in patients with cancer. Homozygous carriers of the fibrinogen gamma gene (FGG) rs2066865 have a moderately increased risk of VTE, but the... Show moreVenous thromboembolism (VTE) is a frequent complication in patients with cancer. Homozygous carriers of the fibrinogen gamma gene (FGG) rs2066865 have a moderately increased risk of VTE, but the effect of the FGG variant in cancer is unknown. We aimed to investigate the effect of the FGG variant and active cancer on the risk of VTE. Cases with incident VTE (n=640) and a randomly selected age-weighted sub-cohort (n=3,734) were derived from a population-based cohort (the Tromso study). Cox-regression was used to estimate hazard ratios (HR) with 95% confidence intervals (CI) for VTE according to categories of cancer and FGG. In those without cancer, homozygosity at the FGG variant was associated with a 70% (HR 1.7, 95% CI: 1.2-2.3) increased risk of VTE compared to non-carriers. Cancer patients homozygous for the FGG variant had a twofold (HR 2.0, 95% CI: 1.1-3.6) higher risk of VTE than cancer patients without the variant. Moreover, the six-months cumulative incidence of VTE among cancer patients was 6.4% (95% CI: 3.5-11.6) in homozygous carriers of FGG and 3.1% (95% CI: 2.3-4.7) in those without risk alleles. A synergistic effect was observed between rs2066865 and active cancer on the risk of VTE (synergy index: 1.81, 95% CI: 1.02-3.21, attributable proportion: 0.43, 95% CI: 0.11-0.74). In conclusion, homozygosity at the FGG variant and active cancer yielded a synergistic effect on the risk of VTE. Show less
Venous thromboembolism (VTE) is a significant contributor to morbidity and mortality. To advance our understanding of the biology contributing to VTE, we conducted a genome-wide association study ... Show moreVenous thromboembolism (VTE) is a significant contributor to morbidity and mortality. To advance our understanding of the biology contributing to VTE, we conducted a genome-wide association study (GWAS) of VTE and a transcriptome-wide association study (TWAS) based on imputed gene expression from whole blood and liver. Wemeta-analyzedGWAS data from18 studies for 30 234 VTE cases and 172 122 controls and assessed the association between 12 923 718 genetic variants and VTE. We generated variant prediction scores of gene expression from whole blood and liver tissue and assessed them for association with VTE. Mendelian randomization analyses were conducted for traits genetically associated with novel VTE loci. We identified 34 independent genetic signals for VTE risk from GWAS meta-analysis, of which 14 are newly reported associations. This included 11 newly associated genetic loci (C1orf198, PLEK, OSMR-AS1, NUGGC/SCARA5, GRK5, MPHOSPH9, ARID4A, PLCG2, SMG6, EIF5A, and STX10) of which 6 replicated, and 3 new independent signals in 3 known genes. Further, TWAS identified 5 additional genetic loci with imputed gene expression levels differing between cases and controls in whole blood (SH2B3, SPSB1, RP11-747H7.3, RP4-737E23.2) and in liver (ERAP1). At some GWAS loci, we found suggestive evidence that the VTE association signal for novel and previously known regions colocalized with expression quantitative trait locus signals. Mendelian randomization analyses suggested that blood traits may contribute to the underlying risk of VTE. To conclude, we identified 16 novel susceptibility loci for VTE; for some loci, the association signals are likely mediated through gene expression of nearby genes. Show less
Background Family history of myocardial infarction (FHMI) is known to increase the risk of venous thromboembolism (VTE). Objectives To investigate the effect of prothrombotic genotypes on the... Show moreBackground Family history of myocardial infarction (FHMI) is known to increase the risk of venous thromboembolism (VTE). Objectives To investigate the effect of prothrombotic genotypes on the association between FHMI and VTE in a case-cohort recruited from a general population. Methods Cases with a first VTE (n = 1493) and a subcohort (n = 13 072) were sampled from the Tromso study (1994-2012) and the Nord-Trondelag health (HUNT) study (1995-2008). The DNA samples were genotyped for rs8176719 (ABO), rs6025 (F5), rs1799963 (F2), rs2066865 (FGG), and rs2036914 (F11). Participants with missing information on risk alleles (n = 175), FHMI (n = 2769), and BMI (n = 52) were excluded. Cox regression models were used to estimate hazard ratios (HRs) with 95% confidence intervals (CI) for VTE. To explore the role of prothrombotic genotypes for the association between FHMI and VTE, we (a) included the genotypes in the multivariable-adjusted models and (b) assessed the joint effects between FHMI and genotypes on VTE risk. Results The FHMI was associated with a 1.3-fold increased risk of VTE (HR 1.32, 95% CI 1.16-1.50) and 1.5-fold increased risk of unprovoked VTE (HR 1.47, 95% CI 1.22-1.78). The risk of VTE by FHMI did not alter after adjustment for the five genotypes. The combination of FHMI and the different prothrombotic genotypes did not result in an excess VTE risk (i.e. no biological interaction). Conclusions Our findings suggest that the risk of VTE by FHMI is not explained by rs8176719 (ABO), rs6025 (F5), rs1799963 (F2), rs2066865 (FGG), and rs2036914 (F11). The combination of FHMI with prothrombotic genotypes had an additive effect on VTE risk. Show less
