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These datasets underpin the analysis presented in the agency's work. Most data may be viewed interactively on screen and downloaded in Excel format. All countries. Topics A-Z. The content in this section is aimed at anyone involved in planning, implementing or making decisions about health and social responses. Best practice. We have developed a systemic approach that brings together the human networks, processes and scientific tools necessary for collecting, analysing and reporting on the many aspects of the European drugs phenomenon. Explore our wide range of publications, videos and infographics on the drugs problem and how Europe is responding to it. All publications. More events. More news. We are your source of drug-related expertise in Europe. We prepare and share independent, scientifically validated knowledge, alerts and recommendations. About the EUDA. Alongside the more well-known substances available on illicit drug markets, a number of other substances with hallucinogenic, anaesthetic, dissociative or depressant properties are used in Europe: these include LSD lysergic acid diethylamide , hallucinogenic mushrooms, ketamine, GHB gamma-hydroxybutyrate and nitrous oxide. On this page, you can find the latest analysis of the situation regarding these substances in Europe, including seizures, prevalence and patterns of use, treatment entry, harms and more. European Drug Report — home. The drug situation in Europe up to Drug supply, production and precursors. Synthetic stimulants. Heroin and other opioids. Other drugs. New psychoactive substances. Injecting drug use in Europe. Drug-related infectious diseases. Drug-induced deaths. Opioid agonist treatment. Harm reduction. Some of these substances appear to have become well-established in some countries, cities or specific populations, although overall their relative prevalence may remain low in comparison to some other better-known drug classes. However, for a variety of methodological and historical reasons, our current monitoring approaches often perform poorly in identifying patterns and trends in the use of less well-known substances. This makes it difficult to comment with confidence on the prevalence of use or recent trends, or on the extent to which these drugs are associated with health or social problems. The information available suggests, however, that in some countries, subgroups or settings, the use of these sorts of substances has become more common. As patterns of drug use can change rapidly and many of the drug-related problems we face are increasingly influenced by the co-consumption of multiple substances, there is a strong argument for increasing investment in the surveillance of substances with hallucinogenic, anaesthetic, dissociative or depressant properties. The quantity of ketamine seized and reported to the EU Early Warning System on new psychoactive substances has varied over time, but has remained at relatively high levels in recent years, tripling from just under a tonne in to 2. Seizures were reported by 17 countries in both years, with both Denmark and the Netherlands reporting large seizures, and these two countries together accounted for two thirds of the overall quantity of ketamine seized in Most of the ketamine seized in Europe is thought to originate from India, but there is some evidence that the drug may also be sourced from Pakistan and China. Available information suggests that production of the drug in Europe remains limited. Overall, there is evidence to suggest that ketamine is likely to be consistently available in some national drug markets and may have become an established drug of choice in some settings. It is also reported to be used in combination with other substances, such as stimulants. In Ireland, for example, the intentional mixing of cocaine and ketamine has been identified at music festivals, as have ketamine-related medical incidents during and In , Euro-DEN sentinel hospital emergency departments in Europe reported that cocaine was the substance most often reported in combination with ketamine in acute toxicity presentations. Ketamine is commonly snorted, but can also be injected, and has been linked to various dose-dependent acute and chronic harms, including neurological and cardiovascular toxicity, mental health problems, such as depression, and urological complications, such as bladder damage from intensive use or the presence of adulterants. Ketamine may also be added to other drug mixtures, including MDMA powders and tablets, potentially making inadvertent consumption an issue. In contrast to some other parts of the world, mixtures sold as pink cocaine are less likely to contain the synthetic drug 2C-B, which has historically been associated with this product. It is also interesting to note that while the overall figure remains low, both the quantity of 2C-B seized and the number of countries reporting seizures increased in , with 14 countries reporting seizures amounting to just under 6 kilograms of this drug. The number of clients reported to receive treatment for problems related to ketamine use remains low. However, it has risen from around cases reported in to in Moreover, this data set is not likely to capture all those having health problems with this drug. For example, those who have developed urological problems may be poorly represented. Nitrous oxide, commonly known as laughing gas, has been linked to various health problems, including poisonings, burns and lung injuries and, in some cases of prolonged exposure, neurotoxicity from vitamin B12 deficiency. There is, however, a debate on the extent to which this substance is associated with negative health risks, especially among episodic users, although given its apparent growing popularity among young people, this is clearly an important area for further research and monitoring. In some European cities, discarded nitrous oxide gas canisters have become a relatively common sight, and the disposal of the smaller stainless steel canisters has been identified as a drug-litter issue in some countries. The drug has become more accessible and cheaper, available online and with the increased availability of larger gas canisters aimed at recreational use. However, high-volume cylinders may also increase the risk of lung damage, due to the higher pressure of their contents and, in general, inhaling directly from gas bottles is reported to be associated with a greater risk of harm. Nitrous oxide has various commercial uses, for example, it is used by the catering industry. Regulatory approaches to the sale and use of this substance vary between countries, with the gas legally available for sale in some countries. Several EU countries, including Denmark, France, Lithuania, the Netherlands and Portugal have restricted the availability of nitrous oxide in recent years. There is limited evaluative information about the effectiveness of legislative or other approaches to restricting access to nitrous oxide. Non-controlled and new benzodiazepines also continued to be available in some European countries but, again, current monitoring approaches make it difficult to comment on the scale of their use, although signals exist that these substances may have important consequences for health, especially when consumed in combination with other drugs. They are often very cheap and may be used by young people in combination with alcohol, sometimes resulting in potentially serious health reactions or aberrant behaviour. These substances have also been linked to overdose deaths among people who use opioids. A lack of toxicological information means the role that benzodiazepines play in opioid-related deaths is not sufficiently understood. So far, seizures of benzo-dope have been reported by Estonia and Latvia. In both countries, the same mixtures have also been identified in residues analysed from used syringes. Both clinical and public interest has been growing in the therapeutic use of some novel substances, particularly psychedelic substances, but also dissociative drugs such as ketamine. At the same time, a growing number of clinical studies, both internationally and in Europe, are exploring the potential of a range of psychedelic substances to treat different mental health conditions. The evidence base in this area is growing rapidly, and some studies have produced evidence to support the view that some substances may have value in the treatment of specific neuropsychiatric disorders, such as post-traumatic stress disorder or treatment-resistant depression and major depressive disorder. However, the interpretation of the results is complicated by a range of methodological issues, and generalisation remains difficult as much of the research in this area remains at an early stage. Nonetheless, these developments have received considerable media attention, raising concerns that this may encourage greater experimental use of a range of potent psychoactive substances without appropriate medical support, potentially putting vulnerable individuals at risk of suffering adverse consequences. At the same time, there are signs of unregulated programmes being operated in the European Union and elsewhere, in which the use of psychedelic substances is included as part of a wellness, therapeutic or spiritually oriented intervention. Strengthening monitoring in this area will be important, as a growth of unlicensed therapeutic uses of psychedelics may adversely affect vulnerable individuals with pre-existing mental health conditions. Mean daily amounts of ketamine in milligrams per population. Sampling was carried out over a week in March and April For the complete data set and analysis, see Wastewater analysis and drugs — a European multi-city study. Increases were observed in the number of clients entering treatment for problems related to ketamine use in Belgium, Germany and Italy in and Spain in most recent data , with the overall number rising from in to an estimated clients in in these countries. Show source tables. The complete set of source data for the European Drug Report including metadata and methodological notes is available in our data catalogue. A subset of this data, used to generate infographics, charts and similar elements on this page, may be found below. Homepage Quick links Quick links. GO Results hosted on duckduckgo. Main navigation Data Open related submenu Data. Latest data Prevalence of drug use Drug-induced deaths Infectious diseases Problem drug use Treatment demand Seizures of drugs Price, purity and potency. Drug use and prison Drug law offences Health and social responses Drug checking Hospital emergencies data Syringe residues data Wastewater analysis Data catalogue. Selected topics Alternatives to coercive sanctions Cannabis Cannabis policy Cocaine Darknet markets Drug checking Drug consumption facilities Drug markets Drug-related deaths Drug-related infectious diseases. Recently published Findings from a scoping literature…. Penalties at a glance. Frequently asked questions FAQ : drug…. FAQ: therapeutic use of psychedelic…. Viral hepatitis elimination barometer…. EU Drug Market: New psychoactive…. EU Drug Market: Drivers and facilitators. Statistical Bulletin home. Quick links Search news Subscribe newsletter for recent news Subscribe to news releases. This make take up to a minute. Once the PDF is ready it will appear in this tab. Sorry, the download of the PDF failed. Table of contents Search within the book. Search within the book Operator Any match. Exact term match only. Main subject. Target audience. Publication type. European Drug Report main page. On this page.

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Leeuwarden buying MDMA pills

Thank you for visiting nature. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser or turn off compatibility mode in Internet Explorer. In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. A Publisher Correction to this article was published on 14 November 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. Effect sizes were highly correlated across ancestries. 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, 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. Characterized by a neurological deficit of sudden onset, stroke is predominantly caused by cerebral ischaemia of which the main aetiological subtypes are large-artery atherosclerotic stroke LAS , cardioembolic stroke CES , and small-vessel stroke SVS and, less often, by intracerebral haemorrhage ICH. The frequency of stroke subtypes differs between ancestry groups as exemplified by a higher prevalence of SVS and ICH in Asian and African populations compared with European populations. Most genetic loci associated with stroke have been identified in populations of European ancestry. To identify new genetic associations and provide insights into stroke pathogenesis and putative drug targets, we first performed a cross-ancestry GWAS of 1,, participants, including , patients who had a stroke, and followed up genome-wide significant signals in an independent dataset of 89, patients who had a stroke and 1,, control individuals. We then characterized the identified stroke risk loci by leveraging expression and protein quantitative trait loci, cross-ancestry fine-mapping and shared genetic variation with other traits. Finally, we used a series of approaches for genomics-driven drug discovery for stroke prevention and treatment, and examined the prediction of stroke with polygenic scores PGSs across ancestries in the setting of both population-based studies and clinical trials. We performed a fixed-effect inverse-variance weighted IVW GWAS meta-analysis on 29 population-based cohorts or biobanks with incident stroke ascertainment and 25 clinic-based case—control studies, comprising up to , patients who had a stroke and 1,, control individuals of whom Genome-wide genotyping and imputation characteristics are described in Supplementary Table 2. The cohorts included individuals of European The linkage-disequilibrium score intercepts for our ancestry-specific GWAS meta-analyses ranged from 0. Our results include a large and comprehensive description of stroke genetic risk variants in each of the five represented ancestries. In cross-ancestry meta-analyses, 53 loci 51 loci after controlling for ancestry-specific linkage-disequilibrium score intercepts reached genome-wide significance Supplementary Table 4 , whereas 42 loci were genome-wide significant in individual ancestries 35 in Europeans, 6 in East Asians, 1 in South Asians and 2 in African Americans; Supplementary Table 4. Ideogram showing 89 genome-wide significant stroke-risk loci. The nearest genes to lead variants are displayed. Loci are characterized as follows, on the basis of replication results Methods : bold with asterisk, high confidence; bold without asterisk, intermediate confidence; not bold, low confidence; underlined, loci identified in secondary MR-MEGA and MTAG analyses. Black and grey font indicate new and known loci, respectively. The numbers at the top indicate the chromosome. We followed up genome-wide significant stroke-risk loci both internally and externally. First, we sought to replicate the 42 stroke-risk loci that reached genome-wide significance in individual ancestries in at least one other ancestry group among the discovery samples. Second, we gathered an independent dataset of 89, individuals who had a stroke AS; of which 85, AIS; The 8 loci that did not replicate were labelled as low confidence Methods and Supplementary Table Four of these were ethnic specific and three were low-frequency variants that were monomorphic in some ancestries and were therefore probably underpowered for replication. Of the eight MTAG loci that did not replicate, seven showed a consistent directionality and four were subtype specific and were therefore underpowered to detect associations with AS or AIS. For the 60 loci associated with stroke risk derived from the IVW meta-analyses, we first demonstrated the added value in terms of locus discovery of including non-European samples, showing a clear gain in power beyond sample size increase, compared with the incremental addition of European ancestry samples Extended Data Fig. We next compared the per-allele effect size across the three ancestries with the largest sample size European, East Asian, African American. Fine-mapped variants are shown only in European and East Asian individuals insufficient power for other ancestries. Variants are coloured on the basis of their linkage disequilibrium with the cross-ancestry lead variant rs , shown by the purple diamonds. Shared variants between credible sets of European and East Asian participants are indicated by black circles. The red vertical lines represent the position of the lead variants in European rs and East Asian rs participants. The linkage disequilibrium of each ancestry was derived from the Genomes Project. To identify putative causal variants at stroke-risk loci identified through IVW meta-analyses, we performed multiple-causal-variant fine-mapping using SuSiE 12 , separately in European and East Asian participants Methods. We found overlapping credible sets between European and East Asian participants at SH3PXD2A 19 overlapping variants , suggesting that there is cross-ancestry-shared genetic architecture at this locus Fig. To detect putative causal regulatory variants, we conducted an in silico mutagenesis analysis using MENTR, a machine-learning method to precisely predict transcriptional changes caused by causal variants 3. From credible sets, we obtained 78 robust predictions of variant—transcript-model sets comprising 13 variants and 19 transcripts Supplementary Table 20 , involving multiple cell types, consistent with the diversity of mechanisms that underlie stroke aetiology. The same G allele has been associated with higher systolic blood pressure We examined shared genetic variation with 12 in Europeans and 10 in East Asians vascular risk factors and disease traits Methods and Supplementary Methods. In Europeans, the lead variants for stroke at 57 of the 89 primary and secondary risk loci The notable consistency of these with the main analyses confirmed their robustness against weak instrument bias Supplementary Table We confirmed directionality using the Steiger test Supplementary Table 24 and ruled out reverse causation with reverse MR Supplementary Table Notably, MR analyses performed with binary exposures should be interpreted with caution owing to the potential violations of the exclusion restriction assumption We identified 27 genes of which the genetically regulated expression is associated with stroke and its subtypes at the transcriptome-wide level and colocalized in at least one tissue 10 genes in arteries and heart; 6 genes in brain tissue; 17 genes across tissues. Of these genes, 18 overlapped with 11 genome-wide significant stroke-risk loci Extended Data Fig. For several genes of which bulk tissue expression levels showed evidence for association with stroke, human single-nucleus sequencing data of brain cells in the dorsolateral prefrontal cortex DLPFC showed distinct cell-specific gene expression patterns suggesting that multiple genes could be involved through different cell types 21 Extended Data Fig. Overall, we observed a significant enrichment mostly in brain vascular endothelial cells and astrocytes, possibly reflecting the importance of both vascular pathology and brain response to the vascular insult in modulating stroke susceptibility Extended Data Fig. We used a three-pronged approach for genomics-driven discovery of drugs for the prevention or treatment of stroke 4 Methods and Fig. This encompasses the previously described PDE3A and FGA genes 1 , which encode targets for cilostazol antiplatelet agent and alteplase thrombolytic drug acting through plasminogen 23 , respectively, as well as F11 , KLKB1 , F2 , TFPI and MUT , which encode targets for conestat alfa, ecallantide both used for hereditary angioedema , lepirudin, dalteparin both used to treat recurrent thromboembolism and vitamin B12, respectively Supplementary Table Second, we used Trans-Phar 24 to test the negative correlations between genetically determined case—control gene expression associated with stroke TWAS using all GTEx v. GR is a thromboxane A2 receptor antagonist that has been proposed as an alternative antiplatelet therapy for stroke prevention 25 , and further drugs of this class are under development Note that one of those drugs, terutroban, was evaluated in a phase III study but did not show non-inferiority against aspirin Additional studies are needed to disentangle causal associations and the most appropriate drug target in this region 29 , To further validate the candidate drugs and estimate their potential side effects, we investigated whether the drug-target genes were associated with stroke-related phenotypes using a phenome-wide association study PheWAS approach. By contrast, we observed no significant association with non-stroke-related phenotypes, suggesting the safety of targeting F We further confirmed the association of rs with venous thromboembolic disorders and that it has no association with other non-stroke-related phenotypes using the Phenoscanner database Supplementary Table Overlap enrichment analysis using GREP 22 top. Middle, integrating MR results using cis - and trans -pQTLs as instrumental variables with data from drug databases. Bottom, negative correlation tests between compound-regulated gene expression profiles and genetically determined case—control gene expression profiles using Trans-Phar. Overall, combining evidence from genomics-driven drug discovery approaches, characterization of stroke-risk loci missense variants, TWAS, PWAS, colocalization, pathway enrichment, MR with pQTL, MENTR and PoPS 34 , and previous knowledge from monogenic disease models and experimental data, we found evidence for the potential functional implication of 56 genes that should be prioritized for further functional follow-up, with evidence from multiple approaches for 20 genes Supplementary Table The iPGS analysis used two datasets for each ancestry for model training and evaluation, respectively. The participants in the training and evaluation datasets did not overlap and were not included in the input GWAS summary data. The age-, sex- and top 5 PC-adjusted hazard ratio HR per s. The two-sided P trend value was computed using Cox regression. The age-, sex- and top 5 PC-adjusted odds ratio OR per s. While this suggests that the transferability of iPGS models from Europeans to East Asians might be limited Supplementary Table 45 , it does indicate that an ancestry-specific stroke iPGS approach yields similar improvement in predictive ability relative to their base models. Following up on previous work 1 , 35 , we further examined whether a genetic risk score GRS based on genome-wide significant risk loci from the cross-ancestry IVW AS meta-analyses could identify individuals who are at higher risk of AIS after accounting for established risk factors in five clinical trials across the spectrum of cardiometabolic disease We observed substantial shared susceptibility to stroke across ancestries, with a strong correlation of effect sizes. Ancestry-specific meta-analyses in smaller non-European populations detected fewer loci than in Europeans that were nevertheless biologically plausible, for example, 3p12 and PTCH1 for SVS in African Americans. Rare variants at 3p12 were recently shown to be associated with WMH volume 36 , whereas common variants at PTCH1 were associated with functional outcome after ischaemic stroke in European individuals Extensive bioinformatics analyses highlight genes for prioritization in functional follow-up studies Supplementary Table For example, a promoter variant of SH3PXD2A , which encodes an adaptor protein that is involved in extracellular matrix degradation through invadopodia and podosome formation, was predicted to modulate its expression in macrophages FURIN expression levels across tissues were associated with an increased stroke risk. Our results provide genetic evidence for putative drug effects using three independent approaches, with converging results from two methods gene enrichment analysis and pQTL-based MR for drugs targeting F11 and KLKB1. A recombinant variant of human activated protein C encoded by PROC was found to be safe for the treatment of acute ischaemic stroke after thrombolysis, mechanical thrombectomy or both in phase 1 and 2 trials 3K3A-APC, NCT 43 , 44 , and is poised for an upcoming phase 3 trial. We investigated stroke PGSs across ancestries. These results were confirmed in several independent datasets. Our results highlight the importance of ancestry-specific and cross-ancestry genomic studies for the transferability of genomic risk prediction across populations, and the urgent need to substantially increase participant diversity in genomic studies, especially from the most under-represented regions such as Africa, to avoid exacerbation of health disparities in the era of precision medicine and precision public health Finally, leveraging data from 5 clinical trials in 52, patients with cardiometabolic disease, we showed that a cross-ancestry GRS predicted ischaemic stroke, independently of clinical risk factors, and outperforming previous genetic risk evaluation Notably, although the trials included predominantly European participants, consistent results were observed in East Asian participants. We provided independent validation of the vast majority of identified genome-wide significant associations and graded loci by level of confidence based on these findings. Despite the notable size of the follow-up study sample, with nearly 90, additional patients who had a stroke, this analysis remains underpowered, especially for low-frequency variants and ancestry- and subtype-specific associations, as most follow-up studies were derived from large biobanks with event ascertainment based on electronic health records and no suitable stroke subtype information. The muted risk prediction in clinical-trial participants with previous stroke history possibly points to the impact of selection or index event biases and secondary prevention therapy All of the participants provided written informed consent. Information on participating studies discovery and follow-up , study design, and definitions of stroke and stroke subtypes is provided in the Supplementary Information. Population characteristics of individual studies are provided in Supplementary Table 1. Genotyping methods, pre-imputation quality control of genotypes and imputation methods of individual cohorts discovery and follow-up are presented in Supplementary Table 2. Individual studies performed a GWAS using logistic regression or Cox regression in some longitudinal population-based cohorts testing association of genotypes with five stroke phenotypes AS, AIS, CES, LAS and SVS under an additive effect model, adjusting for age, sex, principal components of population stratification and study-specific covariates when needed Supplementary Table 2. Marker names and alleles were harmonized across studies. Duplicate markers were removed. The overall analytical strategy is shown in Extended Data Fig. We applied the covariate adjusted linkage disequilibrium score regression cov-LDSC method to ancestry-specific GWAS meta-analyses without GC correction to test for genomic inflation and to compute robust SNP-heritability estimates in admixed populations We conducted cross-ancestry GWAS meta-analyses without genomic correction and with correction of the linkage-disequilibrium score intercept for genomic inflation observed in individual ancestry-specific GWASs. These comprised eight biobanks 82, cases, , controls and four hospital-based cohorts 6, cases, 82, controls. We used Genomes phase 3 continental reference samples of European, East Asian, African, South Asian and South American for our Hispanic samples ancestry and to compute the linkage disequilibrium between variants for respective ancestry-specific gene-based analyses. We then systematically examined genetic correlations and potentially causal associations between vascular-risk traits and risk of stroke using linkage-disequilibrium score regression LDSC and MR analyses, with 12 in Europeans and 6 in East Asians vascular-risk traits. In individuals of European ancestry, we used summary statistics of the aforementioned GWASs 32 , 54 , 55 , 56 , 59 , 60 , 61 , After extraction of the association estimates and harmonization of their direction-of-effect alleles, we computed MR estimates with fixed-effect IVW analyses We further applied alternative MR methods that are more robust to the use of pleiotropic instruments: the weighted median estimator enables the use of invalid instruments under the assumption that at least half of the instruments used in the MR analysis are valid 65 ; MR-Egger regression allows for the estimation of an intercept term, provides less precise estimates and relies on the assumption that the strengths of potential pleiotropic instruments are independent of their direct associations with the outcome MR analyses were performed in R v. Fine-mapping was performed separately for Europeans and East Asians using susieR v. After extracting variants present in the linkage disequilibrium reference panel, the default settings of susieR were used while allowing for a maximum of 10 putative causal variants in each locus. The fine-mapping results were checked for potential false-positive findings using a diagnostic procedure implemented in SuSiE. In brief, we compared observed and expected z -scores for each variant at a given locus and removed the variant if the difference between the observed and expected z -score was too high after manual inspection. We compared the variants in credible sets of the same loci between Europeans and East Asians. The in silico mutations predicted to have strong effects are highly concordant with the observed effects of known variants in a cell-type-dependent manner. Furthermore, MENTR does not use population datasets and is therefore less susceptible to linkage-disequilibrium-dependent association signals, enabling precise prediction of the effects of causal variants on transcriptional changes. As a result, we found 37, variant—transcript pairs comprising 1, variants and 2, transcripts. We restricted the analysis to tissues considered to be relevant for cerebrovascular disease, and used precomputed functional weights from 21 publicly available eQTL reference panels from blood Netherlands Twin Registry; Young Finns Study 19 , 20 , arterial and heart GTEx v. Moreover, we used the newly developed cross-tissue weights generated in GTEx v. Transcriptome-wide significant genes eGenes and the corresponding eQTLs were determined using Bonferroni correction, based on the average number of features We then followed the same method as described for the TWAS. RNA profiles of cells annotated as endothelial, pericytes or smooth muscle cells and vascular leptomeningeal cells VLMC were used, and a pseudobulk RNA profile was generated for each cell type by averaging the expression of all genes across the cells. Average expression levels and the percentage of expressed genes were calculated for genes of interest using the DotPlot function from the Seurat package v. Stroke GWAS summary statistics were first munged. Expression specificity profiles were then calculated using human and mouse single-cell RNA-seq databases Supplementary Table P values were corrected for the number of independent cell types in each database Bonferroni correction. We used three methodologies for in-depth genomics-driven drug discovery as described previously 4 : 1 an overlap enrichment analysis of disease-risk genes in drug-target genes in medication categories; 2 negative correlation tests between genetically determined case—control gene expression profiles and compound-regulated gene expression profiles; and 3 endophenotype MR. Details of the methods are described in the following sections. As for the endophenotype MR, we curated drugs with opposite effects against the signs of the MR effect estimates. By contrast, the negative correlation tests directly prioritized candidate compounds. We manually curated supporting evidence for candidate drugs and compounds. We nominated the compounds with inverse effects on gene expression against genetically determined gene expression by using Trans-Phar In brief, genetically determined case—control gene expression was inferred for 44 tissues in the Genotype-Tissue Expression project v. We used the tier 1 lead variants defined in ref. We restricted the lead variants to the variants associated with drug-target proteins. For the lead variants of pQTLs that were missing in the stroke GWAS summary statistics, the proxy variants with the largest r 2 were used if the r 2 was greater than 0. If SuSiE did not converge after 10, iterations, coloc was used instead. We considered that colocalization occurred when the maximum posterior probability that is, PP. H4 was greater than 0. As stroke and stroke-related traits, we extracted 30 traits belonging to 9 vascular risk factor and disease categories Supplementary Table We applied Bonferroni correction and the corrected P -value threshold was 0. PheWAS analysis was performed using R v. We tested the associations between phecodes and genetic variants using logistic regression and adjusting for sex, birth year and ten genotype PCs. We applied Bonferroni correction to select statistically significant associations number of tested phecodes: 1,; number of tested SNPs: 8; corrected P- value threshold: 0. The results were visualized using the PheWAS library. To further characterize the associations of the genetic variants with other phenotypes, we searched for all eight SNPs in the PhenoScanner database 97 , For each ancestry, independent datasets were used for model training and evaluation. The plink v. Subsequently, among the 37 candidate models, the best sPGS model, which was defined as the model that showed a maximal improvement in AUC over a base model age, sex and top five PCs were included in the base model , was selected using the model training dataset 5 , Then, each retained best sPGS was z -transformed zero mean and unit s. Coefficients weights for the retained sPGS models were then determined by elastic-net logistic regression with the optimal regularization parameters, followed by integration of the sPGS models into a single iPGS model according to a formula presented previously 5. Elastic-net regression was performed using the glmnet R package The predictive ability of the iPGS model was estimated using the model-evaluation dataset, whereby we evaluated the improvement in C -index for a prospective cohort dataset or AUC for a case-control dataset over a base model that includes age, sex and top five genetic PCs. The model-training dataset was composed of 1, cases of prevalent AIS at the baseline and 8, control individuals. The control individuals were randomly selected among EstBB participants who had no history of AS at the baseline and who did not develop AS during the follow-up. Among the participants in the model-evaluation dataset, 1, cases of incident AIS were observed during 4. The model-training dataset was composed of cases of AIS and 9, control individuals, whereas there were 1, cases of AIS and 40, control individuals in the model-evaluation dataset. The percentage of male participants was Methods for genotyping and imputation have previously been published 35 , and are summarized in Supplementary Table 2. A set of 58 sentinel variants at stroke-risk loci identified in the IVW meta-analysis was used to calculate a GRS for each trial participant and identify tertiles of genetic risk Supplementary Table A Cox model was used to estimate HRs for ischaemic stroke associated with the quantitative GRS and across genetic risk groups, adjusted for clinical risk factors age, sex, hypertension, hyperlipidaemia, diabetes, smoking, CAD, atrial fibrillation and congestive heart failure and the first five principal components of population stratification. We also looked separately at associations with incident stroke in participants with and without previous stroke. Further information on research design is available in the Nature Research Reporting Summary linked to this article. Individual level data can be requested directly from the authors of the contributing studies, listed in Supplementary Table 1. Malik, R. Multiancestry genome-wide association study of , subjects identifies 32 loci associated with stroke and stroke subtypes. Traylor, M. Genetic basis of lacunar stroke: a pooled analysis of individual patient data and genome-wide association studies. Lancet Neurol. Koido, M. Predicting cell-type-specific non-coding RNA transcription from genome sequence. Namba, S. A practical guideline of genomics-driven drug discovery in the era of global biobank meta-analysis. Abraham, G. Genomic risk score offers predictive performance comparable to clinical risk factors for ischaemic stroke. GBD Stroke Collaborators. 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A novel approach for pathway analysis of GWAS data highlights role of BMP signaling and muscle cell differentiation in colorectal cancer susceptibility. Burgess, S. Bias due to participant overlap in two-sample Mendelian randomization. GTEx Consortium. Genetic effects on gene expression across human tissues. Nature , — Fromer, M. Gene expression elucidates functional impact of polygenic risk for schizophrenia. Gusev, A. Integrative approaches for large-scale transcriptome-wide association studies. Wright, F. Heritability and genomics of gene expression in peripheral blood. Cain, A. Sakaue, S. Bioinformatics 35 , — Wishart, D. DrugBank 5. Nucleic Acids Res. Konuma, T. Integration of genetically regulated gene expression and pharmacological library provides therapeutic drug candidates. Chamorro, A. TP receptor antagonism: a new concept in atherothrombosis and stroke prevention. Yan, A. Bousser, M. Lancet , — Safdar, H. 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Evolocumab and clinical outcomes in patients with cardiovascular disease. Predicting benefit from evolocumab therapy in patients with atherosclerotic disease using a genetic risk score: results from the FOURIER trial. Download references. Detailed acknowledgements are provided in the Supplementary Information. We thank the participants and staff of contributing studies. These authors jointly supervised this work: Christian T. Ruff, Mayowa O. Owolabi, Jennifer E. Rainer Malik, Marios K. Daniel C. Frederick K. Kamanu, Nicholas A. Marston, Marc S. Marios K. Georgakis, Livia Parodi, Phil L. Anderson, Guido J. Falcone, Phil L. Pedersen, Amy E. Martinsen, Espen S. Brumpton, Jonas B. Nielsen, Maiken E. Gabrielsen, Anne H. Skogholt, Ben M. Brumpton, Maiken E. Gabrielsen, Amy E. Martinsen, Jonas B. Nielsen, Kristian Hveem, Laurent F. Vinodh Srinivasasainagendra, Hemant K. Rufus Akinyemi, Abiodun M. Gennady V. Roshchupkin, Maria J. Knol, Cornelia M. Department of Epidemiology, Harvard T. Adam J. Nicole D. Armstrong, Marguerite R. Mark K. Bakker, L. Jaap Kappelle, Sara L. Traci M. Bartz, Joshua C. Bis, Bruce M. Psaty, Kerri L. Wiggins, Joshua C. Bartz, Natalie C. Paul M. Ridker, Franco Giulianini, Julie E. Ridker, Julie E. Leslie E. Ferreira, Leslie E. Mirjam I. Geerlings, N. Charlotte Onland-Moret, Paul I. Geerlings, Jet M. Vonk, N. Charlotte Onland-Moret, Ina L. Aki S. Hyacinth I. Hyacinth, Daniel Woo, Brett M. Mina A. Swiss Institute of Bioinformatics, Lausanne, Switzerland. Hugh S. Braxton D. Felipe A. Bruce M. Psaty, Nicholas L. Heckbert, Alexander P. Jonathan Rosand, Christopher D. Evelyn F. Muralidharan Sargurupremraj, Claudia L. Claudia L. Puurunen, Chris J. DeStefano, Hugo J. Aparicio, Alexa S. Beiser, Ayesha Chowhan, Jose R. Romero, Alexa S. Carsten O. Qiong Yang, Anita L. DeStefano, Alexa S. Beiser, Alexa S. Kent D. Taylor, Kent D. Christopher D. Hugo J. Aparicio, Ayesha Chowhan, Jose R. Abiodun M. Adeoye, Adekunle G. Alan B. Zonderman, Michele K. Evans, Tamara B. Rebecca F. Gottesman, Rebecca F. Raji P. Erin N. Smith, Kelly A. Frazer, Sigrid K. Mariza de Andrade, Sebastian M. Armasu, Bryan M. Rebecca D. Jackson, Rebecca D. Jonas B. Nielsen, Cristen J. Paul J. Nederkoorn, Marieke C. Arne G. John Danesh, Adam S. Giorgio B. Landspitali University Hospital, Reykjavik, Iceland. Anne H. You can also search for this author in PubMed Google Scholar. Debette, M. Debette and M. Konuma, Y. Trompet, J. Mishra, S. Strbian, Q. Lepik, J. Shi, Y. Koido, A. Mishra, Q. Lin, M. He, K. Srinivasasainagendra, Y. Meitinger, K. Cho, K. Sasaki, C. Strbian, J. Saleheen, R. Hata, J. Koido, T. Kitazono, S. Tiedt, M. Morisaki, T. Meitinger, M. Kamouchi, Y. Debette, I. Damrauer, S. Salomaa, Y. Lee and Y. Mishra, R. Shi, K. All of the authors provided critical revision. Correspondence to Martin Dichgans or Stephanie Debette. Damrauer receives research support from RenalytixAI and personal consulting fees from Calico Labs, outside the scope of the current research. The funders of the study had no role in the collection, analysis or interpretation of data, in the writing of the report or in the decision to submit the paper for publication. Koido, Q. Srinivasasainagendra, L. Cho, Z. Kamouchi, K. Lee, K. Manichaikul, H. Meitinger, B. Saleheen, E. Salomaa, M. Tiedt, T. Trompet, A. Strbian, Y. Christensen, M. Debette declare no competing interests. Nature thanks Paul Timmers and the other, anonymous, reviewer s for their contribution to the peer review of this work. Peer reviewer reports are available. Study workflow and rationale. The scatter plot shows the number of loci identified with incremental increase in sample size and population diversity. The diagonal line reflects the increase in number of genome-wide significant loci with increasing sample size of European ancestry only. Colours represent the Z-scores of association of stroke risk increasing alleles with the trait. CPD: cigarettes per day. Dashed line indicates an odds ratio of 1. Each triangle in the plot represents one Phecode and the direction of the triangle represents direction of effect. B The significant PGS models were used as the variables for elastic-net logistic regression and the weights for the variables were trained using the model training dataset. The European iPGS model consisting of 1,, variants and an East-Asian iPGS model consisting of 6,, variants were constructed by combining the 11 and 7 significant PGS models using the elastic-net derived weights respectively. Reprints and permissions. Stroke genetics informs drug discovery and risk prediction across ancestries. Download citation. Received : 15 December Accepted : 29 July Published : 30 September Issue Date : 03 November Anyone you share the following link with will be able to read this content:. Sorry, a shareable link is not currently available for this article. Provided by the Springer Nature SharedIt content-sharing initiative. European Journal of Medical Research Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily. Skip to main content Thank you for visiting nature. Download PDF. Subjects Genetic markers Genome-wide association studies Predictive markers Stroke. This article has been updated. Abstract 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. Genetics of common cerebral small vessel disease Article 05 January Genetic discovery from GWASs We performed a fixed-effect inverse-variance weighted IVW GWAS meta-analysis on 29 population-based cohorts or biobanks with incident stroke ascertainment and 25 clinic-based case—control studies, comprising up to , patients who had a stroke and 1,, control individuals of whom Full size image. Independent follow-up of GWAS signals We followed up genome-wide significant stroke-risk loci both internally and externally. Cross-ancestry effects and fine-mapping For the 60 loci associated with stroke risk derived from the IVW meta-analyses, we first demonstrated the added value in terms of locus discovery of including non-European samples, showing a clear gain in power beyond sample size increase, compared with the incremental addition of European ancestry samples Extended Data Fig. Genomics-driven drug discovery We used a three-pronged approach for genomics-driven discovery of drugs for the prevention or treatment of stroke 4 Methods and Fig. Risk prediction in clinical trials Following up on previous work 1 , 35 , we further examined whether a genetic risk score GRS based on genome-wide significant risk loci from the cross-ancestry IVW AS meta-analyses could identify individuals who are at higher risk of AIS after accounting for established risk factors in five clinical trials across the spectrum of cardiometabolic disease Study design and phenotypes Information on participating studies discovery and follow-up , study design, and definitions of stroke and stroke subtypes is provided in the Supplementary Information. Genotyping, imputation and GWASs Genotyping methods, pre-imputation quality control of genotypes and imputation methods of individual cohorts discovery and follow-up are presented in Supplementary Table 2. Cross-ancestry fine mapping Fine-mapping was performed separately for Europeans and East Asians using susieR v. Genomics-driven drug discovery We used three methodologies for in-depth genomics-driven drug discovery as described previously 4 : 1 an overlap enrichment analysis of disease-risk genes in drug-target genes in medication categories; 2 negative correlation tests between genetically determined case—control gene expression profiles and compound-regulated gene expression profiles; and 3 endophenotype MR. Negative correlation tests between genetically determined and compound-regulated gene expression profiles We nominated the compounds with inverse effects on gene expression against genetically determined gene expression by using Trans-Phar Reporting summary Further information on research design is available in the Nature Research Reporting Summary linked to this article. References Malik, R. Article Google Scholar Nielsen, J. Article Google Scholar Chang, C. Acknowledgements Detailed acknowledgements are provided in the Supplementary Information. Posner These authors jointly supervised this work: Christian T. Frazer K. View author publications. Keene , Hyacinth I. Hyacinth , Joshua C. Bis , Steven J. Kittner , Braxton D. Chong , Stephen S. Rich , Mike A. Nalls , Hugh S. Markus , Thomas H. Mosley , Daniel Woo , W. Longstreth , Bruce M. Psaty , Ralph L. Sale , Alan B. Zonderman , Michele K. Evans , James G. Lewis , Cara L. Langefeld , Rebecca F. Lange , Karen L. Furie , Donna K. Arnett , Oscar R. Benavente , Raji P. Chasman , Kerri L. Wiggins , Jerome I. Rotter , Bruce M. Brody , Jack W. Pattee , Jeffrey Haessler , Ben M. Braekkan , Sebastian M. Armasu , Nathan Pankratz , Rebecca D. Jackson , Jonas B. Nielsen , Franco Giulianini , Marja K. Puurunen , Manal Ibrahim , Susan R. Heckbert , Theo K. Bammler , Bryan M. McCauley , Kent D. Taylor , James S. Pankow , Alexander P. Reiner , Maiken E. Rosendaal , John A. Bakker , Ynte M. Ruigrok , Ewoud J. Nederkoorn , Robert J. Visser , Marieke J. Jaap Kappelle. Vaura , Teemu J. Cole , Christina Jern , Steven J. Kittner , Hugh S. Markus , Braxton D. Mitchell , Jonathan Rosand , Ralph L. Thijs , Arne G. Rexrode , Peter M. Rothwell , Leslie A. Lange , Tara M. Stanne , Julie A. Johnson , John Danesh , Adam S. Jackson , Owen A. Bartz , Paul M. Ridker , Carlos Cruchaga , John W. Havulinna , Jemma C. Hopewell , Hyacinth I. Keene , Takanari Kitazono , Steven J. Kittner , Ani Manichaikul , Hugh S. Mitchell , Thomas H. Mosley , Mike A. Nalls , Martin J. Psaty , Stephen S. Rich , Jonathan Rosand , Ralph L. Satizabal , Carsten O. Howson , Marguerite R. Ikram , Tatjana Rundek , Bradford B. Worrall , W. Chasman , Jerome I. Rotter , Christopher D. Lopez , Cara L. Carty , Adolfo Correa , Raji P. Grewal , Jeffrey Haessler , Susan R. Lange , Carl D. Lewis , James F. Wilson , Donna K. Boncoraglio , Robert D. Brown Jr , Adam S. Butterworth , Caty Carrera , Julie E. Engelter , Guido J. Falcone , Rebecca F. Harris , Julie A. Johnson , Brett M. Kissela , Dawn O. Lindgren , Erik Lorentzen , Patrik K. Magnusson , Jane Maguire , Patrick F. McArdle , Sara L. Rexrode , Kenneth Rice , Peter M. Rothwell , Saori Sakaue , Bishwa R. Sudlow , Christian Tanislav , Vincent N. Wareham , Najaf Amin , Hugo J. Aparicio , John Attia , Alexa S. Koudstaal , Daniel L. Labovitz , Cathy C. Laurie , Christopher R. Parati , Nancy L. Romero , Anthony G. Stanne , O. Colin Stine , David J. Uitterlinden , Einar M. Valdimarsson , Sven J. Williams , Charles D. Tiwari , Mayowa O. Owolabi , Onoja Akpa , Fred S. Millwood , Robin G. Sun , Peter W. Knol , Mark K. Bakker , Joshua C. Cole , Leslie E. Ferreira , Jemma C. Hyacinth , Christina Jern , Keith L. Keene , Steven J. Mitchell , Yukinori Okada , Stephen S. Sacco , Muralidharan Sargurupremraj , Claudia L. Ruigrok , W. Walters , Mayowa O. Roshchupkin , Hampton L. Leonard , Chaojie Yang , Maria J. Knol , Traci M. Bartz , Joshua C. Bis , Constance Bordes , Paul M. Ridker , Mirjam I. Geerlings , Natalie C. Launer , Ani Manichaikul , Thomas H. Nalls , Stephen S. Rich , Muralidharan Sargurupremraj , Claudia L. Grabe , J. Wouter Jukema , Ina L. Ikram , Moeen Riaz , Eleanor M. Simonsick , W. Longstreth , Daniel I. Gottesman , Naveed Sattar , David J. Stott , Eric J. Shiroma , Oscar L. Aparicio , Alexa S. Beiser , Jose R. Posner , Frederick K. Knol , Adam J. Lewis , Renae L. Armstrong , Mark K. Bakker , Traci M. Bartz , David A. Bennett , Joshua C. Cole , Phil L. Ferreira , Mirjam I. Hyacinth , Michael Inouye , Mina A. Jacob , Christina E. Markus , Nicholas A. Marston , Thomas Meitinger , Braxton D. Mitchell , Felipe A. Montellano , Takayuki Morisaki , Thomas H. Nordestgaard , Martin J. Rich , Jonathan Rosand , Marc S. Sabatine , Ralph L. Schmidt , Atsushi Shimizu , Nicholas L. Smith , Kelly L. Sloane , Yoichi Sutoh , Yan V. Torres-Aguila , Hemant K. Verma , Kerri L. Anderson , Marguerite R. Worrall , G. Ruigrok , Peter Ulrich Heuschmann , W. Damrauer , Daniel I. Walters , Christian T. Ruff , Mayowa O. Owolabi , Jennifer E. Vermeer , Paul J. Brouwers , Rob A. Gons , Paul J. Nederkoorn , Tom den Heijer , Robert J. Aamodt , Anne H. Skogholt , Ben M. Brumpton , Cristen J. Fritsche , Linda M. Pedersen , Maiken E. Martinsen , Espen S. Kristoffersen , Jonas B. Rissanen , Mirjam I. Geerlings , Jessica van Setten , Sander W. Charlotte Onland-Moret , Alicia K. Heath , Christopher D. Ethics declarations Competing interests C. Peer review Peer review information Nature thanks Paul Timmers and the other, anonymous, reviewer s for their contribution to the peer review of this work. Extended data figures and tables. Extended Data Fig. Reporting Summary. Peer Review File. Supplementary Tables Supplementary Tables 1— About this article. Cite this article Mishra, A. Copy to clipboard. This article is cited by NeuroimaGene: an R package for assessing the neurological correlates of genetically regulated gene expression Xavier Bledsoe Eric R. Schmidt Michael H. Search Search articles by subject, keyword or author. Show results from All journals This journal. Advanced search. Close banner Close. Email address Sign up. Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing.

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