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Funding: This work was supported by grants from the Emergency Medicine Foundation Career Development Grant; AHA Mentored Clinical & Population Research Award (14CRP18860027); NIH/NINDS-R01-NS085419 (C.C., J.M.L.); NIH/NINDS-R37-NS107230, NIH/NINDS U24-NS107230 (J.M.L.); NIH/NINDS-K23-NS099487 (L.H.); NIH/NIA-K99-AG062723 (L.I.); Barnes-Jewish Hospital Foundation (J.M.L.); Biogen (C.C., J.M.L.); Bright Focus Foundation, US Department of Defense, Helsinki University Central Hospital; Finnish Medical Foundation; Finland government subsidiary funds; Spanish Ministry of Science and Innovation; Instituto de Salud Carlos III (grants ‘Registro BASICMAR’ Funding for Research in Health (PI051737), ‘GWALA project’ from Fondos de Investigación Sanitaria ISC III (PI10/02064, PI12/01238 and PI15/00451), JR18/00004); Fondos FEDER/EDRF Red de Investigación Cardiovascular (RD12/0042/0020); Fundació la Marató TV3; Genestroke Consortium (76/C/2011); Recercaixa’13 (JJ086116). Tomás Sobrino (CPII17/00027), Francisco Campos (CPII19/00020) and Israel Fernandez are supported by Miguel Servet II Program from Instituto de Salud Carlos III and Fondos FEDER. I.F. is also supported by Maestro project (PI18/01338) and Pre-test project (PMP15/00022) from Instituto de Salud Carlos III and Fondos Feder, Agaur; and Epigenesis project from Marató TV3 Foundation. J.C., J.M., A.D., J.M.-F., J.A. and I.F. are supported by Invictus plus Network (RD16/0019) from Instituto de Salud Carlos III and Fondos Feder. Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP-2013/07559-3) (I.L.-C.), Sigrid Juselius Foundation. The MEGASTROKE project received funding from sources specified at http://www.megastroke.org/acknowledgments.html. B.S., B.A. and F.S. are supported by NIH awards NS097000, NS101718, NS075035, NS079153 and NS106950. During the first hours after stroke onset, neurological deficits can be highly unstable: some patients rapidly improve, while others deteriorate. This early neurological instability has a major impact on long-term outcome. Here, we aimed to determine the genetic architecture of early neurological instability measured by the difference between the National Institutes of Health Stroke Scale (NIHSS) within 6h of stroke onset and NIHSS at 24h. A total of 5876 individuals from seven countries (Spain, Finland, Poland, USA, Costa Rica, Mexico and Korea) were studied using a multi-ancestry meta-analyses. We found that 8.7% of NIHSS at 24h of variance was explained by common genetic variations, and also that early neurological instability has a different genetic architecture from that of stroke risk. Eight loci (1p21.1, 1q42.2, 2p25.1, 2q31.2, 2q33.3, 5q33.2, 7p21.2 and 13q31.1) were genome-wide significant and explained 1.8% of the variability suggesting that additional variants influence early change in neurological deficits. We used functional genomics and bioinformatic annotation to identify the genes driving the association from each locus. Expression quantitative trait loci mapping and summary data-based Mendelian randomization indicate that ADAM23 (log Bayes factor = 5.41) was driving the association for 2q33.3. Gene-based analyses suggested that GRIA1 (log Bayes factor = 5.19), which is predominantly expressed in the brain, is the gene driving the association for the 5q33.2 locus. These analyses also nominated GNPAT (log Bayes factor = 7.64) ABCB5 (log Bayes factor = 5.97) for the 1p21.1 and 7p21.1 loci. Human brain single-nuclei RNA-sequencing indicates that the gene expression of ADAM23 and GRIA1 is enriched in neurons. ADAM23, a presynaptic protein and GRIA1, a protein subunit of the AMPA receptor, are part of a synaptic protein complex that modulates neuronal excitability. These data provide the first genetic evidence in humans that excitotoxicity may contribute to early neurological instability after acute ischaemic stroke. Postprint

Background: Multi-phenotype analysis of genetically correlated phenotypes can increase the statistical power to detect loci associated with multiple traits, leading to the discovery of novel loci. This is the first study to date to comprehensively analyze the shared genetic effects within different hemostatic traits, and between these and their associated disease outcomes. Objectives: To discover novel genetic associations by combining summary data of correlated hemostatic traits and disease events. Methods: Summary statistics from genome wide-association studies (GWAS) from seven hemostatic traits (factor VII [FVII], factor VIII [FVIII], von Willebrand factor [VWF] factor XI [FXI], fibrinogen, tissue plasminogen activator [tPA], plasminogen activator inhibitor 1 [PAI-1]) and three major cardiovascular (CV) events (venous thromboembolism [VTE], coronary artery disease [CAD], ischemic stroke [IS]), were combined in 27 multi-trait combinations using metaUSAT. Genetic correlations between phenotypes were calculated using Linkage Disequilibrium Score Regression (LDSC). Newly associated loci were investigated for colocalization. We considered a significance threshold of 1.85 × 10−9 obtained after applying Bonferroni correction for the number of multi-trait combinations performed (n = 27). Results: Across the 27 multi-trait analyses, we found 4 novel pleiotropic loci (XXYLT1, KNG1, SUGP1/MAU2, TBL2/MLXIPL) that were not significant in the original individual datasets, were not described in previous GWAS for the individual traits, and that presented a common associated variant between the studied phenotypes. Conclusions: The discovery of four novel loci contributes to the understanding of the relationship between hemostasis and CV events and elucidate common genetic factors between these traits.

Chagas disease, caused by the protozoan parasite Trypanosoma cruzi, is a vector-borne disease with a major disease burden in the Americas, with over 6 million cases. There are about 200,000 cases in Ecuador, but the epidemiology of the disease is poorly understood, particularly in the Amazon region, making surveillance and control challenging. We determined here the seroprevalence of T. cruzi antibodies in a cohort of 516 schoolchildren aged 5–15 years from Chontapunta parish, in the Napo province, Ecuador, using ELISA and indirect hemaglutination tests. We detected a seroprevalence of 0.77% (95% confidence interval 0.31–1.97%), with some significant variation among the three studied communities. These data provide evidence of the ongoing transmission of T. cruzi in this area, and support the need to strengthen epidemiological surveillance and patient care.

Perivascular space burden (PVS) is an emerging and possibly the earliest magnetic resonance imaging (MRI)-marker of cerebral small vessel disease (cSVD), a leading cause of stroke and dementia. Its molecular underpinnings are unknown. Genome-wide and whole-exome association studies in 40,095 participants (21 population-based cohorts, 66.3±8.6 years) revealed 24 genome-wide significant PVS risk loci. These showed association with white matter PVS already at age 20, suggesting an important role of early-life factors. PVS loci were enriched in genes causing early-onset leukodystrophies and genes expressed in fetal brain endothelial cells. Mendelian randomization analyses supported causal associations of high blood pressure with basal ganglia (BG) and hippocampal PVS, and of BG PVS with stroke. Transcriptome-wide association studies suggest causal implication of 11 genes, to prioritize for experimental follow-up as putative biotargets for cSVD. Two-thirds of PVS loci point to novel pathways, involving extracellular matrix, membrane transport, and developmental processes, with enrichment in targets of existing drugs for vascular/cognitive disorders.

Producción Científica, Stroke is one of the most common causes of death and disability. Reperfusion therapies are the only treatment available during the acute phase of stroke. Due to recent clinical trials, these therapies may increase their frequency of use by extending the time-window administration, which may lead to an increase in complications such as hemorrhagic transformation, with parenchymal hematoma (PH) being the more severe subtype, associated with higher mortality and disability rates. Our aim was to find genetic risk factors associated with PH, as that could provide molecular targets/pathways for their prevention/treatment and study its genetic correlations to find traits sharing genetic background. We performed a GWAS and meta-analysis, following standard quality controls and association analysis (fastGWAS), adjusting age, NIHSS, and principal components. FUMA was used to annotate, prioritize, visualize, and interpret the meta-analysis results. The total number of patients in the meta-analysis was 2034 (216 cases and 1818 controls). We found rs79770152 having a genome-wide significant association (beta 0.09, p-value 3.90 × 10−8) located in the RP11-362K2.2:RP11-767I20.1 gene and a suggestive variant (rs13297983: beta 0.07, p-value 6.10 × 10−8) located in PCSK5 associated with PH occurrence. The genetic correlation showed a shared genetic background of PH with Alzheimer’s disease and white matter hyperintensities. In addition, genes containing the ten most significant associations have been related to aggregated amyloid-β, tau protein, white matter microstructure, inflammation, and matrix metalloproteinases., Instituto de Salud Carlos III y Fondo Europeo de Desarrollo Regional (FEDER) - ( Projects PI 11/0176 and PI18/01338), Instituto de Salud Carlos III - (Project CM18/00198), Agencia de Gestión de Ayudas Universitarias y de Investigación (AGAUR) y Fondo Social Europeo - (Grant 2020FI_B1 00157), Instituto de Salud Carlos III y Fondo Europeo de Desarrollo Regional (FEDER) - (Project CD20/00043), Instituto de Salud Carlos III - (Projects FI19/00309, CP12/03298, CPII17/00027, CPII19/00020)

Rationale: Ischemic stroke is among the leading causes of adult disability. Part of the variability in functional outcome after stroke has been attributed to genetic factors but no locus has been consistently associated with stroke outcome. Objective: Our aim was to identify genetic loci influencing the recovery process using accurate phenotyping to produce the largest GWAS (genome-wide association study) in ischemic stroke recovery to date. Methods and Results: A 12-cohort, 2-phase (discovery-replication and joint) meta-analysis of GWAS included anterior-territory and previously independent ischemic stroke cases. Functional outcome was recorded using 3-month modified Rankin Scale. Analyses were adjusted for confounders such as discharge National Institutes of Health Stroke Scale. A gene-based burden test was performed. The discovery phase (n=1225) was followed by open (n=2482) and stringent joint-analyses (n=1791). Those cohorts with modified Rankin Scale recorded at time points other than 3-month or incomplete data on previous functional status were excluded in the stringent analyses. Novel variants in PATJ (Pals1-associated tight junction) gene were associated with worse functional outcome at 3-month after stroke. The top variant was rs76221407 (G allele, β=0.40, P =1.70×10 −9 ). Conclusions: Our results identify a set of common variants in PATJ gene associated with 3-month functional outcome at genome-wide significance level. Future studies should examine the role of PATJ in stroke recovery and consider stringent phenotyping to enrich the information captured to unveil additional stroke outcome loci.

CADASIL is a small vessel disease caused by mutations in NOTCH3 that lead to an odd number of cysteines in the EGF-like repeat domain, causing protein misfolding and aggregation. The main symptoms are migraine, psychiatric disturbances, recurrent strokes and dementia, being executive function characteristically impaired. The molecular pathways altered by this receptor aggregation need to be studied further. A genome-wide transcriptome study (four cases paired with three healthy siblings) was carried out, in addition to a qRT-PCR for validation purposes (ten new cases and eight new controls). To study the expression profile by cell type of the significant mRNAs found, we performed an in situ hybridization (ISH) (nine cases and eight controls) and a research in the Single-nuclei Brain RNA-seq expression browser (SNBREB). Pathway analysis enrichment was carried out with Gene Ontology and Reactome. Neuropsychological tests were performed in five of the qRT-PCR cases. The two most significant differentially expressed mRNAs (BANP, p-value = 7.23 × 10–4 and PDCD6IP, p-value = 8.36 × 10–4) were selected for the validation study by qRT-PCR. Additionally, we selected two more mRNAs (CAMK2G, p-value = 4.52 × 10–3 and E2F4, p-value = 4.77 × 10–3) due to their association with ischemic neuronal death. E2F4 showed differential expression in the genome-wide transcriptome study and in the qRT-PCR (p = 1.23 × 10–3), and it was upregulated in CADASIL cases. Furthermore, higher E2F4 expression was associated with worse executive function (p = 2.04 × 10–2) and attention and information processing speed (IPS) (p = 8.73 × 10–2). In situ hibridization showed E2F4 expression in endothelial and vascular smooth vessel cells. In silico studies indicated that E2F4 is also expressed in brain endothelial cells. Among the most significant pathways analyzed, there was an enrichment of vascular development, cell adhesion and vesicular machinery terms and autophagy process. E2F4 is more highly expressed in the skin biopsy of CADASIL patients compared to controls, and its expression is present in endothelial cells and VSMCs. Further studies are needed to understand whether E2F4 could be useful as a biomarker, to monitor the disease or be used as a therapeutic target., This work was supported by a grant from the Carlos III Health Institute (PI 11/0176), Generación Project, Maestro Project, INVICTUS + network, Epigenesis Project (Marató de TV3), FEDER funds and economic donations from “Asociación CADASIL España”. E. Muiño is supported by a Río Hortega Contract (CM18/00198) from the Carlos III Health Institute. J. Cárcel-Márquez is supported by an AGAUR Contract (agència de gestió d'ajuts universitaris i de recerca; FI_DGR 2019, grant number 2019_FI_B 00853) co-financed with Fons Social Europeu (FSE). M. Lledós is supported by a PFIS Contract (Contratos Predoctorales de Formación en Investigación en Salud) from the Carlos III Health Institute.

Background and Purpose: Large-scale observational studies of acute ischemic stroke (AIS) promise to reveal mechanisms underlying cerebral ischemia. However, meaningful quantitative phenotypes attainable in large patient populations are needed. We characterize a dynamic metric of AIS instability, defined by change in National Institutes of Health Stroke Scale score (NIHSS) from baseline to 24 hours baseline to 24 hours (NIHSS baseline – NIHSS 24hours = ΔNIHSS 6-24h ), to examine its relevance to AIS mechanisms and long-term outcomes. Methods: Patients with NIHSS prospectively recorded within 6 hours after onset and then 24 hours later were enrolled in the GENISIS study (Genetics of Early Neurological Instability After Ischemic Stroke). Stepwise linear regression determined variables that independently influenced ΔNIHSS 6 –24h . In a subcohort of tPA (alteplase)-treated patients with large vessel occlusion, the influence of early sustained recanalization and hemorrhagic transformation on ΔNIHSS 6–24h was examined. Finally, the association of ΔNIHSS 6 –24h with 90-day favorable outcomes (modified Rankin Scale score 0–2) was assessed. Independent analysis was performed using data from the 2 NINDS-tPA stroke trials (National Institute of Neurological Disorders and Stroke rt-PA). Results: For 2555 patients with AIS, median baseline NIHSS was 9 (interquartile range, 4–16), and median ΔNIHSS 6 –24h was 2 (interquartile range, 0–5). In a multivariable model, baseline NIHSS, tPA-treatment, age, glucose, site, and systolic blood pressure independently predicted ΔNIHSS 6 –24h (R 2 =0.15). In the large vessel occlusion subcohort, early sustained recanalization and hemorrhagic transformation increased the explained variance (R 2 =0.27), but much of the variance remained unexplained. ΔNIHSS 6 –24h had a significant and independent association with 90-day favorable outcome. For the subjects in the 2 NINDS-tPA trials, ΔNIHSS 3 –24h was similarly associated with 90-day outcomes. Conclusions: The dynamic phenotype, ΔNIHSS 6–24h , captures both explained and unexplained mechanisms involved in AIS and is significantly and independently associated with long-term outcomes. Thus, ΔNIHSS 6 –24h promises to be an easily obtainable and meaningful quantitative phenotype for large-scale genomic studies of AIS.

During the first hours after stroke onset neurological deficits can be highly unstable: some patients rapidly improve, while others deteriorate. This early neurological instability has a major impact on long-term outcome. Here, we aimed to determine the genetic architecture of early neurological instability measured by the difference between NIH stroke scale (NIHSS) within six hours of stroke onset and NIHSS at 24h (ΔNIHSS). A total of 5,876 individuals from seven countries (Spain, Finland, Poland, United States, Costa Rica, Mexico and Korea) were studied using a multi-ancestry meta-analyses. We found that 8.7% of ΔNIHSS variance was explained by common genetic variations, and also that early neurological instability has a different genetic architecture than that of stroke risk. Seven loci (2p25.1, 2q31.2, 2q33.3, 4q34.3, 5q33.2, 6q26 and 7p21.1) were genome-wide significant and explained 2.1% of the variability suggesting that additional variants influence early change in neurological deficits. We used functional genomics and bioinformatic annotation to identify the genes driving the association from each loci. eQTL mapping and SMR indicate that ADAM23 (log Bayes Factor (LBF)=6.34) was driving the association for 2q33.3. Gene based analyses suggested that GRIA1 (LBF=5.26), which is predominantly expressed in brain, is the gene driving the association for the 5q33.2 locus. These analyses also nominated PARK2 (LBF=5.30) and ABCB5 (LBF=5.70) for the 6q26 and 7p21.1 loci. Human brain single nuclei RNA-seq indicates that the gene expression of ADAM23 and GRIA1 is enriched in neurons. ADAM23, a pre-synaptic protein, and GRIA1, a protein subunit of the AMPA receptor, are part of a synaptic protein complex that modulates neuronal excitability. These data provides the first evidence in humans that excitotoxicity may contribute to early neurological instability after acute ischemic stroke.RESEARCH INTO CONTEXTEvidence before this studyNo previous genome-wide association studies have investigated the genetic architecture of early outcomes after ischemic stroke.Added Value of this studyThis is the first study that investigated genetic influences on early outcomes after ischemic stroke using a genome-wide approach, revealing seven genome-wide significant loci. A unique aspect of this genetic study is the inclusion of all of the major ethnicities by recruiting from participants throughout the world. Most genetic studies to date have been limited to populations of European ancestry.Implications of all available evidenceThe findings provide the first evidence that genes implicating excitotoxicity contribute to human acute ischemic stroke, and demonstrates proof of principle that GWAS of acute ischemic stroke patients can reveal mechanisms involved in ischemic brain injury.

[Background] Most of the models to predict prognosis after an ischemic stroke include complex mathematical equations or too many variables, making them difficult to use in the daily clinic. We want to predict disability 3 months after an ischemic stroke in an independent patient not receiving recanalization treatment within the first 24 h, using a minimum set of variables and an easy tool to facilitate its implementation. As a secondary aim, we calculated the capacity of the score to predict an excellent/devastating outcome and mortality., [Methods] Eight hundred and forty-four patients were evaluated. A multivariable ordinal logistic regression was used to obtain the score. The Modified Rankin Scale (mRS) was used to estimate disability at the third month. The results were replicated in another independent cohort (378 patients). The “polr” function of R was used to perform the regression, stratifying the sample into seven groups with different cutoffs (from mRS 0 to 6)., [Results] The Parsifal score was generated with: age, previous mRS, initial NIHSS, glycemia on admission, and dyslipidemia. This score predicts disability with an accuracy of 80–76% (discovery–replication cohorts). It has an AUC of 0.86 in the discovery and replication cohort. The specificity was 90–80% (discovery–replication cohorts); while, the sensitivity was 64–74% (discovery–replication cohorts). The prediction of an excellent or devastating outcome, as well as mortality, obtained good discrimination with AUC > 0.80., [Conclusions] The Parsifal Score is a model that predicts disability at the third month, with only five variables, with good discrimination and calibration, and being replicated in an independent cohort., This work was supported by a grant from Instituto de Salud Carlos III (PI 11/0176), Generación Project, Maestro Project, INVICTUS + network, Epigenesis Project (Marató de TV3) and FEDER funds. E. Muiño is supported by a Río Hortega Contract (CM18/00198) from Instituto de Salud Carlos III. J. Cárcel-Márquez is supported by AGAUR Contract (agència de gestió d'ajuts universitaris i de recerca; FI_DGR 2019, grant number 2019_FI_B 00853). A. Bustamante is supported by a Juan Rodés Research Contract (JR16/00008) from Instituto de Salud Carlos III.

Acenocoumarol is an oral anticoagulant with significant interindividual dose variations. Variants in CYP2C9 and VKORC1 have been associated with acenocoumarol maintenance dose. We analysed whether any of the 49 polymorphisms in CYP2C9 and VKORC1 previously associated with acenocoumarol maintenance dose in a Genome-Wide Association study (GWAs) in Dutch population are associated with stroke recurrence, intracranial haemorrhage (ICH) and acenocoumarol maintenance dose in a Spanish population. We performed a GWAs using Human Core Exome-chip (Illumina) in 78 patients stroke patients treated with acenocoumarol for secondary prevention enrolled as part of the prospective investigator-initiated study (IIS) SEDMAN Study. Patients were followed-up a median of 12.8 months. Three and eight patients had recurrent stroke and ICH events, respectively. We found 14 of the 49 published variants associated with acenocoumarol maintenance dose (p, We would like to thank the International Stroke Genetics Consortium, the Spanish Stroke Genetics Consortium, and the RETICS Network INVICTUS plus (RD16/0019/0001, RD16/0019/0002, RD16/0019/0007, RD16/0019/0010, and RD16/0019/0011, RD16/0019/0017, RD16/0019/0019 and RD16/0019/0021).

Funding: This study was funded by the INVICTUS network, Generacion, Maestro EPIGENESIS, FEDER-ERDF, and BasicMar Regist projects from the Carlos III Health Institute, the AGAUR, the RecerCaixa 2013 and the European Regional Development Fund (ERDF). I. Fernandez is recipient of a research contract from Miguel Servet Program from the Carlos III Health Institute (CPII17/00021). EPIGENESIS project (CarlosIII Institute, Marató TV3 and Fundació MútuaTerrassa). Background and Purpose: Polymorphisms and serum levels of Matrix Metalloproteinases (MMP) and Tissue Inhibitor of Metalloproteinases (TIMP) have been studied with regard to atheromatous plaques and ischemic stroke, while no studies of DNA methylation (DNAm) patterns of MMP or TIMP have been performed to that end. Here, we evaluate DNAm levels of the MMP and TIMP gene families in human carotid plaques and blood samples of atherothrombotic stroke patients. Methods: We profiled the DNAm status of stable and ulcerated atherosclerotic plaques obtained as pair sets from three patients who underwent carotid endarterectomy surgery. We selected 415 CpG sites, mapping into MMPs and TIMPs genes for further study. Secondly, the statistically associated CpG sites were analyzed in blood samples from two separate atherothrombotic stroke cohorts (total sample size = 307), ischemic stroke-cohort 1 (ISC-1): 37 atherothrombotic patients and 6 controls, ischemic stroke-cohort 2 (ISC-2): 80 atherothrombotic patients and 184 controls. DNAm levels from plaque tissue and blood samples were evaluated using a high-density microarray Infinium, HumanMethylation450 BeadChip and Infinium MethylationEPIC BeadChip. Results: Three CpG sites were statistically significantly associated with unstable plaque portions; cg02969624, q-value = 0.035 (TIMP2), and cg04316754, q-value = 0.037 (MMP24) were hypermethylated, while cg24211657 q-value = 0.035 (TIMP2) was hypomethylated. Association of cg04316754 (MMP24) methylation levels with atherothrombotic risk was also observed in blood tissue: ISC-1 p-values = 0.03, ISC-2 p-value = 1.9 × 10-04. Conclusions: The results suggest different DNAm status of MMP24 between stable and unstable atherothrombotic carotid plaques, and between atherothrombotic stroke and controls in blood samples. Publisher PDF

[Background and Purpose] Immune cells play a key role in the first 24h poststroke (acute phase), being associated with stroke outcome. We aimed to find genetic risk factors associated with leukocyte counts during the acute phase of stroke., [Methods] Ischemic stroke patients with leukocyte counts data during the first 24h were included. Genome-wide association study and gene expression studies were performed., [Results] Our genome-wide association study, which included 2064 (Discovery) and 407 (Replication) patients, revealed a new locus (14q24.3) associated with leukocyte counts. After Joint analysis (n=2471) 5 more polymorphisms reached genome-wide significance (P, [Conclusions] We have found the first locus associated with leukocyte counts in ischemic stroke, also associated with acute outcome. Genetic analysis of acute endophenotypes could be useful to find the genetic factors associated with stroke outcome. Our findings suggested a different modulation of immune cells in stroke compared with healthy conditions.

Acenocoumarol is an oral anticoagulant with significant interindividual dose variations. Variants in CYP2C9 and VKORC1 have been associated with acenocoumarol maintenance dose. We analysed whether any of the 49 polymorphisms in CYP2C9 and VKORC1 previously associated with acenocoumarol maintenance dose in a Genome-Wide Association study (GWAs) in Dutch population are associated with stroke recurrence, intracranial haemorrhage (ICH) and acenocoumarol maintenance dose in a Spanish population. We performed a GWAs using Human Core Exome-chip (Illumina) in 78 patients stroke patients treated with acenocoumarol for secondary prevention enrolled as part of the prospective investigator-initiated study (IIS) SEDMAN Study. Patients were followed-up a median of 12.8 months. Three and eight patients had recurrent stroke and ICH events, respectively. We found 14 of the 49 published variants associated with acenocoumarol maintenance dose (p

Comment inThe yin and yang of magnesium and calcium: New genetic insights for stroke? [Neurology. 2019]; International audience; Objective To determine whether serum magnesium and calcium concentrations are causally associated with ischemic stroke or any of its subtypes using the mendelian randomization approach. Methods Analyses were conducted using summary statistics data for 13 single-nucleotide polymorphisms robustly associated with serum magnesium (n = 6) or serum calcium (n = 7) concentrations. The corresponding data for ischemic stroke were obtained from the MEGASTROKE consortium (34,217 cases and 404,630 noncases). Results In standard mendelian randomization analysis, the odds ratios for each 0.1 mmol/L (about 1 SD) increase in genetically predicted serum magnesium concentrations were 0.78 (95% confidence interval [CI] 0.69-0.89; p = 1.3 × 10 −4) for all ischemic stroke, 0.63 (95% CI 0.50-0.80; p = 1.6 × 10 −4) for cardioembolic stroke, and 0.60 (95% CI 0.44-0.82; p = 0.001) for large artery stroke; there was no association with small vessel stroke (odds ratio 0.90, 95% CI 0.67-1.20; p = 0.46). Only the association with cardioembolic stroke was robust in sensitivity analyses. There was no association of genetically predicted serum calcium concentrations with all ischemic stroke (per 0.5 mg/dL [about 1 SD] increase in serum calcium: odds ratio 1.03, 95% CI 0.88-1.21) or with any subtype. Conclusions This study found that genetically higher serum magnesium concentrations are associated with a reduced risk of cardioembolic stroke but found no significant association of genetically higher serum calcium concentrations with any ischemic stroke subtype.

Type 2 diabetes mellitus (DM) is an established risk factor for a wide range of vascular diseases, including ischemic stroke (IS). Glycated hemoglobin A1c (HbA1c), a marker for average blood glucose levels over the previous 12 weeks, is used as a measure of glycemic control and also as a diagnostic criterion for diabetes (HbA1c levels ≥ 6.5%). Epigenetic mechanisms, such as DNA methylation, may be associated with aging processes and with modulation of the risk of various pathologies, such as DM. Specifically, DNA methylation could be one of the mechanisms mediating the relation between DM and environmental exposures. Our goal was to identify new CpG methylation sites associated with DM. We performed a genome-wide methylation study in whole-blood DNA from an IS patient cohorts. Illumina HumanMethylation450 BeadChip array was used to measure DNA methylation in CpG sites. All statistical analyses were adjusted for sex, age, hyperlipidemia, body mass index (BMI), smoking habit and cell count. Findings were replicated in two independent cohorts, an IS cohort and a population-based cohort, using the same array. In the discovery phase (N = 355), we identified a CpG site, cg19693031 (located in the TXNIP gene) that was associated with DM (P = 1.17 × 10(-12)); this CpG was replicated in two independent cohorts (N = 167 and N = 645). Methylation of TXNIP was inversely and intensely associated with HbA1c levels (P = 7.3 × 10(-16)), specifically related to diabetic patients with poor control of glucose levels. We identified an association between the TXNIP gene and DM through epigenetic mechanisms, related to sustained hyperglycemia levels (HbA1c ≥ 7%).

ObjectiveTo validate the Genot-PA score, a clinical-genetic logistic regression score that stratifies the thrombolytic therapy safety, in a new cohort of patients with stroke.MethodsWe enrolled 1,482 recombinant tissue plasminogen activator (rtPA)-treated patients with stroke in Spain and Finland from 2003 to 2016. Cohorts were analyzed on the basis of ethnicity and therapy: Spanish patients treated with IV rtPA within 4.5 hours of onset (cohort A and B) or rtPA in combination with mechanical thrombectomy within 6 hours of onset (cohort C) and Finnish participants treated with IV rtPA within 4.5 hours of onset (cohort D). The Genot-PA score was calculated, and hemorrhagic transformation (HT) and parenchymal hematoma (PH) risks were determined for each score stratum.ResultsGenot-PA score was tested in 1,324 (cohort A, n = 726; B, n = 334; C, n = 54; and D, n = 210) patients who had enough information to complete the score. Of these, 213 (16.1%) participants developed HT and 85 (6.4%) developed PH. In cohorts A, B, and D, HT occurrence was predicted by the score (p = 2.02 × 10−6, p = 0.023, p = 0.033); PH prediction was associated in cohorts A through C (p = 0.012, p = 0.034, p = 5.32 × 10−4). Increased frequency of PH events from the lowest to the highest risk group was found (cohort A 4%–15.7%, cohort B 1.5%–18.2%, cohort C 0%–100%). The best odds ratio for PH prediction in the highest-risk group was obtained in cohort A (odds ratio 5.16, 95% confidence interval 1.46–18.08, p = 0.009).ConclusionThe Genot-PA score predicts HT in patients with stroke treated with IV rtPA. Moreover, in an exploratory study, the score was associated with PH risk in mechanical thrombectomy-treated patients.

Background and Purpose— Despite the effectiveness of recombinant tissue-type plasminogen activator (r-tPA) during the acute phase of ischemic stroke, the therapy remains limited by a narrow time window and the occurrence of occasional vascular side effects, particularly symptomatic hemorrhages. Our aim was to investigate the mechanisms underlying the endothelial damage resulting from r-tPA treatment in ischemic-like conditions. Methods— Microarray analyses were performed on cerebral endothelial cells submitted to r-tPA treatment during oxygen and glucose deprivation to identify novel biomarker candidates. Validation was then performed in vivo in a mouse model of thromboembolic stroke and culminated in an analysis in a clinical cohort of patients with ischemic stroke treated with thrombolysis. Results— The transcription factor NURR1 (NR4A2) was identified as a downstream target induced by r-tPA during oxygen and glucose deprivation. Silencing NURR1 expression reversed the endothelial-toxicity induced by the combined stimuli, a protective effect attributable to reduced levels of proinflammatory mediators, such as nuclear factor-kappa-beta 2 (NF-κ-B2), interleukin 1 alpha (IL1α), intercellular adhesion molecule 1 (ICAM1), SMAD family member 3 (SMAD3), colony stimulating factor 2 (granulocyte-macrophage; CSF2). The detrimental effect of delayed thrombolysis, in conditions in which NURR1 gene expression was enhanced, was confirmed in the preclinical stroke model. Finally, we determined that patients with stroke who had a symptomatic hemorrhagic transformation after r-tPA treatment exhibited higher baseline serum NURR1 levels than did patients with an asymptomatic or absence of cerebral bleedings. Conclusions— Our results suggest that NURR1 upregulation by r-tPA during ischemic stroke is associated with endothelial dysfunction and inflammation and the enhancement of hemorrhagic complications associated to thrombolysis.

© 2017 by the authors. Licensee MDPI, Basel, Switzerland. CADASIL (cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy) is caused by mutations in the NOTCH3 gene, affecting the number of cysteines in the extracellular domain of the receptor, causing protein misfolding and receptor aggregation. The pathogenic role of cysteine-sparing NOTCH3 missense mutations in patients with typical clinical CADASIL syndrome is unknown. The aim of this article is to describe these mutations to clarify if any could be potentially pathogenic. Articles on cysteine-sparing NOTCH3 missense mutations in patients with clinical suspicion of CADASIL were reviewed. Mutations were considered potentially pathogenic if patients had: (a) typical clinical CADASIL syndrome; (b) diffuse white matter hyperintensities; (c) the 33 NOTCH3 exons analyzed; (d) mutations that were not polymorphisms; and (e) Granular osmiophilic material (GOM) deposits in the skin biopsy. Twenty-five different mutations were listed. Four fulfill the above criteria: p.R61W; p.R75P; p.D80G; and p.R213K. Patients carrying these mutations had typical clinical CADASIL syndrome and diffuse white matter hyperintensities, mostly without anterior temporal pole involvement. Cysteine-sparing NOTCH3 missense mutations are associated with typical clinical CADASIL syndrome and typical magnetic resonance imaging (MRI) findings, although with less involvement of the anterior temporal lobe. Hence, these mutations should be further studied to confirm their pathological role in CADASIL.

Tumour necrosis factor receptor-associated factor 3 (TRAF3) is a member of the TRAF adaptor protein family, which exerts different effects on the cell depending on the receptor to which it binds and the cell type in which it is expressed. TRAF3 is a major regulator of the innate immune response. To perform its functions properly,TRAF3is transcriptionally and epigenetically regulated. At the transcriptional level,TRAF3expression has been associated with neurological and cardiovascular diseases including stroke, among other pathologies. Epigenetic modifications ofTRAF3have been observed at the histone and DNA levels. It has been observed that acetylation ofTRAF3, as well as other NF-κβ target genes, is associated with cardiac hypertrophy. Furthermore,TRAF3methylation has been associated with vascular recurrence after ischemic stroke in patients treated with clopidogrel. In this overview, we summarise the most interesting studies related to transcriptional and epigenetic regulation ofTRAF3focusing on those studies performed in neurological and cardiovascular diseases.

Introduction and objective: Intracranial atherosclerosis (ICAS) is a major cause of stroke worldwide, and its genetic background remains largely unexplored. The previous studies performed have been based on candidate-gene strategy. We aimed to perform a genome-wide association study (GWAs) to find genetic risk factors associated with symptomatic ICAS. Methods: We studied a cohort of 83 Caucasian patients with ischemic stroke attributed to symptomatic ICAS and 315 controls genotyped with Human Core Exome (Illumina). A score combining number and severity of intracranial stenoses was used to assess ICAS severity in each patient. Quality controls, 1000G imputation and association analysis were performed through PLINK, R, IMPUTE2 and SNPTEST software following previous recommendations. Sex, age, principal components and vascular risk factors were used as covariates. Results: Several loci with a genome wide significant association (P Conclusion: This GWAS in symptomatic ICAS patients has revealed potential genes associated with ICAS presence and severity. These findings need to be replicated in other cohorts, ideally in patients from different ethnicities.

This article provides an overview of stroke genetics studies ranging from the candidate gene approach to more recent studies by the genome wide association. It highlights the complexity of stroke owing to its different aetiopathogenic mechanisms, the difficulties in studying its genetic component, and the solutions provided to date. The study emphasises the importance of cooperation between the different centres, whether this takes place occasionally or through the creation of lasting consortiums. This strategy is currently essential to the completion of high-quality scientific studies that allow researchers to gain a better knowledge of the genetic component of stroke as it relates to aetiology, treatment, and prevention. Resumen: El presente artículo revisa la evolución de los estudios en genética del ictus desde la aproximación por gen candidato hasta los recientes estudios de genome wide association. Se destaca la complejidad de esta afección por sus muy variados mecanismos etiopatogénicos, las dificultades que comporta el estudio de su componente genético y las soluciones que se han aportado. Se subraya en especial el valor de las colaboraciones entre distintos centros, ya sea de manera puntual o sobre todo a través de la creación de consorcios estables. Esta estrategia actualmente se hace imprescindible a la hora de realizar estudios de alta calidad científica que permitan seguir avanzando en el conocimiento de las bases genéticas del ictus tanto en etiología, como en tratamiento y prevención. Keywords: Stroke, Genetics, Association, Genetic risk factors, Prediction, Consortium, Palabras clave: Ictus, Genética, Asociación, Factores de riesgo genético, Predicción, Consorcio

Resumen: El presente artículo revisa la evolución de los estudios en genética del ictus desde la aproximación por gen candidato hasta los recientes estudios de genome wide association. Se destaca la complejidad de esta afección por sus muy variados mecanismos etiopatogénicos, las dificultades que comporta el estudio de su componente genético y las soluciones que se han aportado. Se subraya en especial el valor de las colaboraciones entre distintos centros, ya sea de manera puntual o sobre todo a través de la creación de consorcios estables. Esta estrategia actualmente se hace imprescindible a la hora de realizar estudios de alta calidad científica que permitan seguir avanzando en el conocimiento de las bases genéticas del ictus tanto en etiología, como en tratamiento y prevención. Abstract: This article provides an overview of stroke genetics studies ranging from the candidate gene approach to more recent studies by the genome wide association. It highlights the complexity of stroke owing to its different aetiopathogenic mechanisms, the difficulties in studying its genetic component, and the solutions provided to date. The study emphasises the importance of cooperation between the different centres, whether this takes places occasionally or through the creation of lasting consortiums. This strategy is currently essential to the completion of high-quality scientific studies that allow researchers to gain a better knowledge of the genetic component of stroke as it relates to aetiology, treatment, and prevention. Palabras clave: Ictus, Genética, Asociación, Factores de riesgo genético, Predicción, Consorcio, Keywords: Stroke, Genetics, Association, Genetic risk factors, Prediction, Consortium

SummaryGenetic studies suggest that hundreds of genes associated with stroke remain unidentified. Exome sequencing proves useful for finding new genes associated with stroke. We aimed to find new genetic risk factors for cardioembolic stroke by analysing exome sequence data using new strategies. For discovery, we analysed 42 cardioembolic stroke cases and controls with extreme phenotypes (cohort 1), and for replication, 32 cardioembolic stroke cases and controls (cohort 2) using the SeqCapExome capture kit. We then analysed the replicated genes in two new cohorts that comprised 834 cardioembolic strokes and controls (cohort 3) and 64,373 cardioembolic strokes and controls (cohort 4). Transcriptomic in-silico functional analyses were also performed. We found 26 coding regions with a higher frequency of mutations in cardioembolic strokes after correcting for the number of mutations found in the whole exome of every patient. The TRPV3 gene was associated with cardioembolic stroke after replication of exome sequencing analysis (p-value-discovery: 0.018, p-value-replication: 0.014). The analysis of the TRPV3 gene using polymorphisms in cohort 3 and 4 revealed two polymorphisms associated with cardioembolic stroke in both cohorts, the most significant polymorphism being rs151091899 (p-value: 3.1 × 10−05; odds ratio: 5.4) in cohort 3. The genotype of one polymorphism of TRPV3 was associated with a differential expression of genes linked to cardiac malformations. In conclusion, new strategies using exome sequence data have revealed TRPV3 as a new gene associated with cardioembolic stroke. This strategy among others might be useful in finding new genes associated with complex genetic diseases.

Following acute ischemic stroke (AIS) onset, neurological deficits can be highly unstable. Early neurological change within the first 24 hours, defined here as ΔNIHSS24h (NIHSSbaseline-NIHSS24hours), substantially influences long-term outcome. While several mechanisms, such as hemorrhagic transformation and recanalization, may impact ΔNIHSS24h, little is known about genetic influences. Genetic variants associated with ΔNIHSS24h may identify genes involved in mechanisms of early neurological outcome after AIS. AIS patients were prospectively enrolled between 2008-2014 at two sites (St Louis and BCN; Table 1). NIHSS scores were obtained within 6 hours and again at 24 hours after stroke onset. Genome-wide genotyping was generated for rare and common variants, imputing up to 6 million single nucleotide polymorphisms (SNPs) for all subjects (N=891). ΔNIHSS24h was used as a quantitative trait to measure early improvement/deterioration. Genome-wide complex trait analysis (GCTA) was performed. An association model was done, using NIHSSbaseline, age, gender, glucose, PCA1 and PCA2 as covariates. All samples were analyzed together and then separately by ethnicity (Spanish, European-American (EA), and African-American (AA)). GCTA indicates that common variants account for 23-28% of ΔNIHSS24h variability. VAV3 rs72689643 (p=8.21x10-8) was associated with ΔNIHSS24h in the whole cohort analysis (Figure 1). Three additional suggestive SNPs were found: 2 intergenic SNPs (rs139950151 and rs73706194 - both p=6.1x10-7) in high LD and SNP rs10431426 (p=1.71x10-7) located in an intron. When analyzed by ethnicity, these findings did not reach GWAs significance, likely due to lack of power. Early neurological outcome after AIS is strongly influenced by genetics. Vav3 shows association with ΔNIHSS24h in the whole cohort while several other SNPs are suggestive. Rare variant analysis is underway, and we will also have an additional 800 genotypes analyzed by ISC.

Background and Purpose— Clopidogrel is one of the most used antiplatelet drugs in patients with cardiovascular disease. However, 16% to 50% of patients have a high on-clopidogrel platelet reactivity and an increased risk of ischemic events. The pathogenesis of high on-treatment platelet reactivity in patients with stroke is only partially explained by genetic variations. This study aims to find differentially methylated sites across the genome associated with vascular recurrence in ischemic stroke patients treated with clopidogrel. Methods— From a cohort of 1900 patients with ischemic stroke, we selected 42 patients treated with clopidogrel, including 21 with a recurrent vascular event and 21 without vascular recurrence during the first year of follow-up. Over 480 000 DNA methylation sites were analyzed across the genome. Differentially methylated CpG sites were identified by nonparametric testing using R. Replication analysis was performed in a new cohort of 191 subjects and results were correlated with platelet reactivity in a subset of 90 subjects using light transmission aggregometry. Results— A total of 73 differentially methylated CpG sites ( P −05 ) were identified; 3 of them were selected for further replication: cg03548645 ( P =1.42×10 −05 , TRAF3 ), cg09533145 ( P =7.81×10 −06 , ADAMTS2 ), and cg15107336 ( P =1.89×10 −05 , XRCC1 ). The cg03548645 CpG remained significant in the replication study ( P =0.034), a deep analysis of this region revealed another methylation site associated with vascular recurrence, P =0.037. Lower cg03548645 ( TRAF3 ) DNA methylation levels were correlated with an increased platelet aggregation (ρ=−0.29, P =0.0075). Conclusions— This study suggests for the first time that epigenetics may significantly contribute to the variability of clopidogrel response and recurrence of ischemic events in patients with stroke.

Chagas disease is a parasitic disease caused by the protozoan parasite Trypanosoma cruzi and about 230,000 persons are estimated to be infected in Ecuador. However, limited studies have been performed in the Amazon region, on the eastern side of the country. We evaluated here the seroprevalence of Trypanosoma cruzi infection in 12 rural villages of the Loreto canton, Orellana Province in schoolchildren aged 5–15 years and in pregnant women. A total of 1,649 blood samples were tested for Trypanosoma cruzi antibodies by enzyme-linked immunosorbent assay and indirect hemaglutination, and discordant samples were tested by indirect immunofluorescence assay. We detected a seroprevalence of anti-Trypanosoma cruzi antibodies of 1.3% in schoolchildren aged 5–15 years, indicating the persistence of a constant and active vectorial transmission in the Loreto County and confirming the need of the implementation of nonconventional vector control. We also observed a seroprevalence of 3.8% in pregnant women, indicating a clear risk of congenital transmission. Further studies should help define this risk more precisely and implement current international guidelines for the diagnosis, treatment, and care of these cases.

Introduction: Neurological deficits can be highly unstable within the first 24 hours after acute ischemic stroke (AIS), with some patients showing dramatic improvement while others rapidly deteriorate. We are interested in genetic influences on early neurological recovery/deterioration. Here, we characterize NIHSS changes within the first 24 hours after stoke onset (ΔNIHSS) in a large cohort to determine baseline clinical variables that influence this outcome measure. Methods: AIS patients presenting to two sites (Barnes-Jewish Hospital, St Louis and Vall D’Hebron Hospital Barcelona) between 2008-2013 were prospectively enrolled. Baseline NIHSS was collected within 6 hours and again at 24 hours after symptom onset. ΔNIHSS was calculated as the difference in these stroke scale scores. Demographics, baseline comorbidities and medications, as well as acute treatment variables were recorded for each subject. Stepwise multivariable regression (SAS) was used to determine variables that significantly influence ΔNIHSS. Results: There were 954 patients enrolled (St Louis = 433, Barcelona = 521). Table 1 demonstrates the frequencies and means (SD) of the baseline variables. ΔNIHSS follows a normal distribution (figure). All baseline variables listed in table 1 were analyzed for influence on ΔNIHSS. Only baseline NIHSS (R2 = 0.0597, p Conclusion: Baseline variables (NIHSS, glucose and age) modestly influence early neurological recovery/deterioration. However, 91% of ΔNIHSS variability remains unexplained, suggesting that other factors such as genetics, could play an important role in early outcomes following AIS. A GWAS of ΔNIHSS is currently underway.

BACKGROUND: DNA methylation is a heritable and stable epigenetic mark implicated in complex human traits. Epigenome-wide association studies (EWAS) using array-based technology are becoming widely used to identify differentially methylated sites associated with complex diseases. EWAS studies require large sample sizes to detect small effects, which increases project costs. In the present study we propose to pool DNA samples in methylation array studies as an affordable and accurate alternative to individual samples studies, in order to reduce economic costs or when low amounts of DNA are available. For this study, 20 individual DNA samples and 4 pooled DNA samples were analysed using the Illumina Infinium HumanMethylation450 BeadChip array to evaluate the efficiency of the pooling approach in EWAS studies. Statistical power calculations were also performed to discover the minimum sample size needed for the pooling strategy in EWAS. RESULTS: A total of 485,577 CpG sites across the whole genome were assessed. Comparison of methylation levels of all CpG sites between individual samples and their related pooled samples revealed highly significant correlations (rho > 0.99, p-val 0.98, p-val

Background and Purpose— Despite the benefits of tissue-type plasminogen activator treatment, some stroke patients experience adverse hemorrhagic transformations (HT). Plasma protein levels of MMP9 have been associated with HT occurrence. We aimed to analyze the association of the MMP9 gene with HT occurrence. Methods— We analyzed the MMP9 gene in blood samples from 885 stroke patients treated with tissue-type plasminogen activator by tag-SNP, imputed SNP, direct sequencing, and RNA expression. Results— We did not observe any significant association between MMP9 genetic variations or MMP9 expression and HT occurrence. Moreover, no association was found between MMP9 expression and MMP9 polymorphisms. Conclusions— Genetic variations in the MMP9 gene are not associated with HT occurrence in tissue-type plasminogen activator-treated patients.

A nationwide survey was conducted to obtain an estimate of Chagas disease prevalence among pregnant women in Ecuador. As part of a national probability sample, 5,420 women seeking care for delivery or miscarriage at 15 healthcare facilities were recruited into the study. A small minority of participants reported knowing about Chagas disease or recognized the vector. A national seroprevalence of 0.1% (95% confidence interval [95% CI] = 0.0–0.2%) was found; cases were concentrated in the coastal region (seroprevalence = 0.2%; 95% CI = 0.0–0.4%). No cases of transmission to neonates were identified in the sample. Seropositive participants were referred to the National Chagas Program for evaluation and treatment. Additional studies are necessary to determine if areas of higher prevalence exist in well-known endemic provinces and guide the development of a national strategy for elimination of mother-to-child transmission of Chagas disease in Ecuador.

Summary Background The discovery of disease-associated loci through genome-wide association studies (GWAS) is the leading genetic approach to the identification of novel biological pathways underlying diseases in humans. Until recently, GWAS in ischaemic stroke have been limited by small sample sizes and have yielded few loci associated with ischaemic stroke. We did a large-scale GWAS to identify additional susceptibility genes for stroke and its subtypes. Methods To identify genetic loci associated with ischaemic stroke, we did a two-stage GWAS. In the first stage, we included 16 851 cases with state-of-the-art phenotyping data and 32 473 stroke-free controls. Cases were aged 16 to 104 years, recruited between 1989 and 2012, and subtypes of ischaemic stroke were recorded by centrally trained and certified investigators who used the web-based protocol, Causative Classification of Stroke (CCS). We constructed case-control strata by identifying samples that were genotyped on nearly identical arrays and were of similar genetic ancestral background. We cleaned and imputed data by use of dense imputation reference panels generated from whole-genome sequence data. We did genome-wide testing to identify stroke-associated loci within each stratum for each available phenotype, and we combined summary-level results using inverse variance-weighted fixed-effects meta-analysis. In the second stage, we did in-silico lookups of 1372 single nucleotide polymorphisms identified from the first stage GWAS in 20 941 cases and 364 736 unique stroke-free controls. The ischaemic stroke subtypes of these cases had previously been established with the Trial of Org 10 172 in Acute Stroke Treatment (TOAST) classification system, in accordance with local standards. Results from the two stages were then jointly analysed in a final meta-analysis. Findings We identified a novel locus (G allele at rs12122341) at 1p13.2 near TSPAN2 that was associated with large artery atherosclerosis-related stroke (first stage odds ratio [OR] 1·21, 95% CI 1·13–1·30, p=4·50 × 10 −8 ; joint OR 1·19, 1·12–1·26, p=1·30 × 10 −9 ). Our results also supported robust associations with ischaemic stroke for four other loci that have been reported in previous studies, including PITX2 (first stage OR 1·39, 1·29–1·49, p=3·26 × 10 −19 ; joint OR 1·37, 1·30–1·45, p=2·79 × 10 −32 ) and ZFHX3 (first stage OR 1·19, 1·11–1·27, p=2·93 × 10 −7 ; joint OR 1·17, 1·11–1·23, p=2·29 × 10 −10 ) for cardioembolic stroke, and HDAC9 (first stage OR 1·29, 1·18–1·42, p=3·50 × 10 −8 ; joint OR 1·24, 1·15–1·33, p=4·52 × 10 −9 ) for large artery atherosclerosis stroke. The 12q24 locus near ALDH2 , which has previously been associated with all ischaemic stroke but not with any specific subtype, exceeded genome-wide significance in the meta-analysis of small artery stroke (first stage OR 1·20, 1·12–1·28, p=6·82 × 10 −8 ; joint OR 1·17, 1·11–1·23, p=2·92 × 10 −9 ). Other loci associated with stroke in previous studies, including NINJ2 , were not confirmed. Interpretation Our results suggest that all ischaemic stroke-related loci previously implicated by GWAS are subtype specific. We identified a novel gene associated with large artery atherosclerosis stroke susceptibility. Follow-up studies will be necessary to establish whether the locus near TSPAN2 can be a target for a novel therapeutic approach to stroke prevention. In view of the subtype-specificity of the associations detected, the rich phenotyping data available in the Stroke Genetics Network (SiGN) are likely to be crucial for further genetic discoveries related to ischaemic stroke. Funding US National Institute of Neurological Disorders and Stroke, National Institutes of Health.

Introduction The main objective of this study is to determine the prevalence of apolipoprotein E ( Apo E ) and glutathione peroxidase 1 ( GPX1 ) polymorphisms and their influence on the development of Alzheimer disease (AD) in the Ecuadorian population. Methods The authors performed an analytic transversal case-control study. The study group (n = 39) consisted of patients with AD and dementia. The control group (n = 39) comprised elderly adults who have not been diagnosed with dementia and have the same age and education as the study group. Their inclusion period was from 2007 to 2008. Later on, after obtaining informed consent and after finishing a structural interview; the next step forward was to collect blood and extract DNA by standardized protocols. Besides, the authors performed polymerase chain reaction-restriction fragment length polymorphism technique to determine the genotype of each individual. Results The authors found a positive association between e 4 and e 2 alleles of Apo E . The GPX1 gene shows an association of leu allele, whereas pro allele shows a negative association. The odds ratio test shows no significant relative risk. Conclusions Apo E is not a risk factor, nor a protective one for AD, whereas the leu allele of GPX1 is a possible risk factor for the disease.

Anti-COVID-19 hyperimmune immunoglobulin (hIG) can provide standardized and controlled antibody content. Data from controlled clinical trials using hIG for the prevention or treatment of COVID-19 outpatients have not been reported. We assessed the safety and efficacy of subcutaneous anti-COVID-19 hyperimmune immunoglobulin 20% (C19-IG20%) compared to placebo in preventing development of symptomatic COVID-19 in asymptomatic individuals with SARS-CoV-2 infection. We did a multicentre, randomized, double-blind, placebo-controlled trial, in asymptomatic unvaccinated adults (≥18 years of age) with confirmed SARS-CoV-2 infection within 5 days between April 28 and December 27, 2021. Participants were randomly assigned (1:1:1) to receive a blinded subcutaneous infusion of 10 mL with 1 g or 2 g of C19-IG20%, or an equivalent volume of saline as placebo. The primary endpoint was the proportion of participants who remained asymptomatic through day 14 after infusion. Secondary endpoints included the proportion of individuals who required oxygen supplementation, any medically attended visit, hospitalisation, or ICU, and viral load reduction and viral clearance in nasopharyngeal swabs. Safety was assessed as the proportion of patients with adverse events. The trial was terminated early due to a lack of potential benefit in the target population in a planned interim analysis conducted in December 2021. registry: . 461 individuals (mean age 39.6 years [SD 12.8]) were randomized and received the intervention within a mean of 3.1 (SD 1.27) days from a positive SARS-CoV-2 test. In the prespecified modified intention-to-treat analysis that included only participants who received a subcutaneous infusion, the primary outcome occurred in 59.9% (91/152) of participants receiving 1 g C19-IG20%, 64.7% (99/153) receiving 2 g, and 63.5% (99/156) receiving placebo (difference in proportions 1 g C19-IG20% vs. placebo, −3.6%; 95% CI -14.6% to 7.3%, p = 0.53; 2 g C19-IG20% vs placebo, 1.1%; −9.6% to 11.9%, p = 0.85). None of the secondary clinical efficacy endpoints or virological endpoints were significantly different between study groups. Adverse event rate was similar between groups, and no severe or life-threatening adverse events related to investigational product infusion were reported. Our findings suggested that administration of subcutaneous human hyperimmune immunoglobulin C19-IG20% to asymptomatic individuals with SARS-CoV-2 infection was safe but did not prevent development of symptomatic COVID-19. .

Publisher's version (útgefin grein), Objective: To explore genetic and lifestyle risk factors of MRI-defined brain infarcts (BI) in large population-based cohorts. Methods We performed meta-analyses of genome-wide association studies (GWAS) and examined associations of vascular risk factors and their genetic risk scores (GRS) with MRI-defined BI and a subset of BI, namely, small subcortical BI (SSBI), in 18 population-based cohorts (n=20,949) from 5 ethnicities (3,726 with BI, 2,021 with SSBI). Top loci were followed up in 7 population-based cohorts (n = 6,862; 1,483 with BI, 630 with SBBI), and we tested associations with related phenotypes including ischemic stroke and pathologically defined BI. Results: The mean prevalence was 17.7% for BI and 10.5% for SSBI, steeply rising after age 65. Two loci showed genome-wide significant association with BI: FBN2, p = 1.77 × 10-8; and LINC00539/ZDHHC20, p = 5.82 × 10-9. Both have been associated with blood pressure (BP)-related phenotypes, but did not replicate in the smaller follow-up sample or show associations with related phenotypes. Age- and sex-adjusted associations with BI and SSBI were observed for BP traits (p value for BI, p[BI] = 9.38 × 10-25; p [SSBI] = 5.23 × 10-14 for hypertension), smoking (p[BI]= 4.4 × 10-10; p [SSBI] = 1.2 × 10 -4), diabetes (p[BI] = 1.7 × 10 -8; p [SSBI] = 2.8 × 10 -3), previous cardiovascular disease (p [BI] = 1.0 × 10-18; p [SSBI] = 2.3 × 10-7), stroke (p [BI] = 3.9 × 10-69; p [SSBI] = 3.2 × 10 -24), and MRI-defined white matter hyperintensity burden (p [BI]=1.43 × 10-157; p [SSBI] = 3.16 × 10-106), but not with body mass index or cholesterol. GRS of BP traits were associated with BI and SSBI (p ≤ 0.0022), without indication of directional pleiotropy. Conclusion: In this multiethnic GWAS meta-analysis, including over 20,000 population-based participants, we identified genetic risk loci for BI requiring validation once additional large datasets become available. High BP, including genetically determined, was the most significant modifiable, causal risk factor for BI., CHAP: R01-AG-11101, R01-AG-030146, NIRP-14-302587. SMART: This study was supported by a grant from the Netherlands Organization for Scientific Research–Medical Sciences (project no. 904-65–095). LBC: The authors thank the LBC1936 participants and the members of the LBC1936 research team who collected and collated the phenotypic and genotypic data. The LBC1936 is supported by Age UK (Disconnected Mind Programme grant). The work was undertaken by The University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology, part of the cross-council Lifelong Health and Wellbeing Initiative (MR/K026992/1). The brain imaging was performed in the Brain Research Imaging Centre (https://www.ed.ac.uk/clinical-sciences/edinburgh-imaging), a center in the SINAPSE Collaboration (sinapse.ac.uk) supported by the Scottish Funding Council and Chief Scientist Office. Funding from the UK Biotechnology and Biological Sciences Research Council (BBSRC) and the UK Medical Research Council is acknowledged. Genotyping was supported by a grant from the BBSRC (ref. BB/F019394/1). PROSPER: The PROSPER study was supported by an investigator-initiated grant obtained from Bristol-Myers Squibb. Prof. Dr. J.W. Jukema is an Established Clinical Investigator of the Netherlands Heart Foundation (grant 2001 D 032). Support for genotyping was provided by the seventh framework program of the European commission (grant 223004) and by the Netherlands Genomics Initiative (Netherlands Consortium for Healthy Aging grant 050-060-810). SCES and SiMES: National Medical Research Council Singapore Centre Grant NMRC/CG/013/2013. C.-Y.C. is supported by the National Medical Research Council, Singapore (CSA/033/2012), Singapore Translational Research Award (STaR) 2013. Dr. Kamran Ikram received additional funding from the Singapore Ministry of Health's National Medical Research Council (NMRC/CSA/038/2013). SHIP: SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grants no. 01ZZ9603, 01ZZ0103, and 01ZZ0403), the Ministry of Cultural Affairs, as well as the Social Ministry of the Federal State of Mecklenburg–West Pomerania, and the network “Greifswald Approach to Individualized Medicine (GANI_MED)” funded by the Federal Ministry of Education and Research (grant 03IS2061A). Genome-wide data have been supported by the Federal Ministry of Education and Research (grant no. 03ZIK012) and a joint grant from Siemens Healthineers, Erlangen, Germany, and the Federal State of Mecklenburg–West Pomerania. Whole-body MRI was supported by a joint grant from Siemens Healthineers, Erlangen, Germany, and the Federal State of Mecklenburg–West Pomerania. The University of Greifswald is a member of the Caché Campus program of the InterSystems GmbH. OATS (Older Australian Twins Study): OATS was supported by an Australian National Health and Medical Research Council (NHRMC)/Australian Research Council (ARC) Strategic Award (ID401162) and by a NHMRC grant (ID1045325). OATS was facilitated via access to the Australian Twin Registry, which is supported by the NHMRC Enabling Grant 310667. The OATS genotyping was partly supported by a Commonwealth Scientific and Industrial Research Organisation Flagship Collaboration Fund Grant. NOMAS: The Northern Manhattan Study is funded by the NIH grant “Stroke Incidence and Risk Factors in a Tri-Ethnic Region” (NINDS R01NS 29993). TASCOG: NHMRC and Heart Foundation. AGES: The study was funded by the National Institute on Aging (NIA) (N01-AG-12100), Hjartavernd (the Icelandic Heart Association), and the Althingi (the Icelandic Parliament), with contributions from the Intramural Research Programs at the NIA, the National Heart, Lung, and Blood Institute (NHLBI), and the National Institute of Neurological Disorders and Stroke (NINDS) (Z01 HL004607-08 CE). ERF: The ERF study as a part of European Special Populations Research Network (EUROSPAN) was supported by European Commission FP6 STRP grant no. 018947 (LSHG-CT-2006-01947) and also received funding from the European Community's Seventh Framework Programme (FP7/2007–2013)/grant agreement HEALTH-F4-2007-201413 by the European Commission under the programme “Quality of Life and Management of the Living Resources” of 5th Framework Programme (no. QLG2-CT-2002-01254). High-throughput analysis of the ERF data was supported by a joint grant from Netherlands Organization for Scientific Research and the Russian Foundation for Basic Research (NWO-RFBR 047.017.043). Exome sequencing analysis in ERF was supported by the ZonMw grant (project 91111025). Najaf Amin is supported by the Netherlands Brain Foundation (project no. F2013[1]-28). ARIC: The Atherosclerosis Risk in Communities study was performed as a collaborative study supported by NHLBI contracts (HHSN268201100005C, HSN268201100006C, HSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, and HHSN268201100012C), R01HL70825, R01HL087641, R01HL59367, and R01HL086694; National Human Genome Research Institute contract U01HG004402; and NIH contract HHSN268200625226C. Infrastructure was partly supported by grant no. UL1RR025005, a component of the NIH and NIH Roadmap for Medical Research. This project was also supported by NIH R01 grant NS087541 to M.F. FHS: This work was supported by the National Heart, Lung and Blood Institute's Framingham Heart Study (contracts no. N01-HC-25195 and no. HHSN268201500001I), and its contract with Affymetrix, Inc. for genotyping services (contract no. N02-HL-6-4278). A portion of this research utilized the Linux Cluster for Genetic Analysis (LinGA-II) funded by the Robert Dawson Evans Endowment of the Department of Medicine at Boston University School of Medicine and Boston Medical Center. This study was also supported by grants from the NIA (R01s AG033040, AG033193, AG054076, AG049607, AG008122, and U01-AG049505) and the NINDS (R01-NS017950, UH2 NS100605). Dr. DeCarli is supported by the Alzheimer's Disease Center (P30 AG 010129). ASPS: The research reported in this article was funded by the Austrian Science Fund (FWF) grant nos. P20545-P05, P13180, and P20545-B05, by the Austrian National Bank Anniversary Fund, P15435, and the Austrian Ministry of Science under the aegis of the EU Joint Programme–Neurodegenerative Disease Research (JPND) (jpnd.eu). LLS: The Leiden Longevity Study has received funding from the European Union's Seventh Framework Programme (FP7/2007–2011) under grant agreement no. 259679. This study was supported by a grant from the Innovation-Oriented Research Program on Genomics (SenterNovem IGE05007), the Centre for Medical Systems Biology, and the Netherlands Consortium for Healthy Ageing (grant 050-060-810), all in the framework of the Netherlands Genomics Initiative, Netherlands Organization for Scientific Research (NWO), UnileverColworth, and by BBMRI-NL, a Research Infrastructure financed by the Dutch government (NWO 184.021.007). CHS: This CHS research was supported by contracts HHSN268201200036C, HHSN268200800007C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086, N01HC15103, and HHSN268200960009C and grants U01HL080295, R01HL087652, R01HL105756, R01HL103612, R01HL120393, R01HL085251, and R01HL130114 from the NHLBI with additional contribution from NINDS. Additional support was provided through R01AG023629 from the NIA. A full list of principal CHS investigators and institutions can be found at CHS-NHLBI.org. The provision of genotyping data was supported in part by the National Center for Advancing Translational Sciences, CTSI grant UL1TR001881, and the National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center grant DK063491 to the Southern California Diabetes Endocrinology Research Center. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. Rotterdam Study: The generation and management of GWAS genotype data for the Rotterdam Study is supported by the Netherlands Organisation of Scientific Research (NWO) Investments (no. 175.010.2005.011, 911-03-012). This study is funded by the Research Institute for Diseases in the Elderly (014-93-015; RIDE2), the Netherlands Genomics Initiative (NGI)/NWO project no. 050-060-810. The Rotterdam Study is funded by Erasmus MC Medical Center and Erasmus MC University, Rotterdam, Netherlands Organization for Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam. M.A.I. is supported by an NWO Veni grant (916.13.054). The 3-City Study: The 3-City Study is conducted under a partnership agreement among the Institut National de la Santé et de la Recherche Médicale (INSERM), the University of Bordeaux, and Sanofi-Aventis. The Fondation pour la Recherche Médicale funded the preparation and initiation of the study. The 3C Study is also supported by the Caisse Nationale Maladie des Travailleurs Salariés, Direction Générale de la Santé, Mutuelle Générale de l’Education Nationale (MGEN), Institut de la Longévité, Conseils Régionaux of Aquitaine and Bourgogne, Fondation de France, and Ministry of Research–INSERM Programme “Cohortes et collections de données biologiques.” C.T. and S.D. have received investigator-initiated research funding from the French National Research Agency (ANR) and from the Fondation Leducq. S.D. is supported by a starting grant from the European Research Council (SEGWAY), a grant from the Joint Programme of Neurodegenerative Disease research (BRIDGET), from the European Union's Horizon 2020 research and innovation programme under grant agreements No 643417 & No 640643, and by the Initiative of Excellence of Bordeaux University. Part of the computations were performed at the Bordeaux Bioinformatics Center (CBiB), University of Bordeaux. This work was supported by the National Foundation for Alzheimer's Disease and Related Disorders, the Institut Pasteur de Lille, the Labex DISTALZ, and the Centre National de Génotypage. ADGC: The Alzheimer Disease Genetics Consortium is supported by NIH. NIH-NIA supported this work through the following grants: ADGC, U01 AG032984, RC2 AG036528; NACC, U01 AG016976; NCRAD, U24 AG021886; NIA LOAD, U24 AG026395, U24 AG026390; Banner Sun Health Research Institute, P30 AG019610; Boston University, P30 AG013846, U01 AG10483, R01 CA129769, R01 MH080295, R01 AG017173, R01 AG025259, R01AG33193; Columbia University, P50 AG008702, R37 AG015473; Duke University, P30 AG028377, AG05128; Emory University, AG025688; Group Health Research Institute, UO1 AG06781, UO1 HG004610; Indiana University, P30 AG10133; Johns Hopkins University, P50 AG005146, R01 AG020688; Massachusetts General Hospital, P50 AG005134; Mayo Clinic, P50 AG016574; Mount Sinai School of Medicine, P50 AG005138, P01 AG002219; New York University, P30 AG08051, MO1RR00096, UL1 RR029893, 5R01AG012101, 5R01AG022374, 5R01AG013616, 1RC2AG036502, 1R01AG035137; Northwestern University, P30 AG013854; Oregon Health & Science University, P30 AG008017, R01 AG026916; Rush University, P30 AG010161, R01 AG019085, R01 AG15819, R01 AG17917, R01 AG30146; TGen, R01 NS059873; University of Alabama at Birmingham, P50 AG016582, UL1RR02777; University of Arizona, R01 AG031581; University of California, Davis, P30 AG010129; University of California, Irvine, P50 AG016573, P50, P50 AG016575, P50 AG016576, P50 AG016577; University of California, Los Angeles, P50 AG016570; University of California, San Diego, P50 AG005131; University of California, San Francisco, P50 AG023501, P01 AG019724; University of Kentucky, P30 AG028383, AG05144; University of Michigan, P50 AG008671; University of Pennsylvania, P30 AG010124; University of Pittsburgh, P50 AG005133, AG030653; University of Southern California, P50 AG005142; University of Texas Southwestern, P30 AG012300; University of Miami, R01 AG027944, AG010491, AG027944, AG021547, AG019757; University of Washington, P50 AG005136; Vanderbilt University, R01 AG019085; and Washington University, P50 AG005681, P01 AG03991. The Kathleen Price Bryan Brain Bank at Duke University Medical Center is funded by NINDS grant NS39764, NIMH MH60451, and by GlaxoSmithKline. Genotyping of the TGEN2 cohort was supported by Kronos Science. The TGen series was also funded by NIA grant AG041232, the Banner Alzheimer's Foundation, The Johnnie B. Byrd Sr. Alzheimer's Institute, the Medical Research Council, and the state of Arizona and also includes samples from the following sites: Newcastle Brain Tissue Resource (funding via the Medical Research Council [MRC], local NHS trusts, and Newcastle University), MRC London Brain Bank for Neurodegenerative Diseases (funding via the Medical Research Council), South West Dementia Brain Bank (funding via numerous sources including the Higher Education Funding Council for England [HEFCE], Alzheimer's Research Trust [ART], BRACE, as well as North Bristol NHS Trust Research and Innovation Department and DeNDRoN), The Netherlands Brain Bank (funding via numerous sources including Stichting MS Research, Brain Net Europe, Hersenstichting Nederland Breinbrekend Werk, International Parkinson Fonds, Internationale Stiching Alzheimer Onderzoek), Institut de Neuropatologia, Servei Anatomia Patologica, and Universitat de Barcelona). ADNI: Funding for ADNI is through the Northern California Institute for Research and Education by grants from Abbott, AstraZeneca AB, Bayer Schering Pharma AG, Bristol-Myers Squibb, Eisai Global Clinical Development, Elan Corporation, Genentech, GE Healthcare, GlaxoSmithKline, Innogenetics, Johnson & Johnson, Eli Lilly and Co., Medpace, Inc., Merck and Co., Inc., Novartis AG, Pfizer Inc, F. Hoffman-La Roche, Schering-Plough, Synarc, Inc., Alzheimer's Association, Alzheimer's Drug Discovery Foundation, the Dana Foundation, and the National Institute of Biomedical Imaging and Bioengineering and NIA grants U01 AG024904, RC2 AG036535, and K01 AG030514. Support was also provided by the Alzheimer's Association (LAF, IIRG-08-89720; MAP-V, IIRG-05-14147) and the US Department of Veterans Affairs Administration, Office of Research and Development, Biomedical Laboratory Research Program. SiGN: Stroke Genetic Network (SiGN) was supported in part by award nos. U01NS069208 and R01NS100178 from NINDS. Genetics of Early-Onset Stroke (GEOS) Study was supported by the NIH Genes, Environment and Health Initiative (GEI) grant U01 HG004436, as part of the GENEVA consortium under GEI, with additional support provided by the Mid-Atlantic Nutrition and Obesity Research Center (P30 DK072488); and the Office of Research and Development, Medical Research Service, and the Baltimore Geriatrics Research, Education, and Clinical Center of the Department of Veterans Affairs. Genotyping services were provided by the Johns Hopkins University Center for Inherited Disease Research (CIDR), which is fully funded through a federal contract from the NIH to Johns Hopkins University (contract no. HHSN268200782096C). Assistance with data cleaning was provided by the GENEVA Coordinating Center (U01 HG 004446; PI Bruce S. Weir). Study recruitment and assembly of datasets were supported by a Cooperative Agreement with the Division of Adult and Community Health, Centers for Disease Control and Prevention, and by grants from NINDS and the NIH Office of Research on Women's Health (R01 NS45012, U01 NS069208-01). METASTROKE: ASGC: Australian population control data were derived from the Hunter Community Study. This research was funded by grants from the Australian National and Medical Health Research Council (NHMRC Project Grant ID: 569257), the Australian National Heart Foundation (NHF Project Grant ID: G 04S 1623), the University of Newcastle, the Gladys M Brawn Fellowship scheme, and the Vincent Fairfax Family Foundation in Australia. E.G.H. was supported by a Fellowship from the NHF and National Stroke Foundation of Australia (ID: 100071). J.M. was supported by an Australian Postgraduate Award. BRAINS: Bio-Repository of DNA in Stroke (BRAINS) is partly funded by a Senior Fellowship from the Department of Health (UK) to P.S., the Henry Smith Charity, and the UK-India Education Research Institutive (UKIERI) from the British Council. GEOS: Genetics of Early Onset Stroke (GEOS) Study, Baltimore, was supported by GEI Grant U01 HG004436, as part of the GENEVA consortium under GEI, with additional support provided by the Mid-Atlantic Nutrition and Obesity Research Center (P30 DK072488), and the Office of Research and Development, Medical Research Service, and the Baltimore Geriatrics Research, Education, and Clinical Center of the Department of Veterans Affairs. Genotyping services were provided by the Johns Hopkins University Center for Inherited Disease Research (CIDR), which is fully funded through a federal contract from the NIH to the Johns Hopkins University (contract no. HHSN268200782096C). Assistance with data cleaning was provided by the GENEVA Coordinating Center (U01 HG 004446; PI Bruce S. Weir). Study recruitment and assembly of datasets were supported by a Cooperative Agreement with the Division of Adult and Community Health, Centers for Disease Control and Prevention, and by grants from NINDS and the NIH Office of Research on Women's Health (R01 NS45012, U01 NS069208-01). HPS: Heart Protection Study (HPS) (ISRCTN48489393) was supported by the UK MRC, British Heart Foundation, Merck and Co. (manufacturers of simvastatin), and Roche Vitamins Ltd. (manufacturers of vitamins). Genotyping was supported by a grant to Oxford University and CNG from Merck and Co. J.C.H. acknowledges support from the British Heart Foundation (FS/14/55/30806). ISGS: Ischemic Stroke Genetics Study (ISGS)/Siblings With Ischemic Stroke Study (SWISS) was supported in part by the Intramural Research Program of the NIA, NIH project Z01 AG-000954-06. ISGS/SWISS used samples and clinical data from the NIH-NINDS Human Genetics Resource Center DNA and Cell Line Repository (ccr.coriell.org/ninds), human subjects protocol nos. 2003-081 and 2004-147. ISGS/SWISS used stroke-free participants from the Baltimore Longitudinal Study of Aging (BLSA) as controls. The inclusion of BLSA samples was supported in part by the Intramural Research Program of the NIA, NIH project Z01 AG-000015-50, human subjects protocol no. 2003-078. The ISGS study was funded by NIH-NINDS Grant R01 NS-42733 (J.F.M.). The SWISS study was funded by NIH-NINDS Grant R01 NS-39987 (J.F.M.). This study used the high-performance computational capabilities of the Biowulf Linux cluster at the NIH (biowulf.nih.gov). MGH-GASROS: MGH Genes Affecting Stroke Risk and Outcome Study (MGH-GASROS) was supported by NINDS (U01 NS069208), the American Heart Association/Bugher Foundation Centers for Stroke Prevention Research 0775010N, the NIH and NHLBI's STAMPEED genomics research program (R01 HL087676), and a grant from the National Center for Research Resources. The Broad Institute Center for Genotyping and Analysis is supported by grant U54 RR020278 from the National Center for Research resources. Milan: Milano–Besta Stroke Register Collection and genotyping of the Milan cases within CEDIR were supported by the Italian Ministry of Health (grant nos.: RC 2007/LR6, RC 2008/LR6; RC 2009/LR8; RC 2010/LR8; GR-2011-02347041), FP6 LSHM-CT-2007-037273 for the PROCARDIS control samples. WTCCC2: Wellcome Trust Case-Control Consortium 2 (WTCCC2) was principally funded by the Wellcome Trust, as part of the Wellcome Trust Case Control Consortium 2 project (085475/B/08/Z and 085475/Z/08/Z and WT084724MA). The Stroke Association provided additional support for collection of some of the St George's, London cases. The Oxford cases were collected as part of the Oxford Vascular Study, which is funded by the MRC, Stroke Association, Dunhill Medical Trust, National Institute of Health Research (NIHR), and the NIHR Biomedical Research Centre, Oxford. The Edinburgh Stroke Study was supported by the Wellcome Trust (clinician scientist award to C.L.M.S.) and the Binks Trust. Sample processing occurred in the Genetics Core Laboratory of the Wellcome Trust Clinical Research Facility, Western General Hospital, Edinburgh. Much of the neuroimaging occurred in the Scottish Funding Council Brain Imaging Research Centre (https://www.ed.ac.uk/clinical-sciences/edinburgh-imaging), Division of Clinical Neurosciences, University of Edinburgh, a core area of the Wellcome Trust Clinical Research Facility, and part of the SINAPSE (Scottish Imaging Network: A Platform for Scientific Excellence) collaboration (sinapse.ac.uk), funded by the Scottish Funding Council and the Chief Scientist Office. Collection of the Munich cases and data analysis was supported by the Vascular Dementia Research Foundation. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreements no. 666881, SVDs@target (to M.D.) and no. 667375, CoSTREAM (to M.D.); the DFG as part of the Munich Cluster for Systems Neurology (EXC 1010 SyNergy) and the CRC 1123 (B3) (to M.D.); the Corona Foundation (to M.D.); the Fondation Leducq (Transatlantic Network of Excellence on the Pathogenesis of Small Vessel Disease of the Brain) (to M.D.); the e:Med program (e:AtheroSysMed) (to M.D.) and the FP7/2007-2103 European Union project CVgenes@target (grant agreement no. Health-F2-2013-601456) (to M.D.). M.F. and A.H. acknowledge support from the BHF Centre of Research Excellence in Oxford and the Wellcome Trust core award (090532/Z/09/Z). VISP: The GWAS component of the Vitamin Intervention for Stroke Prevention (VISP) study was supported by the US National Human Genome Research Institute (NHGRI), grant U01 HG005160 (PI Michèle Sale and Bradford Worrall), as part of the Genomics and Randomized Trials Network (GARNET). Genotyping services were provided by the Johns Hopkins University Center for Inherited Disease Research (CIDR), which is fully funded through a federal contract from the NIH to Johns Hopkins University. Assistance with data cleaning was provided by the GARNET Coordinating Center (U01 HG005157; PI Bruce S. Weir). Study recruitment and collection of datasets for the VISP clinical trial were supported by an investigator-initiated research grant (R01 NS34447; PI James Toole) from the US Public Health Service, NINDS, Bethesda, MD. Control data obtained through the database of genotypes and phenotypes (dbGAP) maintained and supported by the United States National Center for Biotechnology Information, US National Library of Medicine. WHI: Funding support for WHI-GARNET was provided through the NHGRI GARNET (grant no. U01 HG005152). Assistance with phenotype harmonization and genotype cleaning, as well as with general study coordination, was provided by the GARNET Coordinating Center (U01 HG005157). Funding support for genotyping, which was performed at the Broad Institute of MIT and Harvard, was provided by the GEI (U01 HG004424). R.L. is a senior clinical investigator of FWO Flanders. F.W.A. is supported by a Dekker scholarship-Junior Staff Member 2014T001–Netherlands Heart Foundation and UCL Hospitals NIHR Biomedical Research Centre.