Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.

Data availabilitySummary statistics generated by COVID-19 Host Genetics Initiative are available online (https://www.covid19hg.org/results/r6/). The analyses described here use the freeze 6 data. The COVID-19 Host Genetics Initiative continues to regularly release new data freezes. Summary statistics for samples from individuals of non-European ancestry are not currently available owing to the small individual sample sizes of these groups, but the results for 23 loci lead variants are reported in Supplementary Table 3. Individual-level data can be requested directly from the authors of the contributing studies, listed in Supplementary Table 1.

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.

Rationale: Ischemic stroke (IS) 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 genome-wide association study (GWAS) in IS recovery to date. Methods and Results: A 12-cohort, two-phase (discovery-replication and joint) meta-analysis of GWAS included anterior-territory and previously independent IS cases. Functional outcome was recorded using 3-month modified Rankin Scale (mRS). Analyses were adjusted for confounders such as discharge NIHSS. A gene-based burden test was performed. The discovery phase (n=1,225) was followed by open (n=2,482) and stringent joint-analyses (n=1,791). Those cohorts with mRS recorded at timepoints other than 3-month or incomplete data on previous functional status were excluded in the stringent analyses. Novel variants in Pals1-Associated Tight Junction (PATJ) gene were associated with worse functional outcome at 3-month after stroke. The top variant was rs76221407 (G allele, beta=0•40, p=1•70×10 −9). Conclusions: Our results identify a set of common variants in PATJ gene associated with 3month 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.

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.