Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry(1,2). Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis(3), and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach(4), we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry(5). Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.</p

Stroke genetics informs drug discovery and risk prediction across ancestries

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

Cerebral venous sinus thrombosis associated with coronavirus disease 2019: Case report and review of the literature

INTRODUCTION: Coronavirus disease 2019 (COVID-19) is associated with significant risk of acute thrombosis. We present a case report of a patient with cerebral venous sinus thrombosis (CVST) associated with COVID-19 and performed a literature review of CVST associated with COVID-19 cases. CASE REPORT: A 38-year-old woman was admitted with severe headache and acute altered mental status a week after confirmed diagnosis of COVID-19. Magnetic resonance imaging brain showed diffuse venous sinus thrombosis involving the superficial and deep veins, and diffuse edema of bilateral thalami, basal ganglia and hippocampi because of venous infarction. Her neurological exam improved with anticoagulation (AC) and was subsequently discharged home. We identified 43 patients presenting with CVST associated with COVID-19 infection. 56% were male with mean age of 51.8±18.2 years old. The mean time of CVST diagnosis was 15.6±23.7 days after onset of COVID-19 symptoms. Most patients (87%) had thrombosis of multiple dural sinuses and parenchymal changes (79%). Almost 40% had deep cerebral venous system thrombosis. Laboratory findings revealed elevated mean D-dimer level (7.14/mL±12.23 mg/L) and mean fibrinogen level (4.71±1.93 g/L). Less than half of patients had prior thrombotic risk factors. Seventeen patients (52%) had good outcomes (mRS \u3c=2). The mortality rate was 39% (13 patients). CONCLUSION: CVST should be in the differential diagnosis when patients present with acute neurological symptoms in this COVID pandemic. The mortality rate of CVST associated with COVID-19 can be very high, therefore, early diagnosis and prompt treatment are crucial to the outcomes of these patients

2024 AHA/ASA Performance and Quality Measures for Spontaneous Intracerebral Hemorrhage: A Report From the American Heart Association/American Stroke Association

The American Heart Association/American Stroke Association released a revised spontaneous intracerebral hemorrhage guideline in 2022. A working group of stroke experts reviewed this guideline and identified a subset of recommendations that were deemed suitable for creating performance measures. These 15 performance measures encompass a wide spectrum of intracerebral hemorrhage patient care, from prehospital to posthospital settings, highlighting the importance of timely interventions. The measures also include 5 quality measures and address potential challenges in data collection, with the aim of future improvements

Education research: NeuroBytes: A new rapid, high-yield e-learning platform for continuing professional development in neurology

Objective: To determine whether NeuroBytes is a helpful e-Learning tool in neurology through usage, viewer type, estimated time and cost of development, and post-course survey responses.BackgroundA sustainable continuing professional development (CPD) system is vital in neurology due to the field\u27s expanding therapeutic options and vulnerable patient populations. In an effort to offer concise, evidence based updates to a wide range of neurology professionals, the AAN launched NeuroBytes in 2018. NeuroBytes are brief (min) videos that provide high-yield updates to AAN members.MethodsNeuroBytes was beta tested from August-December 2018 and launched for pilot circulation from January-April 2019. Usage was assessed by quantifying course enrollment and completion rates; feasibility by cost and time required to design and release a module; appeal by user satisfaction; and impact by self-reported change in practice.ResultsA total of 5,130 NeuroBytes enrollments (1,026±551/month) occurred from January 11-May 28, 2019 with a median of 588 enrollments per module (interquartile range, 194-922) and 37% course completion. The majority of viewers were neurologists (54%), neurologists in training (26%), and students (8%). NeuroBytes took 59 hours to develop at an estimated $77.94/hour. Of the 1,895 users who completed the survey, 82% were extremely or very likely to recommend NeuroBytes to a colleague and 60% agreed that the depth of educational content was just right. ConclusionsNeuroBytes is a user-friendly, easily accessible CPD product that delivers concise updates to a broad range of neurology practitioners and trainees. Future efforts will explore models where NeuroBytes combines with other CPD programs to impact quality of training and clinical practice

Stroke genetics informs drug discovery and risk prediction across ancestries.

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