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This study aimed to investigate the influence of stroke lesions in pre-defined highly interconnected (rich club) brain regions on functional outcome post-stroke, determine their spatial specificity and explore the effects of biological sex on their relevance.We analyzed MRI data recorded at index stroke and ∼3-months modified Rankin Scale (mRS) data from patients with acute ischemic stroke (AIS) enrolled in the multisite MRI-GENIE study. Structural stroke lesions were spatially normalized and parcellated into 108 atlas-defined bilateral (sub)cortical brain regions. Unfavorable outcome (mRS>2) was modeled in a Bayesian logistic regression framework that relied on both lesion location, as well as the covariates: age, sex, total DWI lesion volume and comorbidities. Effects of individual brain regions were captured as two compound effects for (i) six bilateral rich club and (ii) all further non-rich club regions. Via model comparisons, we first tested whether the rich club region model was superior to a baseline model considering clinical covariates and lesion volume only. In spatial specificity analyses, we randomized the split into “rich club” and “non-rich club” regions and compared the effect of the actual rich club regions to the distribution of effects from 1,000 combinations of six random regions. In sex-specific analyses, we introduced an additional hierarchical level in our model structure to compare male and female-specific rich club region effects.A total of 822 patients (age: 64.7 (standard deviation: 15.0), 39% women, 27.7% with mRS>2) were analyzed. The rich club model substantially outperformed the baseline model (weights of model comparison: rich club model: 0.96; baseline: 0.04). Rich club regions had substantial relevance in explaining unfavorable functional outcome (mean of posterior distribution: 0.08, area under the curve: 0.8). In particular, the rich club-combination had a higher relevance than 98.4% of random constellations (15/1,000 random constellations with higher mean posterior values). Among the these 15 random constellations with higher means, the most frequently selected regions were the inferior temporal gyrus (posterior division, 8/15), the putamen (8/15), the cingulate gyrus (7/15) and the superior parietal lobule (6/15). Rich club regions were substantially more important in explaining long-term outcome in women than in men (mean of the difference distribution:-0.107, 90%-HDPI:-0.193 to -0.0124).Lesions in rich club regions were associated with increased odds of unfavorable outcome. These effects were spatially specific, i.e., the majority of random combinations of six regions had comparably smaller effects on long-term outcome. Effects were substantially more pronounced in women.

Patients with migraine suffer from high morbidity related to the repeated headache attacks, characteristic of the disorder, poor sleep, and a high prevalence of comorbid psychosocial disorders. Current pharmacological therapies do not address these aspects of migraine, but nonpharmacological treatments such as mindfulness-based stress reduction (MBSR) have been shown to improve both pain and psychological well-being. In this secondary analysis, we examined the change over time in sleep quality and psychosocial outcomes from the magnetic resonance imaging outcomes for mindfulness meditation clinical trial and assessed how these mediated treatment response (50% reduction in headache frequency postintervention). We also examined the relationship between baseline values and treatment response. The trial (primary outcomes previously reported) included 98 patients with episodic migraine randomized to either enhanced MBSR (MBSR+) or stress management for headache. They completed psychosocial questionnaires and headache diaries at baseline (preintervention), midintervention (10 weeks after baseline), and postintervention (20 weeks after baseline). There was a significant improvement in sleep quality from baseline to postintervention (P = 0.0025) in both groups. There were no significant changes from baseline or between groups in anxiety, depression, and stress. There was also no significant association between baseline scores and treatment response. Mediation analysis showed a significant indirect effect of 6% for sleep: In other words, small improvements in sleep may have contributed to the efficacy of MBSR+.Trial registration: NCT02133209.

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.

ObjectiveTo examine etiologic stroke subtypes and vascular risk factor profiles and their association with white matter hyperintensity (WMH) burden in patients hospitalized for acute ischemic stroke (AIS).MethodsFor the MRI Genetics Interface Exploration (MRI-GENIE) study, we systematically assembled brain imaging and phenotypic data for 3,301 patients with AIS. All cases underwent standardized web tool–based stroke subtyping with the Causative Classification of Ischemic Stroke (CCS). WMH volume (WMHv) was measured on T2 brain MRI scans of 2,529 patients with a fully automated deep-learning trained algorithm. Univariable and multivariable linear mixed-effects modeling was carried out to investigate the relationship of vascular risk factors with WMHv and CCS subtypes.ResultsPatients with AIS with large artery atherosclerosis, major cardioembolic stroke, small artery occlusion (SAO), other, and undetermined causes of AIS differed significantly in their vascular risk factor profile (all p < 0.001). Median WMHv in all patients with AIS was 5.86 cm3 (interquartile range 2.18–14.61 cm3) and differed significantly across CCS subtypes (p < 0.0001). In multivariable analysis, age, hypertension, prior stroke, smoking (all p < 0.001), and diabetes mellitus (p = 0.041) were independent predictors of WMHv. When adjusted for confounders, patients with SAO had significantly higher WMHv compared to those with all other stroke subtypes (p < 0.001).ConclusionIn this international multicenter, hospital-based cohort of patients with AIS, we demonstrate that vascular risk factor profiles and extent of WMH burden differ by CCS subtype, with the highest lesion burden detected in patients with SAO. These findings further support the small vessel hypothesis of WMH lesions detected on brain MRI of patients with ischemic stroke.

OBJECTIVE:To determine whether brain volume is associated with functional outcome after acute ischemic stroke (AIS). PATIENTS AND METHODS:This study was conducted between July 1, 2014, and March 16, 2019. We analyzed cross-sectional data of the multisite, international hospital-based MRI-Genetics Interface Exploration study with clinical brain magnetic resonance imaging obtained on admission for index stroke and functional outcome assessment. Poststroke outcome was determined using the modified Rankin Scale score (0-6; 0 = asymptomatic; 6 = death) recorded between 60 and 190 days after stroke. Demographic characteristics and other clinical variables including acute stroke severity (measured as National Institutes of Health Stroke Scale score), vascular risk factors, and etiologic stroke subtypes (Causative Classification of Stroke system) were recorded during index admission. RESULTS:Utilizing the data from 912 patients with AIS (mean ± SD age, 65.3±14.5 years; male, 532 [58.3%]; history of smoking, 519 [56.9%]; hypertension, 595 [65.2%]) in a generalized linear model, brain volume (per 155.1 cm3) was associated with age (β -0.3 [per 14.4 years]), male sex (β 1.0), and prior stroke (β -0.2). In the multivariable outcome model, brain volume was an independent predictor of modified Rankin Scale score (β -0.233), with reduced odds of worse long-term functional outcomes (odds ratio, 0.8; 95% CI, 0.7-0.9) in those with larger brain volumes. CONCLUSION:Larger brain volume quantified on clinical magnetic resonance imaging of patients with AIS at the time of stroke purports a protective mechanism. The role of brain volume as a prognostic, protective biomarker has the potential to forge new areas of research and advance current knowledge of the mechanisms of poststroke recovery.

Ischemic stroke (IS), caused by obstruction of cerebral blood flow, is one of the leading causes of death. While neurologists agree on delineation of IS into three subtypes (cardioembolic stroke (CES), large artery stroke (LAS), and small vessel stroke (SVS)), several subtyping systems exist. The most commonly used systems are TOAST (Trial of Org 10172 in Acute Stroke Treatment) and CCS (Causative Classification System for Stroke), but agreement is only moderate. We have compared two approaches to combining the existing subtyping systems for a phenotype suited for a genome-wide association study (GWAS). We used the NINDS Stroke Genetics Network dataset (SiGN, 11,477 cases with CCS and TOAST subtypes and 28,026 controls). We defined two new phenotypes: the intersect, for which an individual must be assigned the same subtype by CCS and TOAST; and the union, for which an individual must be assigned a subtype by either CCS or TOAST. The union yields the largest sample size while the intersect yields a phenotype with less potential misclassification. We performed GWAS for all subtypes, using the original subtyping systems, the intersect, and the union as phenotypes. In each subtype, heritability was higher for the intersect compared with the other phenotypes. We observed stronger effects at known IS variants with the intersect compared with the other phenotypes. With the intersect, we identify rs10029218:G>A as an associated variant with SVS. We conclude that this approach increases the likelihood to detect genetic associations in ischemic stroke.

Introduction Females have a reduced risk of Parkinson's disease (PD). However, it is unclear if sex is a prognostic factor. We aimed to examine differences in presentation, physician- and patient-reported PD outcomes, and progression by sex in a large clinical cohort. Methods This study was a secondary analysis of a cohort of PD patients seen at a tertiary care center. Sociodemographic and clinical characteristics, treatment, care timing, and outcomes were examined by sex. Sex differences in progression of impairment, disability, and health-related quality of life (HRQoL) were tested with five-year piecewise linear mixed-effects models. A mediation analysis assessed drivers of sex differences. Results The study included 914 males and 549 females. Females had significantly less social support, more psychological distress, and worse self-reported (but not physician-reported) disability and HRQoL at initial PD care visits, compared to males. Addressing anxiety symptoms may attenuate this difference. PD progression sex differences were minimal. Conclusion PD progression does not differ by sex, yet patient-reported measures of disease severity are worse in females than males. To attenuate this sex difference in disease experience, psychological distress screening and management, particularly targeting females, should be implemented as part of PD clinical care.

Background and Purpose: Although the US Black population has a higher incidence of stroke compared with the US White population, few studies have addressed Black-White differences in the contribution of vascular risk factors to the population burden of ischemic stroke in young adults. Methods: A population-based case-control study of early-onset ischemic stroke, ages 15 to 49 years, was conducted in the Baltimore-Washington DC region between 1992 and 2007. Risk factor data was obtained by in-person interview in both cases and controls. The prevalence, odds ratio, and population-attributable risk percent (PAR%) of smoking, diabetes, and hypertension was determined among Black patients and White patients, stratified by sex. Results: The study included 1044 cases and 1099 controls. Of the cases, 47% were Black patients, 54% were men, and the mean (±SD) age was 41.0 (±6.8) years. For smoking, the population-attributable risk percent were White men 19.7%, White women 32.5%, Black men 10.1%, and Black women 23.8%. For diabetes, the population-attributable risk percent were White men 10.5%, White women 7.4%, Black men 17.2%, and Black women 13.4%. For hypertension, the population-attributable risk percent were White men 17.2%, White women 19.3%, Black men 45.8%, and Black women 26.4%. Conclusions: Modifiable vascular risk factors account for a large proportion of ischemic stroke in young adults. Cigarette smoking was the strongest contributor to stroke among White patients while hypertension was the strongest contributor to stroke among Black patients. These results support early primary prevention efforts focused on smoking cessation and hypertension detection and treatment.

ObjectiveTo examine whether high white matter hyperintensity (WMH) burden is associated with greater stroke severity and worse functional outcomes in lesion pattern-specific ways.MethodsMR neuroimaging and National Institutes of Health Stroke Scale data at index stroke, as well as modified Rankin Scale (mRS) at 3-6 months post-stroke were obtained from MRI-GENIE study of acute ischemic stroke (AIS) patients. Individual WMH volume was automatically derived from FLAIR-images. Stroke lesions were automatically segmented from DWI-images, spatially normalized and parcellated into atlas-defined brain regions. Stroke lesion effects on AIS severity and unfavorable outcomes (mRS>2) were modeled within a purpose-built machine learning and Bayesian regression framework. In particular, interaction effects between stroke lesions and a high versus low WMH burden were integrated via hierarchical model structures. Models were adjusted for the covariates age, age2, sex, total DWI-lesion and WMH volumes, and comorbidities. Data were split into derivation and validation cohorts.ResultsA total of 928 AIS patients contributed to stroke severity analyses (mean age: 64.8(14.5), 40% women), 698 patients to functional outcome analyses (mean age: 65.9(14.7), 41% women). Individual stroke lesions were represented in five anatomically distinct left-hemispheric and five right-hemispheric lesion patterns. Across all patients, acute stroke severity was substantially explained by three of these patterns, that were particularly focused on bilateral subcortical and left-hemispherically pronounced cortical regions. In high WMH burden patients, two lesion patterns consistently emerged as more pronounced in case of stroke severity: the first pattern was centered on left-hemispheric insular, opercular and inferior frontal regions, while the second pattern combined right-hemispheric temporo-parietal regions. Bilateral subcortical regions were most relevant in explaining long term unfavorable outcome. No WMH-specific lesion patterns of functional outcomes were substantiated. However, a higher overall WMH burden was associated with higher odds of unfavorable outcomes.ConclusionsHigher WMH burden increases stroke severity in case of stroke lesions involving left-hemispheric insular, opercular and inferior frontal regions (potentially linked to language functions) and right-hemispheric temporo-parietal regions (potentially linked to attention). These findings may contribute to augment stroke outcome predictions and motivate a WMH burden and stroke lesion pattern-specific clinical management of AIS patients.

Background Variation exists in outcomes following out‐of‐hospital cardiac arrest (OHCA), but whether racial and ethnic disparities exist in post‐arrest provision of targeted temperature management (TTM) is unknown. Methods and Results We performed a retrospective analysis of a prospectively collected cohort of patients who survived to admission following OHCA from the Cardiac Arrest Registry to Enhance Survival, whose catchment area represents ~50% of the United States from 2013‐2019. Our primary exposure was race/ethnicity and primary outcome was utilization of TTM. We built a mixed‐effects model with both state of arrest and admitting hospital modeled as random intercepts to account for clustering. Among 96,695 patients (24.6% Black, 8.0% Hispanic/Latino, 63.4% White), a smaller percentage of Hispanic/Latino patients received TTM than Black or White patients (37.5% vs. 45.0 % vs 43.3%, P < .001) following OHCA. In the mixed‐effects model, Black patients (Odds Ratio [OR] 1.153, 95% Confidence Interval [CI] 1.102‐1.207, P < .001) and Hispanic/Latino patients (OR 1.086, 95% CI 1.017‐1.159, P < .001) were slightly more likely to receive TTM compared to White patients, perhaps due to worse admission neurological status. We did find community level disparity as Hispanic/Latino‐serving hospitals (defined as the top decile of hospitals that cared for the highest proportion of Hispanic/Latino patients) provided less TTM (OR 0.587, 95% CI 0.474 to 0.742, P < .001). Conclusions Reassuringly, we did not find evidence of intrahospital or interpersonal racial or ethnic disparity in the provision of TTM. However, we did find inter‐hospital, community level disparity. Hispanic/Latino‐serving hospitals provided less guideline‐recommended TTM after OHCA.

ObjectiveTo determine the contribution of common genetic variants to risk of early onset ischemic stroke (IS).MethodsWe performed a meta-analysis of genome-wide association studies of early onset IS, ages 18-59, using individual level data or summary statistics in 16,927 cases and 576,353 non-stroke controls from 48 different studies across North America, Europe, and Asia. We further compared effect sizes at our most genome-wide significant loci between early and late onset IS and compared polygenic risk scores for venous thromboembolism between early versus later onset IS.ResultsWe observed an association between early onset IS and ABO, a known stroke locus. The effect size of the peak ABO SNP, rs8176685, was significantly larger in early compared to late onset IS (OR 1.17 (95% C.I.: 1.11-1.22) vs 1.05 (0.99-1.12); p for interaction = 0.008). Analysis of genetically determined ABO blood groups revealed that early onset IS cases were more likely to have blood group A and less likely to have blood group O compared to both non-stroke controls and to late onset IS cases. Using polygenic risk scores, we observed that greater genetic risk for venous thromboembolism, another prothrombotic condition, was more strongly associated with early, compared to late, onset IS (p=0.008).ConclusionThe ABO locus, genetically predicted blood group A, and higher genetic propensity for venous thrombosis are more strongly associated with early onset IS, compared with late onset IS, supporting a stronger role of prothrombotic factors in early onset IS.

While chronological age is one of the most influential determinants of post-stroke outcomes, little is known of the impact of neuroimaging-derived biological brain age. We here first examine whether radiomics analysis of the texture of brain T2-FLAIR MRI images can be used to predict brain age in stroke patients. We then assess the clinical determinants of accelerated brain aging and, finally, its impact on post-stroke functional outcomes. Leveraging a multisite cohort of 4,163 ischemic stroke patients, we show that older-appearing patients have more hypertension, diabetes mellitus, prior strokes, and smoking history and are more likely to develop worse post-stroke outcomes than their younger-appearing counterparts. Our results strengthen the importance of preventive medicine for maintaining brain health in stroke patients as they age and suggest a novel methodology to capture previously undescribed prognostic information available on commonly acquired MRI sequences during routine stroke care.

Women experience worse neurological outcomes following out-of-hospital cardiac arrest (OHCA). It is unknown whether sex disparities exist in the use of targeted temperature management (TTM), a standard of care treatment to improve neurological outcomes.We performed a retrospective study of prospectively collected patients who survived to hospital admission following OHCA from the Cardiac Arrest Registry to Enhance Survival from 2013 through 2019. We compared receipt of TTM by sex in a mixed-effects model adjusted for patient, arrest, neighborhood, and hospital factors, with the admitting hospital modeled as a random intercept.Among 123,419 patients, women had lower rates of shockable rhythms (24.4 % vs. 39.2%, P .001) and lower rates of presumed cardiac aetiologies for arrest (74.3% vs. 81.1%, P .001). Despite receiving a similar rate of TTM in the field (12.1% vs. 12.6%, P = .02), women received less TTM than men upon admission to the hospital (41.6% vs. 46.4%, P .001). In an adjusted mixed-effects model, women were less likely than men to receive TTM (Odds Ratio 0.91, 95% Confidence Interval 0.89 to 0.94). Among the 27,729 patients with data indicating the reason for not using TTM, a higher percentage of women did not receive TTM due to Do-Not-Resuscitate orders/family requests (15.1% vs. 11.4%, p .001) and non-shockable rhythms (11.1% vs. 8.4%, p .001).We found that women received less TTM than men, likely due to early care limitations and a preponderance of non-shockable rhythms.

Background and Purpose: Few studies have examined the dose-response and temporal relationships between marijuana use and ischemic stroke while controlling for important confounders, including the amount of tobacco smoking. The purpose of our study was to address these knowledge gaps. Methods: A population-based case-control study with 1090 cases and 1152 controls was used to investigate the relationship of marijuana use and early-onset ischemic stroke. Cases were first-ever ischemic stroke between the ages of 15 and 49 identified from 59 hospitals in the Baltimore-Washington region. Controls obtained by random digit dialing from the same geographic region were frequency-matched to cases by age, sex, region of residence and, except for the initial study phase, race. After excluding subjects with cocaine and other vasoactive substance use, the final study sample consisted of 751 cases and 813 controls. All participants underwent standardized interviews to characterize stroke risk factors and marijuana use. Unconditional logistic regression analysis was used to assess the relationships between marijuana use and risk of ischemic stroke, adjusting for age, sex, race, study phase, the amount of current tobacco smoking, current alcohol use, hypertension, and diabetes. Results: After adjusting for other risk factors, including the amount of current tobacco smoking, marijuana use was not associated with ischemic stroke, regardless of the timing of use in relationship to the stroke, including ever use, use within 30 days, and use within 24 hours. There was a nonsignificant trend towards increased stroke risk among those who smoked marijuana at least once a week (odds ratio, 1.9 [95% CI, 0.8–4.9]). Conclusions: These analyses do not demonstrate an association between marijuana use and an increased risk of early-onset ischemic stroke, although statistical power was limited for assessing the association among very heavy users.

Acute ischemic stroke affects men and women differently. In particular, women are often reported to experience higher acute stroke severity than men. We derived a low-dimensional representation of anatomical stroke lesions and designed a Bayesian hierarchical modeling framework tailored to estimate possible sex differences in lesion patterns linked to acute stroke severity (National Institute of Health Stroke Scale). This framework was developed in 555 patients (38% female). Findings were validated in an independent cohort (n = 503, 41% female). Here, we show brain lesions in regions subserving motor and language functions help explain stroke severity in both men and women, however more widespread lesion patterns are relevant in female patients. Higher stroke severity in women, but not men, is associated with left hemisphere lesions in the vicinity of the posterior circulation. Our results suggest there are sex-specific functional cerebral asymmetries that may be important for future investigations of sex-stratified approaches to management of acute ischemic stroke., Acute ischemic stroke impacts men and women differently. Here, the authors show how different lesion patterns in men and women are linked to the extent of stroke severity.

Introduction: While oral contraceptive (OC) use is generally safe, women at higher risk for vascular disease are advised to use alternative forms of contraception. Smoking, a prothrombotic factor, is a contraindication for OC use in women over age 35. ABO blood group, specifically the non-O blood types, has also been associated with thrombosis risk. We therefore hypothesized that the effects of smoking and OC use on stroke risk would be accentuated in women with non-O blood groups. Methods: Using data from the Genetics of Early Onset Stroke Study, we used 3 polymorphisms within the ABO locus to classify blood group type in women under age 50, including 347 cases and 383 controls. Logistic regression was used to assess the stroke risk of current OC use, defined as use within 30 days, adjusted for other risk factors, and stratified by O and non-O blood group type. Results: Of the 347 women with early-onset stroke, 45% had African ancestry, 51% had European ancestry, and 4% had other ancestry. The median age was 42 years. After adjusting for race, age, hypertension, diabetes, migraines and aura, and smoking status, the odds ratio (OR) for stroke for smoking alone and OC use alone were 3.0 (95% CI 2.1-4.2) and 3.7 (95% CI 1.7-8.4), respectively in this population. Blood group (O vs non-O) did not appreciably alter the magnitude of these associations. However, the joint risk of smoking and OC use was substantially higher in women with blood group non-O (OR = 9.5, 95% CI 3.2-34.9) vs in women with blood group O (OR=4.9, 95% CI 0.4-110.2). Conclusions: Our findings are consistent with the possibility that non-O type blood group confers an increased risk of early onset stroke among OC users who smoke. Further studies are needed to confirm or refute this possibility and to determine whether non-O blood type should be considered in assessing the risk of OC use.

Intro: In the Early Onset Stroke Consortium (EOSC) trans-ancestry analysis we found the ABO locus to be strongly associated with early onset stroke (rs529565, OR=1.10, p-value= 2.01 x 10-12). The lead SNP at this locus has a significantly larger effect size in early onset cases compared to stroke cases after age sixty and is independently associated with venous thromboembolism. This finding, in addition with previously reported candidate gene studies ( F5 , F11 , PROCR ), suggests that coagulation and hemostasis related pathways may be a major driver of early onset stroke. Motivation: To examine the genetic relationship between VTE risk burden and early onset stroke, we performed a polygenic risk score analysis to determine whether increased genetic risk for VTE was also more strongly associated with early compared to late age of onset stroke. Methods: Weighted VTE polygenetic risk scores based on recent GWAS of VTE were calculated for each individual in 7K early onset, under age 60, stroke cases from the EOSC and in 9K late onset, ages 60 and older, stroke cases from SiGN. Logistic regression was performed to test the association between the VTE-PRS score and ischemic stroke outcome controlling for sex and the first ten principal components to account for ancestry. Analyses were stratified by age of onset. Fixed effects meta-analysis was performed to combined results across the analysis strata. Results: PRS of VTE was associated with early ischemic stroke (OR=1.11, p-value=0.02) and we saw no association between VTE-PRS and late onset stroke (OR=1.04, p-value=0.5). Early cases had a greater PRS of VTE than late cases (p-value=0.01). Conclusion: While VTE has been shown to associate with stroke risk, we observed a greater genetic risk for VTE in early onset ischemic stroke compared to older onset stroke. This complements existing evidence implicating coagulation-related mechanisms as an important genetic mechanism in early onset strokes.

Introduction: Severity of leukoaraiosis detected on T2 MRI scans as white matter hyperintensities (WMH) is associated with infarct growth and poor poststroke outcomes in patients with acute ischemic stroke (AIS). Traditional vascular risk factors (VRF) such as age, hypertension (HTN), type 2 diabetes mellitus (T2D), and cigarette smoking are linked to WMH in large population-based studies, yet casual inferences for WMH in AIS patients are limited. We sought to examine the VRFs for evidence of causal relationships with WMH burden in AIS patients using mendelian randomization principles and polygenic risk score (PRS) methods. Method: We examined FLAIR MRIs obtained within 48 hours of AIS onset in 4,362 European Caucasian patients from the MRI-GENetics Interface Exploration (MRI-GENIE) study. WMH volume (WMHv) was measured using a fully automated deep-learning trained algorithm. We considered 13 VRFs: blood pressure (HTN, SBP, DBP, Pulse Pressure), lipid (total cholesterol, HDL, LDL, TG), BMI, T2D, atrial fibrillation, alcohol use and smoking. For each factor, we calculated a weighted PRS for each individual based on the most recent GWAS with various GWAS p-value cutoff. We then used linear regression to estimate associations between each PRS and log transformed WMHv, controlling for age, gender and principal components of genetic ancestries. Strata-specific estimates were combined using inverse-variance weighting based meta-analysis. Results: PRS of both SBP and DBP were positively and robustly associated with WMHv in the meta-analysis (p value of the association ranging from Conclusion: Using mendelian randomization, our results lend further evidence that high blood pressure is a causal risk factor for WMH in AIS patients. This result is consistent with previous epidemiological studies of leukoaraiosis in stroke-free populations, and it supports universal control of HTN as common contributor to WMH burden and the overall brain health.

IntroductionNeuroimaging measurements of brain structural integrity are thought to be surrogates for brain health, but precise assessments require dedicated advanced image acquisitions. By means of describing the texture of conventional images beyond what meets the naked eye, radiomic analyses hold potential for evaluating brain health. We sought to: 1) evaluate this novel approach to assess brain structural integrity by predicting white matter hyperintensities burdens (WMH) and 2) uncover associations between predictive radiomic features and patients’ clinical phenotypes.MethodsOur analyses were based on a multi-site cohort of 4,163 acute ischemic strokes (AIS) patients with T2-FLAIR MR images and corresponding deep-learning-generated total brain and WMH segmentation. Radiomic features were extracted from normal-appearing brain tissue (brain mask–WMH mask). Radiomics-based prediction of personalized WMH burden was done using ElasticNet linear regression. We built a radiomic signature of WMH with the most stable selected features predictive of WMH burden and then related this signature to clinical variables (age, sex, hypertension (HTN), atrial fibrillation (AF), diabetes mellitus (DM), coronary artery disease (CAD), and history of smoking) using canonical correlation analysis.ResultsRadiomic features were highly predictive of WMH burden (R2=0.855±0.011). Seven pairs of canonical variates (CV) significantly correlated the radiomics signature of WMH and clinical traits with respective canonical correlations of 0.81, 0.65, 0.42, 0.24, 0.20, 0.15, and 0.15 (FDR-corrected p-valuesCV1-6CV7=.012). The clinical CV1 was mainly influenced by age, CV2 by sex, CV3 by history of smoking and DM, CV4 by HTN, CV5 by AF and DM, CV6 by CAD, and CV7 by CAD and DM.ConclusionRadiomics extracted from T2-FLAIR images of AIS patients capture microstructural damage of the cerebral parenchyma and correlate with clinical phenotypes. Further research could evaluate radiomics to predict the progression of WMH.Research in contextEvidence before this studyWe did a systematic review on PubMed until December 1, 2020, for original articles and reviews in which radiomics were used to characterize stroke or cerebrovascular diseases. Radiomic analyses cover a broad ensemble of high-throughput quantification methods applicable to digitalized medical images that extract high-dimensional data by describing a given region of interest by its size, shape, histogram, and relationship between voxels. We used the search terms “radiomics” or “texture analysis”, and “stroke”, “cerebrovascular disease”, “small vessel disease”, or “white matter hyperintensities”. Our research identified 24 studies, 18 studying radiomics of stroke lesions and 6 studying cerebrovascular diseases. All the latter six studies were based on MRI (T1-FLAIR, dynamic contrast-enhanced imaging, T1 & T2-FLAIR, T2-FLAIR post-contrast, T2-FLAIR, and T2-TSE images). Four studies were describing small vessel disease, and two were predicting longitudinal progression of WMH. The average sample size was small with 96 patients included (maximum: 204). One study on 141 patients identified 7 T1-FLAIR radiomic features correlated with cardiovascular risk factors (age and hyperlipidemia) using univariate correlations. All studies were monocentric and performed on a single MRI scanner.Added value of this studyTo date and to the best of our knowledge, this is the largest radiomics study performed on cerebrovascular disease or any topic, and one of the very few to include a great diversity of participating sites with diverse clinical MRI scanners. This study is the first one to establish a radiomic signature of WMH and to interpret its relationship with common cardiovascular risk factors. Our findings add to the body of evidence that damage caused by small vessel disease extend beyond the visible white matter hyperintensities, but the added value resides in the detection of that subvisible damage on routinely acquired T2-FLAIR imaging. It also suggests that cardiovascular phenotypes might manifest in distinct textural patterns detectable on conventional clinical-grade T2-FLAIR images.Implications of all the available evidenceAssessing brain structural integrity has implications for treatment selection, follow-up, prognosis, and recovery prediction in stroke patients but also other neurological disease populations. Measuring cerebral parenchymal structural integrity usually requires advanced imaging such as diffusion tensor imaging or functional MRI. Translation of those neuroimaging biomarkers remains uncommon in clinical practice mainly because of their time-consuming and costly acquisition. Our study provides a potential novel solution to assess brains’ structural integrity applicable to standard, routinely acquired T2-FLAIR imaging.Future research could, for instance, benchmark this radiomics approach against diffusion or functional MRI metrics in the prediction of cognitive or functional outcomes after stroke.

Acute ischemic stroke affects men and women differently in many ways. In particular, women are oftentimes reported to experience a higher acute stroke severity than men. Here, we derived a low-dimensional representation of anatomical stroke lesions and designed a sex-aware Bayesian hierarchical modelling framework for a large-scale, well phenotyped stroke cohort. This framework was tailored to carefully estimate possible sex differences in lesion patterns explaining acute stroke severity (NIHSS) in 1,058 patients (39% female). Anatomical regions known to subserve motor and language functions emerged as relevant regions for both men and women. Female patients, however, presented a more widespread pattern of stroke severity-relevant lesions than male patients. Furthermore, particularly lesions in the posterior circulation of the left hemisphere underlay a higher stroke severity exclusively in women. These sex-sensitive lesion pattern effects could be discovered and subsequently robustly replicated in two large independent, multisite lesion datasets. The constellation of findings has several important conceptual and clinical implications: 1) suggesting sex-specific functional cerebral asymmetries, and 2) motivating a sex-stratified approach to management of acute ischemic stroke. To go beyond sex-averaged stroke research, future studies should explicitly test whether acute therapies administered on the basis of sex-specific cutoff volumes of salvageable tissue will lead to improved outcomes in women after acute ischemic stroke.

Background and Purpose: The genetic contribution to ischemic stroke may include rare- or low-frequency variants of high-penetrance and large-effect sizes. Analyses focusing on early-onset disease, an extreme-phenotype, and on the exome, the protein-coding portion of genes, may increase the likelihood of identifying such rare functional variants. To evaluate this hypothesis, we implemented a 2-stage discovery and replication design, and then addressed whether the identified variants also associated with older-onset disease. Methods: Discovery was performed in UMD-GEOS Study (University of Maryland-Genetics of Early-Onset Stroke), a biracial population-based study of first-ever ischemic stroke cases 15 to 49 years of age (n=723) and nonstroke controls (n=726). All participants had prior GWAS (Genome Wide Association Study) and underwent Illumina exome-chip genotyping. Logistic-regression was performed to test single-variant associations with all-ischemic stroke and TOAST (Trial of ORG 10172 in Acute Stroke Treatment) subtypes in Whites and Blacks. Population level results were combined using meta-analysis. Gene-based aggregation testing and meta-analysis were performed using seqMeta. Covariates included age and gender, and principal-components for population structure. Pathway analyses were performed across all nominally associated genes for each stroke outcome. Replication was attempted through lookups in a previously reported meta-analysis of early-onset stroke and a large-scale stroke genetics study consisting of primarily older-onset cases. Results: Gene burden tests identified a significant association with NAT10 in small-vessel stroke ( P =3.79×10 − 6 ). Pathway analysis of the top 517 genes ( P P −7 ), several were near, including an intronic variant in LEXM (rs7549251; P =4.08×10 − 7 ) and an exonic variant in TRAPPC11 (rs67383011; P =5.19×10 − 6 ). Conclusions: Exome-based analysis in the setting of early-onset stroke is a promising strategy for identifying novel genetic risk variants, loci, and pathways.

ObjectiveTo examine the change over time in sleep quality and psychosocial outcomes from the MRI Outcomes for Mindfulness Meditation Clinical Trial, assess how these mediated treatment response (50% reduction in headache frequency post-intervention) and examine the relationship between baseline values and treatment response.MethodsThis is a secondary analysis of a randomized placebo-controlled trial with single masking. Patients were recruited from the community, headache clinics and primary care offices in Baltimore Maryland. Eligible patients were aged 18-65 and met the International Classification of Headache Disorders criteria for episodic migraine (4-14 headache days in 28 days).The trial (primary outcomes previously reported) included 98 episodic migraine patients randomized to either enhanced (MBSR+) or stress management for headache (SMH). Follow-up visits occurred at 10, 20 and 52 weeks post baseline. Intervention groups met separately for two hours weekly for 8 weeks and then biweekly for an additional 8 weeks. MBSR+ had an additional half-day retreat held between weeks 6 and 8.ResultsThere was a significant improvement in sleep quality from baseline to post-intervention (p=0.0025), in both groups. There were no significant change from baseline or between groups in anxiety, depression and stress. There was also no significant association between baseline scores and treatment response. Mediation analysis showed a significant indirect effect for sleep, anxiety, stress, and depression on treatment response, ranging from 6-8%.ConclusionsThe findings indicate that in episodic migraine, treatment response to MBSR+ compared to SMH was mediated by small, but significant improvements in sleep, anxiety, stress, and depression.

BackgroundThe burden of diabetes and cardiovascular risk is not uniform across the USA, with much of this disparity tracking differences in socioeconomic status, cultural practices and lifestyle. To further evaluate disparities in these disorders, we assessed the prevalence of diabetes, hypertension, and hypercholesterolemia in an Old Order Amish community that is characterized by distinctive sociocultural practices that include a very cohesive social structure and limited use of modern technologies and medications. We compared prevalence of these conditions with that of the overall US population.MethodWe performed a community-wide survey in 5377 Amish individuals aged 18 years and older from the Lancaster County, Pennsylvania, Amish settlement that included a basic physical examination and fasting blood draw during the period 2010–2018. We then compared the prevalence of diabetes, hypertension, and high cholesterol, defined using standard criteria, between the Amish and the European Caucasian subsample of the 2013–2014 US National Health and Nutrition Examination Survey (NHANES).ResultsPrevalence rates for diabetes, hypertension and hypercholesterolemia were 3.3%, 12.7%, and 26.2% in the Amish compared with 13.2%, 37.8% and 35.7% in NHANES (pConclusionThere is substantially lower prevalence of diabetes, hypertension and hypercholesterolemia in the Amish compared with non-Amish Caucasians in the USA. Possible factors contributing to this disparity include higher physical activity levels in the Amish or other protective sociocultural factors, a greater understanding of which could inform risk reduction interventions for these chronic diseases.

Lipoprotein(a), Lp(a), is a modified low-density lipoprotein particle that contains apolipoprotein(a), encoded by LPA, and is a highly heritable, causal risk factor for cardiovascular diseases that varies in concentrations across ancestries. Here, we use deep-coverage whole genome sequencing in 8392 individuals of European and African ancestry to discover and interpret both single-nucleotide variants and copy number (CN) variation associated with Lp(a). We observe that genetic determinants between Europeans and Africans have several unique determinants. The common variant rs12740374 associated with Lp(a) cholesterol is an eQTL for SORT1 and independent of LDL cholesterol. Observed associations of aggregates of rare non-coding variants are largely explained by LPA structural variation, namely the LPA kringle IV 2 (KIV2)-CN. Finally, we find that LPA risk genotypes confer greater relative risk for incident atherosclerotic cardiovascular diseases compared to directly measured Lp(a), and are significantly associated with measures of subclinical atherosclerosis in African Americans., Circulating lipoprotein(a) is an important risk factor for cardiovascular disease and shows variability between different ethnic groups. Here, Zekavat et al. perform whole-genome sequencing in individuals of European and African ancestries and find ancestry-specific genetic determinants for lipoprotein(a) levels.

Context Sulfate is critical in the biotransformation of multiple compounds via sulfation. These compounds include neurotransmitters, proteoglycans, xenobiotics, and hormones such as dehydroepiandrosterone (DHEA). Sulfation reactions are thought to be rate-limited by endogenous sulfate concentrations. The gene, SLC13A1, encodes the sodium-sulfate cotransporter NaS1, responsible for sulfate (re)absorption in the intestines and kidneys. We previously reported two rare, non-linked, nonsense variants in SLC13A1 (R12X and W48X) associated with hyposulfatemia (P = 9 × 10− 20). Objective To examine the effect of serum sulfate concentration and sulfate-lowering genotype on DHEA homeostasis. Design Retrospective cohort study. Setting Academic research. Patients Participants of the Amish Pharmacogenomics of Anti-Platelet Intervention (PAPI) Study and the Amish Hereditary and Phenotype Intervention (HAPI) Study. Main outcome measures DHEA, DHEA-S, and DHEA-S/DHEA ratio. Results Increased serum sulfate was associated with decreased DHEA-S (P = 0.03) and DHEA-S/DHEA ratio (P = 0.06) in males but not females. Female SLC13A1 nonsense variant carriers, who had lower serum sulfate (P = 9 × 10− 13), exhibited 14% lower DHEA levels (P = 0.01) and 7% higher DHEA-S/DHEA ratios compared to female non-carriers (P = 0.002). Consistent with this finding, female SLC13A1 nonsense variant carriers also had lower total testosterone levels compared to non-carrier females (P = 0.03). Conclusions Our results demonstrate an inverse relationship between serum sulfate, and DHEA-S and DHEA-S/DHEA ratio in men, while also suggesting that the sulfate-lowering variants, SLC13A1 R12X and W48X, decrease DHEA and testosterone levels, and increase DHEA-S/DHEA ratio in women. While paradoxical, these results illustrate the complexity of the mechanisms involved in DHEA homeostasis and warrant additional studies to better understand sulfate's role in hormone physiology.

White matter hyperintensity (WMH) burden is a critically important cerebrovascular phenotype linked to prediction of diagnosis and prognosis of diseases, such as acute ischemic stroke (AIS). However, current approaches to its quantification on clinical MRI often rely on time intensive manual delineation of the disease on T2 fluid attenuated inverse recovery (FLAIR), which hinders high-throughput analyses such as genetic discovery. In this work, we present a fully automated pipeline for quantification of WMH in clinical large-scale studies of AIS. The pipeline incorporates automated brain extraction, intensity normalization and WMH segmentation using spatial priors. We first propose a brain extraction algorithm based on a fully convolutional deep learning architecture, specifically designed for clinical FLAIR images. We demonstrate that our method for brain extraction outperforms two commonly used and publicly available methods on clinical quality images in a set of 144 subject scans across 12 acquisition centers, based on dice coefficient (median 0.95; inter-quartile range 0.94-0.95; p < 0.01) and Pearson correlation of total brain volume (r = 0.90). Subsequently, we apply it to the large-scale clinical multi-site MRI-GENIE study (N = 2783) and identify a decrease in total brain volume of -2.4 cc/year. Additionally, we show that the resulting total brain volumes can successfully be used for quality control of image preprocessing. Finally, we obtain WMH volumes by building on an existing automatic WMH segmentation algorithm that delineates and distinguishes between different cerebrovascular pathologies. The learning method mimics expert knowledge of the spatial distribution of the WMH burden using a convolutional auto-encoder. This enables successful computation of WMH volumes of 2533 clinical AIS patients. We utilize these results to demonstrate the increase of WMH burden with age (0.950 cc/year) and show that single site estimates can be biased by the number of subjects recruited. This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 753896 (M.D. Schirmer). This study was supported by NIH-NINDS (MRI-GENIE: R01NS086905 - PI N.Rost, K23NS064052, R01NS082285 - N. Rost, SiGN: U01 NS069208 - J. Rosand, S. Kittner, R01NS059775, R01NS063925, R01NS082285,P50NS051343, R01NS086905, U01 NS069208 - O. Wu), NIH NIBIBNAC (P41EB015902–P. Golland).

Background: Cerebral small vessel disease accounts for ~25-30% of strokes and is a leading cause of age- and hypertension-related cognitive decline and disability. Specific treatments for cerebral small vessel disease are lacking, and therapeutic options for secondary prevention are limited as compared to other common causes of stroke. Identifying stroke-associated protein coding variants is a promising tool to better understand disease etiology and identify novel targets. Methods: The GEOS Study was initiated as a biracial population-based study of cases with first-ever ischemic stroke 15 to 49 years of age and controls. All participants had prior GWAS and underwent Illumina exome-chip genotyping. Logistic regression analysis was conducted to identify associated variants after accounting for population substructure using Principal Component Analysis based on GWAS array data. Gene-based aggregation testing (SKAT) and meta-analysis were performed using seqMeta with ethnicity-specific GWAS PCs. Covariates for these analyses included age and gender. This was followed by Ingenuity Pathway Analyses on the top genes. Results: Gene-based testing using a filter (cumulative MAC>40, # of SNPs per gene≥2, missingness=0) was performed on 7448 genes in 123 small vessel cases and 727 non-stroke controls. Two genes reached exome wide statistical significance (p-6 ) in the meta-analyses: FNDC9 (Fibronectin type III domain containing 9, p=9.2*10 -7 ) and ASXL1 (ASXL Transcriptional Regulator 1, p=3.4*10 -7 ). Although no individual SNPs reached genome-wide significance (3x10 -7 ), a rare missense variant in ASXL1 (MAF=0.02, p=3.5*10 -6 ) was near the threshold. ASXL1 SNPs have been associated with an increased risk of CVD. Pathway analyses of the top 438 genes (p Conclusion: Exome-based analyses of small vessel young-onset ischemic stroke is a promising methodology to identify novel genetic risk variants, genes and pathways.

Background and Purpose— We evaluated deep learning algorithms’ segmentation of acute ischemic lesions on heterogeneous multi-center clinical diffusion-weighted magnetic resonance imaging (MRI) data sets and explored the potential role of this tool for phenotyping acute ischemic stroke. Methods— Ischemic stroke data sets from the MRI-GENIE (MRI-Genetics Interface Exploration) repository consisting of 12 international genetic research centers were retrospectively analyzed using an automated deep learning segmentation algorithm consisting of an ensemble of 3-dimensional convolutional neural networks. Three ensembles were trained using data from the following: (1) 267 patients from an independent single-center cohort, (2) 267 patients from MRI-GENIE, and (3) mixture of (1) and (2). The algorithms’ performances were compared against manual outlines from a separate 383 patient subset from MRI-GENIE. Univariable and multivariable logistic regression with respect to demographics, stroke subtypes, and vascular risk factors were performed to identify phenotypes associated with large acute diffusion-weighted MRI volumes and greater stroke severity in 2770 MRI-GENIE patients. Stroke topography was investigated. Results— The ensemble consisting of a mixture of MRI-GENIE and single-center convolutional neural networks performed best. Subset analysis comparing automated and manual lesion volumes in 383 patients found excellent correlation (ρ=0.92; P 3 (0.9–16.6 cm 3 ). Patients with small artery occlusion stroke subtype had smaller lesion volumes ( P Conclusions— Automated accurate clinical diffusion-weighted MRI lesion segmentation using deep learning algorithms trained with multi-center and diverse data is feasible. Both lesion volume and topography can provide insight into stroke subtypes with sufficient sample size from big heterogeneous multi-center clinical imaging phenotype data sets.

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.

Objective Posterior circulation ischemic stroke (PCiS) constitutes 20–30% of ischemic stroke cases. Detailed information about differences between PCiS and anterior circulation ischemic stroke (ACiS) remains scarce. Such information might guide clinical decision making and prevention strategies. We studied risk factors and ischemic stroke subtypes in PCiS vs. ACiS and lesion location on magnetic resonance imaging (MRI) in PCiS. Methods Out of 3,301 MRIs from 12 sites in the National Institute of Neurological Disorders and Stroke (NINDS) Stroke Genetics Network (SiGN), we included 2,381 cases with acute DWI lesions. The definition of ACiS or PCiS was based on lesion location. We compared the groups using Chi-squared and logistic regression. Results PCiS occurred in 718 (30%) patients and ACiS in 1663 (70%). Diabetes and male sex were more common in PCiS vs. ACiS (diabetes 27% vs. 23%, p .05; male sex 68% vs. 58%, p p p p Conclusion Ischemic stroke subtypes differ between the two phenotypes. Diabetes and male sex have a stronger association with PCiS than ACiS. Definitive MRI-based PCiS diagnosis aids etiological investigation and contributes additional insights into specific risk factors and mechanisms of injury in PCiS.

Vegetable intake is far below recommendations among African-American adolescents living in economically-underserved urban areas. While the National School Lunch Program (NSLP) helps overcome access barriers, vegetable intake remains challenging and novel interventions are required. A two-year, multi-phase, school-based intervention was conducted at an urban, economically-underserved, and predominantly African-American high school in Baltimore, Maryland to determine whether stakeholder-informed addition of spices and herbs to NSLP vegetables would increase intake. The stakeholder engagement phase included assessment of NSLP vegetable attitudes/preferences among 43 school stakeholders and subsequent student sensory testing. The second phase was conducted in the school cafeteria and consisted of eight weeks comparing student intake of typical vegetable recipes versus otherwise-identical recipes with spices and herbs. 4,570 student lunch plates were included in the vegetable intake comparison. Vegetable intake was measured by lunch tray plate waste. Willingness to try vegetables was assessed by the difference between plate waste and estimated mean vegetable served weight. Intake of typical vegetable recipes and vegetable recipes with spices and herbs was compared with student’s t-test. Chi-square test was used to compare willingness to try vegetables. Total vegetable intake was 18.2% higher (8.22 grams per meal, p

Background/Aims: Alpha-carotene is a provitamin A carotenoid present in fruits and vegetables. Higher serum concentrations of α-carotene have been associated with lower risk of cancer and all-cause mortality. Previous studies have suggested that genetic variants influence serum concentrations of provitamin A carotenoids, but to date no variants have been robustly associated with serum α-carotene concentrations. The aim of this study was to identify genetic associations with serum α-carotene concentrations using the genome-wide association study (GWAS) approach. Methods: A GWAS of serum α-carotene concentrations was conducted in 433 Old Order Amish adults who had consumed a 6-day controlled diet. Linear regression models adjusting for age, gender, and family structure were utilized to evaluate associations between genetic variants and serum α-carotene concentrations. Results: Genome-wide significant associations with α-carotene concentrations were observed for loci on chromosome 1q41 between the genes CAPN2 and CAPN8 (rs12137025, p = 3.55 × 10-8), chromosome 2p21 in PRKCE (rs2594495, p = 1.01 × 10-8), and chromosome 4q34 (rs17830069, p = 2.89 × 10-8). Conclusions: We identified 3 novel loci associated with serum α-carotene concentrations among a population that consumed a controlled diet. While replication is necessary, the CAPN2/CAPN8 locus provides compelling evidence for an association with serum α-carotene concentrations and may suggest a relationship with the development and progression of cancers.

Introduction: Genome-wide association (GWA) studies have contributed substantially to the understanding of complex vascular traits including ischemic stroke; however, genetic determinants of acute cerebral ischemia remain to be elucidated. Objective: To investigate the genetic architecture of cerebral infarct lesion burden in patients with acute ischemic stroke (AIS). Methods: Twelve international sites contributed 3,301 AIS subjects with acute MRI and genome-wide genotyping to the MRI-GENIE study. In a preliminary analysis of 657 subjects of European ancestry, acute cerebral infarct lesions were outlined on diffusion-weighted images (DWI) using a semi-automated volumetric method. Standard quality control measures were performed per single nucleotide polymorphism (SNP) and per subject. SNPs were imputed to the Haplotype Reference Consortium v1.1 panel. Natural log-transformed DWI volume was used for GWA analysis with allelic dosage per SNP, age, sex and principal components 1-5 of genetic ancestry as covariates. Results: GWA testing for DWI volume in 7.7 million SNPs yielded no signal crossing the Bonferroni-corrected genome-wide significance threshold of p -8 . However, several loci passed the nominal significance threshold of p -6 (Figure 1), including a locus on chromosome 2 in the SPATA3-AS1 (spermatogenesis associated 3 antisense RNA 1) gene (lead SNP: rs2368999, MAF=36%, p =8.4*10 -7 ) and an intronic locus on chromosome 10 in the ATRNL1 (Attractin like 1) gene (lead SNP: rs592284, MAF=10%, p =9.1*10 -7 ). Conclusion: In this first-to-date, preliminary GWAS of acute cerebral infarct volume in AIS patients, we identified several new, nominally significant loci including a locus in ATRNL1, a gene previously linked to carotid plaque burden. Further analyses of the MRI-GENIE cohort to replicate these findings, to include stroke subtype specific analyses, and to increase the overall statistical power of the study are ongoing.

Background: Current ischemic stroke (IS) subtyping systems are very labor-intensive and costly to implement in large samples. There is a need to develop phenotyping approaches for genetic and other studies that can be implemented using generally available items captured in electronic medical records. Objective: In this report, we seek to validate a simplified approach using results from a genetic association study. Specifically, the strength of association for known genetic signals in the NINDS Stroke Genetics Network study (SiGN) is compared between the established IS subtyping systems (TOAST and Causative Classification System (CCS) subtypes) and phenotyping based on a single item within the CCS. Methods: Non-mutually exclusive “Simple” IS subtypes were defined from single CCS items as follows: 1) Small vessel stroke- lacunar infarct on imaging (with no other imaging or other requirements); 2) large artery stroke - vascular imaging showing > 50% stenosis or Results: The Table shows that, for loci significant in SiGN GWAS study, the “Simple” IS subtypes had similar strengths of association and p-values compared to results from TOAST and the causative and phenotypic CCS subtypes. Conclusions: “Simple” IS subtypes perform as well in GWAS analyses as more complex phenotyping systems and could potentially be derived through automated or semi-automated methods applied to electronic medical record systems. Since the ‘Simple” phenotypes were based on high quality CCS data, the current findings reflect optimal performance. Additional validation studies will be required for implementation in other settings.

Background: The genetic architecture of ischemic stroke (IS) is poorly understood and may differ by age of onset. To identify stroke susceptibility variants, genes and pathways for IS in young adults, we genotyped participants in the Genetics of Early-Onset Stroke (GEOS) with an exome array to interrogate the protein-coding portion of genes. Methods: The GEOS Study was initiated as a biracial population-based study of cases with first-ever ischemic stroke 15 to 49 years of age (n=828) and controls (n=850). All participants had prior GWAS and underwent Illumina exome-chip genotyping. Mixed model regression in EMMAX was conducted to calculate variant-specific associations using pooled European-Caucasians (EUR) and African-Americans (AA) samples, with population structure controlled by kinship matrix relationships using GWAS data. Gene-based burden testing and meta-analysis were performed using seqMeta with ethnicity-specific GWAS PCs. In both analyses covariates included age and gender. This was followed by Ingenuity Pathway Analyses on the top genes. Results: While no individual SNPs reached chip-wide significance (3x10 -7 ), several were near, including one exonic variant in TRAPPC11 (rs67383011, p=1.7*10 -6 ). Gene-based burden testing using a filter (cumulative MAC>40, # of SNPs per gene≥2, missingness=0) was performed on 6934 genes in EURs and 9423 genes in AAs. While several interesting genes were identified, notably in methylation pathways, none reached statistical significance in the ethnicity-stratified (p=3.3*10 -4 ) or meta-analyses (p=1.1*10 -4 ). Pathway analyses on the top 448 genes (p Conclusion: Exome-based analyses in the setting of early-onset stroke is a promising methodology to identify novel genetic risk variants, loci and pathways.

Introduction: White matter hyperintensity (WMH) is a highly heritable trait and a significant contributor to stroke risk and severity. Vascular risk factors contribute to WMH severity; however, knowledge of the determinants of WMH in acute ischemic stroke (AIS) is still limited. Hypothesis: WMH volume (WMHv) varies across AIS subtypes and is modified by vascular risk factors. Methods: We extracted WMHv from the clinical MRI scans of 2683 AIS subjects from the MRI-Genetics Interface Exploration (MRI-GENIE) study using a novel fully-automated, volumetric analysis pipeline. Demographic data, stroke risk factors and stroke subtyping for the Causative Classification of Stroke (CCS) were performed at each of the 12 international study sites. WMHv was natural log-transformed for linear regression analyses. Results: Median WMHv was 5.7cm 3 (interquartile range (IQR): 2.2-12.8cm 3 ). In univariable analysis, age (63.1 ± 14.7 years, β=0.04, SE=0.002), prior stroke (10.2%, β=0.66, SE=0.08), hypertension (65.4%, β=0.75, SE=0.05), diabetes mellitus (23.1%, β=0.35, SE=0.06), coronary artery disease (17.6%, β=0.04, SE=0.002), and atrial fibrillation (14.6%, β=0.48, SE=0.07) were significant predictors of WMHv (all p3 , IQR: 4.2-15.4cm 3 ), large-artery stroke (6.9cm 3 , IQR: 3.1-14.7cm 3 ), small-vessel stroke (5.8cm 3 , IQR: 2.5-13.5cm 3 ), stroke of undetermined (4.7cm 3 , IQR: 1.6-11.0cm 3 ) or other (2.55cm 3 , IQR: 0.9-8.8cm 3 ) causes. Conclusion: In this largest-to-date, multicenter hospital-based cohort of AIS patients with automated WMHv analysis, common vascular risk factors contribute significantly to WMH burden and WMHv varies by CCS subtype.

Background: Ischemic stroke is a heterogeneous trait and its genetic architecture is poorly understood. The genetic contribution may be stronger for stroke occurring at younger (vs. older) ages. To identify additional stroke susceptibility variants, we genotyped participants in the Genetics of Early Onset Stroke (GEOS) with the exome array and conducted association analyses with the goal of identifying functional risk variants by interrogating the protein-coding portion of genes. Methods: The GEOS Study was initiated as a biracial population-based study of cases with first-ever ischemic stroke 15 to 49 years of age (n=828) and matched controls (n=850). All participants underwent exome-chip genotyping. Logistic regression was used to calculate associations in European-Caucasians (EUR) and African-Americans (AA), and summary results were combined by meta-analysis. Results: Our analyses revealed four highly associated variants for all-stroke and several others that were stroke subtype specific. Among these for all-stroke, we identified a missense variant in VWDE (rs6460939 (K (AA G ) --> N (AA C )), which encodes the Von Willebrand Factor D and EGF domain-containing protein. This protein plays a role in intracellular calcium ion binding within a variety of cell-types. The association was present in both European-Caucasians (OR = 1.34, p = 0.002) and African-Americans (OR = 1.32, p = 0.01), and was strengthened in a meta-analysis of both ethnic groups (OR = 1.41, p = 8.95 х 10 -6 ). The frequency of the effect C allele was 0.46 in EUR and 0.55 in AA. Efforts in additional data sets to further replicate this association, and the others identified, are ongoing. Conclusion: Exome-based analyses in the setting of young-onset stroke is a productive methodology to identify genetic risk variants.