Acute-to-chronic glycemic ratio as an outcome predictor in ischemic stroke in patients with and without diabetes mellitus.

OBJECTIVE: Elevated plasma glucose levels are common in patients suffering acute ischemic stroke (AIS), and acute hyperglycemia has been defined as an independent determinant of adverse outcomes. The impact of acute-to-chronic glycemic ratio (ACR) has been analyzed in other diseases, but its impact on AIS prognosis remains unclear. The main aim of this study was to assess whether the ACR was associated with a 3-month poor prognosis in patients with AIS. RESEARCH, DESIGN AND METHODS: Retrospective analysis of patients admitted for AIS in Hospital del Mar, Barcelona. To estimate the chronic glucose levels (CGL) we used the formula eCGL= [28.7xHbA1c (%)]-46.7. The ACR (glycemic at admission / eCGL) was calculated for all subjects. Tertile 1 was defined as: 0.28-0.92, tertile 2: 0.92-1.13 and tertile 3: > 1.13. Poor prognosis at 3 months after stroke was defined as mRS score 3-6. RESULTS: 2.774 subjects with AIS diagnosis were included. Age, presence of diabetes, previous disability (mRS), initial severity (NIHSS) and revascularization therapy were associated with poor prognosis (p values < 0.05). For each 0.1 increase in ACR, there was a 7% increase in the risk of presenting a poor outcome. The 3rd ACR tertile was independently associated with a poor prognosis and mortality. In the ROC curves, adding the ACR variable to the classical clinical model did not increase the prediction of AIS prognosis (0.786 vs. 0.781). CONCLUSIONS: ACR was positively associated with a poor prognosis and mortality at 3-months follow-up after AIS. Subjects included in the 3rd ACR tertile presented a higher risk of poor prognosis and mortality. Baseline glucose or ACR did not add predictive value in comparison to only using classical clinical variables.

The influence of epigenetic biological age on key complications and outcomes in aneurysmal subarachnoid haemorrhage.

BACKGROUND: We aimed to investigate the association between DNA-methylation biological age (B-age) calculated as age acceleration (ageAcc) and key aneurysmal subarachnoid haemorrhage (aSAH) complications such as vasospasm, delayed cerebral ischaemia (DCI), poor outcome, and mortality. METHODS: We conducted a prospective study involving 277 patients with aSAH. B-age was determined in whole blood samples using five epigenetic clocks: Hannum's, Horvath's, Levine's and both versions of Zhang's clocks. Age acceleration was calculated as the residual obtained from regressing out the effect of C-age on the mismatch between C-age and B-age. We then tested the association between ageAcc and vasospasm, DCI and 12-month poor outcome (mRS 3-5) and mortality using linear regression models adjusted for confounders. RESULTS: Average C-age was 55.0 years, with 66.8% being female. Vasospasm occurred in 143 cases (51.6%), DCI in 70 (25.3%) and poor outcomes in 99 (35.7%), with a mortality rate of 20.6%. Lower ageAcc was linked to vasospasm in Horvath's and Levine's clocks, whereas increased ageAcc was associated with 12-month mortality in Hannum's clock. No significant differences in ageAcc were found for DCI or poor outcome at 12 months with other clocks. CONCLUSIONS: Our study indicates that B-age is independently associated with vasospasm and 12-month mortality in patients with aSAH. These findings underscore the potential role of epigenetics in understanding the pathophysiology of aSAH-related complications and outcomes.

The Role of Epigenetics in Brain Aneurysm and Subarachnoid Hemorrhage: A Comprehensive Review.

This comprehensive review explores the emerging field of epigenetics in intracranial aneurysm (IA) and aneurysmal subarachnoid hemorrhage (aSAH). Despite recent advancements, the high mortality of aSAH needs an understanding of its underlying pathophysiology, where epigenetics plays a crucial role. This review synthesizes the current knowledge, focusing on three primary epigenetic mechanisms: DNA methylation, non-coding RNA (ncRNA), and histone modification in IA and aSAH. While DNA methylation studies are relatively limited, they suggest a significant role in the pathogenesis and prognosis of IA and aSAH, highlighting differentially methylated positions in genes presumably involved in these pathologies. However, methodological limitations, including small sample sizes and a lack of diverse population studies, temper these results. The role of ncRNAs, particularly miRNAs, has been more extensively studied, but there are still few studies focused on histone modifications. Despite methodological challenges and inconsistent findings, these studies underscore the involvement of miRNAs in key pathophysiological processes, including vascular smooth muscle regulation and the inflammatory response. This review emphasizes methodological challenges in epigenetic research, advocating for large-scale epigenome-wide association studies integrating genetic and environmental factors, along with longitudinal studies. Such research could unravel the complex mechanisms behind IA and aSAH, guiding the development of targeted therapeutic approaches.

The relevance of rich club regions for functional outcome post-stroke is enhanced in women.

This study aimed to investigate the influence of stroke lesions in predefined 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 enrolled in the multisite MRI-GENIE study. Spatially normalized structural stroke lesions were parcellated into 108 atlas-defined bilateral (sub)cortical brain regions. Unfavorable outcome (mRS > 2) was modeled in a Bayesian logistic regression framework. 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. 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 1000 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 effects. A total of 822 patients (age: 64.7[15.0], 39% women) were analyzed. 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. Rich club regions were substantially more important in explaining long-term outcome in women than in men. All in all, lesions in rich club regions were associated with increased odds of unfavorable outcome. These effects were spatially specific and more pronounced in women.

Factors associated with migraine aura mimicking stroke in code stroke.

INTRODUCTION: Migraine with aura (MA) is a frequent stroke simulator that can lead to erroneous diagnosis and subsequent unnecessary acute or secondary prevention treatments. We analyzed clinical and laboratory data of migraine with aura and ischemic stroke patients to detect differences that could help in the diagnosis. METHODS: Retrospective analysis of a consecutive register of code strokes between January 2005 and June 2020. Diagnosis of ischemic stroke or MA was collected. Multivariable logistic regression analyses were performed to test associations between clinical and blood data with ischemic stroke. RESULTS: Of 3140 code strokes, 2424 (77.2%) were ischemic strokes and 34 (1.1%) were MA. Migraine cases were younger, more frequently females and with lower prevalence of vascular risk factors. Initial NIHSS was lower in MA cases, but no differences were seen in fibrinolysis rate (30%). Blood test showed lower levels of glucose, D-dimer, and fibrinogen in MA cases. Multivariable model showed and independent association for ischemic stroke with age [OR, (95%CI): 1.09, (1.07-1.12, p < 0.001], male sex [OR, (95%CI): 4.47, (3.80-5.13), p < 0.001], initial NIHSS [OR, (95%CI): 1.21, (1.07-1.34), p < 0.01], and fibrinogen levels [OR, (95%CI): 1.01, (1.00-1.01), p < 0.05]. A model including sex male OR: 3.55 [2.882; 4.598], p < 0.001, and cutoff points (age > 65, OR: 7.953 [7.256; 8.649], p < 0.001, NIHSS > 6, OR: 3.740 [2.882; 4.598], p < 0.01, and fibrinogen > 400 mg/dL, OR: 2.988 [2.290; 3.686], p < 0.01) showed a good global discrimination capability AUC = 0.89 (95%CI: 0.88-0.94). CONCLUSIONS: In code stroke, a model including age, sex, NIHSS, and fibrinogen showed a good discrimination capability to differentiate between MA and Ischemic stroke. Whether these variables can be implemented in a diagnostic rule should be tested in future studies.

Machine Learning Approximations to Predict Epigenetic Age Acceleration in Stroke Patients.

Age acceleration (Age-A) is a useful tool that is able to predict a broad range of health outcomes. It is necessary to determine DNA methylation levels to estimate it, and it is known that Age-A is influenced by environmental, lifestyle, and vascular risk factors (VRF). The aim of this study is to estimate the contribution of these easily measurable factors to Age-A in patients with cerebrovascular disease (CVD), using different machine learning (ML) approximations, and try to find a more accessible model able to predict Age-A. We studied a CVD cohort of 952 patients with information about VRF, lifestyle habits, and target organ damage. We estimated Age-A using Hannum's epigenetic clock, and trained six different models to predict Age-A: a conventional linear regression model, four ML models (elastic net regression (EN), K-Nearest neighbors, random forest, and support vector machine models), and one deep learning approximation (multilayer perceptron (MLP) model). The best-performing models were EN and MLP; although, the predictive capability was modest (R2 0.358 and 0.378, respectively). In conclusion, our results support the influence of these factors on Age-A; although, they were not enough to explain most of its variability.

Increased COVID-19 Mortality in People With Previous Cerebrovascular Disease: A Population-Based Cohort Study.

BACKGROUND: The aim of the study was to determine the association between previous stroke and mortality after coronavirus disease 2019 (COVID-19) according to sex, age groups, and stroke subtypes. METHODS: Prospective population-based cohort study including all COVID-19 positive cases between February 1 and July 31, 2020. Comorbidities and mortality were extracted using linked health administration databases. Previous stroke included transient ischemic attack, ischemic stroke, hemorrhagic stroke, spontaneous subarachnoid hemorrhage, and combined stroke for cases with more than one category. Other comorbidities were obesity, diabetes, hypertension, ischemic heart disease, atrial fibrillation, heart failure, chronic obstructive pulmonary disease, chronic kidney disease, cirrhosis, dementia, individual socioeconomic index, and deprivation index. Cases were followed up until December 31, 2020. Primary outcome was mortality of any cause after COVID-19 positivity. Cox proportional regression analysis adjusted for comorbidities was used. Stratified analyses were performed for sex and age (<60, 60-79, and ≥80 years). RESULTS: There were 91 629 COVID-19 cases. Previous strokes were 5752 (6.27%), of which 3887 (67.57%) were ischemic, 1237 (21.50%) transient ischemic attack, 255 (4.43%) combined, 203 (3.53%) hemorrhagic, and 170 (2.96%) subarachnoid hemorrhage. There were 9512 deaths (10.38%). Mortality was associated with previous stroke (hazard ratio [HR]=1.12 [95% CI, 1.06-1.18]; P<0.001), in both sexes separately (men=1.13 [1.05-1.22]; P=0.001; women=1.09 [1.01-1.18]; P=0.023), in people <60 years (HR=2.97 [1.97-4.48]; P<0.001) and 60 to 79 years (HR=1.32 [1.19-1.48]; P<0.001) but not in people ≥80 years (HR=1.02 [0.96-1.09]; P=0.437). Ischemic (HR=1.11 [1.05-1.18]; P=0.001), hemorrhagic (HR=1.53 [1.20-1.96]; P=0.001) and combined (HR=1.31 [1.05-1.63]; P=0.016) strokes were associated but not transient ischemic attack. Subarachnoid hemorrhage was associated only in people <60 years (HR=5.73 [1.82-18.06]; P=0.003). CONCLUSIONS: Previous stroke was associated with a higher mortality in people younger than 80 years. The association occurred for both ischemic and hemorrhagic stroke but not for transient ischemic attack. These data might help healthcare authorities to establish prioritization strategies for COVID-19 vaccination.

Risk factors analysis according to regional distribution of white matter hyperintensities in a stroke cohort.

OBJECTIVES: The spectrum of distribution of white matter hyperintensities (WMH) may reflect different functional, histopathological, and etiological features. We examined the relationships between cerebrovascular risk factors (CVRF) and different patterns of WMH in MRI using a qualitative visual scale in ischemic stroke (IS) patients. METHODS: We assembled clinical data and imaging findings from patients of two independent cohorts with recent IS. MRI scans were evaluated using a modified visual scale from Fazekas, Wahlund, and Van Swieten. WMH distributions were analyzed separately in periventricular (PV-WMH) and deep (D-WMH) white matter, basal ganglia (BG-WMH), and brainstem (B-WMH). Presence of confluence of PV-WMH and D-WMH and anterior-versus-posterior WMH predominance were also evaluated. Statistical analysis was performed with SPSS software. RESULTS: We included 618 patients, with a mean age of 72 years (standard deviation [SD] 11 years). The most frequent WMH pattern was D-WMH (73%). In a multivariable analysis, hypertension was associated with PV-WMH (odds ratio [OR] 1.79, 95% confidence interval [CI] 1.29-2.50, p = 0.001) and BG-WMH (OR 2.13, 95% CI 1.19-3.83, p = 0.012). Diabetes mellitus was significantly related to PV-WMH (OR 1.69, 95% CI 1.24-2.30, p = 0.001), D-WMH (OR 1.46, 95% CI 1.07-1.49, p = 0.017), and confluence patterns of D-WMH and PV-WMH (OR 1.62, 95% CI 1.07-2.47, p = 0.024). Hyperlipidemia was found to be independently related to brainstem distribution (OR 1.70, 95% CI 1.08-2.69, p = 0.022). CONCLUSIONS: Different CVRF profiles were significantly related to specific WMH spatial distribution patterns in a large IS cohort. KEY POINTS: • An observational study of WMH in a large IS cohort was assessed by a modified visual evaluation. • Different CVRF profiles were significantly related to specific WMH spatial distribution patterns. • Distinct WMH anatomical patterns could be related to different pathophysiological mechanisms.

Single nucleotide variations in ZBTB46 are associated with post-thrombolytic parenchymal haematoma.

Haemorrhagic transformation is a complication of recombinant tissue-plasminogen activator treatment. The most severe form, parenchymal haematoma, can result in neurological deterioration, disability, and death. Our objective was to identify single nucleotide variations associated with a risk of parenchymal haematoma following thrombolytic therapy in patients with acute ischaemic stroke. A fixed-effect genome-wide meta-analysis was performed combining two-stage genome-wide association studies (n = 1904). The discovery stage (three cohorts) comprised 1324 ischaemic stroke individuals, 5.4% of whom had a parenchymal haematoma. Genetic variants yielding a P-value < 0.05 1 × 10-5 were analysed in the validation stage (six cohorts), formed by 580 ischaemic stroke patients with 12.1% haemorrhagic events. All participants received recombinant tissue-plasminogen activator; cases were parenchymal haematoma type 1 or 2 as defined by the European Cooperative Acute Stroke Study (ECASS) criteria. Genome-wide significant findings (P < 5 × 10-8) were characterized by in silico functional annotation, gene expression, and DNA regulatory elements. We analysed 7 989 272 single nucleotide polymorphisms and identified a genome-wide association locus on chromosome 20 in the discovery cohort; functional annotation indicated that the ZBTB46 gene was driving the association for chromosome 20. The top single nucleotide polymorphism was rs76484331 in the ZBTB46 gene [P = 2.49 × 10-8; odds ratio (OR): 11.21; 95% confidence interval (CI): 4.82-26.55]. In the replication cohort (n = 580), the rs76484331 polymorphism was associated with parenchymal haematoma (P = 0.01), and the overall association after meta-analysis increased (P = 1.61 × 10-8; OR: 5.84; 95% CI: 3.16-10.76). ZBTB46 codes the zinc finger and BTB domain-containing protein 46 that acts as a transcription factor. In silico studies indicated that ZBTB46 is expressed in brain tissue by neurons and endothelial cells. Moreover, rs76484331 interacts with the promoter sites located at 20q13. In conclusion, we identified single nucleotide variants in the ZBTB46 gene associated with a higher risk of parenchymal haematoma following recombinant tissue-plasminogen activator treatment.

Genetics and Epigenetics of Spontaneous Intracerebral Hemorrhage.

Intracerebral hemorrhage (ICH) is a complex and heterogeneous disease, and there is no effective treatment. Spontaneous ICH represents the final manifestation of different types of cerebral small vessel disease, usually categorized as: lobar (mostly related to cerebral amyloid angiopathy) and nonlobar (hypertension-related vasculopathy) ICH. Accurate phenotyping aims to reflect these biological differences in the underlying mechanisms and has been demonstrated to be crucial to the success of genetic studies in this field. This review summarizes how current knowledge on genetics and epigenetics of this devastating stroke subtype are contributing to improve the understanding of ICH pathophysiology and their potential role in developing therapeutic strategies.

Causal Effect of MMP-1 (Matrix Metalloproteinase-1), MMP-8, and MMP-12 Levels on Ischemic Stroke: A Mendelian Randomization Study.

Background and Purpose: MMP (matrix metalloproteinase) levels have been widely associated with ischemic stroke risk and poststroke outcome. However, their role as a risk factor or as a subeffect because of ischemia is uncertain. Methods: We performed a literature search of genome-wide studies that evaluate serum/plasma levels of MMPs. We used a 2-sample Mendelian randomization approach to evaluate the causality of MMP levels on ischemic stroke risk or poststroke outcome, using 2 cohorts: MEGASTROKE (n=440 328) and GODs (n=1791). Results: Genome-wide association studies of MMP-1, MMP-8, and MMP-12 plasma/serum levels were evaluated. A significant association, which was also robust in the sensitivity analysis, was found with all ischemic strokes: MMP-12 (odds ratio=0.90 [95% CI, 0.86­0.94]; q value=7.43×10−5), and with subtypes of stroke, large-artery atherosclerosis: MMP-1 (odds ratio=0.95 [95% CI, 0.92­0.98]; q value=0.01) and MMP-12 (odds ratio=0.71 [95% CI, 0.65­0.77]; q value=5.11×10−14); small-vessel occlusion: MMP-8 (odds ratio=1.24 [95% CI, 1.06­1.45]; q value=0.03). No associations were found in relation to stroke outcome. Conclusions: Our study suggests a causal link between lower serum levels of MMP-12 and the risk of ischemic stroke, lower serum levels of MMP-1 and MMP-12 and the risk of large-artery stroke and higher serum levels of MMP-8 and the risk of lacunar stroke.

Early Neurological Change After Ischemic Stroke Is Associated With 90-Day Outcome.

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 (NIHSSbaseline - NIHSS24hours = ΔNIHSS6-24h), 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 ΔNIHSS6-24h. In a subcohort of tPA (alteplase)-treated patients with large vessel occlusion, the influence of early sustained recanalization and hemorrhagic transformation on ΔNIHSS6-24h was examined. Finally, the association of ΔNIHSS6-24h 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 ΔNIHSS6-24h was 2 (interquartile range, 0-5). In a multivariable model, baseline NIHSS, tPA-treatment, age, glucose, site, and systolic blood pressure independently predicted ΔNIHSS6-24h (R2=0.15). In the large vessel occlusion subcohort, early sustained recanalization and hemorrhagic transformation increased the explained variance (R2=0.27), but much of the variance remained unexplained. ΔNIHSS6-24h had a significant and independent association with 90-day favorable outcome. For the subjects in the 2 NINDS-tPA trials, ΔNIHSS3-24h was similarly associated with 90-day outcomes. CONCLUSIONS: The dynamic phenotype, ΔNIHSS6-24h, captures both explained and unexplained mechanisms involved in AIS and is significantly and independently associated with long-term outcomes. Thus, ΔNIHSS6-24h promises to be an easily obtainable and meaningful quantitative phenotype for large-scale genomic studies of AIS.

Genetically Elevated LDL Associates with Lower Risk of Intracerebral Hemorrhage.

OBJECTIVE: Observational studies point to an inverse correlation between low-density lipoprotein (LDL) cholesterol levels and risk of intracerebral hemorrhage (ICH), but it remains unclear whether this association is causal. We tested the hypothesis that genetically elevated LDL is associated with reduced risk of ICH. METHODS: We constructed one polygenic risk score (PRS) per lipid trait (total cholesterol, LDL, high-density lipoprotein [HDL], and triglycerides) using independent genomewide significant single nucleotide polymorphisms (SNPs) for each trait. We used data from 316,428 individuals enrolled in the UK Biobank to estimate the effect of each PRS on its corresponding trait, and data from 1,286 ICH cases and 1,261 matched controls to estimate the effect of each PRS on ICH risk. We used these estimates to conduct Mendelian Randomization (MR) analyses. RESULTS: We identified 410, 339, 393, and 317 lipid-related SNPs for total cholesterol, LDL, HDL, and triglycerides, respectively. All four PRSs were strongly associated with their corresponding trait (all p < 1.00 × 10-100 ). While one SD increase in the PRSs for total cholesterol (odds ratio [OR] = 0.92; 95% confidence interval [CI] = 0.85-0.99; p = 0.03) and LDL cholesterol (OR = 0.88; 95% CI = 0.81-0.95; p = 0.002) were inversely associated with ICH risk, no significant associations were found for HDL and triglycerides (both p > 0.05). MR analyses indicated that 1mmol/L (38.67mg/dL) increase of genetically instrumented total and LDL cholesterol were associated with 23% (OR = 0.77; 95% CI = 0.65-0.98; p = 0.03) and 41% lower risks of ICH (OR = 0.59; 95% CI = 0.42-0.82; p = 0.002), respectively. INTERPRETATION: Genetically elevated LDL levels were associated with lower risk of ICH, providing support for a potential causal role of LDL cholesterol in ICH. ANN NEUROL 2020 ANN NEUROL 2020;88:56-66.

Defining Minor Intracerebral Hemorrhage.

BACKGROUND AND PURPOSE: The minor stroke concept has not been analyzed in intracerebral hemorrhage (ICH) patients. Our purpose was to determine the optimal cut point on the NIH Stroke Scale (NIHSS) for defining a minor ICH (mICH) in patients with primary ICH. METHODS: An ICH was considered minor if associated with a favorable 3-month outcome (modified Rankin Scale score ≤2). For supratentorial ICH, the discovery cohort consisted of 478 patients prospectively admitted at University Hospital del Mar. Association between NIHSS at admission and 3-month outcome was evaluated with area under the curve-receiver operating characteristics (AUC-ROC) and Youden's index to identify the optimal NIHSS cutoff point to define mICH. External validation was performed in a cohort of 242 supratentorial ICH patients from University Hospital Sant Pau. For infratentorial location, patients from both hospitals (n = 85) were analyzed together. RESULTS: The best -NIHSS cutoff point defining supratentorial-mICH was 6 (AUC-ROC = 0.815 [0.774-0.857] in the discovery cohort and AUC-ROC = 0.819 [0.756-0.882] in the external validation cohort). For infratentorial ICH, the best cutoff point was 4 (AUC-ROC = 0.771 [0.664-0.877]). Using these cutoff points, 40.5% of all primary ICH cases were mICH. Of these, 70.2% were living independently at 3-month follow-up (72% for supratentorial ICH and 56.1% for infratentorial ICH) and 6.5% had died (5.3% for supratentorial ICH, and 14.6% for infratentorial ICH). For patients identified as non-mICH, good 3-month outcome was observed in 11.3% of cases; mortality was 51%. CONCLUSIONS: The definition of mICH using the NIHSS cutoff point of 6 for supratentorial ICH and 4 for infratentorial ICH is useful to identify good outcome in ICH patients.

Genome-wide association study of cerebral small vessel disease reveals established and novel loci.

Intracerebral haemorrhage and small vessel ischaemic stroke (SVS) are the most acute manifestations of cerebral small vessel disease, with no established preventive approaches beyond hypertension management. Combined genome-wide association study (GWAS) of these two correlated diseases may improve statistical power to detect novel genetic factors for cerebral small vessel disease, elucidating underlying disease mechanisms that may form the basis for future treatments. Because intracerebral haemorrhage location is an adequate surrogate for distinct histopathological variants of cerebral small vessel disease (lobar for cerebral amyloid angiopathy and non-lobar for arteriolosclerosis), we performed GWAS of intracerebral haemorrhage by location in 1813 subjects (755 lobar and 1005 non-lobar) and 1711 stroke-free control subjects. Intracerebral haemorrhage GWAS results by location were meta-analysed with GWAS results for SVS from MEGASTROKE, using 'Multi-Trait Analysis of GWAS' (MTAG) to integrate summary data across traits and generate combined effect estimates. After combining intracerebral haemorrhage and SVS datasets, our sample size included 241 024 participants (6255 intracerebral haemorrhage or SVS cases and 233 058 control subjects). Genome-wide significant associations were observed for non-lobar intracerebral haemorrhage enhanced by SVS with rs2758605 [MTAG P-value (P) = 2.6 × 10-8] at 1q22; rs72932727 (P = 1.7 × 10-8) at 2q33; and rs9515201 (P = 5.3 × 10-10) at 13q34. In the GTEx gene expression library, rs2758605 (1q22), rs72932727 (2q33) and rs9515201 (13q34) are significant cis-eQTLs for PMF1 (P = 1 × 10-4 in tibial nerve), NBEAL1, FAM117B and CARF (P < 2.1 × 10-7 in arteries) and COL4A2 and COL4A1 (P < 0.01 in brain putamen), respectively. Leveraging S-PrediXcan for gene-based association testing with the predicted expression models in tissues related with nerve, artery, and non-lobar brain, we found that experiment-wide significant (P < 8.5 × 10-7) associations at three genes at 2q33 including NBEAL1, FAM117B and WDR12 and genome-wide significant associations at two genes including ICA1L at 2q33 and ZCCHC14 at 16q24. Brain cell-type specific expression profiling libraries reveal that SEMA4A, SLC25A44 and PMF1 at 1q22 and COL4A1 and COL4A2 at 13q34 were mainly expressed in endothelial cells, while the genes at 2q33 (FAM117B, CARF and NBEAL1) were expressed in various cell types including astrocytes, oligodendrocytes and neurons. Our cross-phenotype genetic study of intracerebral haemorrhage and SVS demonstrates novel genome-wide associations for non-lobar intracerebral haemorrhage at 2q33 and 13q34. Our replication of the 1q22 locus previous seen in traditional GWAS of intracerebral haemorrhage, as well as the rediscovery of 13q34, which had previously been reported in candidate gene studies with other cerebral small vessel disease-related traits strengthens the credibility of applying this novel genome-wide approach across intracerebral haemorrhage and SVS.

Genome-Wide Association Study of White Blood Cell Counts in Patients With Ischemic Stroke.

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<5×10-8). The 14q24.3 locus was associated with acute stroke outcome (rs112809786, P=0.036) and with ACOT1 and PTGR2 gene expression. Previous polymorphisms associated with leukocyte counts in general-population did not show any significance in our study. 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.

Genetic Imbalance Is Associated With Functional Outcome After Ischemic Stroke.

Background and Purpose- We sought to explore the effect of genetic imbalance on functional outcome after ischemic stroke (IS). Methods- Copy number variation was identified in high-density single-nucleotide polymorphism microarray data of IS patients from the CADISP (Cervical Artery Dissection and Ischemic Stroke Patients) and SiGN (Stroke Genetics Network)/GISCOME (Genetics of Ischaemic Stroke Functional Outcome) networks. Genetic imbalance, defined as total number of protein-coding genes affected by copy number variations in an individual, was compared between patients with favorable (modified Rankin Scale score of 0-2) and unfavorable (modified Rankin Scale score of ≥3) outcome after 3 months. Subgroup analyses were confined to patients with imbalance affecting ohnologs-a class of dose-sensitive genes, or to those with imbalance not affecting ohnologs. The association of imbalance with outcome was analyzed by logistic regression analysis, adjusted for age, sex, stroke subtype, stroke severity, and ancestry. Results- The study sample comprised 816 CADISP patients (age 44.2±10.3 years) and 2498 SiGN/GISCOME patients (age 67.7±14.2 years). Outcome was unfavorable in 122 CADISP and 889 SiGN/GISCOME patients. Multivariate logistic regression analysis revealed that increased genetic imbalance was associated with less favorable outcome in both samples (CADISP: P=0.0007; odds ratio=0.89; 95% CI, 0.82-0.95 and SiGN/GISCOME: P=0.0036; odds ratio=0.94; 95% CI, 0.91-0.98). The association was independent of age, sex, stroke severity on admission, stroke subtype, and ancestry. On subgroup analysis, imbalance affecting ohnologs was associated with outcome (CADISP: odds ratio=0.88; 95% CI, 0.80-0.95 and SiGN/GISCOME: odds ratio=0.93; 95% CI, 0.89-0.98) whereas imbalance without ohnologs lacked such an association. Conclusions- Increased genetic imbalance was associated with poorer functional outcome after IS in both study populations. Subgroup analysis revealed that this association was driven by presence of ohnologs in the respective copy number variations, suggesting a causal role of the deleterious effects of genetic imbalance.

Big Data Approaches to Phenotyping Acute Ischemic Stroke Using Automated Lesion Segmentation of Multi-Center Magnetic Resonance Imaging Data.

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<0.0001). Median (interquartile range) diffusion-weighted MRI lesion volumes from 2770 patients were 3.7 cm3 (0.9-16.6 cm3). Patients with small artery occlusion stroke subtype had smaller lesion volumes ( P<0.0001) and different topography compared with other stroke subtypes. 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.

17p12 Influences Hematoma Volume and Outcome in Spontaneous Intracerebral Hemorrhage.

BACKGROUND AND PURPOSE: Hematoma volume is an important determinant of clinical outcome in spontaneous intracerebral hemorrhage (ICH). We performed a genome-wide association study (GWAS) of hematoma volume with the aim of identifying novel biological pathways involved in the pathophysiology of primary brain injury in ICH. METHODS: We conducted a 2-stage (discovery and replication) case-only genome-wide association study in patients with ICH of European ancestry. We utilized the admission head computed tomography to calculate hematoma volume via semiautomated computer-assisted technique. After quality control and imputation, 7 million genetic variants were available for association testing with ICH volume, which was performed separately in lobar and nonlobar ICH cases using linear regression. Signals with P<5×10-8 were pursued in replication and tested for association with admission Glasgow coma scale and 3-month post-ICH dichotomized (0-2 versus 3-6) modified Rankin Scale using ordinal and logistic regression, respectively. RESULTS: The discovery phase included 394 ICH cases (228 lobar and 166 nonlobar) and identified 2 susceptibility loci: a genomic region on 22q13 encompassing PARVB (top single-nucleotide polymorphism rs9614326: ß, 1.84; SE, 0.32; P=4.4×10-8) for lobar ICH volume and an intergenic region overlying numerous copy number variants on 17p12 (top single-nucleotide polymorphism rs11655160: ß, 0.95; SE, 0.17; P=4.3×10-8) for nonlobar ICH volume. The replication included 240 ICH cases (71 lobar and 169 nonlobar) and corroborated the association for 17p12 (P=0.04; meta-analysis P=2.5×10-9; heterogeneity, P=0.16) but not for 22q13 (P=0.49). In multivariable analysis, rs11655160 was also associated with lower admission Glasgow coma scale (odds ratio, 0.17; P=0.004) and increased risk of poor 3-month modified Rankin Scale (odds ratio, 1.94; P=0.045). CONCLUSIONS: We identified 17p12 as a novel susceptibility risk locus for hematoma volume, clinical severity, and functional outcome in nonlobar ICH. Replication in other ethnicities and follow-up translational studies are needed to elucidate the mechanism mediating the observed association.

Epigenome-wide association study identifies TXNIP gene associated with type 2 diabetes mellitus and sustained hyperglycemia.

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%).