Genetic risk factors for ischaemic stroke and its subtypes (the METASTROKE Collaboration): a meta-analysis of genome-wide association studies

<p>Background - Various genome-wide association studies (GWAS) have been done in ischaemic stroke, identifying a few loci associated with the disease, but sample sizes have been 3500 cases or less. We established the METASTROKE collaboration with the aim of validating associations from previous GWAS and identifying novel genetic associations through meta-analysis of GWAS datasets for ischaemic stroke and its subtypes.</p> <p>Methods - We meta-analysed data from 15 ischaemic stroke cohorts with a total of 12 389 individuals with ischaemic stroke and 62 004 controls, all of European ancestry. For the associations reaching genome-wide significance in METASTROKE, we did a further analysis, conditioning on the lead single nucleotide polymorphism in every associated region. Replication of novel suggestive signals was done in 13 347 cases and 29 083 controls.</p> <p>Findings - We verified previous associations for cardioembolic stroke near PITX2 (p=2·8×10−16) and ZFHX3 (p=2·28×10−8), and for large-vessel stroke at a 9p21 locus (p=3·32×10−5) and HDAC9 (p=2·03×10−12). Additionally, we verified that all associations were subtype specific. Conditional analysis in the three regions for which the associations reached genome-wide significance (PITX2, ZFHX3, and HDAC9) indicated that all the signal in each region could be attributed to one risk haplotype. We also identified 12 potentially novel loci at p<5×10−6. However, we were unable to replicate any of these novel associations in the replication cohort.</p> <p>Interpretation - Our results show that, although genetic variants can be detected in patients with ischaemic stroke when compared with controls, all associations we were able to confirm are specific to a stroke subtype. This finding has two implications. First, to maximise success of genetic studies in ischaemic stroke, detailed stroke subtyping is required. Second, different genetic pathophysiological mechanisms seem to be associated with different stroke subtypes.</p&gt

Serum magnesium and calcium levels in relation to ischemic stroke : Mendelian randomization study

ObjectiveTo determine whether serum magnesium and calcium concentrations are causally associated with ischemic stroke or any of its subtypes using the mendelian randomization approach.MethodsAnalyses 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).ResultsIn 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 7 10-4) for all ischemic stroke, 0.63 (95% CI 0.50-0.80; p = 1.6 7 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.ConclusionsThis 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

Stroke genetics informs drug discovery and risk prediction across ancestries

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

Stroke genetics informs drug discovery and risk prediction across ancestries

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

Stroke genetics informs drug discovery and risk prediction across ancestries

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

Cognitive function in stroke survivors : A 10-year follow-up study

OBJECTIVES: Post-stroke cognitive impairment (PSCI) has considerable impact on patients and society. However, long-term studies on PSCI are scarce and may be influenced by assessment methods and selection bias. We aimed to (i) assess the prevalence of long-term PSCI; (ii) compare two common cognitive assessment instruments; and (iii) compare cognitive function of long-term stroke survivors with non-stroke persons.METHODS: Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) were administered to 10-year survivors from a population-based cohort of first-ever stroke patients included in the Lund Stroke Register, Sweden, in 2001-2002. PSCI was defined as MMSE<27 and/or MoCA<25 and severe cognitive impairment as MMSE<23. Age- and sex-matched non-stroke control subjects who had performed MMSE (but not MoCA) were recruited from the longitudinal population study "Good Ageing in Skåne." The odds of having cognitive impairment for stroke survivors compared to controls were examined with logistic regression analyses adjusting for education.RESULTS: Of 145 stroke survivors after 10 years, 127 participated. MMSE showed PSCI in 46%, whereas MoCA displayed PSCI in 61%. Among the stroke survivors with MoCA<25, 35% had MMSE≥27 (P<.001). The odds of having severe cognitive impairment defined as MMSE<23 were higher among the stroke survivors compared to 354 controls (education-adjusted; OR=2.5; P=.004).CONCLUSIONS: Post-stroke cognitive impairment was prevalent among 10-year stroke survivors, and the odds of having severe cognitive impairment were higher among the stroke survivors compared to non-stroke persons. The burden of long-term PSCI might have been underestimated previously, and MoCA may be more suitable than MMSE to detect long-term PSCI

Secondary prevention and lifestyle indices after stroke in a long-term perspective

OBJECTIVES: To describe the long-term perspective regarding prevalence of risk factors, secondary stroke prevention, and lifestyle indices after stroke.METHODS: From a population-based one-year cohort (n = 416), we performed an observational study of 145 survivors at 16 months and 10 years after stroke (age 27-97 years) regarding secondary prevention including reaching acceptable treatment goals; nutritional status with focus on underweight; and the lifestyle indices: living situation, level of dependence, and self-assessed health condition.RESULTS: Ten years after stroke, 50% of the subjects with hypertension diagnosis and 55% of those without hypertension diagnosis were within the blood pressure goal <140/90 compared with 32% (P = .008) and 37% (N.S.) at 16 months. Acceptable HbA1c levels among subjects with diabetes mellitus diagnosis increased from 35% to 45% (N.S.). Among those without diabetes diagnosis, satisfactory HbA1c levels decreased from 98% to 79% (P < .001). Underweight increased from 9% to 17% (P = .019). Among patients with cerebral infarction, the prevalence of atrial fibrillation increased from 22% to 29% (P = .004), and treatment with oral anticoagulants from 75% to 78% (N.S.). Acceptable LDL cholesterol levels increased from 59% to 80% (P = .033) among subjects on lipid lowering treatment, and from 18% to 40% among untreated (P = .010). At 10 years, 90% still lived in their own home. Health condition was reported as good/very good/excellent by 65%. Age, female sex, and living situation were associated with intensity of secondary prevention measures and underweight.CONCLUSIONS: The proportion of individuals within treatment goals improved over time, but secondary prevention still needed additional consideration 10 years after stroke

Supplementary Material for: Multiplicity of Risk Factors in Ischemic Stroke Patients: Relations to Age, Sex, and Subtype - A Study of 2,505 Patients from the Lund Stroke Register

<b><i>Background:</i></b> The prevalence of risk factors for ischemic stroke may vary between different groups of stroke patients. We examined the distribution of individual well-established risk factors as well as the multiplicity of risk factors in different age groups and among subtypes. <b><i>Methods:</i></b> In the Lund Stroke Register, we consecutively enrolled 2,505 patients with first-ever ischemic stroke from 2001 to 2009 and registered hypertension, diabetes mellitus, heart disease, current smoking, hypercholesterolemia as well as stroke subtype. <b><i>Results:</i></b> Among young patients (<55 years), at least 50% had ≥2 risk factors and 20-25% had ≥3 risk factors. In patients aged 55 years or older, the proportion with ≥2 risk factors was 70-80% and with ≥3 risk factors 35-45%. Men and women had a similar burden of risk factors. Approximately 50% of the cases classified as cardioembolism (CE) and large artery atherosclerosis (LAA) had ≥3 risk factors, which was significantly more than the other TOAST (Trial of Org 10172 in Acute Stroke Treatment) subtypes (CE p < 0.001, LAA p = 0.001). <b><i>Conclusions:</i></b> The prevalence of well-established risk factors is similar among young and old stroke patients with large proportions (50-80%) having ≥2 risk factors. Even though the prevalence of well-established risk factors differs between pathogenetic subtypes, these risk factors as well as the multiplicity of risk factors seem to be of clinical importance in all major subtypes of ischemic stroke

Spontaneous Recovery of Upper Extremity Motor Impairment After Ischemic Stroke : Implications for Stem Cell-Based Therapeutic Approaches

Preclinical studies suggest that stem cell therapy (SCT) may improve sensorimotor recovery after stroke. Upper extremity motor impairment (UEMI) is common after stroke, often entailing substantial disability. To evaluate the feasibility of post-stroke UEMI as a target for SCT, we examined a selected sample of stroke patients potentially suitable for SCT, aiming to assess the frequency and recovery of UEMI, as well as its relation to activity limitations and participation restrictions. Patients aged 20–75 years with first-ever ischemic stroke, and National Institutes of Health Stroke Scale (NIHSS) scores 1–18, underwent brain diffusion-weighted MRI within 4 days of stroke onset (n = 108). Survivors were followed up after 3–5 years, including assessment with NIHSS, Fugl-Meyer assessment of upper extremity (FMA-UE), modified Rankin Scale (mRS), and Stroke Impact Scale (SIS). UEMI was defined as NIHSS arm/hand score ≥1. UEMI recovery was evaluated with change in NIHSS arm/hand scores between baseline and follow-up. Of 97 survivors, 84 were available to follow-up. Among 76 subjects (of 84) without recurrent stroke, 41 had UEMI at baseline of which 10 had residual UEMI at follow-up. The FMA-UE showed moderate-severe impairment in seven of 10 survivors with residual UEMI. UEMI was correlated to mRS (rs = 0.49, p < 0.001) and the SIS social participation domain (rs = −0.38, p = 0.001). Nearly 25% of the subjects with UEMI at baseline had residual impairment after 3–5 years, whereas about 75% showed complete recovery. Most of the subjects with residual UEMI had moderate-severe impairment, which correlated strongly to dependency in daily activities and social participation restrictions. Our findings suggest that SCT targeting post-stroke UEMI may be clinically valuable with significant meaningful benefits for patients but also emphasize the need of early prognostication to detect patients that will have residual impairment in order to optimize patient selection for SCT