White Matter Lesions Are Not Related to β-Amyloid Deposition in an Autopsy-Based Study

Population-based studies have investigated the relation between β-amyloid levels in cerebrospinal fluid or plasma and white matter lesions (WMLs). However, these circulating levels of β-amyloid in cerebrospinal fluid or plasma may not reliably reflect the actual degree of amyloid present in the brain. Therefore, we investigated the relation between WMLs and β-amyloid plaques and amyloid angiopathy in brain tissue. WML on MRI or CT were rated in 28 nondemented patients whose neuroimaging was available prior to death. β-amyloid in plaques and arterioles were immunohistochemically stained and quantified in postmortem brain necropsies. WMLs were present in 43% of the total population. Both cortex and periventricular region showed no differences for β-amyloid deposition in either plaques or blood vessel walls in patients with WMLs compared to those without WMLs. Thus, our results indicate that there is no relation between the degree of WMLs and β-amyloid deposition in the brain

Subtype Specificity of Genetic Loci Associated With Stroke in 16 664 Cases and 32 792 Controls

Background: Genome-wide association studies have identified multiple loci associated with stroke. However, the specific stroke subtypes affected, and whether loci influence both ischemic and hemorrhagic stroke, remains unknown. For loci associated with stroke, we aimed to infer the combination of stroke subtypes likely to be affected, and in doing so assess the extent to which such loci have homogeneous effects across stroke subtypes. Methods: We performed Bayesian multinomial regression in 16 664 stroke cases and 32 792 controls of European ancestry to determine the most likely combination of stroke subtypes affected for loci with published genome-wide stroke associations, using model selection. Cases were subtyped under 2 commonly used stroke classification systems, TOAST (Trial of Org 10172 Acute Stroke Treatment) and causative classification of stroke. All individuals had genotypes imputed to the Haplotype Reference Consortium 1.1 Panel. Results: Sixteen loci were considered for analysis. Seven loci influenced both hemorrhagic and ischemic stroke, 3 of which influenced ischemic and hemorrhagic subtypes under both TOAST and causative classification of stroke. Under causative classification of stroke, 4 loci influenced both small vessel stroke and intracerebral hemorrhage. An EDNRA locus demonstrated opposing effects on ischemic and hemorrhagic stroke. No loci were predicted to influence all stroke subtypes in the same direction, and only one locus (12q24) was predicted to influence all ischemic stroke subtypes. Conclusions: Heterogeneity in the influence of stroke-associated loci on stroke subtypes is pervasive, reflecting differing causal pathways. However, overlap exists between hemorrhagic and ischemic stroke, which may reflect shared pathobiology predisposing to small vessel arteriopathy. Stroke is a complex, heterogeneous disorder requiring tailored analytic strategies to decipher genetic mechanisms

Risk factors and prognosis of young stroke. The FUTURE study: A prospective cohort study. Study rationale and protocol

Contains fulltext : 98322.pdf (postprint version ) (Open Access)BACKGROUND: Young stroke can have devastating consequences with respect to quality of life, the ability to work, plan or run a family, and participate in social life. Better insight into risk factors and the long-term prognosis is extremely important, especially in young stroke patients with a life expectancy of decades. To date, detailed information on risk factors and the long-term prognosis in young stroke patients, and more specific risk of mortality or recurrent vascular events, remains scarce. METHODS/DESIGN: The FUTURE study is a prospective cohort study on risk factors and prognosis of young ischemic and hemorrhagic stroke among 1006 patients, aged 18-50 years, included in our study database between 1-1-1980 and 1-11-2010. Follow-up visits at our research centre take place from the end of 2009 until the end of 2011. Control subjects will be recruited among the patients' spouses, relatives or social environment. Information on mortality and incident vascular events will be retrieved via structured questionnaires. In addition, participants are invited to the research centre to undergo an extensive sub study including MRI. DISCUSSION: The FUTURE study has the potential to make an important contribution to increase the knowledge on risk factors and long-term prognosis in young stroke patients. Our study differs from previous studies by having a maximal follow-up of more than 30 years, including not only TIA and ischemic stroke but also hemorrhagic stroke, the addition of healthy controls and prospectively collect data during an extensive follow-up visit. Completion of the FUTURE study may provide better information for treating physicians and patients with respect to the prognosis of young stroke.8 p

Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting.

OBJECTIVE: To explore genetic and lifestyle risk factors of MRI-defined brain infarcts (BI) in large population-based cohorts. METHODS: We performed meta-analyses of genome-wide association studies (GWAS) and examined associations of vascular risk factors and their genetic risk scores (GRS) with MRI-defined BI and a subset of BI, namely, small subcortical BI (SSBI), in 18 population-based cohorts (n = 20,949) from 5 ethnicities (3,726 with BI, 2,021 with SSBI). Top loci were followed up in 7 population-based cohorts (n = 6,862; 1,483 with BI, 630 with SBBI), and we tested associations with related phenotypes including ischemic stroke and pathologically defined BI. RESULTS: The mean prevalence was 17.7% for BI and 10.5% for SSBI, steeply rising after age 65. Two loci showed genome-wide significant association with BI: FBN2, p = 1.77 × 10-8; and LINC00539/ZDHHC20, p = 5.82 × 10-9. Both have been associated with blood pressure (BP)-related phenotypes, but did not replicate in the smaller follow-up sample or show associations with related phenotypes. Age- and sex-adjusted associations with BI and SSBI were observed for BP traits (p value for BI, p [BI] = 9.38 × 10-25; p [SSBI] = 5.23 × 10-14 for hypertension), smoking (p [BI] = 4.4 × 10-10; p [SSBI] = 1.2 × 10-4), diabetes (p [BI] = 1.7 × 10-8; p [SSBI] = 2.8 × 10-3), previous cardiovascular disease (p [BI] = 1.0 × 10-18; p [SSBI] = 2.3 × 10-7), stroke (p [BI] = 3.9 × 10-69; p [SSBI] = 3.2 × 10-24), and MRI-defined white matter hyperintensity burden (p [BI] = 1.43 × 10-157; p [SSBI] = 3.16 × 10-106), but not with body mass index or cholesterol. GRS of BP traits were associated with BI and SSBI (p ≤ 0.0022), without indication of directional pleiotropy. CONCLUSION: In this multiethnic GWAS meta-analysis, including over 20,000 population-based participants, we identified genetic risk loci for BI requiring validation once additional large datasets become available. High BP, including genetically determined, was the most significant modifiable, causal risk factor for BI

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

FLAIR Brain MRIs scans from two of the patients with notch 3 mutations.

<p>The upper panel 1 shows images from patient 1 (R169C), and the lower panel two shows images from patient 2 panel 2 (C1222G). These show leukoaraiosis in both cases (images C and D) but minimal anterior pole involvement in patient 1 (image upper panel A) and no involvement in patient 2 (image lower panel A). Patient 1 also shows confluent external capsule involvement (image B), but this is absent from patient 4 (lower panel B).</p

Brain MRI (T2-Weighted) of the patient carrying the <i>GLA</i> mutation R118C.

<p>Two lacunes are present in the right caudate nucleus and external capsule (C). An area of white matter hyperintensity is present in the peripheral right posterior frontal white matter (D). There were no abnormalities in the posterior circulation.</p

Characteristics of patients with a <i>NOTCH3</i> mutation.

<p>Abbreviations: WMH, white matter hyperintensities; NA, not available.</p><p>Characteristics of patients with a <i>NOTCH3</i> mutation.</p

Patient characteristics.

<p>Abbreviations: SD: standard deviation; IQR: interquartile range.</p><p>^a Gradient echo imaging was available in 339 (34%) patients.</p><p>Patient characteristics.</p