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Sökning: WFRF:(Kittner Steven)

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1.
  • Malik, R., et al. (författare)
  • Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes
  • 2018
  • Ingår i: Nature Genetics. - : NATURE PUBLISHING GROUP. - 1061-4036 .- 1546-1718. ; 50:D, Munich, Germany. [Chauhan, Ganesh] Indian Inst Sci, Ctr Brain Res, Bangalore, Karnataka, India. [Chauhan, Ganesh; Sargurupremraj, Muralidharan; Mishra, Aniket; Tzourio, Christophe; Debette, [Traylor, Matthew; Rutten-Jacobs, Loes; Markus, Hugh S.] Univ Cambridge, Div Clin Neurosci, Stroke [Sargurupremraj, Muralidharan; Mishra, Aniket; Debette, Stephanie] Bordeaux Univ Hosp, Inst [Okada, Yukinori; Kanai, Masahiro; Kamatani, Yoichiro] RIKEN Ctr Integrat Med Sci, Lab Stat Anal, [Okada, Yukinori; Kanai, Masahiro; Sakaue, Saori] Osaka Univ, Grad Sch Med, Dept Stat Genet, Osaka, [Okada, Yukinori] Osaka Univ, Immunol Frontier Res Ctr WPI IFReC, Lab Stat Immunol, Suita, Osaka, [Giese, Anne-Katrin; Rost, Natalia S.] Harvard Med Sch, MGH, Dept Neurol, Boston, MA USA. [van der Laan, Sander W.] Univ Utrecht, Univ Med Ctr Utrecht, Div Heart & Lungs, Lab Expt Cardiol,Dept [Gretarsdottir, Solveig; Thorleifsson, Gudmar; Thorsteinsdottir, Unnur; Stefansson, Kari] DeCODE Genet [Anderson, Christopher D.; Rosand, Jonathan] MGH, Ctr Genom Med, Boston, MA USA. [Anderson, Christopher D.; Ay, Hakan; Rost, Natalia S.; Rosand, Jonathan] MGH, J Philip Kistler Stroke [Anderson, Christopher D.; Rosand, Jonathan] Broad Inst, Program Med & Populat Genet, Cambridge, s. 524-
  • Tidskriftsartikel (refereegranskat)abstract
    • Stroke has multiple etiologies, but the underlying genes and pathways are largely unknown. We conducted a multiancestry genome-wide-association meta-analysis in 521,612 individuals (67,162 cases and 454,450 controls) and discovered 22 new stroke risk loci, bringing the total to 32. We further found shared genetic variation with related vascular traits, including blood pressure, cardiac traits, and venous thromboembolism, at individual loci (n = 18), and using genetic risk scores and linkage-disequilibrium-score regression. Several loci exhibited distinct association and pleiotropy patterns for etiological stroke sub-types. Eleven new susceptibility loci indicate mechanisms not previously implicated in stroke pathophysiology, with prioritization of risk variants and genes accomplished through bioinformatics analyses using extensive functional datasets. Stroke risk loci were significantly enriched in drug targets for antithrombotic therapy.
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2.
  • Winkler, Thomas W, et al. (författare)
  • The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study.
  • 2015
  • Ingår i: PLoS Genetics. - : Public Library of Science. - 1553-7404 .- 1553-7390. ; 11:10
  • Tidskriftsartikel (refereegranskat)abstract
    • Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age- and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to ~2.8M SNPs with BMI and WHRadjBMI in four strata (men ≤50y, men >50y, women ≤50y, women >50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR<5%) age-specific effects, of which 11 had larger effects in younger (<50y) than in older adults (≥50y). No sex-dependent effects were identified for BMI. For WHRadjBMI, we identified 44 loci (27 previously established for main effects, 17 novel) with sex-specific effects, of which 28 showed larger effects in women than in men, five showed larger effects in men than in women, and 11 showed opposite effects between sexes. No age-dependent effects were identified for WHRadjBMI. This is the first genome-wide interaction meta-analysis to report convincing evidence of age-dependent genetic effects on BMI. In addition, we confirm the sex-specificity of genetic effects on WHRadjBMI. These results may provide further insights into the biology that underlies weight change with age or the sexually dimorphism of body shape.
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3.
  • Ay, Hakan, et al. (författare)
  • Pathogenic Ischemic Stroke Phenotypes in the NINDS-Stroke Genetics Network
  • 2014
  • Ingår i: Stroke. - : American Heart Association. - 0039-2499. ; 45:12, s. 3589-3596
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND AND PURPOSE: NINDS (National Institute of Neurological Disorders and Stroke)-SiGN (Stroke Genetics Network) is an international consortium of ischemic stroke studies that aims to generate high-quality phenotype data to identify the genetic basis of pathogenic stroke subtypes. This analysis characterizes the etiopathogenetic basis of ischemic stroke and reliability of stroke classification in the consortium. METHODS: Fifty-two trained and certified adjudicators determined both phenotypic (abnormal test findings categorized in major pathogenic groups without weighting toward the most likely cause) and causative ischemic stroke subtypes in 16 954 subjects with imaging-confirmed ischemic stroke from 12 US studies and 11 studies from 8 European countries using the web-based Causative Classification of Stroke System. Classification reliability was assessed with blinded readjudication of 1509 randomly selected cases. RESULTS: The distribution of pathogenic categories varied by study, age, sex, and race (P<0.001 for each). Overall, only 40% to 54% of cases with a given major ischemic stroke pathogenesis (phenotypic subtype) were classified into the same final causative category with high confidence. There was good agreement for both causative (κ 0.72; 95% confidence interval, 0.69-0.75) and phenotypic classifications (κ 0.73; 95% confidence interval, 0.70-0.75). CONCLUSIONS: This study demonstrates that pathogenic subtypes can be determined with good reliability in studies that include investigators with different expertise and background, institutions with different stroke evaluation protocols and geographic location, and patient populations with different epidemiological characteristics. The discordance between phenotypic and causative stroke subtypes highlights the fact that the presence of an abnormality in a patient with stroke does not necessarily mean that it is the cause of stroke.
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4.
  • Giese, A. K., et al. (författare)
  • White matter hyperintensity burden in acute stroke patients differs by ischemic stroke subtype
  • 2020
  • Ingår i: Neurology. - : American Academy of Neurology. - 0028-3878. ; 95:1, s. E79-E88
  • Tidskriftsartikel (refereegranskat)abstract
    • 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 cm(3) (interquartile range 2.18-14.61 cm(3)) 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.
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5.
  • Ilinca, A., et al. (författare)
  • Whole-Exome Sequencing in 22 Young Ischemic Stroke Patients With Familial Clustering of Stroke
  • 2020
  • Ingår i: Stroke. - : American Heart Association. - 0039-2499 .- 1524-4628. ; 51:4, s. 1056-1063
  • Tidskriftsartikel (refereegranskat)abstract
    • Backgrounds and Purpose-Although new methods for genetic analyses are rapidly evolving, there are currently knowledge gaps in how to detect Mendelian forms of stroke. Methods-We performed whole-exome sequencing in 22 probands, under 56 years at their first ischemic stroke episode, from multi-incident stroke families. With the use of a comprehensive stroke-gene panel, we searched for variants in stroke-related genes. The probands' clinical stroke subtype was related to clinical characteristics previously associated with pathogenic variants in these genes. Relatives were genotyped in 7 families to evaluate stroke-gene variants of unknown significance. In 2 larger families with embolic stroke of unknown source, whole-exome sequencing was performed in additional members to examine the possibility of identifying new stroke genes. Results-Six of 22 probands carried pathogenic or possibly pathogenic variants in genes reported to be associated with their stroke subtype. A known pathogenic variant in NOTCH3 and a possibly pathogenic variant in ACAD9 gene were identified. A novel JAK2:c.3188G>A (p.Arg1063His) mutation was seen in a proband with embolic stroke of undetermined source and prothrombotic status. However, penetrance in the family was incomplete. COL4A2:c.3368A>G (p.Glu1123Gly) was detected in 2 probands but did not cosegregate with the disease in their families. Whole-exome sequencing in multiple members of 2 pedigrees with embolic stroke of undetermined source revealed possibly pathogenic variants in genes not previously associated with stroke, GPR142:c.148C>G (p.Leu50Val), and PTPRN2:c.2416A>G (p.Ile806Val); LRRC1 c.808A>G (p.Ile270Val), SLC7A10c.1294dupG (p.Val432fs), IKBKB: c.1070C>T (p.Ala357Val), and OXGR1 c.392G>A (p.Arg131His), respectively. Conclusions-Screening with whole-exome sequencing using a comprehensive stroke-gene panel may identify rare monogenic forms of stroke, but careful evaluation of clinical characteristics and potential pathogenicity of novel variants remain important. In our study, the majority of individuals with familial aggregation of stroke lacked any identified genetic causes.
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8.
  • Schirmer, Markus D., et al. (författare)
  • White matter hyperintensity quantification in large-scale clinical acute ischemic stroke cohorts – The MRI-GENIE study
  • 2019
  • Ingår i: NeuroImage: Clinical. - : Elsevier. - 2213-1582. ; 23
  • Tidskriftsartikel (refereegranskat)abstract
    • 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.
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9.
  • Wu, O., et al. (författare)
  • Big Data Approaches to Phenotyping Acute Ischemic Stroke Using Automated Lesion Segmentation of Multi-Center Magnetic Resonance Imaging Data
  • 2019
  • Ingår i: Stroke. - : American Heart Association. - 0039-2499 .- 1524-4628. ; 50:7, s. 1734-1741
  • Tidskriftsartikel (refereegranskat)abstract
    • 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 (rho=0.92; P<0.0001). Median (interquartile range) diffusion-weighted MRI lesion volumes from 2770 patients were 3.7 cm(3) (0.9-16.6 cm(3)). 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.
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10.
  • Bellenguez, Celine, et al. (författare)
  • Genome-wide association study identifies a variant in HDAC9 associated with large vessel ischemic stroke
  • 2012
  • Ingår i: Nature Genetics. - : Nature Publishing Group. - 1546-1718. ; 44:3, s. 141-328
  • Tidskriftsartikel (refereegranskat)abstract
    • Genetic factors have been implicated in stroke risk, but few replicated associations have been reported. We conducted a genome-wide association study (GWAS) for ischemic stroke and its subtypes in 3,548 affected individuals and 5,972 controls, all of European ancestry. Replication of potential signals was performed in 5,859 affected individuals and 6,281 controls. We replicated previous associations for cardioembolic stroke near PITX2 and ZFHX3 and for large vessel stroke at a 9p21 locus. We identified a new association for large vessel stroke within HDAC9 (encoding histone deacetylase 9) on chromosome 7p21.1 (including further replication in an additional 735 affected individuals and 28,583 controls) (rs11984041; combined P = 1.87 x 10(-11); odds ratio (OR) = 1.42, 95% confidence interval (CI) = 1.28-1.57). All four loci exhibited evidence for heterogeneity of effect across the stroke subtypes, with some and possibly all affecting risk for only one subtype. This suggests distinct genetic architectures for different stroke subtypes.
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