| 111. |
- Frid, P., et al.
(författare)
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Migraine-associated common genetic variants confer greater risk of posterior vs. anterior circulation ischemic stroke☆
- 2022
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Ingår i: Journal of Stroke and Cerebrovascular Diseases. - : Elsevier BV. - 1052-3057. ; 31:8
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To examine potential genetic relationships between migraine and the two distinct phenotypes posterior circulation ischemic stroke (PCiS) and anterior circulation ischemic stroke (ACiS), we generated migraine polygenic risk scores (PRSs) and compared these between PCiS and ACiS, and separately vs. non-stroke control subjects. Methods: Acute ischemic stroke cases were classified as PCiS or ACiS based on lesion location on diffusion-weighted MRI. Exclusion criteria were lesions in both vascular territories or uncertain territory; supratentorial PCiS with ipsilateral fetal posterior cerebral artery; and cases with atrial fibrillation. We generated migraine PRS for three migraine phenotypes (any migraine; migraine without aura; migraine with aura) using publicly available GWAS data and compared mean PRSs separately for PCiS and ACiS vs. non-stroke control subjects, and between each stroke phenotype. Results: Our primary analyses included 464 PCiS and 1079 ACiS patients with genetic European ancestry. Compared to non-stroke control subjects (n=15396), PRSs of any migraine were associated with increased risk of PCiS (p=0.01–0.03) and decreased risk of ACiS (p=0.010–0.039). Migraine without aura PRSs were significantly associated with PCiS (p=0.008–0.028), but not with ACiS. When comparing PCiS vs. ACiS directly, migraine PRSs were higher in PCiS vs. ACiS for any migraine (p=0.001–0.010) and migraine without aura (p=0.032–0.048). Migraine with aura PRS did not show a differential association in our analyses. Conclusions: Our results suggest a stronger genetic overlap between unspecified migraine and migraine without aura with PCiS compared to ACiS. Possible shared mechanisms include dysregulation of cerebral vessel endothelial function.
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| 112. |
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| 113. |
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| 114. |
- Feugnet, G., et al.
(författare)
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Improved laser-induced fluorescence method for bio-attack early warning detection system
- 2008
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Ingår i: Proceedings of SPIE - The International Society for Optical Engineering. - : SPIE.
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Konferensbidrag (refereegranskat)abstract
- Laser Induced Fluorescence (LIF) could permit fast early warning systems either for point or standoff detection if a reliable classification of warfare biological agents versus biological or non-biological fluorescing background can be achieved. In order to improve LIF discrimination capability, a new system is described in which the fluorescence pattern is enriched by the use of multiple wavelength delayed excitation while usual spectral fluorescence analysis is extended to time domain to use both aspects as criteria for classification. General considerations and guidelines for the system design are given as well as results showing good discrimination between background and simulants.
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| 115. |
- Wu, O., et al.
(författare)
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Big Data Approaches to Phenotyping Acute Ischemic Stroke Using Automated Lesion Segmentation of Multi-Center Magnetic Resonance Imaging Data
- 2019
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Ingår i: Stroke. - : Ovid Technologies (Wolters Kluwer Health). - 0039-2499 .- 1524-4628. ; 50:7, s. 1734-1741
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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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| 116. |
- Bailey-Wilson, Joan E, et al.
(författare)
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Analysis of Xq27-28 linkage in the international consortium for prostate cancer genetics (ICPCG) families
- 2012
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Ingår i: BMC Medical Genetics. - London : BioMed Central. - 1471-2350. ; 13, s. 46-
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Tidskriftsartikel (refereegranskat)abstract
- Background: Genetic variants are likely to contribute to a portion of prostate cancer risk. Full elucidation of the genetic etiology of prostate cancer is difficult because of incomplete penetrance and genetic and phenotypic heterogeneity. Current evidence suggests that genetic linkage to prostate cancer has been found on several chromosomes including the X; however, identification of causative genes has been elusive.Methods: Parametric and non-parametric linkage analyses were performed using 26 microsatellite markers in each of 11 groups of multiple-case prostate cancer families from the International Consortium for Prostate Cancer Genetics (ICPCG). Meta-analyses of the resultant family-specific linkage statistics across the entire 1,323 families and in several predefined subsets were then performed.Results: Meta-analyses of linkage statistics resulted in a maximum parametric heterogeneity lod score (HLOD) of 1.28, and an allele-sharing lod score (LOD) of 2.0 in favor of linkage to Xq27-q28 at 138 cM. In subset analyses, families with average age at onset less than 65 years exhibited a maximum HLOD of 1.8 (at 138 cM) versus a maximum regional HLOD of only 0.32 in families with average age at onset of 65 years or older. Surprisingly, the subset of families with only 2-3 affected men and some evidence of male-to-male transmission of prostate cancer gave the strongest evidence of linkage to the region (HLOD = 3.24, 134 cM). For this subset, the HLOD was slightly increased (HLOD = 3.47 at 134 cM) when families used in the original published report of linkage to Xq27-28 were excluded.Conclusions: Although there was not strong support for linkage to the Xq27-28 region in the complete set of families, the subset of families with earlier age at onset exhibited more evidence of linkage than families with later onset of disease. A subset of families with 2-3 affected individuals and with some evidence of male to male disease transmission showed stronger linkage signals. Our results suggest that the genetic basis for prostate cancer in our families is much more complex than a single susceptibility locus on the X chromosome, and that future explorations of the Xq27-28 region should focus on the subset of families identified here with the strongest evidence of linkage to this region.
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| 117. |
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| 118. |
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| 119. |
- Frid, Petrea, et al.
(författare)
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Detailed phenotyping of posterior vs. anterior circulation ischemic stroke: a multi-center MRI study
- 2020
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Ingår i: Journal of Neurology. - : Springer Science and Business Media LLC. - 0340-5354 .- 1432-1459. ; 267
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Tidskriftsartikel (refereegranskat)abstract
- 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 < 0.05; male sex 68% vs. 58%, p < 0.001). Both were independently associated with PCiS (diabetes, OR = 1.29; 95% CI 1.04-1.61; male sex, OR = 1.46; 95% CI 1.21-1.78). ACiS more commonly had large artery atherosclerosis (25% vs. 20%, p < 0.01) and cardioembolic mechanisms (17% vs. 11%, p < 0.001) compared to PCiS. Small artery occlusion was more common in PCiS vs. ACiS (20% vs. 14%, p < 0.001). Small artery occlusion accounted for 47% of solitary brainstem infarctions. 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.
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| 120. |
- Giese, A. K., et al.
(författare)
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Design and rationale for examining neuroimaging genetics in ischemic stroke The MRI-GENIE study
- 2017
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Ingår i: Neurology-Genetics. - : Ovid Technologies (Wolters Kluwer Health). - 2376-7839. ; 3:5
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To describe the design and rationale for the genetic analysis of acute and chronic cerebrovascular neuroimaging phenotypes detected on clinical MRI in patients with acute ischemic stroke (AIS) within the scope of the MRI-GENetics Interface Exploration (MRI-GENIE) study.& para;& para;Methods: MRI-GENIE capitalizes on the existing infrastructure of the Stroke Genetics Network (SiGN). In total, 12 international SiGN sites contributed MRIs of 3,301 patients with AIS. Detailed clinical phenotyping with the web-based Causative Classification of Stroke (CCS) system and genome-wide genotyping data were available for all participants. Neuroimaging analyses include the manual and automated assessments of established MRI markers. A high-throughput MRI analysis pipeline for the automated assessment of cerebrovascular lesions on clinical scans will be developed in a subset of scans for both acute and chronic lesions, validated against gold standard, and applied to all available scans. The extracted neuroimaging phenotypes will improve characterization of acute and chronic cerebrovascular lesions in ischemic stroke, including CCS subtypes, and their effect on functional outcomes after stroke. Moreover, genetic testing will uncover variants associated with acute and chronic MRI manifestations of cerebrovascular disease.& para;& para;Conclusions: The MRI-GENIE study aims to develop, validate, and distribute the MRI analysis platform for scans acquired as part of clinical care for patients with AIS, which will lead to (1) novel genetic discoveries in ischemic stroke, (2) strategies for personalized stroke risk assessment, and (3) personalized stroke outcome assessment.
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