1. |
- Alexander, Stephen P. H., et al.
(author)
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The Concise Guide to PHARMACOLOGY 2023/24: G protein-coupled receptors
- 2023
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In: BRITISH JOURNAL OF PHARMACOLOGY. - : British pharmacological society. - 0007-1188 .- 1476-5381. ; 180
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Journal article (peer-reviewed)abstract
- The Concise Guide to PHARMACOLOGY 2023/24 is the sixth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of approximately 1800 drug targets, and about 6000 interactions with about 3900 ligands. There is an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes almost 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at . G protein-coupled receptors are one of the six major pharmacological targets into which the Guide is divided, with the others being: ion channels, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2023, and supersedes data presented in the 2021/22, 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.
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3. |
- Bonkhoff, Anna K, et al.
(author)
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The relevance of rich club regions for functional outcome post-stroke is enhanced in women.
- 2023
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In: Human brain mapping. - : Wiley. - 1097-0193 .- 1065-9471. ; 44:4, s. 1579-1592
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Journal article (peer-reviewed)abstract
- 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.
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4. |
- Bourached, Anthony, et al.
(author)
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Scaling behaviours of deep learning and linear algorithms for the prediction of stroke severity
- 2023
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In: BRAIN COMMUNICATIONS. - 2632-1297. ; 6:1
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Journal article (peer-reviewed)abstract
- Deep learning has allowed for remarkable progress in many medical scenarios. Deep learning prediction models often require 105-107 examples. It is currently unknown whether deep learning can also enhance predictions of symptoms post-stroke in real-world samples of stroke patients that are often several magnitudes smaller. Such stroke outcome predictions however could be particularly instrumental in guiding acute clinical and rehabilitation care decisions. We here compared the capacities of classically used linear and novel deep learning algorithms in their prediction of stroke severity. Our analyses relied on a total of 1430 patients assembled from the MRI-Genetics Interface Exploration collaboration and a Massachusetts General Hospital-based study. The outcome of interest was National Institutes of Health Stroke Scale-based stroke severity in the acute phase after ischaemic stroke onset, which we predict by means of MRI-derived lesion location. We automatically derived lesion segmentations from diffusion-weighted clinical MRI scans, performed spatial normalization and included a principal component analysis step, retaining 95% of the variance of the original data. We then repeatedly separated a train, validation and test set to investigate the effects of sample size; we subsampled the train set to 100, 300 and 900 and trained the algorithms to predict the stroke severity score for each sample size with regularized linear regression and an eight-layered neural network. We selected hyperparameters on the validation set. We evaluated model performance based on the explained variance (R2) in the test set. While linear regression performed significantly better for a sample size of 100 patients, deep learning started to significantly outperform linear regression when trained on 900 patients. Average prediction performance improved by similar to 20% when increasing the sample size 9x [maximum for 100 patients: 0.279 +/- 0.005 (R2, 95% confidence interval), 900 patients: 0.337 +/- 0.006]. In summary, for sample sizes of 900 patients, deep learning showed a higher prediction performance than typically employed linear methods. These findings suggest the existence of non-linear relationships between lesion location and stroke severity that can be utilized for an improved prediction performance for larger sample sizes. Bourached et al. contrast linear and deep learning-based algorithms in their prediction performances of stroke severity depending on the training set sample sizes. They find that linear regression outperforms deep learning-based algorithms for smaller training samples comprising lesion location information of 100 patients, while deep learning excels in the case of larger samples (N = 900).
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5. |
- Bretzner, Martin, et al.
(author)
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Radiomics-Derived Brain Age Predicts Functional Outcome After Acute Ischemic Stroke.
- 2023
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In: Neurology. - 1526-632X .- 0028-3878. ; 100:8
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Journal article (peer-reviewed)abstract
- While chronological age is one of the most influential determinants of poststroke outcomes, little is known of the impact of neuroimaging-derived biological "brain age." We hypothesized that radiomics analyses of T2-FLAIR images texture would provide brain age estimates and that advanced brain age of patients with stroke will be associated with cardiovascular risk factors and worse functional outcomes.We extracted radiomics from T2-FLAIR images acquired during acute stroke clinical evaluation. Brain age was determined from brain parenchyma radiomics using an ElasticNet linear regression model. Subsequently, relative brain age (RBA), which expresses brain age in comparison with chronological age-matched peers, was estimated. Finally, we built a linear regression model of RBA using clinical cardiovascular characteristics as inputs and a logistic regression model of favorable functional outcomes taking RBA as input.We reviewed 4,163 patients from a large multisite ischemic stroke cohort (mean age = 62.8 years, 42.0% female patients). T2-FLAIR radiomics predicted chronological ages (mean absolute error = 6.9 years, r = 0.81). After adjustment for covariates, RBA was higher and therefore described older-appearing brains in patients with hypertension, diabetes mellitus, a history of smoking, and a history of a prior stroke. In multivariate analyses, age, RBA, NIHSS, and a history of prior stroke were all significantly associated with functional outcome (respective adjusted odds ratios: 0.58, 0.76, 0.48, 0.55; all p-values < 0.001). Moreover, the negative effect of RBA on outcome was especially pronounced in minor strokes.T2-FLAIR radiomics can be used to predict brain age and derive RBA. Older-appearing brains, characterized by a higher RBA, reflect cardiovascular risk factor accumulation and are linked to worse outcomes after stroke.
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6. |
- Christopoulos, Arthur, et al.
(author)
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THE CONCISE GUIDE TO PHARMACOLOGY 2021/22: G protein-coupled receptors.
- 2021
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In: British journal of pharmacology. - : Wiley. - 1476-5381 .- 0007-1188. ; 178 Suppl 1
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Research review (peer-reviewed)abstract
- The Concise Guide to PHARMACOLOGY 2021/22 is the fifth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of nearly 1900 human drug targets with an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes over 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/bph.15538. G protein-coupled receptors are one of the six major pharmacological targets into which the Guide is divided, with the others being: ion channels, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2021, and supersedes data presented in the 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.
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7. |
- Fazey, Ioan, et al.
(author)
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Transforming knowledge systems for life on Earth : Visions of future systems and how to get there
- 2020
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In: Energy Research & Social Science. - : Elsevier. - 2214-6296 .- 2214-6326. ; 70
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Journal article (peer-reviewed)abstract
- Formalised knowledge systems, including universities and research institutes, are important for contemporary societies. They are, however, also arguably failing humanity when their impact is measured against the level of progress being made in stimulating the societal changes needed to address challenges like climate change. In this research we used a novel futures-oriented and participatory approach that asked what future envisioned knowledge systems might need to look like and how we might get there. Findings suggest that envisioned future systems will need to be much more collaborative, open, diverse, egalitarian, and able to work with values and systemic issues. They will also need to go beyond producing knowledge about our world to generating wisdom about how to act within it. To get to envisioned systems we will need to rapidly scale methodological innovations, connect innovators, and creatively accelerate learning about working with intractable challenges. We will also need to create new funding schemes, a global knowledge commons, and challenge deeply held assumptions. To genuinely be a creative force in supporting longevity of human and non-human life on our planet, the shift in knowledge systems will probably need to be at the scale of the enlightenment and speed of the scientific and technological revolution accompanying the second World War. This will require bold and strategic action from governments, scientists, civic society and sustained transformational intent.
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8. |
- Gill, Dipender, et al.
(author)
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Genetically Determined Risk of Depression and Functional Outcome After Ischemic Stroke
- 2019
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In: Stroke. - 1524-4628. ; 50:8, s. 2219-2222
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Journal article (peer-reviewed)abstract
- Background and Purpose- Psychosocial factors can have implications for ischemic stroke risk and recovery. This study investigated the effect of genetically determined risk of depression on these outcomes using the Mendelian randomization (MR) framework. Methods- Genetic instruments for risk of depression were identified in a discovery genome-wide association study of 246 363 cases and 561 190 controls and further replicated in a separate population of 474 574 cases and 1 032 579 controls. Corresponding genetic association estimates for risk of ischemic stroke were taken from 60 341 cases and 454 450 controls, with those for functional outcome 3 months after ischemic stroke taken from an analysis of 6021 patients. Following statistical power calculation, inverse-variance weighted MR was performed to pool estimates across different instruments. The Cochran Q heterogeneity test, weighted median MR, and MR pleiotropy residual sum and outlier were used to explore possible bias relating to inclusion of pleiotropic variants. Results- There was no MR evidence for an effect of genetically determined risk of depression on ischemic stroke risk. Although suffering low statistical power, the main inverse-variance weighted MR analysis was suggestive of a detrimental effect of genetically determined risk of depression on functional outcome after ischemic stroke (odds ratio of poor outcome [modified Rankin Scale, ≥3] per 1-SD increase in genetically determined risk of depression, 1.81; 95% CI, 0.98-3.35; P=0.06). There was no evidence of heterogeneity between MR estimates produced by different instruments (Q P=0.26). Comparable MR estimates were obtained with weighted median MR (odds ratio, 2.57; 95% CI, 1.05-6.25; P=0.04) and MR pleiotropy residual sum and outlier (odds ratio, 1.81; 95% CI, 0.95-3.46; P=0.08). Conclusions- We found no MR evidence of genetically determined risk of depression affecting ischemic stroke risk but did find consistent MR evidence suggestive of a possible effect on functional outcome after ischemic stroke. Given the widespread prevalence of depression-related morbidity, these findings could have implications for prognostication and personalized rehabilitation after stroke.
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9. |
- Johansson, Malin, et al.
(author)
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Genetic Predisposition to Mosaic Chromosomal Loss Is Associated with Functional Outcome after Ischemic Stroke
- 2021
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In: Neurology: Genetics. - 2376-7839. ; 7:6
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Journal article (peer-reviewed)abstract
- Background and ObjectivesTo test the hypothesis that a predisposition to acquired genetic alterations is associated with ischemic stroke outcome by investigating the association between a polygenic risk score (PRS) for mosaic loss of chromosome Y (mLOY) and outcome in a large international data set.MethodsWe used data from the genome-wide association study performed within the Genetics of Ischemic Stroke Functional Outcome network, which included 6,165 patients (3,497 men and 2,668 women) with acute ischemic stroke of mainly European ancestry. We assessed a weighted PRS for mLOY and examined possible associations with the modified Rankin Scale (mRS) score 3 months poststroke in logistic regression models. We investigated the whole study sample as well as men and women separately.ResultsIncreasing PRS for mLOY was associated with poor functional outcome (mRS score >2) with an odds ratio (OR) of 1.11 (95% confidence interval [CI] 1.03-1.19) per 1 SD increase in the PRS after adjustment for age, sex, ancestry, stroke severity (NIH Stroke Scale), smoking, and diabetes mellitus. In sex-stratified analyses, we found a statistically significant association in women (adjusted OR 1.20, 95% CI 1.08-1.33). In men, the association was in the same direction (adjusted OR 1.04, 95% CI 0.95-1.14), and we observed no significant genotype-sex interaction.DiscussionIn this exploratory study, we found associations between genetic variants predisposing to mLOY and stroke outcome. The significant association in women suggests underlying mechanisms related to genomic instability that operate in both sexes. These findings need replication and mechanistic exploration.
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10. |
- Lagging, Cecilia, et al.
(author)
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APOE ε4 is associated with younger age at ischemic stroke onset but not with stroke outcome
- 2019
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In: Neurology. - 1526-632X. ; 93:19, s. 849-853
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Journal article (peer-reviewed)abstract
- Stroke outcome is determined by a complex interplay, where age and stroke severity are predominant predictors. Studies on hemorrhagic stroke indicate that APOE genotype is a predictor of poststroke outcomes,1,2 but results from studies on ischemic stroke are more conflicting.1,3 There is 1 study suggesting an influence of APOE genotype on age at ischemic stroke onset,4 and sex-specific effects on outcome have been reported.5 Taken together, there is a need for larger studies on APOE and ischemic stroke outcomes with integrated information on age, severity, and sex.The 3 common APOE alleles ε2, ε3, and ε4 can be separated by a combination of 2 single nucleotide polymorphisms (SNPs), rs429358 and rs7412. Thus, associations with APOE alleles are not directly captured in a regular genome-wide association study (GWAS), where each SNP is investigated separately. We derived the 3 common APOE alleles and investigated the interplay between APOE, age at ischemic stroke onset, severity, sex, and outcome within a large international collaboration, the Genetics of Ischaemic Stroke Functional Outcome (GISCOME) network.
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11. |
- Lemmens, Robin, et al.
(author)
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The association of the 4q25 susceptibility variant for atrial fibrillation with stroke is limited to stroke of cardioembolic etiology.
- 2010
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In: Stroke; a journal of cerebral circulation. - 1524-4628. ; 41:9, s. 1850-7
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Journal article (peer-reviewed)abstract
- BACKGROUND AND PURPOSE: Genome-wide association studies recently identified 2 variants on chromosome 4q25 as susceptibility factors for atrial fibrillation. Interestingly, these variants were subsequently also shown to be associated with stroke. However, it remains unclear whether 4q25 associates with all the stroke subtypes or with cardioembolic stroke in particular, which is often attributable to atrial fibrillation. METHODS: We performed a large case-control association study in 4199 ischemic stroke patients, all subtyped according to Trial of Org 10172 in Acute Stroke Treatment criteria, and 3750 controls derived from 6 studies conducted in Australia, Austria, Belgium, Poland, Spain, and Sweden. Two variants on chromosome 4q25, rs1906591 and rs10033464, were genotyped. RESULTS: Within cases, the A-allele of rs1906591 was associated with atrial fibrillation (odds ratio, 1.64 [95% CI, 1.43 to 1.90]; P=9.2 . 10(-12)), whereas rs10033464 was only marginally associated. There was an association between overall ischemic stroke and rs1906591 (odds ratio, 1.20 [95% CI, 1.09 to 1.32]; P=1.2 . 10(-4)). However, this was probably caused by the large effect of stroke of cardioembolic etiology because no relation was obtained in any other subgroup of stroke. The rs10033464 variant failed to show any relationship with ischemic stroke. CONCLUSIONS: We replicated the association of the rs1906591 variant on chromosome 4q25 with atrial fibrillation and ischemic stroke of cardioembolic etiology. The 4q25 locus failed to associate with noncardiac subtypes of ischemic stroke.
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12. |
- Lindgren, Arne, et al.
(author)
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Stroke Recovery Genetics
- 2016
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In: Stroke: a journal of cerebral circulation. - 0039-2499. ; 47:9, s. 2427-2434
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Journal article (peer-reviewed)
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13. |
- Maguire, Jane M., et al.
(author)
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GISCOME – Genetics of Ischaemic Stroke Functional Outcome network : A protocol for an international multicentre genetic association study
- 2017
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In: European Stroke Journal. - : SAGE Publications. - 2396-9873 .- 2396-9881. ; 2:3, s. 229-237
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Journal article (peer-reviewed)abstract
- Introduction: Genome-wide association studies have identified several novel genetic loci associated with stroke risk, but how genetic factors influence stroke outcome is less studied. The Genetics of Ischaemic Stroke Functional outcome network aims at performing genetic studies of stroke outcome. We here describe the study protocol and methods basis of Genetics of Ischaemic Stroke Functional outcome. Methods: The Genetics of Ischaemic Stroke Functional outcome network has assembled patients from 12 ischaemic stroke projects with genome-wide genotypic and outcome data from the International Stroke Genetics Consortium and the National Institute of Neurological Diseases Stroke Genetics Network initiatives. We have assessed the availability of baseline variables, outcome metrics and time-points for collection of outcome data. Results: We have collected 8831 ischaemic stroke cases with genotypic and outcome data. Modified Rankin score was the outcome metric most readily available. We detected heterogeneity between cohorts for age and initial stroke severity (according to the NIH Stroke Scale), and will take this into account in analyses. We intend to conduct a first phase genome-wide association outcome study on ischaemic stroke cases with data on initial stroke severity and modified Rankin score within 60–190 days. To date, we have assembled 5762 such cases and are currently seeking additional cases meeting these criteria for second phase analyses. Conclusion: Genetics of Ischaemic Stroke Functional outcome is a unique collection of ischaemic stroke cases with detailed genetic and outcome data providing an opportunity for discovery of genetic loci influencing functional outcome. Genetics of Ischaemic Stroke Functional outcome will serve as an exploratory study where the results as well as the methodological observations will provide a basis for future studies on functional outcome. Genetics of Ischaemic Stroke Functional outcome can also be used for candidate gene replication or assessing stroke outcome non-genetic association hypotheses.
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15. |
- Pfeiffer, Dorothea, et al.
(author)
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Genetic Imbalance Is Associated With Functional Outcome After Ischemic Stroke
- 2019
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In: Stroke. - 1524-4628. ; 50:2, s. 298-304
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Journal article (peer-reviewed)abstract
- 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.
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16. |
- Söderholm, Martin, et al.
(author)
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Genome-wide association meta-analysis of functional outcome after ischemic stroke
- 2019
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In: Neurology. - 1526-632X. ; 92:12, s. 1271-1283
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Journal article (peer-reviewed)abstract
- OBJECTIVE: To discover common genetic variants associated with poststroke outcomes using a genome-wide association (GWA) study. METHODS: The study comprised 6,165 patients with ischemic stroke from 12 studies in Europe, the United States, and Australia included in the GISCOME (Genetics of Ischaemic Stroke Functional Outcome) network. The primary outcome was modified Rankin Scale score after 60 to 190 days, evaluated as 2 dichotomous variables (0-2 vs 3-6 and 0-1 vs 2-6) and subsequently as an ordinal variable. GWA analyses were performed in each study independently and results were meta-analyzed. Analyses were adjusted for age, sex, stroke severity (baseline NIH Stroke Scale score), and ancestry. The significance level was p < 5 × 10-8. RESULTS: We identified one genetic variant associated with functional outcome with genome-wide significance (modified Rankin Scale scores 0-2 vs 3-6, p = 5.3 × 10-9). This intronic variant (rs1842681) in the LOC105372028 gene is a previously reported trans-expression quantitative trait locus for PPP1R21, which encodes a regulatory subunit of protein phosphatase 1. This ubiquitous phosphatase is implicated in brain functions such as brain plasticity. Several variants detected in this study demonstrated suggestive association with outcome (p < 10-5), some of which are within or near genes with experimental evidence of influence on ischemic stroke volume and/or brain recovery (e.g., NTN4, TEK, and PTCH1). CONCLUSIONS: In this large GWA study on functional outcome after ischemic stroke, we report one significant variant and several variants with suggestive association to outcome 3 months after stroke onset with plausible mechanistic links to poststroke recovery. Future replication studies and exploration of potential functional mechanisms for identified genetic variants are warranted.
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17. |
- Traylor, Matthew, et al.
(author)
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A Novel MMP12 Locus Is Associated with Large Artery Atherosclerotic Stroke Using a Genome-Wide Age-at-Onset Informed Approach.
- 2014
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In: PLoS Genetics. - : Public Library of Science (PLoS). - 1553-7404. ; 10:7
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Journal article (peer-reviewed)abstract
- Genome-wide association studies (GWAS) have begun to identify the common genetic component to ischaemic stroke (IS). However, IS has considerable phenotypic heterogeneity. Where clinical covariates explain a large fraction of disease risk, covariate informed designs can increase power to detect associations. As prevalence rates in IS are markedly affected by age, and younger onset cases may have higher genetic predisposition, we investigated whether an age-at-onset informed approach could detect novel associations with IS and its subtypes; cardioembolic (CE), large artery atherosclerosis (LAA) and small vessel disease (SVD) in 6,778 cases of European ancestry and 12,095 ancestry-matched controls. Regression analysis to identify SNP associations was performed on posterior liabilities after conditioning on age-at-onset and affection status. We sought further evidence of an association with LAA in 1,881 cases and 50,817 controls, and examined mRNA expression levels of the nearby genes in atherosclerotic carotid artery plaques. Secondly, we performed permutation analyses to evaluate the extent to which age-at-onset informed analysis improves significance for novel loci. We identified a novel association with an MMP12 locus in LAA (rs660599; p = 2.5×10-7), with independent replication in a second population (p = 0.0048, OR(95% CI) = 1.18(1.05-1.32); meta-analysis p = 2.6×10-8). The nearby gene, MMP12, was significantly overexpressed in carotid plaques compared to atherosclerosis-free control arteries (p = 1.2×10-15; fold change = 335.6). Permutation analyses demonstrated improved significance for associations when accounting for age-at-onset in all four stroke phenotypes (p<0.001). Our results show that a covariate-informed design, by adjusting for age-at-onset of stroke, can detect variants not identified by conventional GWAS.
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19. |
- Wu, Ona, et al.
(author)
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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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In: Stroke. - 1524-4628. ; 50:7, s. 1734-1741
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Journal article (peer-reviewed)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 (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.
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