| 1. |
- Chung, Jaeyoon, et al.
(författare)
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Genome-wide association study of cerebral small vessel disease reveals established and novel loci
- 2019
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Ingår i: Brain : a journal of neurology. - : Oxford University Press (OUP). - 1460-2156. ; 142:10, s. 3176-3189
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Tidskriftsartikel (refereegranskat)abstract
- Intracerebral haemorrhage and small vessel ischaemic stroke (SVS) are the most acute manifestations of cerebral small vessel disease, with no established preventive approaches beyond hypertension management. Combined genome-wide association study (GWAS) of these two correlated diseases may improve statistical power to detect novel genetic factors for cerebral small vessel disease, elucidating underlying disease mechanisms that may form the basis for future treatments. Because intracerebral haemorrhage location is an adequate surrogate for distinct histopathological variants of cerebral small vessel disease (lobar for cerebral amyloid angiopathy and non-lobar for arteriolosclerosis), we performed GWAS of intracerebral haemorrhage by location in 1813 subjects (755 lobar and 1005 non-lobar) and 1711 stroke-free control subjects. Intracerebral haemorrhage GWAS results by location were meta-analysed with GWAS results for SVS from MEGASTROKE, using 'Multi-Trait Analysis of GWAS' (MTAG) to integrate summary data across traits and generate combined effect estimates. After combining intracerebral haemorrhage and SVS datasets, our sample size included 241 024 participants (6255 intracerebral haemorrhage or SVS cases and 233 058 control subjects). Genome-wide significant associations were observed for non-lobar intracerebral haemorrhage enhanced by SVS with rs2758605 [MTAG P-value (P) = 2.6 × 10-8] at 1q22; rs72932727 (P = 1.7 × 10-8) at 2q33; and rs9515201 (P = 5.3 × 10-10) at 13q34. In the GTEx gene expression library, rs2758605 (1q22), rs72932727 (2q33) and rs9515201 (13q34) are significant cis-eQTLs for PMF1 (P = 1 × 10-4 in tibial nerve), NBEAL1, FAM117B and CARF (P < 2.1 × 10-7 in arteries) and COL4A2 and COL4A1 (P < 0.01 in brain putamen), respectively. Leveraging S-PrediXcan for gene-based association testing with the predicted expression models in tissues related with nerve, artery, and non-lobar brain, we found that experiment-wide significant (P < 8.5 × 10-7) associations at three genes at 2q33 including NBEAL1, FAM117B and WDR12 and genome-wide significant associations at two genes including ICA1L at 2q33 and ZCCHC14 at 16q24. Brain cell-type specific expression profiling libraries reveal that SEMA4A, SLC25A44 and PMF1 at 1q22 and COL4A1 and COL4A2 at 13q34 were mainly expressed in endothelial cells, while the genes at 2q33 (FAM117B, CARF and NBEAL1) were expressed in various cell types including astrocytes, oligodendrocytes and neurons. Our cross-phenotype genetic study of intracerebral haemorrhage and SVS demonstrates novel genome-wide associations for non-lobar intracerebral haemorrhage at 2q33 and 13q34. Our replication of the 1q22 locus previous seen in traditional GWAS of intracerebral haemorrhage, as well as the rediscovery of 13q34, which had previously been reported in candidate gene studies with other cerebral small vessel disease-related traits strengthens the credibility of applying this novel genome-wide approach across intracerebral haemorrhage and SVS.
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| 2. |
- Giese, Anne Katrin, 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. - 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. Methods: MRI-GENIE capitalizes on the existing infrastructure of the Stroke Genetics Network (SiGN). In total, 12 international SiGN sites contributedMRIs 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 themanual and automated assessments of established MRI markers. A high-throughputMRI 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.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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| 3. |
- Malik, Rainer, et al.
(författare)
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Low-frequency and common genetic variation in ischemic stroke : The METASTROKE collaboration
- 2016
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Ingår i: Neurology. - 1526-632X. ; 86:13, s. 26-1217
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: To investigate the influence of common and low-frequency genetic variants on the risk of ischemic stroke (all IS) and etiologic stroke subtypes.METHODS: We meta-analyzed 12 individual genome-wide association studies comprising 10,307 cases and 19,326 controls imputed to the 1000 Genomes (1 KG) phase I reference panel. We selected variants showing the highest degree of association (p < 1E-5) in the discovery phase for replication in Caucasian (13,435 cases and 29,269 controls) and South Asian (2,385 cases and 5,193 controls) samples followed by a transethnic meta-analysis. We further investigated the p value distribution for different bins of allele frequencies for all IS and stroke subtypes.RESULTS: We showed genome-wide significance for 4 loci: ABO for all IS, HDAC9 for large vessel disease (LVD), and both PITX2 and ZFHX3 for cardioembolic stroke (CE). We further refined the association peaks for ABO and PITX2. Analyzing different allele frequency bins, we showed significant enrichment in low-frequency variants (allele frequency <5%) for both LVD and small vessel disease, and an enrichment of higher frequency variants (allele frequency 10% and 30%) for CE (all p < 1E-5).CONCLUSIONS: Our findings suggest that the missing heritability in IS subtypes can in part be attributed to low-frequency and rare variants. Larger sample sizes are needed to identify the variants associated with all IS and stroke subtypes.
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| 4. |
- Rannikmaee, Kristiina, et al.
(författare)
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Common variation in COL4A1/COL4A2 is associated with sporadic cerebral small vessel disease
- 2015
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Ingår i: Neurology. - 1526-632X. ; 84:9, s. 918-926
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Tidskriftsartikel (refereegranskat)abstract
- Objectives:We hypothesized that common variants in the collagen genes COL4A1/COL4A2 are associated with sporadic forms of cerebral small vessel disease.Methods:We conducted meta-analyses of existing genotype data among individuals of European ancestry to determine associations of 1,070 common single nucleotide polymorphisms (SNPs) in the COL4A1/COL4A2 genomic region with the following: intracerebral hemorrhage and its subtypes (deep, lobar) (1,545 cases, 1,485 controls); ischemic stroke and its subtypes (cardioembolic, large vessel disease, lacunar) (12,389 cases, 62,004 controls); and white matter hyperintensities (2,733 individuals with ischemic stroke and 9,361 from population-based cohorts with brain MRI data). We calculated a statistical significance threshold that accounted for multiple testing and linkage disequilibrium between SNPs (p < 0.000084).Results:Three intronic SNPs in COL4A2 were significantly associated with deep intracerebral hemorrhage (lead SNP odds ratio [OR] 1.29, 95% confidence interval [CI] 1.14-1.46, p = 0.00003; r(2) > 0.9 between SNPs). Although SNPs associated with deep intracerebral hemorrhage did not reach our significance threshold for association with lacunar ischemic stroke (lead SNP OR 1.10, 95% CI 1.03-1.18, p = 0.0073), and with white matter hyperintensity volume in symptomatic ischemic stroke patients (lead SNP OR 1.07, 95% CI 1.01-1.13, p = 0.016), the direction of association was the same. There was no convincing evidence of association with white matter hyperintensities in population-based studies or with non-small vessel disease cerebrovascular phenotypes.Conclusions:Our results indicate an association between common variation in the COL4A2 gene and symptomatic small vessel disease, particularly deep intracerebral hemorrhage. These findings merit replication studies, including in ethnic groups of non-European ancestry.
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| 5. |
- Roselli, Carolina, et al.
(författare)
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Multi-ethnic genome-wide association study for atrial fibrillation
- 2018
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 50:9, s. 1225-1233
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Tidskriftsartikel (refereegranskat)abstract
- Atrial fibrillation (AF) affects more than 33 million individuals worldwide(1) and has a complex heritability(2). We conducted the largest meta-analysis of genome-wide association studies (GWAS) for AF to date, consisting of more than half a million individuals, including 65,446 with AF. In total, we identified 97 loci significantly associated with AF, including 67 that were novel in a combined-ancestry analysis, and 3 that were novel in a European-specific analysis. We sought to identify AF-associated genes at the GWAS loci by performing RNA-sequencing and expression quantitative trait locus analyses in 101 left atrial samples, the most relevant tissue for AF. We also performed transcriptome-wide analyses that identified 57 AF-associated genes, 42 of which overlap with GWAS loci. The identified loci implicate genes enriched within cardiac developmental, electrophysiological, contractile and structural pathways. These results extend our understanding of the biological pathways underlying AF and may facilitate the development of therapeutics for AF.
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| 6. |
- Traylor, Matthew, et al.
(författare)
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Genetic Variation at 16q24.2 is associated with small vessel stroke.
- 2017
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Ingår i: Annals of neurology. - : Wiley. - 1531-8249 .- 0364-5134. ; 81:3, s. 383-394
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Tidskriftsartikel (refereegranskat)abstract
- Genome-wide association studies (GWAS) have been successful at identifying associations with stroke and stroke subtypes, but have not yet identified any associations solely with small vessel stroke (SVS). SVS comprises a quarter of all ischaemic stroke and is a major manifestation of cerebral small vessel disease, the primary cause of vascular cognitive impairment. Studies across neurological traits have shown younger onset cases have an increased genetic burden. We leveraged this increased genetic burden by performing an age-at-onset informed GWAS meta-analysis, including a large younger onset SVS population, to identify novel associations with stroke.We used a three-stage age-at-onset informed GWAS to identify novel genetic variants associated with stroke. On identifying a novel locus associated with SVS, we assessed its influence on other small vessel disease phenotypes, as well as on mRNA expression of nearby genes, and on DNA methylation of nearby CpG sites in whole blood and in the fetal brain.We identified an association with SVS in 4,203 cases and 50,728 controls on chromosome 16q24.2 (OR(95% CI)=1.16(1.10-1.22); p=3.2x10(-9) ). The lead SNP (rs12445022) was also associated with cerebral white matter hyperintensities (OR(95% CI)=1.10(1.05-1.16); p=5.3x10(-5) ; N=3,670), but not intracerebral haemorrhage (OR(95% CI)=0.97(0.84-1.12); p=0.71; 1,545 cases, 1,481 controls). rs12445022 is associated with mRNA expression of ZCCHC14 in arterial tissues (p=9.4x10(-7) ), and DNA methylation at probe cg16596957 in whole blood (p=5.3x10(-6) ).16q24.2 is associated with SVS. Associations of the locus with expression of ZCCHC14 and DNA methylation suggest the locus acts through changes to regulatory elements. This article is protected by copyright. All rights reserved.
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| 7. |
- Wu, Ona, 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. - 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 (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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