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| 2. |
- Franceschini, N., et al.
(författare)
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GWAS and colocalization analyses implicate carotid intima-media thickness and carotid plaque loci in cardiovascular outcomes
- 2018
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 9:1
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Tidskriftsartikel (refereegranskat)abstract
- Carotid artery intima media thickness (cIMT) and carotid plaque are measures of subclinical atherosclerosis associated with ischemic stroke and coronary heart disease (CHD). Here, we undertake meta-analyses of genome-wide association studies (GWAS) in 71,128 individuals for cIMT, and 48,434 individuals for carotid plaque traits. We identify eight novel susceptibility loci for cIMT, one independent association at the previously-identified PINX1 locus, and one novel locus for carotid plaque. Colocalization analysis with nearby vascular expression quantitative loci (cis-eQTLs) derived from arterial wall and metabolic tissues obtained from patients with CHD identifies candidate genes at two potentially additional loci, ADAMTS9 and LOXL4. LD score regression reveals significant genetic correlations between cIMT and plaque traits, and both cIMT and plaque with CHD, any stroke subtype and ischemic stroke. Our study provides insights into genes and tissue-specific regulatory mechanisms linking atherosclerosis both to its functional genomic origins and its clinical consequences in humans. © 2018, The Author(s).
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| 3. |
- Mola-Caminal, M., et al.
(författare)
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PATJ Low Frequency Variants Are Associated With Worse Ischemic Stroke Functional Outcome A Genome-Wide Meta-Analysis
- 2019
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Ingår i: Circulation research. - : Ovid Technologies (Wolters Kluwer Health). - 0009-7330 .- 1524-4571. ; 124:1, s. 114-120
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Tidskriftsartikel (refereegranskat)abstract
- Rationale: Ischemic stroke is among the leading causes of adult disability. Part of the variability in functional outcome after stroke has been attributed to genetic factors but no locus has been consistently associated with stroke outcome. Objective: Our aim was to identify genetic loci influencing the recovery process using accurate phenotyping to produce the largest GWAS (genome-wide association study) in ischemic stroke recovery to date. Methods and Results: A 12-cohort, 2-phase (discovery-replication and joint) meta-analysis of GWAS included anterior-territory and previously independent ischemic stroke cases. Functional outcome was recorded using 3-month modified Rankin Scale. Analyses were adjusted for confounders such as discharge National Institutes of Health Stroke Scale. A gene-based burden test was performed. The discovery phase (n=1225) was followed by open (n=2482) and stringent joint-analyses (n=1791). Those cohorts with modified Rankin Scale recorded at time points other than 3-month or incomplete data on previous functional status were excluded in the stringent analyses. Novel variants in PATJ (Pals1-associated tight junction) gene were associated with worse functional outcome at 3-month after stroke. The top variant was rs76221407 (G allele, beta=0.40, P=1.70x10-9). Conclusions: Our results identify a set of common variants in PATJ gene associated with 3-month functional outcome at genome-wide significance level. Future studies should examine the role of PATJ in stroke recovery and consider stringent phenotyping to enrich the information captured to unveil additional stroke outcome loci.
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| 6. |
- 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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| 7. |
- Soderholm, M., et al.
(författare)
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Genome-wide association meta-analysis of functional outcome after ischemic stroke
- 2019
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Ingår i: Neurology. - : Ovid Technologies (Wolters Kluwer Health). - 0028-3878 .- 1526-632X. ; 92:12
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Tidskriftsartikel (refereegranskat)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 x 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 x 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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| 8. |
- Chen, X., et al.
(författare)
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A genome-wide association study of IgM antibody against phosphorylcholine: shared genetics and phenotypic relationship to chronic lymphocytic leukemia
- 2018
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Ingår i: Human Molecular Genetics. - : Oxford University Press (OUP). - 0964-6906 .- 1460-2083. ; 27:10, s. 1809-1818
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Tidskriftsartikel (refereegranskat)abstract
- Phosphorylcholine (PC) is an epitope on oxidized low-density lipoprotein (oxLDL), apoptotic cells and several pathogens like Streptococcus pneumoniae. Immunoglobulin M against PC (IgM anti-PC) has the ability to inhibit uptake of oxLDL by macrophages and increase clearance of apoptotic cells. From our genome-wide association studies (GWASs) in four European-ancestry cohorts, six single nucleotide polymorphisms (SNPs) in 11q24.1 were discovered (in 3002 individuals) and replicated (in 646 individuals) to be associated with serum level of IgM anti-PC (the leading SNP rs35923643-G, combined beta = 0.19, 95% confidence interval 0.13-0.24, P = 4.3 x 10-11). The haplotype tagged by rs35923643-G (or its proxy SNP rs735665-A) is also known as the top risk allele for chronic lymphocytic leukemia (CLL), and a main increasing allele for general IgM. By using summary GWAS results of IgM anti-PC and CLL in the polygenic risk score (PRS) analysis, PRS on the basis of IgM anti-PC risk alleles positively associated with CLL risk (explained 0.6% of CLL variance, P = 1.2 x 10-15). Functional prediction suggested that rs35923643-G might impede the binding of Runt-related transcription factor 3, a tumor suppressor playing a central role in the immune regulation of cancers. Contrary to the expectations from the shared genetics between IgM anti-PC and CLL, an inverse relationship at the phenotypic level was found in a nested case-control study (30 CLL cases with 90 age- and sex-matched controls), potentially reflecting reverse causation. The suggested function of the top variant as well as the phenotypic association between IgM anti-PC and CLL risk needs replication and motivates further studies.
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| 9. |
- 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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| 10. |
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| 11. |
- Nielson, Carrie M., et al.
(författare)
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Novel Genetic Variants Associated With Increased Vertebral Volumetric BMD, Reduced Vertebral Fracture Risk, and Increased Expression of SLC1A3 and EPHB2
- 2016
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Ingår i: Journal of Bone and Mineral Research. - : Wiley. - 0884-0431. ; 31:12, s. 2085-2097
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Tidskriftsartikel (refereegranskat)abstract
- Genome-wide association studies (GWASs) have revealed numerous loci for areal bone mineral density (aBMD). We completed the first GWAS meta-analysis (n=15,275) of lumbar spine volumetric BMD (vBMD) measured by quantitative computed tomography (QCT), allowing for examination of the trabecular bone compartment. SNPs that were significantly associated with vBMD were also examined in two GWAS meta-analyses to determine associations with morphometric vertebral fracture (n=21,701) and clinical vertebral fracture (n=5893). Expression quantitative trait locus (eQTL) analyses of iliac crest biopsies were performed in 84 postmenopausal women, and murine osteoblast expression of genes implicated by eQTL or by proximity to vBMD-associated SNPs was examined. We identified significant vBMD associations with five loci, including: 1p36.12, containing WNT4 and ZBTB40; 8q24, containing TNFRSF11B; and 13q14, containing AKAP11 and TNFSF11. Two loci (5p13 and 1p36.12) also contained associations with radiographic and clinical vertebral fracture, respectively. In 5p13, rs2468531 (minor allele frequency [MAF]=3%) was associated with higher vBMD (β=0.22, p=1.9×10-8) and decreased risk of radiographic vertebral fracture (odds ratio [OR]=0.75; false discovery rate [FDR] p=0.01). In 1p36.12, rs12742784 (MAF=21%) was associated with higher vBMD (β=0.09, p=1.2×10-10) and decreased risk of clinical vertebral fracture (OR=0.82; FDR p=7.4×10-4). Both SNPs are noncoding and were associated with increased mRNA expression levels in human bone biopsies: rs2468531 with SLC1A3 (β=0.28, FDR p=0.01, involved in glutamate signaling and osteogenic response to mechanical loading) and rs12742784 with EPHB2 (β=0.12, FDR p=1.7×10-3, functions in bone-related ephrin signaling). Both genes are expressed in murine osteoblasts. This is the first study to link SLC1A3 and EPHB2 to clinically relevant vertebral osteoporosis phenotypes. These results may help elucidate vertebral bone biology and novel approaches to reducing vertebral fracture incidence.
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