scholarly journals Common Genetic Variation Indicates Separate Causes for Periventricular and Deep White Matter Hyperintensities

Stroke ◽  
2020 ◽  
Vol 51 (7) ◽  
pp. 2111-2121 ◽  
Author(s):  
Nicola J. Armstrong ◽  
Karen A. Mather ◽  
Muralidharan Sargurupremraj ◽  
Maria J. Knol ◽  
Rainer Malik ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
White Matter ◽  
White Matter Hyperintensities ◽  
Meta Analysis ◽  
Genetic Correlations ◽  
Imaging Genetics ◽  
Genome Wide Association ◽  
Association Analyses ◽  
New Genes ◽  
Genome Wide

Background and Purpose: Periventricular white matter hyperintensities (WMH; PVWMH) and deep WMH (DWMH) are regional classifications of WMH and reflect proposed differences in cause. In the first study, to date, we undertook genome-wide association analyses of DWMH and PVWMH to show that these phenotypes have different genetic underpinnings. Methods: Participants were aged 45 years and older, free of stroke and dementia. We conducted genome-wide association analyses of PVWMH and DWMH in 26,654 participants from CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology), ENIGMA (Enhancing Neuro-Imaging Genetics Through Meta-Analysis), and the UKB (UK Biobank). Regional correlations were investigated using the genome-wide association analyses -pairwise method. Cross-trait genetic correlations between PVWMH, DWMH, stroke, and dementia were estimated using LDSC. Results: In the discovery and replication analysis, for PVWMH only, we found associations on chromosomes 2 ( NBEAL ), 10q23.1 ( TSPAN14/FAM231A ), and 10q24.33 ( SH3PXD2A). In the much larger combined meta-analysis of all cohorts, we identified ten significant regions for PVWMH: chromosomes 2 (3 regions), 6, 7, 10 (2 regions), 13, 16, and 17q23.1. New loci of interest include 7q36.1 ( NOS3 ) and 16q24.2. In both the discovery/replication and combined analysis, we found genome-wide significant associations for the 17q25.1 locus for both DWMH and PVWMH. Using gene-based association analysis, 19 genes across all regions were identified for PVWMH only, including the new genes: CALCRL (2q32.1), KLHL24 (3q27.1), VCAN (5q27.1), and POLR2F (22q13.1). Thirteen genes in the 17q25.1 locus were significant for both phenotypes. More extensive genetic correlations were observed for PVWMH with small vessel ischemic stroke. There were no associations with dementia for either phenotype. Conclusions: Our study confirms these phenotypes have distinct and also shared genetic architectures. Genetic analyses indicated PVWMH was more associated with ischemic stroke whilst DWMH loci were implicated in vascular, astrocyte, and neuronal function. Our study confirms these phenotypes are distinct neuroimaging classifications and identifies new candidate genes associated with PVWMH only.

scholarly journals Common genetic variation indicates separate etiologies for periventricular and deep white matter hyperintensities

2019 ◽  
Author(s):  
Nicola J Armstrong ◽  
Karen A Mather ◽  
Muralidharan Sargurupremraj ◽  
Maria J Knol ◽  
Rainer Malik ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
White Matter ◽  
White Matter Hyperintensities ◽  
Meta Analysis ◽  
Neuronal Function ◽  
Deep White Matter ◽  
Genome Wide ◽  
A Genome ◽  
Genetic Overlap ◽  
Disease Subtypes

AbstractWe conducted a genome-wide association meta-analysis of two ischemic white matter disease subtypes in the brain, periventricular and deep white matter hyperintensities (PVWMH and DWMH). In 26,654 participants, we found 10 independent genome-wide significant loci only associated with PVWMH, four of which have not been described previously for total WMH burden (16q24.2, 17q21.31, 10q23.1, 7q36.1). Additionally, in both PVWMH and DWMH we observed the previous association of the 17q25.1 locus with total WMH. We found that both phenotypes have shared but also distinct genetic architectures, consistent with both different underlying and related pathophysiology. PVWMH had more extensive genetic overlap with small vessel ischemic stroke, and unique associations with several loci implicated in ischemic stroke. DWMH were characterized by associations with loci previously implicated in vascular as well as astrocytic and neuronal function. Our study confirms the utility of these phenotypes and identifies new candidate genes associated only with PVWMH.

scholarly journals Genome-wide association meta-analysis of childhood and adolescent internalising symptoms

2020 ◽  
Author(s):  
Eshim S Jami ◽  
Anke R Hammerschlag ◽  
Hill F Ip ◽  
Andrea G Allegrini ◽  
Beben Benyamin ◽  
...  
Keyword(s):  
Confidence Intervals ◽  
Meta Analysis ◽  
Genetic Correlations ◽  
Genetic Effects ◽  
Childhood Aggression ◽  
Genome Wide Association ◽  
Childhood And Adolescence ◽  
Obsessive Compulsive ◽  
Compulsive Disorder ◽  
Genome Wide

Internalising symptoms in childhood and adolescence are as heritable as adult depression and anxiety, yet little is known of their molecular basis. This genome-wide association meta-analysis of internalising symptoms included repeated observations from 64,641 individuals, aged between 3 and 18. The N-weighted meta-analysis of overall internalising symptoms (INToverall) detected no genome-wide significant hits and showed low SNP heritability (1.66%, 95% confidence intervals 0.84-2.48%, Neffective=132,260). Stratified analyses showed rater-based heterogeneity in genetic effects, with self-reported internalising symptoms showing the highest heritability (5.63%, 95% confidence intervals 3.08-8.18%). Additive genetic effects on internalising symptoms appeared stable over age, with overlapping estimates of SNP heritability from early-childhood to adolescence. Gene-based analyses showed significant associations with three genes: WNT3 (p=1.13×10-06), CCL26 (p=1.88×10-06), and CENPO (p=2.54×10-06). Of these, WNT3 was previously associated with neuroticism, with which INToverall also shared a strong genetic correlation (rg=0.76). Genetic correlations were also observed with adult anxiety, depression, and the wellbeing spectrum (|rg|> 0.70), as well as with insomnia, loneliness, attention-deficit hyperactivity disorder, autism, and childhood aggression (range |rg|=0.42-0.60), whereas there were no robust associations with schizophrenia, bipolar disorder, obsessive-compulsive disorder, or anorexia nervosa. Overall, childhood and adolescent internalising symptoms share substantial genetic vulnerabilities with adult internalising disorders and other childhood psychiatric traits, which could explain both the persistence of internalising symptoms over time, and the high comorbidity amongst childhood psychiatric traits. Reducing phenotypic heterogeneity in childhood samples will be key in paving the way to future GWAS success.

scholarly journals A genome-wide association study identifies new loci for factor VII and implicates factor VII in ischemic stroke etiology

Blood ◽  
2019 ◽  
Vol 133 (9) ◽  
pp. 967-977 ◽  
Author(s):  
Paul S. de Vries ◽  
Maria Sabater-Lleal ◽  
Jennifer E. Huffman ◽  
Jonathan Marten ◽  
Ci Song ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Meta Analysis ◽  
Genome Wide Association ◽  
Coagulation Cascade ◽  
Factor Vii ◽  
Phenotypic Variance ◽  
Genome Wide ◽  
Huh7 Cells

Abstract Factor VII (FVII) is an important component of the coagulation cascade. Few genetic loci regulating FVII activity and/or levels have been discovered to date. We conducted a meta-analysis of 9 genome-wide association studies of plasma FVII levels (7 FVII activity and 2 FVII antigen) among 27 495 participants of European and African ancestry. Each study performed ancestry-specific association analyses. Inverse variance weighted meta-analysis was performed within each ancestry group and then combined for a trans-ancestry meta-analysis. Our primary analysis included the 7 studies that measured FVII activity, and a secondary analysis included all 9 studies. We provided functional genomic validation for newly identified significant loci by silencing candidate genes in a human liver cell line (HuH7) using small-interfering RNA and then measuring F7 messenger RNA and FVII protein expression. Lastly, we used meta-analysis results to perform Mendelian randomization analysis to estimate the causal effect of FVII activity on coronary artery disease, ischemic stroke (IS), and venous thromboembolism. We identified 2 novel (REEP3 and JAZF1-AS1) and 6 known loci associated with FVII activity, explaining 19.0% of the phenotypic variance. Adding FVII antigen data to the meta-analysis did not result in the discovery of further loci. Silencing REEP3 in HuH7 cells upregulated FVII, whereas silencing JAZF1 downregulated FVII. Mendelian randomization analyses suggest that FVII activity has a positive causal effect on the risk of IS. Variants at REEP3 and JAZF1 contribute to FVII activity by regulating F7 expression levels. FVII activity appears to contribute to the etiology of IS in the general population.

scholarly journals Genome-Wide Association Analyses of Equine Metabolic Syndrome Phenotypes in Welsh Ponies and Morgan Horses

Genes ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 893 ◽  
Author(s):  
Elaine Norton ◽  
Nichol Schultz ◽  
Ray Geor ◽  
Dianne McFarlane ◽  
James Mickelson ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Candidate Genes ◽  
Meta Analysis ◽  
Complex Trait ◽  
Genome Wide Association ◽  
Protein Coding ◽  
Association Analyses ◽  
Risk Alleles ◽  
Equine Metabolic Syndrome ◽  
Genome Wide

Equine metabolic syndrome (EMS) is a complex trait for which few genetic studies have been published. Our study objectives were to perform within breed genome-wide association analyses (GWA) to identify associated loci in two high-risk breeds, coupled with meta-analysis to identify shared and unique loci between breeds. GWA for 12 EMS traits identified 303 and 142 associated genomic regions in 264 Welsh ponies and 286 Morgan horses, respectively. Meta-analysis demonstrated that 65 GWA regions were shared across breeds. Region boundaries were defined based on a fixed-size or the breakdown of linkage disequilibrium, and prioritized if they were: shared between breeds or across traits (high priority), identified in a single GWA cohort (medium priority), or shared across traits with no SNPs reaching genome-wide significance (low priority), resulting in 56 high, 26 medium, and seven low priority regions including 1853 candidate genes in the Welsh ponies; and 39 high, eight medium, and nine low priority regions including 1167 candidate genes in the Morgans. The prioritized regions contained protein-coding genes which were functionally enriched for pathways associated with inflammation, glucose metabolism, or lipid metabolism. These data demonstrate that EMS is a polygenic trait with breed-specific risk alleles as well as those shared across breeds.

scholarly journals A combined analysis of genetically correlated traits identifies 107 loci associated with intelligence

2017 ◽  
Author(s):  
W. D. Hill ◽  
G. Davies ◽  
A. M. McIntosh ◽  
C. R. Gale ◽  
I. J. Deary
Keyword(s):  
Household Income ◽  
Association Studies ◽  
Meta Analysis ◽  
Genetic Correlations ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Correlated Traits ◽  
Single Measure ◽  
Combined Analysis ◽  
Genome Wide

AbstractIntelligence, or general cognitive function, is phenotypically and genetically correlated with many traits, including many physical and mental health variables. Both education and household income are strongly genetically correlated with intelligence, at rg =0.73 and rg =0.70 respectively. This allowed us to utilize a novel approach, Multi-Trait Analysis of Genome-wide association studies (MTAG; Turley et al. 2017), to combine two large genome-wide association studies (GWASs) of education and household income to increase power in the largest GWAS on intelligence so far (Sniekers et al. 2017). This study had four goals: firstly, to facilitate the discovery of new genetic loci associated with intelligence; secondly, to add to our understanding of the biology of intelligence differences; thirdly, to examine whether combining genetically correlated traits in this way produces results consistent with the primary phenotype of intelligence; and, finally, to test how well this new meta-analytic data sample on intelligence predict phenotypic intelligence variance in an independent sample. We apply MTAG to three large GWAS: Sniekers et al (2017) on intelligence, Okbay et al. (2016) on Educational attainment, and Hill et al. (2016) on household income. By combining these three samples our functional sample size increased from 78 308 participants to 147 194. We found 107 independent loci associated with intelligence, implicating 233 genes, using both SNP-based and gene-based GWAS. We find evidence that neurogenesis may explain some of the biological differences in intelligence as well as genes expressed in the synapse and those involved in the regulation of the nervous system. We show that the results of our combined analysis demonstrate the same pattern of genetic correlations as a single measure/the simple measure of intelligence, providing support for the meta-analysis of these genetically-related phenotypes. We find that our MTAG meta-analysis of intelligence shows similar genetic correlations to 26 other phenotypes when compared with a GWAS consisting solely of cognitive tests. Finally, using an independent sample of 6 844 individuals we were able to predict 7% of intelligence using SNP data alone.

scholarly journals Genome-Wide Association Study of Metamizole-Induced Agranulocytosis in European Populations

Genes ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1275
Author(s):  
Anca Cismaru ◽  
Deborah Rudin ◽  
Luisa Ibañez ◽  
Evangelia Liakoni ◽  
Nicolas Bonadies ◽  
...  
Keyword(s):  
Association Study ◽  
Genome Wide Association Study ◽  
Meta Analysis ◽  
Underlying Mechanism ◽  
Chromosome 9 ◽  
Genome Wide Association ◽  
Association Analyses ◽  
Genome Wide ◽  
Risk Patients ◽  
European Populations

Agranulocytosis is a rare yet severe idiosyncratic adverse drug reaction to metamizole, an analgesic widely used in countries such as Switzerland and Germany. Notably, an underlying mechanism has not yet been fully elucidated and no predictive factors are known to identify at-risk patients. With the aim to identify genetic susceptibility variants to metamizole-induced agranulocytosis (MIA) and neutropenia (MIN), we conducted a retrospective multi-center collaboration including cases and controls from three European populations. Association analyses were performed using genome-wide genotyping data from a Swiss cohort (45 cases, 191 controls) followed by replication in two independent European cohorts (41 cases, 273 controls) and a joint discovery meta-analysis. No genome-wide significant associations (p < 1 × 10−7) were observed in the Swiss cohort or in the joint meta-analysis, and no candidate genes suggesting an immune-mediated mechanism were identified. In the joint meta-analysis of MIA cases across all cohorts, two candidate loci on chromosome 9 were identified, rs55898176 (OR = 4.01, 95%CI: 2.41–6.68, p = 1.01 × 10−7) and rs4427239 (OR = 5.47, 95%CI: 2.81–10.65, p = 5.75 × 10−7), of which the latter is located in the SVEP1 gene previously implicated in hematopoiesis. This first genome-wide association study for MIA identified suggestive associations with biological plausibility that may be used as a stepping-stone for post-GWAS analyses to gain further insight into the mechanism underlying MIA.

scholarly journals Genomic Risk Profiling of Ischemic Stroke: Results of an International Genome-Wide Association Meta-Analysis

PLoS ONE ◽  
2011 ◽  
Vol 6 (9) ◽  
pp. e23161 ◽  
Author(s):  
James F. Meschia ◽  
Andrew Singleton ◽  
Michael A. Nalls ◽  
Stephen S. Rich ◽  
Pankaj Sharma ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Meta Analysis ◽  
Genome Wide Association ◽  
Risk Profiling ◽  
Genome Wide ◽  
Genomic Risk

scholarly journals A multivariate to multivariate approach for voxel-wise genome-wide association analysis

2021 ◽  
Author(s):  
Qiong Wu ◽  
Yuan Zhang ◽  
Xiaoqi Huang ◽  
Tianzhou Ma ◽  
L. Elliot Hong ◽  
...  
Keyword(s):  
White Matter ◽  
Association Analysis ◽  
Imaging Genetics ◽  
Statistical Testing ◽  
Genome Wide Association ◽  
White Matter Integrity ◽  
Genome Wide Association Analysis ◽  
Genome Wide ◽  
Clique Graph ◽  
Human Connectome Project

The joint analysis of imaging-genetics data facilitates the systematic investigation of genetic effects on brain structures and functions with spatial specificity. We focus on voxel-wise genome-wide association analysis, which may involve trillions of single nucleotide polymorphism (SNP)-voxel pairs. We attempt to identify underlying organized association patterns of SNP-voxel pairs and understand the polygenic and pleiotropic networks on brain imaging traits. We propose a bi-clique graph structure (i.e., a set of SNPs highly correlated with a cluster of voxels) for the systematic association pattern. Next, we develop computational strategies to detect latent SNP-voxel bi-cliques and inference model for statistical testing. We further provide theoretical results to guarantee the accuracy of our computational algorithms and statistical inference. We validate our method by extensive simulation studies and then apply it to the whole genome genetic and voxel-level white matter integrity data collected from 1052 participants of the human connectome project (HCP). The results demonstrate multiple genetic loci influencing white matter integrity measures on splenium and genu of the corpus callosum.

scholarly journals Genetic variation in PLEKHG1 is associated with white matter hyperintensities (n = 11,226)

Neurology ◽  
2019 ◽  
Vol 92 (8) ◽  
pp. e749-e757 ◽  
Author(s):  
Matthew Traylor ◽  
Daniel J. Tozer ◽  
Iain D. Croall ◽  
Danuta M. Lisiecka Ford ◽  
Abiodun Olubunmi Olorunda ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Ischemic Stroke ◽  
White Matter ◽  
White Matter Hyperintensities ◽  
Small Vessel ◽  
Uk Biobank ◽  
Narrow Sense Heritability ◽  
Genome Wide ◽  
A Genome ◽  
Genome Wide Significance

ObjectiveTo identify novel genetic associations with white matter hyperintensities (WMH).MethodsWe performed a genome-wide association meta-analysis of WMH volumes in 11,226 individuals, including 8,429 population-based individuals from UK Biobank and 2,797 stroke patients. Replication of novel loci was performed in an independent dataset of 1,202 individuals. In all studies, WMH were quantified using validated automated or semi-automated methods. Imputation was to either the Haplotype Reference Consortium or 1,000 Genomes Phase 3 panels.ResultsWe identified a locus at genome-wide significance in an intron of PLEKHG1 (rs275350, β [SE] = 0.071 [0.013]; p = 1.6 × 10−8), a Rho guanine nucleotide exchange factor that is involved in reorientation of cells in the vascular endothelium. This association was validated in an independent sample (overall p value, 2.4 × 10−9). The same single nucleotide polymorphism was associated with all ischemic stroke (odds ratio [OR] [95% confidence interval (CI)] 1.07 [1.03–1.12], p = 0.00051), most strongly with the small vessel subtype (OR [95% CI] 1.09 [1.00–1.19], p = 0.044). Previous associations at 17q25 and 2p16 reached genome-wide significance in this analysis (rs3744020; β [SE] = 0.106 [0.016]; p = 1.2 × 10−11 and rs7596872; β [SE] = 0.143 [0.021]; p = 3.4 × 10−12). All identified associations with WMH to date explained 1.16% of the trait variance in UK Biobank, equivalent to 6.4% of the narrow-sense heritability.ConclusionsGenetic variation in PLEKHG1 is associated with WMH and ischemic stroke, most strongly with the small vessel subtype, suggesting it acts by promoting small vessel arteriopathy.

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