Genetic architecture of white matter hyperintensities differs in hypertensive and nonhypertensive ischemic stroke.

BACKGROUND AND PURPOSE: Epidemiological studies suggest that white matter hyperintensities (WMH) are extremely heritable, but the underlying genetic variants are largely unknown. Pathophysiological heterogeneity is known to reduce the power of genome-wide association studies (GWAS). Hypertensive and nonhypertensive individuals with WMH might have different underlying pathologies. We used GWAS data to calculate the variance in WMH volume (WMHV) explained by common single nucleotide polymorphisms (SNPs) as a measure of heritability (SNP heritability [HSNP]) and tested the hypothesis that WMH heritability differs between hypertensive and nonhypertensive individuals. METHODS: WMHV was measured on MRI in the stroke-free cerebral hemisphere of 2336 ischemic stroke cases with GWAS data. After adjustment for age and intracranial volume, we determined which cardiovascular risk factors were independent predictors of WMHV. Using the genome-wide complex trait analysis tool to estimate HSNP for WMHV overall and within subgroups stratified by risk factors found to be significant in multivariate analyses. RESULTS: A significant proportion of the variance of WMHV was attributable to common SNPs after adjustment for significant risk factors (HSNP=0.23; P=0.0026). HSNP estimates were higher among hypertensive individuals (HSNP=0.45; P=7.99×10(-5)); this increase was greater than expected by chance (P=0.012). In contrast, estimates were lower, and nonsignificant, in nonhypertensive individuals (HSNP=0.13; P=0.13). CONCLUSIONS: A quarter of variance is attributable to common SNPs, but this estimate was greater in hypertensive individuals. These findings suggest that the genetic architecture of WMH in ischemic stroke differs between hypertensives and nonhypertensives. Future WMHV GWAS studies may gain power by accounting for this interaction

Weak geodesics on prox-regular subsets of Riemannian manifolds

We give a definition of weak geodesics on prox-regular subsets of Riemannian manifolds as continuous curves with some weak regularities. Then obtaining a suitable Lipschitz constant of the projection map, we characterize weak geodesics on a prox-regular set with assigned end points as viscosity critical points of the energy functional

Large-scale analyses of common and rare variants identify 12 new loci associated with atrial fibrillation

Atrial fibrillation affects more than 33 million people worldwide and increases the risk of stroke, heart failure, and death. Fourteen genetic loci have been associated with atrial fibrillation in European and Asian ancestry groups. To further define the genetic basis of atrial fibrillation, we performed large-scale, trans-ancestry meta-analyses of common and rare variant association studies. The genome-wide association studies (GWAS) included 17,931 individuals with atrial fibrillation and 115,142 referents; the exome-wide association studies (ExWAS) and rare variant association studies (RVAS) involved 22,346 cases and 132,086 referents. We identified 12 new genetic loci that exceeded genome-wide significance, implicating genes involved in cardiac electrical and structural remodeling. Our results nearly double the number of known genetic loci for atrial fibrillation, provide insights into the molecular basis of atrial fibrillation, and may facilitate the identification of new potential targets for drug discovery

Identification of additional risk loci for stroke and small vessel disease: a meta-analysis of genome-wide association studies

BACKGROUND: Genetic determinants of stroke, the leading neurological cause of death and disability, are poorly understood and have seldom been explored in the general population. Our aim was to identify additional loci for stroke by doing a meta-analysis of genome-wide association studies. METHODS: For the discovery sample, we did a genome-wide analysis of common genetic variants associated with incident stroke risk in 18 population-based cohorts comprising 84 961 participants, of whom 4348 had stroke. Stroke diagnosis was ascertained and validated by the study investigators. Mean age at stroke ranged from 45·8 years to 76·4 years, and data collection in the studies took place between 1948 and 2013. We did validation analyses for variants yielding a significant association (at p<5 × 10(-6)) with all-stroke, ischaemic stroke, cardioembolic ischaemic stroke, or non-cardioembolic ischaemic stroke in the largest available cross-sectional studies (70 804 participants, of whom 19 816 had stroke). Summary-level results of discovery and follow-up stages were combined using inverse-variance weighted fixed-effects meta-analysis, and in-silico lookups were done in stroke subtypes. For genome-wide significant findings (at p<5 × 10(-8)), we explored associations with additional cerebrovascular phenotypes and did functional experiments using conditional (inducible) deletion of the probable causal gene in mice. We also studied the expression of orthologs of this probable causal gene and its effects on cerebral vasculature in zebrafish mutants. FINDINGS: We replicated seven of eight known loci associated with risk for ischaemic stroke, and identified a novel locus at chromosome 6p25 (rs12204590, near FOXF2) associated with risk of all-stroke (odds ratio [OR] 1·08, 95% CI 1·05-1·12, p=1·48 × 10(-8); minor allele frequency 21%). The rs12204590 stroke risk allele was also associated with increased MRI-defined burden of white matter hyperintensity-a marker of cerebral small vessel disease-in stroke-free adults (n=21 079; p=0·0025). Consistently, young patients (aged 2-32 years) with segmental deletions of FOXF2 showed an extensive burden of white matter hyperintensity. Deletion of Foxf2 in adult mice resulted in cerebral infarction, reactive gliosis, and microhaemorrhage. The orthologs of FOXF2 in zebrafish (foxf2b and foxf2a) are expressed in brain pericytes and mutant foxf2b(-/-) cerebral vessels show decreased smooth muscle cell and pericyte coverage. INTERPRETATION: We identified common variants near FOXF2 that are associated with increased stroke susceptibility. Epidemiological and experimental data suggest that FOXF2 mediates this association, potentially via differentiation defects of cerebral vascular mural cells. Further expression studies in appropriate human tissues, and further functional experiments with long follow-up periods are needed to fully understand the underlying mechanisms

Common and Rare Coding Genetic Variation Underlying the Electrocardiographic PR Interval

Background: Electrical conduction from the cardiac sinoatrial node to the ventricles is critical for normal heart function. Genome-wide association studies have identified more than a dozen common genetic loci that are associated with PR interval. However, it is unclear whether rare and low-frequency variants also contribute to PR interval heritability. Methods: We performed large-scale meta-analyses of the PR interval that included 83 367 participants of European ancestry and 9436 of African ancestry. We examined both common and rare variants associated with the PR interval. Results: We identified 31 genetic loci that were significantly associated with PR interval after Bonferroni correction (P<1.2×10−6), including 11 novel loci that have not been reported previously. Many of these loci are involved in heart morphogenesis. In gene-based analysis, we found that multiple rare variants at MYH6 (P=5.9×10−11) and SCN5A (P=1.1×10−7) were associated with PR interval. SCN5A locus also was implicated in the common variant analysis, whereas MYH6 was a novel locus. Conclusions: We identified common variants at 11 novel loci and rare variants within 2 gene regions that were significantly associated with PR interval. Our findings provide novel insights to the current understanding of atrioventricular conduction, which is critical for cardiac activity and an important determinant of health

Discovery of novel heart rate-associated loci using the Exome Chip

Resting heart rate is a heritable trait, and an increase in heart rate is associated with increased mortality risk. Genome-wide association study analyses have found loci associated with resting heart rate, at the time of our study these loci explained 0.9% of the variation. This study aims to discover new genetic loci associated with heart rate from Exome Chip meta-analyses. Heart rate was measured from either elecrtrocardiograms or pulse recordings. We meta-analysed heart rate association results from 104 452 European-ancestry individuals from 30 cohorts, genotyped using the Exome Chip. Twenty-four variants were selected for follow-up in an independent dataset (UK Biobank, N = 134 251). Conditional and gene-based testing was undertaken, and variants were investigated with bioinformatics methods. We discovered five novel heart rate loci, and one new independent low-frequency non-synonymous variant in an established heart rate locus (KIAA1755). Lead variants in four of the novel loci are non-synonymous variants in the genes C10orf71, DALDR3, TESK2 and SEC31B. The variant at SEC31B is significantly associated with SEC31B expression in heart and tibial nerve tissue. Further candidate genes were detected from long-range regulatory chromatin interactions in heart tissue (SCD, SLF2 and MAPK8). We observed significant enrichment in DNase I hypersensitive sites in fetal heart and lung. Moreover, enrichment was seen for the first time in human neuronal progenitor cells (derived from embryonic stem cells) and fetal muscle samples by including our novel variants. Our findings advance the knowledge of the genetic architecture of heart rate, and indicate new candidate genes for follow-up functional studies

MRI-based radiomics for prognosis of pediatric diffuse intrinsic pontine glioma: an international study.

Background: Diffuse intrinsic pontine gliomas (DIPGs) are lethal pediatric brain tumors. Presently, MRI is the mainstay of disease diagnosis and surveillance. We identify clinically significant computational features from MRI and create a prognostic machine learning model. Methods: We isolated tumor volumes of T1-post-contrast (T1) and T2-weighted (T2) MRIs from 177 treatment-naïve DIPG patients from an international cohort for model training and testing. The Quantitative Image Feature Pipeline and PyRadiomics was used for feature extraction. Ten-fold cross-validation of least absolute shrinkage and selection operator Cox regression selected optimal features to predict overall survival in the training dataset and tested in the independent testing dataset. We analyzed model performance using clinical variables (age at diagnosis and sex) only, radiomics only, and radiomics plus clinical variables. Results: All selected features were intensity and texture-based on the wavelet-filtered images (3 T1 gray-level co-occurrence matrix (GLCM) texture features, T2 GLCM texture feature, and T2 first-order mean). This multivariable Cox model demonstrated a concordance of 0.68 (95% CI: 0.61-0.74) in the training dataset, significantly outperforming the clinical-only model (C = 0.57 [95% CI: 0.49-0.64]). Adding clinical features to radiomics slightly improved performance (C = 0.70 [95% CI: 0.64-0.77]). The combined radiomics and clinical model was validated in the independent testing dataset (C = 0.59 [95% CI: 0.51-0.67], Noether's test P = .02). Conclusions: In this international study, we demonstrate the use of radiomic signatures to create a machine learning model for DIPG prognostication. Standardized, quantitative approaches that objectively measure DIPG changes, including computational MRI evaluation, could offer new approaches to assessing tumor phenotype and serve a future role for optimizing clinical trial eligibility and tumor surveillance

Genome-wide meta-analysis of cerebral white matter hyperintensities in patients with stroke.

OBJECTIVE: For 3,670 stroke patients from the United Kingdom, United States, Australia, Belgium, and Italy, we performed a genome-wide meta-analysis of white matter hyperintensity volumes (WMHV) on data imputed to the 1000 Genomes reference dataset to provide insights into disease mechanisms. METHODS: We first sought to identify genetic associations with white matter hyperintensities in a stroke population, and then examined whether genetic loci previously linked to WMHV in community populations are also associated in stroke patients. Having established that genetic associations are shared between the 2 populations, we performed a meta-analysis testing which associations with WMHV in stroke-free populations are associated overall when combined with stroke populations. RESULTS: There were no associations at genome-wide significance with WMHV in stroke patients. All previously reported genome-wide significant associations with WMHV in community populations shared direction of effect in stroke patients. In a meta-analysis of the genome-wide significant and suggestive loci (p < 5 × 10(-6)) from community populations (15 single nucleotide polymorphisms in total) and from stroke patients, 6 independent loci were associated with WMHV in both populations. Four of these are novel associations at the genome-wide level (rs72934505 [NBEAL1], p = 2.2 × 10(-8); rs941898 [EVL], p = 4.0 × 10(-8); rs962888 [C1QL1], p = 1.1 × 10(-8); rs9515201 [COL4A2], p = 6.9 × 10(-9)). CONCLUSIONS: Genetic associations with WMHV are shared in otherwise healthy individuals and patients with stroke, indicating common genetic susceptibility in cerebral small vessel disease

A genome-wide association study of outcome from traumatic brain injury

Background Factors such as age, pre-injury health, and injury severity, account for less than 35% of outcome variability in traumatic brain injury (TBI). While some residual outcome variability may be attributable to genetic factors, published candidate gene association studies have often been underpowered and subject to publication bias. Methods We performed the first genome- and transcriptome-wide association studies (GWAS, TWAS) of genetic effects on outcome in TBI. The study population consisted of 5268 patients from prospective European and US studies, who attended hospital within 24 h of TBI, and satisfied local protocols for computed tomography. Findings The estimated heritability of TBI outcome was 0·26. GWAS revealed no genetic variants with genome-wide significance (p < 5 × 10−8), but identified 83 variants in 13 independent loci which met a lower pre-specified sub-genomic statistical threshold (p < 10−5). Similarly, none of the genes tested in TWAS met tissue-wide significance. An exploratory analysis of 75 published candidate variants associated with 28 genes revealed one replicable variant (rs1800450 in the MBL2 gene) which retained significance after correction for multiple comparison (p = 5·24 × 10−4). Interpretation While multiple novel loci reached less stringent thresholds, none achieved genome-wide significance. The overall heritability estimate, however, is consistent with the hypothesis that common genetic variation substantially contributes to inter-individual variability in TBI outcome. The meta-analytic approach to the GWAS and the availability of summary data allows for a continuous extension with additional cohorts as data becomes available