Atrial fibrillation genetic risk differentiates cardioembolic stroke from other stroke subtypes

Objective We sought to assess whether genetic risk factors for atrial fibrillation (AF) can explain cardioembolic stroke risk. Methods We evaluated genetic correlations between a previous genetic study of AF and AF in the presence of cardioembolic stroke using genome-wide genotypes from the Stroke Genetics Network (N = 3,190 AF cases, 3,000 cardioembolic stroke cases, and 28,026 referents). We tested whether a previously validated AF polygenic risk score (PRS) associated with cardioembolic and other stroke subtypes after accounting for AF clinical risk factors. Results We observed a strong correlation between previously reported genetic risk for AF, AF in the presence of stroke, and cardioembolic stroke (Pearson r = 0.77 and 0.76, respectively, across SNPs with p 0.1). Conclusion: s Genetic risk of AF is associated with cardioembolic stroke, independent of clinical risk factors. Studies are warranted to determine whether AF genetic risk can serve as a biomarker for strokes caused by AF

Atrial fibrillation genetic risk differentiates cardioembolic stroke from other stroke subtypes

Objective: We sought to assess whether genetic risk factors for atrial fibrillation (AF) can explain cardioembolic stroke risk. Methods: We evaluated genetic correlations between a previous genetic study of AF and AF in the presence of cardioembolic stroke using genome-wide genotypes from the Stroke Genetics Network (N = 3,190 AF cases, 3,000 cardioembolic stroke cases, and 28,026 referents). We tested whether a previously validated AF polygenic risk score (PRS) associated with cardioembolic and other stroke subtypes after accounting for AF clinical risk factors. Results: We observed a strong correlation between previously reported genetic risk for AF, AF in the presence of stroke, and cardioembolic stroke (Pearson r = 0.77 and 0.76, respectively, across SNPs with p < 4.4 × 10−4 in the previous AF meta-analysis). An AF PRS, adjusted for clinical AF risk factors, was associated with cardioembolic stroke (odds ratio [OR] per SD = 1.40, p = 1.45 × 10−48), explaining ∼20% of the heritable component of cardioembolic stroke risk. The AF PRS was also associated with stroke of undetermined cause (OR per SD = 1.07, p = 0.004), but no other primary stroke subtypes (all p > 0.1). Conclusions: Genetic risk of AF is associated with cardioembolic stroke, independent of clinical risk factors. Studies are warranted to determine whether AF genetic risk can serve as a biomarker for strokes caused by AF

Multiethnic Genetic Association Studies Improve Power for Locus Discovery

To date, genome-wide association studies have focused almost exclusively on populations of European ancestry. These studies continue with the advent of next-generation sequencing, designed to systematically catalog and test low-frequency variation for a role in disease. A complementary approach would be to focus further efforts on cohorts of multiple ethnicities. This leverages the idea that population genetic drift may have elevated some variants to higher allele frequency in different populations, boosting statistical power to detect an association. Based on empirical allele frequency distributions from eleven populations represented in HapMap Phase 3 and the 1000 Genomes Project, we simulate a range of genetic models to quantify the power of association studies in multiple ethnicities relative to studies that exclusively focus on samples of European ancestry. In each of these simulations, a first phase of GWAS in exclusively European samples is followed by a second GWAS phase in any of the other populations (including a multiethnic design). We find that nontrivial power gains can be achieved by conducting future whole-genome studies in worldwide populations, where, in particular, African populations contribute the largest relative power gains for low-frequency alleles (<5%) of moderate effect that suffer from low power in samples of European descent. Our results emphasize the importance of broadening genetic studies to worldwide populations to ensure efficient discovery of genetic loci contributing to phenotypic trait variability, especially for those traits for which large numbers of samples of European ancestry have already been collected and tested

Machine Learning based histology phenotyping to investigate the epidemiologic and genetic basis of adipocyte morphology and cardiometabolic traits

Genetic studies have recently highlighted the importance of fat distribution, as well as overall adiposity, in the pathogenesis of obesity-associated diseases. Using a large study (n = 1,288) from 4 independent cohorts, we aimed to investigate the relationship between mean adipocyte area and obesity-related traits, and identify genetic factors associated with adipocyte cell size. To perform the first large-scale study of automatic adipocyte phenotyping using both histological and genetic data, we developed a deep learning-based method, the Adipocyte U-Net, to rapidly derive mean adipocyte area estimates from histology images. We validate our method using three state-of-the-art approaches; CellProfiler, Adiposoft and floating adipocytes fractions, all run blindly on two external cohorts. We observe high concordance between our method and the state-of-the-art approaches (Adipocyte U-net vs. CellProfiler: R2visceral = 0.94, P < 2.2 × 10-16, R2subcutaneous = 0.91, P < 2.2 × 10-16), and faster run times (10,000 images: 6mins vs 3.5hrs). We applied the Adipocyte U-Net to 4 cohorts with histology, genetic, and phenotypic data (total N = 820). After meta-analysis, we found that mean adipocyte area positively correlated with body mass index (BMI) (Psubq = 8.13 × 10-69, βsubq = 0.45; Pvisc = 2.5 × 10-55, βvisc = 0.49; average R2 across cohorts = 0.49) and that adipocytes in subcutaneous depots are larger than their visceral counterparts (Pmeta = 9.8 × 10-7). Lastly, we performed the largest GWAS and subsequent meta-analysis of mean adipocyte area and intra-individual adipocyte variation (N = 820). Despite having twice the number of samples than any similar study, we found no genome-wide significant associations, suggesting that larger sample sizes and a homogenous collection of adipose tissue are likely needed to identify robust genetic associations.This article is freely available via Open Access. Click on the Publisher URL to access it via the publisher's site.C.A.G received a pump priming grant from Novo Nordisk to carry out this work. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.published version, accepted versio

COL4A2 is associated with lacunar ischemic stroke and deep ICH: Meta-analyses among 21,500 cases and 40,600 controls

Objective: To determine whether common variants in familial cerebral small vessel disease (SVD) genes confer risk of sporadic cerebral SVD. Methods: We meta-analyzed genotype data from individuals of European ancestry to determine associations of common single nucleotide polymorphisms (SNPs) in 6 familial cerebral SVD genes (COL4A1, COL4A2, NOTCH3, HTRA1, TREX1, and CECR1) with intracerebral hemorrhage (ICH) (deep, lobar, all; 1,878 cases, 2,830 controls) and ischemic stroke (IS) (lacunar, cardioembolic, large vessel disease, all; 19,569 cases, 37,853 controls). We applied data quality filters and set statistical significance thresholds accounting for linkage disequilibrium and multiple testing. Results: A locus in COL4A2 was associated (significance threshold p , 3.5 3 1024) with both lacunar IS (lead SNP rs9515201: odds ratio [OR] 1.17, 95%confidence interval [CI] 1.11-1.24, p 56.62 31028) and deep ICH (lead SNP rs4771674: OR 1.28, 95%CI 1.13-1.44, p 55.76 3 1025). A SNP in HTRA1 was associated (significance threshold p , 5.5 3 1024) with lacunar IS (rs79043147: OR 1.23, 95%CI 1.10-1.37, p 5 1.90 3 1024) and less robustly with deep ICH. There was no clear evidence for association of common variants in either COL4A2 or HTRA1 with non-SVD strokes or in any of the other genes with any stroke phenotype

Genetic association study of QT interval highlights role for calcium signaling pathways in myocardial repolarization.

The QT interval, an electrocardiographic measure reflecting myocardial repolarization, is a heritable trait. QT prolongation is a risk factor for ventricular arrhythmias and sudden cardiac death (SCD) and could indicate the presence of the potentially lethal mendelian long-QT syndrome (LQTS). Using a genome-wide association and replication study in up to 100,000 individuals, we identified 35 common variant loci associated with QT interval that collectively explain ∼8-10% of QT-interval variation and highlight the importance of calcium regulation in myocardial repolarization. Rare variant analysis of 6 new QT interval-associated loci in 298 unrelated probands with LQTS identified coding variants not found in controls but of uncertain causality and therefore requiring validation. Several newly identified loci encode proteins that physically interact with other recognized repolarization proteins. Our integration of common variant association, expression and orthogonal protein-protein interaction screens provides new insights into cardiac electrophysiology and identifies new candidate genes for ventricular arrhythmias, LQTS and SCD

Major histocompatibility complex associations of ankylosing spondylitis are complex and involve further epistasis with ERAP1

Ankylosing spondylitis (AS) is a common, highly heritable, inflammatory arthritis for which HLA-B*27 is the major genetic risk factor, although its role in the aetiology of AS remains elusive. To better understand the genetic basis of the MHC susceptibility loci, we genotyped 7,264 MHC SNPs in 22,647 AS cases and controls of European descent. We impute SNPs, classical HLA alleles and amino-acid residues within HLA proteins, and tested these for association to AS status. Here we show that in addition to effects due to HLA-B*27 alleles, several other HLA-B alleles also affect susceptibility. After controlling for the associated haplotypes in HLA-B, we observe independent associations with variants in the HLA-A, HLA-DPB1 and HLA-DRB1 loci. We also demonstrate that the ERAP1 SNP rs30187 association is not restricted only to carriers of HLA-B*27 but also found in HLA-B*40:01 carriers independently of HLA-B*27 genotype