193 research outputs found

    Rare missense functional variants at COL4A1 and COL4A2 in sporadic intracerebral Hhmorrhage

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    Objective: To test the genetic contribution of rare missense variants in COL4A1 and COL4A2 in which common variants are genetically associated with sporadic intracerebral hemorrhage (ICH), we performed rare variant analysis in multiple sequencing data for the risk for sporadic ICH. Methods: We performed sequencing across 559Kbp at 13q34 including COL4A1 and COL4A2 among 2,133 individuals (1,055 ICH cases; 1,078 controls) in US-based and 1,492 individuals (192 ICH cases; 1,189 controls) from Scotland-based cohorts, followed by sequence annotation, functional impact prediction, genetic association testing, and in silico thermodynamic modeling. Results: We identified 107 rare nonsynonymous variants in sporadic ICH, of which two missense variants, rs138269346 (COL4A1I110T) and rs201716258 (COL4A2H203L), were predicted to be highly functional and occurred in multiple ICH cases but not in controls from the US-based cohort. The minor allele of rs201716258 was also present in Scottish ICH patients, and rs138269346 was observed in two ICH-free controls with a history of hypertension and myocardial infarction. Rs138269346 was nominally associated with non-lobar ICH risk (P=0.05), but not with lobar ICH (P=0.08), while associations between rs201716258 and ICH subtypes were non-significant (P>0.12). Both variants were considered pathogenic based on minor allele frequency (<0.00035 in EUR), predicted functional impact (deleterious or probably damaging), and in silico modeling studies (substantially altered physical length and thermal stability of collagen). Conclusions: We identified rare missense variants in COL4A1/A2 in association with sporadic ICH. Our annotation and simulation studies suggest that these variants are highly functional and may represent targets for translational follow-up

    Genetic Associations With Toxicity-related Discontinuation of Aromatase Inhibitor Therapy for Breast Cancer

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    Up to 25 % of patients discontinue adjuvant aromatase inhibitor (AI) therapy due to intolerable symptoms. Predictors of which patients will be unable to tolerate these medications have not been defined. We hypothesized that inherited variants in candidate genes are associated with treatment discontinuation because of AI-associated toxicity. We prospectively evaluated reasons for treatment discontinuation in women with hormone receptor-positive breast cancer initiating adjuvant AI through a multicenter, prospective, randomized clinical trial of exemestane versus letrozole. Using multiple genetic models, we evaluated potential associations between discontinuation of AI therapy because of toxicity and 138 variants in 24 candidate genes, selected a priori, primarily with roles in estrogen metabolism and signaling. To account for multiple comparisons, statistical significance was defined as p < 0.00036. Of the 467 enrolled patients with available germline DNA, 152 (33 %) discontinued AI therapy because of toxicity. Using a recessive statistical model, an intronic variant in ESR1 (rs9322336) was associated with increased risk of musculoskeletal toxicity-related exemestane discontinuation [HR 5.0 (95 % CI 2.1-11.8), p < 0.0002]. An inherited variant potentially affecting estrogen signaling may be associated with exemestane-associated toxicity, which could partially account for intra-patient differences in AI tolerability. Validation of this finding is required

    Burden of Risk Alleles for Hypertension Increases Risk of Intracerebral Hemorrhage

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    Background and Purpose-Genetic variation influences risk of intracerebral hemorrhage (ICH). Hypertension (HTN) is a potent risk factor for ICH and several common genetic variants (single nucleotide polymorphisms [SNPs]) associated with blood pressure levels have been identified. We sought to determine whether the cumulative burden of blood pressure-related SNPs is associated with risk of ICH and pre-ICH diagnosis of HTN. Methods-We conducted a prospective multicenter case-control study in 2272 subjects of European ancestry (1025 cases and 1247 control subjects). Thirty-nine SNPs reported to be associated with blood pressure levels were identified from the National Human Genome Research Institute genomewide association study catalog. Single-SNP association analyses were performed for the outcomes ICH and pre-ICH HTN. Subsequently, weighted and unweighted genetic risk scores were constructed using these SNPs and entered as the independent variable in logistic regression models with ICH and pre-ICH HTN as the dependent variables. Results-No single SNP was associated with either ICH or pre-ICH HTN. The blood pressure-based unweighted genetic risk score was associated with risk of ICH (OR, 1.11; 95% CI, 1.02-1.21; P=0.01) and the subset of ICH in deep regions (OR, 1.18; 95% CI, 1.07-1.30; P=0.001), but not with the subset of lobar ICH. The score was associated with a history of HTN among control subjects (OR, 1.17; 95% CI, 1.04-1.31; P=0.009) and ICH cases (OR, 1.15; 95% CI, 1.01-1.31; P=0.04). Similar results were obtained when using a weighted score. Conclusion-Increasing numbers of high blood pressure-related alleles are associated with increased risk of deep ICH as well as with clinically identified HTN. (Stroke. 2012; 43: 2877-2883.

    Evidence that Adaptation in Drosophila Is Not Limited by Mutation at Single Sites

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    Adaptation in eukaryotes is generally assumed to be mutation-limited because of small effective population sizes. This view is difficult to reconcile, however, with the observation that adaptation to anthropogenic changes, such as the introduction of pesticides, can occur very rapidly. Here we investigate adaptation at a key insecticide resistance locus (Ace) in Drosophila melanogaster and show that multiple simple and complex resistance alleles evolved quickly and repeatedly within individual populations. Our results imply that the current effective population size of modern D. melanogaster populations is likely to be substantially larger (≥100-fold) than commonly believed. This discrepancy arises because estimates of the effective population size are generally derived from levels of standing variation and thus reveal long-term population dynamics dominated by sharp—even if infrequent—bottlenecks. The short-term effective population sizes relevant for strong adaptation, on the other hand, might be much closer to census population sizes. Adaptation in Drosophila may therefore not be limited by waiting for mutations at single sites, and complex adaptive alleles can be generated quickly without fixation of intermediate states. Adaptive events should also commonly involve the simultaneous rise in frequency of independently generated adaptive mutations. These so-called soft sweeps have very distinct effects on the linked neutral polymorphisms compared to the standard hard sweeps in mutation-limited scenarios. Methods for the mapping of adaptive mutations or association mapping of evolutionarily relevant mutations may thus need to be reconsidered

    Environmental Predictors of Diversity in Recent Planktonic Foraminifera as Recorded in Marine Sediments

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    © 2016 Fenton et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. [4.0 license]. The attached file is the published version of the article

    European research priorities for intracerebral haemorrhage

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    Over 2 million people are affected by intracerebral haemorrhage (ICH) worldwide every year, one third of them dying within 1 month, and many survivors being left with permanent disability. Unlike most other stroke types, the incidence, morbidity and mortality of ICH have not declined over time. No standardised diagnostic workup for the detection of the various underlying causes of ICH currently exists, and the evidence for medical or surgical therapeutic interventions remains limited. A dedicated European research programme for ICH is needed to identify ways to reduce the burden of ICH-related death and disability. The European Research Network on Intracerebral Haemorrhage EURONICH is a multidisciplinary academic research collaboration that has been established to define current research priorities and to conduct large clinical studies on all aspects of ICH. Copyright (C) 2011 S. Karger AG, Base

    Genetic Variants in CETP Increase Risk of Intracerebral Hemorrhage

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    OBJECTIVE: In observational epidemiologic studies, higher plasma high-density lipoprotein cholesterol (HDL-C) has been associated with increased risk of intracerebral hemorrhage (ICH). DNA sequence variants that decrease cholesteryl ester transfer protein (CETP) gene activity increase plasma HDL-C; as such, medicines that inhibit CETP and raise HDL-C are in clinical development. Here, we test the hypothesis that CETP DNA sequence variants associated with higher HDL-C also increase risk for ICH.METHODS: We performed 2 candidate-gene analyses of CETP. First, we tested individual CETP variants in a discovery cohort of 1,149 ICH cases and 1,238 controls from 3 studies, followed by replication in 1,625 cases and 1,845 controls from 5 studies. Second, we constructed a genetic risk score comprised of 7 independent variants at the CETP locus and tested this score for association with HDL-C as well as ICH risk.RESULTS: Twelve variants within CETP demonstrated nominal association with ICH, with the strongest association at the rs173539 locus (odds ratio [OR] = 1.25, standard error [SE] = 0.06, p = 6.0 × 10(-4) ) with no heterogeneity across studies (I(2) = 0%). This association was replicated in patients of European ancestry (p = 0.03). A genetic score of CETP variants found to increase HDL-C by ∼2.85mg/dl in the Global Lipids Genetics Consortium was strongly associated with ICH risk (OR = 1.86, SE = 0.13, p = 1.39 × 10(-6) ).INTERPRETATION: Genetic variants in CETP associated with increased HDL-C raise the risk of ICH. Given ongoing therapeutic development in CETP inhibition and other HDL-raising strategies, further exploration of potential adverse cerebrovascular outcomes may be warranted. Ann Neurol 2016;80:730-740

    Deep learning-based detection and segmentation of diffusion abnormalities in acute ischemic stroke

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    Background: Accessible tools to efficiently detect and segment diffusion abnormalities in acute strokes are highly anticipated by the clinical and research communities. Methods: We developed a tool with deep learning networks trained and tested on a large dataset of 2,348 clinical diffusion weighted MRIs of patients with acute and sub-acute ischemic strokes, and further tested for generalization on 280 MRIs of an external dataset (STIR). Results: Our proposed model outperforms generic networks and DeepMedic, particularly in small lesions, with lower false positive rate, balanced precision and sensitivity, and robustness to data perturbs (e.g., artefacts, low resolution, technical heterogeneity). The agreement with human delineation rivals the inter-evaluator agreement; the automated lesion quantification of volume and contrast has virtually total agreement with human quantification. Conclusion: Our tool is fast, public, accessible to non-experts, with minimal computational requirements, to detect and segment lesions via a single command line. Therefore, it fulfills the conditions to perform large scale, reliable and reproducible clinical and translational research
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