438 research outputs found

    Genetic risk factors for ischaemic stroke and its subtypes (the METASTROKE Collaboration): a meta-analysis of genome-wide association studies

    Get PDF
    <p>Background - Various genome-wide association studies (GWAS) have been done in ischaemic stroke, identifying a few loci associated with the disease, but sample sizes have been 3500 cases or less. We established the METASTROKE collaboration with the aim of validating associations from previous GWAS and identifying novel genetic associations through meta-analysis of GWAS datasets for ischaemic stroke and its subtypes.</p> <p>Methods - We meta-analysed data from 15 ischaemic stroke cohorts with a total of 12 389 individuals with ischaemic stroke and 62 004 controls, all of European ancestry. For the associations reaching genome-wide significance in METASTROKE, we did a further analysis, conditioning on the lead single nucleotide polymorphism in every associated region. Replication of novel suggestive signals was done in 13 347 cases and 29 083 controls.</p> <p>Findings - We verified previous associations for cardioembolic stroke near PITX2 (p=2·8×10−16) and ZFHX3 (p=2·28×10−8), and for large-vessel stroke at a 9p21 locus (p=3·32×10−5) and HDAC9 (p=2·03×10−12). Additionally, we verified that all associations were subtype specific. Conditional analysis in the three regions for which the associations reached genome-wide significance (PITX2, ZFHX3, and HDAC9) indicated that all the signal in each region could be attributed to one risk haplotype. We also identified 12 potentially novel loci at p<5×10−6. However, we were unable to replicate any of these novel associations in the replication cohort.</p> <p>Interpretation - Our results show that, although genetic variants can be detected in patients with ischaemic stroke when compared with controls, all associations we were able to confirm are specific to a stroke subtype. This finding has two implications. First, to maximise success of genetic studies in ischaemic stroke, detailed stroke subtyping is required. Second, different genetic pathophysiological mechanisms seem to be associated with different stroke subtypes.</p&gt

    Plasmin Generation Potential and Recanalization in Acute Ischaemic Stroke; an Observational Cohort Study of Stroke Biobank Samples.

    Full text link
    Rationale: More than half of patients who receive thrombolysis for acute ischaemic stroke fail to recanalize. Elucidating biological factors which predict recanalization could identify therapeutic targets for increasing thrombolysis success. Hypothesis: We hypothesize that individual patient plasmin potential, as measured by in vitro response to recombinant tissue-type plasminogen activator (rt-PA), is a biomarker of rt-PA response, and that patients with greater plasmin response are more likely to recanalize early. Methods: This study will use historical samples from the Barcelona Stroke Thrombolysis Biobank, comprised of 350 pre-thrombolysis plasma samples from ischaemic stroke patients who received serial transcranial-Doppler (TCD) measurements before and after thrombolysis. The plasmin potential of each patient will be measured using the level of plasmin-antiplasmin complex (PAP) generated after in-vitro addition of rt-PA. Levels of antiplasmin, plasminogen, t-PA activity, and PAI-1 activity will also be determined. Association between plasmin potential variables and time to recanalization [assessed on serial TCD using the thrombolysis in brain ischemia (TIBI) score] will be assessed using Cox proportional hazards models, adjusted for potential confounders. Outcomes: The primary outcome will be time to recanalization detected by TCD (defined as TIBI ≥4). Secondary outcomes will be recanalization within 6-h and recanalization and/or haemorrhagic transformation at 24-h. This analysis will utilize an expanded cohort including ~120 patients from the Targeting Optimal Thrombolysis Outcomes (TOTO) study. Discussion: If association between proteolytic response to rt-PA and recanalization is confirmed, future clinical treatment may customize thrombolytic therapy to maximize outcomes and minimize adverse effects for individual patients

    Chlorine Dioxide Is a Size-Selective Antimicrobial Agent

    Get PDF
    Background / Aims: ClO2, the so-called "ideal biocide", could also be applied as an antiseptic if it was understood why the solution killing microbes rapidly does not cause any harm to humans or to animals. Our aim was to find the source of that selectivity by studying its reaction-diffusion mechanism both theoretically and experimentally. Methods: ClO2 permeation measurements through protein membranes were performed and the time delay of ClO2 transport due to reaction and diffusion was determined. To calculate ClO2 penetration depths and estimate bacterial killing times, approximate solutions of the reaction-diffusion equation were derived. In these calculations evaporation rates of ClO2 were also measured and taken into account. Results: The rate law of the reaction-diffusion model predicts that the killing time is proportional to the square of the characteristic size (e. g. diameter) of a body, thus, small ones will be killed extremely fast. For example, the killing time for a bacterium is on the order of milliseconds in a 300 ppm ClO2 solution. Thus, a few minutes of contact time (limited by the volatility of ClO2) is quite enough to kill all bacteria, but short enough to keep ClO2 penetration into the living tissues of a greater organism safely below 0.1 mm, minimizing cytotoxic effects when applying it as an antiseptic. Additional properties of ClO2, advantageous for an antiseptic, are also discussed. Most importantly, that bacteria are not able to develop resistance against ClO2 as it reacts with biological thiols which play a vital role in all living organisms. Conclusion: Selectivity of ClO2 between humans and bacteria is based not on their different biochemistry, but on their different size. We hope initiating clinical applications of this promising local antiseptic

    Genome-wide association meta-analysis of functional outcome after ischemic stroke

    Get PDF
    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.Peer reviewe

    An experimental study of the intrinsic stability of random forest variable importance measures

    Get PDF
    BACKGROUND: The stability of Variable Importance Measures (VIMs) based on random forest has recently received increased attention. Despite the extensive attention on traditional stability of data perturbations or parameter variations, few studies include influences coming from the intrinsic randomness in generating VIMs, i.e. bagging, randomization and permutation. To address these influences, in this paper we introduce a new concept of intrinsic stability of VIMs, which is defined as the self-consistence among feature rankings in repeated runs of VIMs without data perturbations and parameter variations. Two widely used VIMs, i.e., Mean Decrease Accuracy (MDA) and Mean Decrease Gini (MDG) are comprehensively investigated. The motivation of this study is two-fold. First, we empirically verify the prevalence of intrinsic stability of VIMs over many real-world datasets to highlight that the instability of VIMs does not originate exclusively from data perturbations or parameter variations, but also stems from the intrinsic randomness of VIMs. Second, through Spearman and Pearson tests we comprehensively investigate how different factors influence the intrinsic stability. RESULTS: The experiments are carried out on 19 benchmark datasets with diverse characteristics, including 10 high-dimensional and small-sample gene expression datasets. Experimental results demonstrate the prevalence of intrinsic stability of VIMs. Spearman and Pearson tests on the correlations between intrinsic stability and different factors show that #feature (number of features) and #sample (size of sample) have a coupling effect on the intrinsic stability. The synthetic indictor, #feature/#sample, shows both negative monotonic correlation and negative linear correlation with the intrinsic stability, while OOB accuracy has monotonic correlations with intrinsic stability. This indicates that high-dimensional, small-sample and high complexity datasets may suffer more from intrinsic instability of VIMs. Furthermore, with respect to parameter settings of random forest, a large number of trees is preferred. No significant correlations can be seen between intrinsic stability and other factors. Finally, the magnitude of intrinsic stability is always smaller than that of traditional stability. CONCLUSION: First, the prevalence of intrinsic stability of VIMs demonstrates that the instability of VIMs not only comes from data perturbations or parameter variations, but also stems from the intrinsic randomness of VIMs. This finding gives a better understanding of VIM stability, and may help reduce the instability of VIMs. Second, by investigating the potential factors of intrinsic stability, users would be more aware of the risks and hence more careful when using VIMs, especially on high-dimensional, small-sample and high complexity datasets

    Elucidating the mechanism of ferrocytochrome c heme disruption by peroxidized cardiolipin

    Get PDF
    The interaction of peroxidized cardiolipin with ferrocytochrome c induces two kinetically and chemically distinct processes. The first is a rapid oxidation of ferrocytochrome c, followed by a slower, irreversible disruption of heme c. The oxidation of ferrocytochrome c by peroxidized cardiolipin is explained by a Fenton-type reaction. Heme scission is a consequence of the radical-mediated reactions initiated by the interaction of ferric heme iron with peroxidized cardiolipin. Simultaneously with the heme c disruption, generation of hydroxyl radical is detected by EPR spectroscopy using the spin trapping technique. The resulting apocytochrome c sediments as a heterogeneous mixture of high aggregates, as judged by sedimentation analysis. Both the oxidative process and the destructive process were suppressed by nonionic detergents and/or high ionic strength. The mechanism for generating radicals and heme rupture is presented

    Modelling the Role of the Hsp70/Hsp90 System in the Maintenance of Protein Homeostasis

    Get PDF
    Neurodegeneration is an age-related disorder which is characterised by the accumulation of aggregated protein and neuronal cell death. There are many different neurodegenerative diseases which are classified according to the specific proteins involved and the regions of the brain which are affected. Despite individual differences, there are common mechanisms at the sub-cellular level leading to loss of protein homeostasis. The two central systems in protein homeostasis are the chaperone system, which promotes correct protein folding, and the cellular proteolytic system, which degrades misfolded or damaged proteins. Since these systems and their interactions are very complex, we use mathematical modelling to aid understanding of the processes involved. The model developed in this study focuses on the role of Hsp70 (IPR00103) and Hsp90 (IPR001404) chaperones in preventing both protein aggregation and cell death. Simulations were performed under three different conditions: no stress; transient stress due to an increase in reactive oxygen species; and high stress due to sustained increases in reactive oxygen species. The model predicts that protein homeostasis can be maintained during short periods of stress. However, under long periods of stress, the chaperone system becomes overwhelmed and the probability of cell death pathways being activated increases. Simulations were also run in which cell death mediated by the JNK (P45983) and p38 (Q16539) pathways was inhibited. The model predicts that inhibiting either or both of these pathways may delay cell death but does not stop the aggregation process and that eventually cells die due to aggregated protein inhibiting proteasomal function. This problem can be overcome if the sequestration of aggregated protein into inclusion bodies is enhanced. This model predicts responses to reactive oxygen species-mediated stress that are consistent with currently available experimental data. The model can be used to assess specific interventions to reduce cell death due to impaired protein homeostasis
    corecore