Preclinical Aortic Atherosclerosis in Adolescents With Chronic Disease.

Background Adolescents with chronic disease are often exposed to inflammatory, metabolic, and hemodynamic risk factors for early atherosclerosis. Since postmortem studies have shown that atherogenesis starts in the aorta, the CDACD (Cardiovascular Disease in Adolescents with Chronic Disease) study investigated preclinical aortic atherosclerosis in these adolescents. Methods and Results The cross-sectional CDACD study enrolled 114 adolescents 12 to 18 years old with chronic disorders including juvenile idiopathic arthritis, cystic fibrosis, obesity, corrected coarctation of the aorta, and healthy controls with a corrected atrial septal defect. Cardiovascular magnetic resonance was used to assess aortic pulse wave velocity and aortic wall thickness, as established aortic measures of preclinical atherosclerosis. Cardiovascular magnetic resonance showed a higher aortic pulse wave velocity, which reflects aortic stiffness, and higher aortic wall thickness in all adolescent chronic disease groups, compared with controls (P<0.05). Age (ß=0.253), heart rate (ß=0.236), systolic blood pressure (ß=-0.264), and diastolic blood pressure (ß=0.365) were identified as significant predictors for aortic pulse wave velocity, using multivariable linear regression analysis. Aortic wall thickness was predicted by body mass index (ß=0.248) and fasting glucose (ß=0.242), next to aortic lumen area (ß=0.340). Carotid intima-media thickness was assessed using ultrasonography, and was only higher in adolescents with coarctation of the aorta, compared with controls (P<0.001). Conclusions Adolescents with chronic disease showed enhanced aortic stiffness and wall thickness compared with controls. The enhanced aortic pulse wave velocity and aortic wall thickness in adolescents with chronic disease could indicate accelerated atherogenesis. Our findings underscore the importance of the aorta for assessment of early atherosclerosis, and the need for tailored cardiovascular follow-up of children with chronic disease.

Application of Deep Neural Network Models in Drug Discovery Programs.

In silico driven optimization of compound properties related to pharmacokinetics, pharmacodynamics, and safety is a key requirement in modern drug discovery. Nowadays, large and harmonized datasets allow to implement deep neural networks (DNNs) as a framework for leveraging predictive models. Nevertheless, various available model architectures differ in their global applicability and performance in lead optimization projects, such as stability over time and interpretability of the results. Here, we describe and compare the value of established DNN-based methods for the prediction of key ADME property trends and biological activity in an industrial drug discovery environment, represented by microsomal lability, CYP3A4 inhibition and factor Xa inhibition. Three architectures are exemplified, our earlier described multilayer perceptron approach (MLP), graph convolutional network-based models (GCN) and a vector representation approach, Mol2Vec. From a statistical perspective, MLP and GCN were found to perform superior over Mol2Vec, when applied to external validation sets. Interestingly, GCN-based predictions are most stable over a longer period in a time series validation study. Apart from those statistical observations, DNN prove of value to guide local SAR. To illustrate this important aspect in pharmaceutical research projects, we discuss challenging applications in medicinal chemistry towards a more realistic picture of artificial intelligence in drug discovery.

Low-Density Lipoprotein Cholesterol Target Attainment in Patients With Established Cardiovascular Disease: Analysis of Routine Care Data.

BACKGROUND: Direct feedback on quality of care is one of the key features of a learning health care system (LHS), enabling health care professionals to improve upon the routine clinical care of their patients during practice. OBJECTIVE: This study aimed to evaluate the potential of routine care data extracted from electronic health records (EHRs) in order to obtain reliable information on low-density lipoprotein cholesterol (LDL-c) management in cardiovascular disease (CVD) patients referred to a tertiary care center. METHODS: We extracted all LDL-c measurements from the EHRs of patients with a history of CVD referred to the University Medical Center Utrecht. We assessed LDL-c target attainment at the time of referral and per year. In patients with multiple measurements, we analyzed LDL-c trajectories, truncated at 6 follow-up measurements. Lastly, we performed a logistic regression analysis to investigate factors associated with improvement of LDL-c at the next measurement. RESULTS: Between February 2003 and December 2017, 250,749 LDL-c measurements were taken from 95,795 patients, of whom 23,932 had a history of CVD. At the time of referral, 51% of patients had not reached their LDL-c target. A large proportion of patients (55%) had no follow-up LDL-c measurements. Most of the patients with repeated measurements showed no change in LDL-c levels over time: the transition probability to remain in the same category was up to 0.84. Sequence clustering analysis showed more women (odds ratio 1.18, 95% CI 1.07-1.10) in the cluster with both most measurements off target and the most LDL-c measurements furthest from the target. Timing of drug prescription was difficult to determine from our data, limiting the interpretation of results regarding medication management. CONCLUSIONS: Routine care data can be used to provide feedback on quality of care, such as LDL-c target attainment. These routine care data show high off-target prevalence and little change in LDL-c over time. Registrations of diagnosis; follow-up trajectory, including primary and secondary care; and medication use need to be improved in order to enhance usability of the EHR system for adequate feedback.

Model selection for metabolomics: predicting diagnosis of coronary artery disease using automated machine learning.

MOTIVATION: Selecting the optimal machine learning (ML) model for a given dataset is often challenging. Automated ML (AutoML) has emerged as a powerful tool for enabling the automatic selection of ML methods and parameter settings for the prediction of biomedical endpoints. Here, we apply the tree-based pipeline optimization tool (TPOT) to predict angiographic diagnoses of coronary artery disease (CAD). With TPOT, ML models are represented as expression trees and optimal pipelines discovered using a stochastic search method called genetic programing. We provide some guidelines for TPOT-based ML pipeline selection and optimization-based on various clinical phenotypes and high-throughput metabolic profiles in the Angiography and Genes Study (ANGES). RESULTS: We analyzed nuclear magnetic resonance-derived lipoprotein and metabolite profiles in the ANGES cohort with a goal to identify the role of non-obstructive CAD patients in CAD diagnostics. We performed a comparative analysis of TPOT-generated ML pipelines with selected ML classifiers, optimized with a grid search approach, applied to two phenotypic CAD profiles. As a result, TPOT-generated ML pipelines that outperformed grid search optimized models across multiple performance metrics including balanced accuracy and area under the precision-recall curve. With the selected models, we demonstrated that the phenotypic profile that distinguishes non-obstructive CAD patients from no CAD patients is associated with higher precision, suggesting a discrepancy in the underlying processes between these phenotypes. AVAILABILITY AND IMPLEMENTATION: TPOT is freely available via http://epistasislab.github.io/tpot/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Association of Chromosome 9p21 With Subsequent Coronary Heart Disease Events.

BACKGROUND: Genetic variation at chromosome 9p21 is a recognized risk factor for coronary heart disease (CHD). However, its effect on disease progression and subsequent events is unclear, raising questions about its value for stratification of residual risk. METHODS: A variant at chromosome 9p21 (rs1333049) was tested for association with subsequent events during follow-up in 103 357 Europeans with established CHD at baseline from the GENIUS-CHD (Genetics of Subsequent Coronary Heart Disease) Consortium (73.1% male, mean age 62.9 years). The primary outcome, subsequent CHD death or myocardial infarction (CHD death/myocardial infarction), occurred in 13 040 of the 93 115 participants with available outcome data. Effect estimates were compared with case/control risk obtained from the CARDIoGRAMplusC4D consortium (Coronary Artery Disease Genome-wide Replication and Meta-analysis [CARDIoGRAM] plus The Coronary Artery Disease [C4D] Genetics) including 47 222 CHD cases and 122 264 controls free of CHD. RESULTS: Meta-analyses revealed no significant association between chromosome 9p21 and the primary outcome of CHD death/myocardial infarction among those with established CHD at baseline (GENIUS-CHD odds ratio, 1.02; 95% CI, 0.99-1.05). This contrasted with a strong association in CARDIoGRAMPlusC4D odds ratio 1.20; 95% CI, 1.18-1.22; P for interaction <0.001 compared with the GENIUS-CHD estimate. Similarly, no clear associations were identified for additional subsequent outcomes, including all-cause death, although we found a modest positive association between chromosome 9p21 and subsequent revascularization (odds ratio, 1.07; 95% CI, 1.04-1.09). CONCLUSIONS: In contrast to studies comparing individuals with CHD to disease-free controls, we found no clear association between genetic variation at chromosome 9p21 and risk of subsequent acute CHD events when all individuals had CHD at baseline. However, the association with subsequent revascularization may support the postulated mechanism of chromosome 9p21 for promoting atheroma development.

Subsequent Event Risk in Individuals With Established Coronary Heart Disease.

BACKGROUND: The Genetics of Subsequent Coronary Heart Disease (GENIUS-CHD) consortium was established to facilitate discovery and validation of genetic variants and biomarkers for risk of subsequent CHD events, in individuals with established CHD. METHODS: The consortium currently includes 57 studies from 18 countries, recruiting 185 614 participants with either acute coronary syndrome, stable CHD, or a mixture of both at baseline. All studies collected biological samples and followed-up study participants prospectively for subsequent events. RESULTS: Enrollment into the individual studies took place between 1985 to present day with a duration of follow-up ranging from 9 months to 15 years. Within each study, participants with CHD are predominantly of self-reported European descent (38%-100%), mostly male (44%-91%) with mean ages at recruitment ranging from 40 to 75 years. Initial feasibility analyses, using a federated analysis approach, yielded expected associations between age (hazard ratio, 1.15; 95% CI, 1.14-1.16) per 5-year increase, male sex (hazard ratio, 1.17; 95% CI, 1.13-1.21) and smoking (hazard ratio, 1.43; 95% CI, 1.35-1.51) with risk of subsequent CHD death or myocardial infarction and differing associations with other individual and composite cardiovascular endpoints. CONCLUSIONS: GENIUS-CHD is a global collaboration seeking to elucidate genetic and nongenetic determinants of subsequent event risk in individuals with established CHD, to improve residual risk prediction and identify novel drug targets for secondary prevention. Initial analyses demonstrate the feasibility and reliability of a federated analysis approach. The consortium now plans to initiate and test novel hypotheses as well as supporting replication and validation analyses for other investigators.

Association of the coronary artery disease risk gene GUCY1A3 with ischaemic events after coronary intervention.

AIM: A common genetic variant at the GUCY1A3 coronary artery disease locus has been shown to influence platelet aggregation. The risk of ischaemic events including stent thrombosis varies with the efficacy of aspirin to inhibit platelet reactivity. This study sought to investigate whether homozygous GUCY1A3 (rs7692387) risk allele carriers display higher on-aspirin platelet reactivity and risk of ischaemic events early after coronary intervention. METHODS AND RESULTS: The association of GUCY1A3 genotype and on-aspirin platelet reactivity was analysed in the genetics substudy of the ISAR-ASPI registry (n = 1678) using impedance aggregometry. The clinical outcome cardiovascular death or stent thrombosis within 30 days after stenting was investigated in a meta-analysis of substudies of the ISAR-ASPI registry, the PLATO trial (n = 3236), and the Utrecht Coronary Biobank (n = 1003) comprising a total 5917 patients. Homozygous GUCY1A3 risk allele carriers (GG) displayed increased on-aspirin platelet reactivity compared with non-risk allele (AA/AG) carriers [150 (interquartile range 91-209) vs. 134 (85-194) AU⋅min, P < 0.01]. More homozygous risk allele carriers, compared with non-risk allele carriers, were assigned to the high-risk group for ischaemic events (>203 AU⋅min; 29.5 vs. 24.2%, P = 0.02). Homozygous risk allele carriers were also at higher risk for cardiovascular death or stent thrombosis (hazard ratio 1.70, 95% confidence interval 1.08-2.68; P = 0.02). Bleeding risk was not altered. CONCLUSION: We conclude that homozygous GUCY1A3 risk allele carriers are at increased risk of cardiovascular death or stent thrombosis within 30 days after coronary stenting, likely due to higher on-aspirin platelet reactivity. Whether GUCY1A3 genotype helps to tailor antiplatelet treatment remains to be investigated.

Routinely measured hematological parameters and prediction of recurrent vascular events in patients with clinically manifest vascular disease.

BACKGROUND AND AIMS: The predictive value of traditional risk factors for vascular events in patients with manifest vascular disease is limited, underscoring the need for novel biomarkers to improve risk stratification. Since hematological parameters are routinely assessed in clinical practice, they are readily available candidates. METHODS: We used data from 3,922 vascular patients, who participated in the Second Manifestations of ARTerial Disease (SMART) study. We first investigated associations between recurrent vascular events and 22 hematological parameters, obtained from the Utrecht Patient Oriented Database (UPOD), and then assessed whether parameters associated with outcome improved risk prediction. RESULTS: After adjustment for all SMART risk score (SRS) variables, lymphocyte %, neutrophil count, neutrophil % and red cell distribution width (RDW) were significantly associated with vascular events. When individually added to the SRS, lymphocyte % improved prediction of recurrent vascular events with a continuous net reclassification improvement (cNRI) of 17.4% [95% CI: 2.1, 32.1%] and an increase in c-statistic of 0.011 [0.000, 0.022]. The combination of lymphocyte % and neutrophil count resulted in a cNRI of 22.2% [3.2, 33.4%] and improved c-statistic by 0.011 [95% CI: 0.000, 0.022]. Lymphocyte % and RDW yielded a cNRI of 18.7% [3.3, 31.9%] and improved c-statistic by 0.016 [0.004, 0.028]. However, the addition of hematological parameters only modestly increased risk estimates for patients with an event during follow-up. CONCLUSIONS: Several hematological parameters were independently associated with recurrent vascular events. Lymphocyte % alone and in combination with other parameters enhanced discrimination and reclassification. However, the incremental value for patients with a recurrent event was limited.

Comprehensive pathway analyses of schizophrenia risk loci point to dysfunctional postsynaptic signaling.

Large-scale genome-wide association studies (GWAS) have implicated many low-penetrance loci in schizophrenia. However, its pathological mechanisms are poorly understood, which in turn hampers the development of novel pharmacological treatments. Pathway and gene set analyses carry the potential to generate hypotheses about disease mechanisms and have provided biological context to genome-wide data of schizophrenia. We aimed to examine which biological processes are likely candidates to underlie schizophrenia by integrating novel and powerful pathway analysis tools using data from the largest Psychiatric Genomics Consortium schizophrenia GWAS (N=79,845) and the most recent 2018 schizophrenia GWAS (N=105,318). By applying a primary unbiased analysis (Multi-marker Analysis of GenoMic Annotation; MAGMA) to weigh the role of biological processes from the Molecular Signatures Database (MSigDB), we identified enrichment of common variants in synaptic plasticity and neuron differentiation gene sets. We supported these findings using MAGMA, Meta-Analysis Gene-set Enrichment of variaNT Associations (MAGENTA) and Interval Enrichment Analysis (INRICH) on detailed synaptic signaling pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG) and found enrichment in mainly the dopaminergic and cholinergic synapses. Moreover, shared genes involved in these neurotransmitter systems had a large contribution to the observed enrichment, protein products of top genes in these pathways showed more direct and indirect interactions than expected by chance, and expression profiles of these genes were largely similar among brain tissues. In conclusion, we provide strong and consistent genetics and protein-interaction informed evidence for the role of postsynaptic signaling processes in schizophrenia, opening avenues for future translational and psychopharmacological studies.

Statin Effects on Metabolic Profiles: Data From the PREVEND IT (Prevention of Renal and Vascular End-stage Disease Intervention Trial).

BACKGROUND: Statins lower cholesterol by inhibiting HMG-CoA reductase, the rate-limiting enzyme of the metabolic pathway that produces cholesterol and other isoprenoids. Little is known about their effects on metabolite and lipoprotein subclass profiles. We, therefore, investigated the molecular changes associated with pravastatin treatment compared with placebo administration using a nuclear magnetic resonance-based metabolomics platform. METHODS AND RESULTS: We performed metabolic profiling of 231 lipoprotein and metabolite measures in the PREVEND IT (Prevention of Renal and Vascular End-stage Disease Intervention Trial) study, a placebo-controlled randomized clinical trial designed to test the effects of pravastatin (40 mg once daily) on cardiovascular risk. Metabolic profiles were assessed at baseline and after 3 months of treatment. Pravastatin lowered low-density lipoprotein cholesterol (change in SD units [95% confidence interval]: -1.01 [-1.14, -0.88]), remnant cholesterol (change in SD units [95% confidence interval]: -1.03 [-1.17, -0.89]), and apolipoprotein B (change in SD units [95% confidence interval]: -0.98 [-1.11, -0.86]) with similar effect magnitudes. In addition, pravastatin globally lowered levels of lipoprotein subclasses, with the exception of high-density lipoprotein subclasses, which displayed a more heterogeneous response pattern. The lipid-lowering effect of pravastatin was accompanied by selective changes in lipid composition, particularly in the cholesterol content of very-low-density lipoproteinparticles. In addition, pravastatin reduced levels of several fatty acids but had limited effects on fatty acid ratios. CONCLUSIONS: These randomized clinical trial data demonstrate the widespread effects of pravastatin treatment on lipoprotein subclass profiles and fatty acids. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT03073018.

Loss of Y Chromosome in Blood Is Associated With Major Cardiovascular Events During Follow-Up in Men After Carotid Endarterectomy.

BACKGROUND: Recent studies found an immune regulatory role for Y chromosome and a relationship between loss of Y chromosome (LOY) in blood cells and a higher risk of cancer and mortality. Given involvement of immune cells in atherosclerosis, we hypothesized that LOY is associated with the severity of atherosclerotic plaque characteristics and outcome in men undergoing carotid endarterectomy. METHODS AND RESULTS: LOY was quantified in blood and plaque from raw intensity genotyping data in men within the Athero-Express biobank study. Plaques were dissected, and the culprit lesions used for histology and the measurement of inflammatory proteins. We tested LOY for association with (inflammatory) atherosclerotic plaque phenotypes and cytokines and assessed the association of LOY with secondary events during 3-year follow-up. Of 366 patients with carotid endarterectomy, 61 exhibited some degree of LOY in blood. LOY was also present in atherosclerotic plaque lesions (n=8/242, 3%). LOY in blood was negatively associated with age (ß=-0.03/10 y; r2=0.07; P=1.6×10-7) but not with cardiovascular disease severity at baseline. LOY in blood was associated with a larger atheroma size (odds ratio, 2.15; 95% confidence interval, 1.06-4.76; P=0.04); however, this association was not significant after correction for multiple testing. LOY was independently associated with secondary major cardiovascular events (hazard ratio=2.28; 95% confidence interval, 1.11-4.67; P=0.02) in blood when corrected for confounders. CONCLUSIONS: In this hypothesis-generating study, LOY in blood is independently associated with secondary major cardiovascular events in a severely atherosclerotic population. Our data could indicate that LOY affects secondary outcome via other mechanisms than inflammation in the atherosclerotic plaque.

Generic atorvastatin is as effective as the brand-name drug (LIPITOR®) in lowering cholesterol levels: a cross-sectional retrospective cohort study.

BACKGROUND: In a world of ever increasing health care costs, generic drugs represent a major opportunity to ensure access to essential medicines for people who otherwise would be unable to afford them. However, some clinicians and patients are still questioning the safety and effectiveness of generic formulations compared to the proprietary drugs necessitating further systematic research analyzing the generic drugs' efficacy. Our objective was to compare the lipid lowering effects of generic and branded atorvastatin. METHODS: This cross-sectional, retrospective cohort study was conducted at the University of Malaya Medical Centre from 1 May 2013 until 30 May 2013. We analyzed the lipid profiles (total cholesterol, LDL-cholesterol, HDL-cholesterol, triglycerides) of 629 patients before and at least 3 months after switching them from proprietary atorvastatin (Lipitor®) to generic atorvastatin (atorvastatin calcium from Ranbaxy Laboratories, Inc.). We also investigated if there was any difference in the effectiveness of both atorvastatin formulations in various ethnic groups. RESULTS: 266 patients were included in this study. When comparing the median values we found no statistically significant differences (Wilcoxon signed-rank test; p < 0.05) between proprietary and generic atorvastatin in lowering total cholesterol (4.60 mmol/l pre-transition vs. 4.50 mmol/l post-transition; p = 0.583), LDL-cholesterol (2.42 mmol/l vs. 2.41 mmol/l; p = 0.923) and triglycerides (1.50 mmol/l vs. 1.50 mmol/l; p = 0.513). While there was a statistically significant (p = 0.009) difference in HDL-cholesterol levels favouring proprietary atorvastatin, the extent of this change (1.26 mmol/l vs. 1.25 mmol/l) was deemed not to be clinically relevant. There was no statistically significant difference when analyzing the effects on various ethnic groups. CONCLUSIONS: Substituting proprietary atorvastatin for its generic formulation atorvastatin calcium does not result in a less effective management of hyperlipidemia. Our findings lend support to the approach of lowering health care costs by switching patients from branded drugs to their less expensive generic analogues.

Additional Candidate Genes for Human Atherosclerotic Disease Identified Through Annotation Based on Chromatin Organization.

BACKGROUND: As genome-wide association efforts, such as CARDIoGRAM and METASTROKE, are ongoing to reveal susceptibility loci for their underlying disease-atherosclerotic disease-identification of candidate genes explaining the associations of these loci has proven the main challenge. Many disease susceptibility loci colocalize with DNA regulatory elements, which influence gene expression through chromatin interactions. Therefore, the target genes of these regulatory elements can be considered candidate genes. Applying these biological principles, we used an alternative approach to annotate susceptibility loci and identify candidate genes for human atherosclerotic disease based on circular chromosome conformation capture followed by sequencing. METHODS AND RESULTS: In human monocytes and coronary endothelial cells, we generated 63 chromatin interaction data sets for 37 active DNA regulatory elements that colocalize with known susceptibility loci for coronary artery disease (CARDIoGRAMplusC4D) and large artery stroke (METASTROKE). By circular chromosome conformation capture followed by sequencing, we identified a physical 3-dimensional interaction with 326 candidate genes expressed in at least 1 of these cell types, of which 294 have not been reported before. We highlight 16 genes based on expression quantitative trait loci. CONCLUSIONS: Our findings provide additional candidate-gene annotation for 37 disease susceptibility loci for human atherosclerotic disease that are of potential interest to better understand the complex pathophysiology of cardiovascular diseases.

Effect of Metformin on Metabolites and Relation With Myocardial Infarct Size and Left Ventricular Ejection Fraction After Myocardial Infarction.

BACKGROUND: Left ventricular ejection fraction (LVEF) and infarct size (ISZ) are key predictors of long-term survival after myocardial infarction (MI). However, little is known about the biochemical pathways driving LV dysfunction after MI. To identify novel biomarkers predicting post-MI LVEF and ISZ, we performed metabolic profiling in the GIPS-III randomized clinical trial (Glycometabolic Intervention as Adjunct to Primary Percutaneous Intervention in ST Elevation Myocardial Infarction). We also investigated the metabolic footprint of metformin, a drug associated with improved post-MI LV function in experimental studies. METHODS AND RESULTS: Participants were patients with ST-segment-elevated MI who were randomly assigned to receive metformin or placebo for 4 months. Blood samples were obtained on admission, 24 hours post-MI, and 4 months post-MI. A total of 233 metabolite measures were quantified using nuclear magnetic resonance spectrometry. LVEF and ISZ were assessed 4 months post-MI. Twenty-four hours post-MI measurements of high-density lipoprotein (HDL) triglycerides (HDL-TG) predicted LVEF (ß=1.90 [95% confidence interval (CI), 0.82 to 2.98]; P=6.4×10-4) and ISZ (ß=-0.41 [95% CI, -0.60 to -0.21]; P=3.2×10-5). In addition, 24 hours post-MI measurements of medium HDL-TG (ß=-0.40 [95% CI, -0.60 to -0.20]; P=6.4×2×10-5), small HDL-TG (ß=-0.34 [95% CI, -0.53 to -0.14]; P=7.3×10-4), and the triglyceride content of very large HDL (ß=-0.38 [95% CI, -0.58 to -0.18]; P=2.7×10-4) were associated with ISZ. After the 4-month treatment, the phospholipid content of very large HDL was lower in metformin than in placebo-treated patients (28.89% versus 38.79%; P=7.5×10-5); alanine levels were higher in the metformin group (0.46 versus 0.44 mmol/L; P=2.4×10-4). CONCLUSIONS: HDL triglyceride concentrations predict post-MI LVEF and ISZ. Metformin increases alanine levels and reduces the phospholipid content in very large HDL particles. CLINICAL TRIAL REGISTRATION: URL: https://clinicaltrials.gov/ct2/show/NCT01217307. Unique Identifier: NCT01217307.

The SPEED (sepsis patient evaluation in the emergency department) score: a risk stratification and outcome prediction tool.

OBJECTIVES: The aim of the study was to identify covariates associated with 28-day mortality in septic patients admitted to the emergency department and derive and validate a score that stratifies mortality risk utilizing parameters that are readily available. METHODS: Patients with an admission diagnosis of suspected or confirmed infection and fulfilling at least two criteria for severe inflammatory response syndrome were included in this study. Patients' characteristics, vital signs, and laboratory values were used to identify prognostic factors for mortality. A scoring system was derived and validated. The primary outcome was the 28-day mortality rate. RESULTS: A total of 440 patients were included in the study. The 28-day hospital mortality rate was 32.4 and 25.2% for the derivation (293 patients) and validation (147 patients) sets, respectively. Factors associated with a higher mortality were immune-suppressed state (odds ratio 4.7; 95% confidence interval 2.0-11.4), systolic blood pressure on arrival less than 90 mmHg (3.8; 1.7-8.3), body temperature less than 36.0°C (4.1; 1.3-12.9), oxygen saturation less than 90% (2.3; 1.1-4.8), hematocrit less than 0.38 (3.1; 1.6-5.9), blood pH less than 7.35 (2.0; 1.04-3.9), lactate level more than 2.4 mmol/l (2.27; 1.2-4.2), and pneumonia as the source of infection (2.7; 1.5-5.0). The area under the receiver operating characteristic curve was 0.81 (0.75-0.86) in the derivation and 0.81 (0.73-0.90) in the validation set. The SPEED (sepsis patient evaluation in the emergency department) score performed better (P=0.02) than the Mortality in Emergency Department Sepsis score when applied to the complete study population with an area under the curve of 0.81 (0.76-0.85) as compared with 0.74 (0.70-0.79). CONCLUSION: The SPEED score predicts 28-day mortality in septic patients. It is simple and its predictive value is comparable to that of other scoring systems.

Epigenetic dynamics in psychiatric disorders: environmental programming of neurodevelopmental processes.

Epigenetic processes have profound influence on gene translation and play a key role in embryonic development and tissue type specification. Recent advances in our understanding of epigenetics have pointed out that epigenetic alterations also play an important role in neurodevelopment and may increase the risk to psychiatric disorders. In addition to genetic regulation of these processes, compelling evidence suggests that environmental conditions produce persistent changes in development through epigenetic mechanisms. Adverse environmental influences in early life such as maternal care, alcohol exposure and prenatal nutrition interact with epigenetic factors and may induce neurodevelopmental disturbances that are related to psychiatric disorders. This review outlines recent findings linking environmentally induced modifications of the epigenome to brain development and psychopathology. Better understanding of these modifications is relevant from the perspective that they may be reversible and, therefore, offer potential for novel treatment strategies. We present the current state of knowledge and show that integrative approaches are necessary to further understand the causal pathways between environmental influences, epigenetic modification, and neuronal function.

Stress-induced enhancement of mouse amygdalar synaptic plasticity depends on glucocorticoid and ß-adrenergic activity.

BACKGROUND: Glucocorticoid hormones, in interaction with noradrenaline, enable the consolidation of emotionally arousing and stressful experiences in rodents and humans. Such interaction is thought to occur at least partly in the basolateral nucleus of the amygdala (BLA) which is crucially involved in emotional memory formation. Extensive evidence points to long-term synaptic potentiation (LTP) as a mechanism contributing to memory formation. Here we determined in adolescent C57/Bl6 mice the effects of stress on LTP in the LA-BLA pathway and the specific roles of corticosteroid and ß-adrenergic receptor activation in this process. PRINCIPAL FINDINGS: Exposure to 20 min of restraint stress (compared to control treatment) prior to slice preparation enhanced subsequent LTP induction in vitro, without affecting baseline fEPSP responses. The role of glucocorticoid receptors, mineralocorticoid receptors and ß2-adrenoceptors in the effects of stress was studied by treating mice with the antagonists mifepristone, spironolactone or propranolol respectively (or the corresponding vehicles) prior to stress or control treatment. In undisturbed controls, mifepristone and propranolol administration in vivo did not influence LTP induced in vitro. By contrast, spironolactone caused a gradually attenuating form of LTP, both in unstressed and stressed mice. Mifepristone treatment prior to stress strongly reduced the ability to induce LTP in vitro. Propranolol normalized the stress-induced enhancement of LTP to control levels during the first 10 min after high frequency stimulation, after which synaptic responses further declined. CONCLUSIONS: Acute stress changes BLA electrical properties such that subsequent LTP induction is facilitated. Both ß-adrenergic and glucocorticoid receptors are involved in the development of these changes. Mineralocorticoid receptors are important for the maintenance of LTP in the BLA, irrespective of stress-induced changes in the circuit. The prolonged changes in BLA network function after stress may contribute to effective memory formation of emotional and stressful events.