Role of cellular senescence and NOX4-mediated oxidative stress in systemic sclerosis pathogenesis.

Systemic sclerosis (SSc) is a systemic autoimmune disease characterized by progressive fibrosis of skin and numerous internal organs and a severe fibroproliferative vasculopathy resulting frequently in severe disability and high mortality. Although the etiology of SSc is unknown and the detailed mechanisms responsible for the fibrotic process have not been fully elucidated, one important observation from a large US population study was the demonstration of a late onset of SSc with a peak incidence between 45 and 54 years of age in African-American females and between 65 and 74 years of age in white females. Although it is not appropriate to consider SSc as a disease of aging, the possibility that senescence changes in the cellular elements involved in its pathogenesis may play a role has not been thoroughly examined. The process of cellular senescence is extremely complex, and the mechanisms, molecular events, and signaling pathways involved have not been fully elucidated; however, there is strong evidence to support the concept that oxidative stress caused by the excessive generation of reactive oxygen species may be one important mechanism involved. On the other hand, numerous studies have implicated oxidative stress in SSc pathogenesis, thus, suggesting a plausible mechanism in which excessive oxidative stress induces cellular senescence and that the molecular events associated with this complex process play an important role in the fibrotic and fibroproliferative vasculopathy characteristic of SSc. Here, recent studies examining the role of cellular senescence and of oxidative stress in SSc pathogenesis will be reviewed

Self-reported suicidal ideation among individuals with first episode psychosis and healthy controls: Findings from the international multicentre EU-GEI study

Introduction: Suicidal ideation is common among individuals with first episode psychosis (FEP), with prevalence estimates up to 56.5 %. Despite its high prevalence, relatively little is known about how sociodemographic, clinical and/or developmental characteristics contribute to the experience of suicidal ideation in individuals with FEP. // Methods: In this cross-sectional study (FEP n = 551 and controls n = 857), univariate logistic regression analyses were performed to study the associations of sociodemographic, clinical, and developmental factors with suicidal ideation in individuals with FEP as well as controls. Suicidal ideation was assessed using the Community Assessment of Psychic Experiences (CAPE). In addition, multivariate logistic regression analyses were conducted based on a stepwise approach. // Results: In FEP, only depressive symptoms remained significantly associated with suicidal ideation when all correlates were integrated into one model. In the multivariate model in controls, depressive symptoms, positive symptoms, and traumatic childhood experiences were significantly associated with suicidal ideation. // Conclusions: This study showed that depressive symptoms are an important factor relating to suicidal ideation in individuals with FEP, over and above other clinical, sociodemographic, and developmental factors. This underscores the relevance of screening for suicidal ideation in individuals with FEP, and highlights the need for a better understanding of the diagnostic uncertainty and course of mood symptoms in early psychosis

Development and Validation of Predictive Model for a Diagnosis of First Episode Psychosis Using the Multinational EU-GEI Case–control Study and Modern Statistical Learning Methods

Background and Hypothesis: It is argued that availability of diagnostic models will facilitate a more rapid identification of individuals who are at a higher risk of first episode psychosis (FEP). Therefore, we developed, evaluated, and validated a diagnostic risk estimation model to classify individual with FEP and controls across six countries. / Study Design: We used data from a large multi-center study encompassing 2627 phenotypically well-defined participants (aged 18-64 years) recruited from six countries spanning 17 research sites, as part of the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions study. To build the diagnostic model and identify which of important factors for estimating an individual risk of FEP, we applied a binary logistic model with regularization by the least absolute shrinkage and selection operator. The model was validated employing the internal-external cross-validation approach. The model performance was assessed with the area under the receiver operating characteristic curve (AUROC), calibration, sensitivity, and specificity. / Study Results: Having included preselected 22 predictor variables, the model was able to discriminate adults with FEP and controls with high accuracy across all six countries (rangesAUROC=0.84-0.86). Specificity (range=73.9-78.0%) and sensitivity (range=75.6-79.3%) were equally good, cumulatively indicating an excellent model accuracy; though, calibration slope for the diagnostic model showed a presence of some overfitting when applied specifically to participants from France, the UK, and The Netherlands. / Conclusions: The new FEP model achieved a good discrimination and good calibration across six countries with different ethnic contributions supporting its robustness and good generalizability

Perceived major experiences of discrimination, ethnic group, and risk of psychosis in a six-country case-control study

BACKGROUND: Perceived discrimination is associated with worse mental health. Few studies have assessed whether perceived discrimination (i) is associated with the risk of psychotic disorders and (ii) contributes to an increased risk among minority ethnic groups relative to the ethnic majority. METHODS: We used data from the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions Work Package 2, a population-based case-control study of incident psychotic disorders in 17 catchment sites across six countries. We calculated odds ratios (OR) and 95% confidence intervals (95% CI) for the associations between perceived discrimination and psychosis using mixed-effects logistic regression models. We used stratified and mediation analyses to explore differences for minority ethnic groups. RESULTS: Reporting any perceived experience of major discrimination (e.g. unfair treatment by police, not getting hired) was higher in cases than controls (41.8% v. 34.2%). Pervasive experiences of discrimination (≥3 types) were also higher in cases than controls (11.3% v. 5.5%). In fully adjusted models, the odds of psychosis were 1.20 (95% CI 0.91-1.59) for any discrimination and 1.79 (95% CI 1.19-1.59) for pervasive discrimination compared with no discrimination. In stratified analyses, the magnitude of association for pervasive experiences of discrimination appeared stronger for minority ethnic groups (OR = 1.73, 95% CI 1.12-2.68) than the ethnic majority (OR = 1.42, 95% CI 0.65-3.10). In exploratory mediation analysis, pervasive discrimination minimally explained excess risk among minority ethnic groups (5.1%). CONCLUSIONS: Pervasive experiences of discrimination are associated with slightly increased odds of psychotic disorders and may minimally help explain excess risk for minority ethnic groups

The Independent Effects of Psychosocial Stressors on Subclinical Psychosis: Findings From the Multinational EU-GEI Study

The influence of psychosocial stressors on psychosis risk has usually been studied in isolation and after the onset of the disorder, potentially ignoring important confounding relationships or the fact that some stressors that may be the consequence of the disorder rather than preexisting. The study of subclinical psychosis could help to address some of these issues. In this study, we investigated whether there was (i) an association between dimensions of subclinical psychosis and several psychosocial stressors including: childhood trauma, self-reported discrimination experiences, low social capital, and stressful life experiences, and (ii) any evidence of environment-environment (ExE) interactions between these factors. Data were drawn from the EUGEI study, in which healthy controls (N = 1497) and siblings of subjects with a psychotic disorder (N = 265) were included in six countries. The association between psychosocial stressors and subclinical psychosis dimensions (positive, negative and depressive dimension as measured by the Community Assessment of Psychic Experiences (CAPE) scale) and possible ExE interactions were assessed using linear regression models. After adjusting for sex, age, ethnicity, country, and control/sibling status, childhood trauma (β for positive dimension: 0.13, negative: 0.49, depressive: 0.26) and stressful life events (positive: 0.08, negative: 0.16, depressive: 0.17) were associated with the three dimensions. Lower social capital was associated with the negative and depression dimensions (negative: 0.26, depressive: 0.13), and self-reported discrimination experiences with the positive dimension (0.06). Our findings are in favor of independent, cumulative and non-specific influences of social adversities in subclinical psychosis in non-clinical populations, without arguments for E × E interactions

Synergistic effects of childhood adversity and polygenic risk in first-episode psychosis: The EU-GEI study

BACKGROUND: A history of childhood adversity is associated with psychotic disorder, with an increase in risk according to the number of exposures. However, it is not known why only some exposed individuals go on to develop psychosis. One possibility is pre-existing polygenic vulnerability. Here, we investigated, in the largest sample of first-episode psychosis (FEP) cases to date, whether childhood adversity and high polygenic risk scores for schizophrenia (SZ-PRS) combine synergistically to increase the risk of psychosis, over and above the effect of each alone. METHODS: We assigned a schizophrenia-polygenic risk score (SZ-PRS), calculated from the Psychiatric Genomics Consortium (PGC2), to all participants in a sample of 384 FEP patients and 690 controls from the case–control component of the EU-GEI study. Only participants of European ancestry were included in the study. A history of childhood adversity was collected using the Childhood Trauma Questionnaire (CTQ). Synergistic effects were estimated using the interaction contrast ratio (ICR) [odds ratio (OR)exposure and PRS − ORexposure − ORPRS + 1] with adjustment for potential confounders. RESULTS: There was some evidence that the combined effect of childhood adversities and polygenic risk was greater than the sum of each alone, as indicated by an ICR greater than zero [i.e. ICR 1.28, 95% confidence interval (CI) −1.29 to 3.85]. Examining subtypes of childhood adversities, the strongest synergetic effect was observed for physical abuse (ICR 6.25, 95% CI −6.25 to 20.88). CONCLUSIONS: Our findings suggest possible synergistic effects of genetic liability and childhood adversity experiences in the onset of FEP, but larger samples are needed to increase precision of estimates

Estimating the Diets of Animals Using Stable Isotopes and a Comprehensive Bayesian Mixing Model

Using stable isotope mixing models (SIMMs) as a tool to investigate the foraging ecology of animals is gaining popularity among researchers. As a result, statistical methods are rapidly evolving and numerous models have been produced to estimate the diets of animals—each with their benefits and their limitations. Deciding which SIMM to use is contingent on factors such as the consumer of interest, its food sources, sample size, the familiarity a user has with a particular framework for statistical analysis, or the level of inference the researcher desires to make (e.g., population- or individual-level). In this paper, we provide a review of commonly used SIMM models and describe a comprehensive SIMM that includes all features commonly used in SIMM analysis and two new features. We used data collected in Yosemite National Park to demonstrate IsotopeR's ability to estimate dietary parameters. We then examined the importance of each feature in the model and compared our results to inferences from commonly used SIMMs. IsotopeR's user interface (in R) will provide researchers a user-friendly tool for SIMM analysis. The model is also applicable for use in paleontology, archaeology, and forensic studies as well as estimating pollution inputs