Negative Symptoms in Early-Onset Psychosis and Their Association With Antipsychotic Treatment Failure.

This is the author accepted manuscript. The final version is available from OUP via the DOI in this recordThe prevalence of negative symptoms (NS) at first episode of early-onset psychosis (EOP), and their effect on psychosis prognosis is unclear. In a sample of 638 children with EOP (aged 10-17 y, 51% male), we assessed (1) the prevalence of NS at first presentation to mental health services and (2) whether NS predicted eventual development of multiple treatment failure (MTF) prior to the age of 18 (defined by initiation of a third trial of novel antipsychotic due to prior insufficient response, intolerable adverse-effects or non-adherence). Data were extracted from the electronic health records held by child inpatient and community-based services in South London, United Kingdom. Natural Language Processing tools were used to measure the presence of Marder Factor NS and antipsychotic use. The association between presenting with ≥2 NS and the development of MTF over a 5-year period was modeled using Cox regression. Out of the 638 children, 37.5% showed ≥2 NS at first presentation, and 124 (19.3%) developed MTF prior to the age of 18. The presence of NS at first episode was significantly associated with MTF (adjusted hazard ratio 1.62, 95% CI 1.07-2.46; P = .02) after controlling for a number of potential confounders including psychosis diagnostic classification, positive symptoms, comorbid depression, and family history of psychosis. Other factors associated with MTF included comorbid autism spectrum disorder, older age at first presentation, Black ethnicity, and family history of psychosis. In EOP, NS at first episode are prevalent and may help identify a subset of children at higher risk of responding poorly to antipsychotics.J.D. received supported by a Medical Research Council (MRC) Clinical Research Training Fellowship (MR/L017105/1) and Psychiatry Research Trust Peggy Pollak Research Fellowship in Developmental Psychiatry. H.D. and S.L. have received salary support from the Foundation of Professional Services to Adolescents, UK. R.D.H. was funded by an MRC Fellowship (MR/J01219X/1). R.P. was funded by an MRC CRTF (MR/K002813/1). C.A., L.P-C., and C.M.D-C. have held grants from the Spanish Ministry of Economy, Industry and Competitiveness. Instituto de Salud Carlos III, co-financed by ERDF Funds from the European Commission, “A way of making Europe,” CIBERSAM, Madrid Regional Government (S2010/BMD-2422 AGES), European Union Structural Funds and European Union Seventh Framework Program under grant agreements FP7-HEALTH-2009-2.2.1-2-241909 (EU-GEI), FP7-HEALTH-2009-2.2.1-3-242114 (OPTiMISE), FP7-HEALTH-2013-2.2.1-2-603196 (PSYSCAN)and FP7- HEALTH-2013-2.2.1-2-602478 (METSY); European Union H2020 Program under the Innovative Medicines Initiative 2 Joint Undertaking (grant agreement No-115916; PRISM); Fundación Alicia Koplowitz and Fundación Mutua Madrileña. M.H., J.H.M. and H.S. receive salary support from the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health

Persistence of accuracy of genomic estimated breeding values over generations in layer chickens

<p>Abstract</p> <p>Background</p> <p>The predictive ability of genomic estimated breeding values (GEBV) originates both from associations between high-density markers and QTL (Quantitative Trait Loci) and from pedigree information. Thus, GEBV are expected to provide more persistent accuracy over successive generations than breeding values estimated using pedigree-based methods. The objective of this study was to evaluate the accuracy of GEBV in a closed population of layer chickens and to quantify their persistence over five successive generations using marker or pedigree information.</p> <p>Methods</p> <p>The training data consisted of 16 traits and 777 genotyped animals from two generations of a brown-egg layer breeding line, 295 of which had individual phenotype records, while others had phenotypes on 2,738 non-genotyped relatives, or similar data accumulated over up to five generations. Validation data included phenotyped and genotyped birds from five subsequent generations (on average 306 birds/generation). Birds were genotyped for 23,356 segregating SNP. Animal models using genomic or pedigree relationship matrices and Bayesian model averaging methods were used for training analyses. Accuracy was evaluated as the correlation between EBV and phenotype in validation divided by the square root of trait heritability.</p> <p>Results</p> <p>Pedigree relationships in outbred populations are reduced by 50% at each meiosis, therefore accuracy is expected to decrease by the square root of 0.5 every generation, as observed for pedigree-based EBV (Estimated Breeding Values). In contrast the GEBV accuracy was more persistent, although the drop in accuracy was substantial in the first generation. Traits that were considered to be influenced by fewer QTL and to have a higher heritability maintained a higher GEBV accuracy over generations. In conclusion, GEBV capture information beyond pedigree relationships, but retraining every generation is recommended for genomic selection in closed breeding populations.</p

Breeding value prediction for production traits in layer chickens using pedigree or genomic relationships in a reduced animal model

<p>Abstract</p> <p>Background</p> <p>Genomic selection involves breeding value estimation of selection candidates based on high-density SNP genotypes. To quantify the potential benefit of genomic selection, accuracies of estimated breeding values (EBV) obtained with different methods using pedigree or high-density SNP genotypes were evaluated and compared in a commercial layer chicken breeding line.</p> <p>Methods</p> <p>The following traits were analyzed: egg production, egg weight, egg color, shell strength, age at sexual maturity, body weight, albumen height, and yolk weight. Predictions appropriate for early or late selection were compared. A total of 2,708 birds were genotyped for 23,356 segregating SNP, including 1,563 females with records. Phenotypes on relatives without genotypes were incorporated in the analysis (in total 13,049 production records).</p> <p>The data were analyzed with a Reduced Animal Model using a relationship matrix based on pedigree data or on marker genotypes and with a Bayesian method using model averaging. Using a validation set that consisted of individuals from the generation following training, these methods were compared by correlating EBV with phenotypes corrected for fixed effects, selecting the top 30 individuals based on EBV and evaluating their mean phenotype, and by regressing phenotypes on EBV.</p> <p>Results</p> <p>Using high-density SNP genotypes increased accuracies of EBV up to two-fold for selection at an early age and by up to 88% for selection at a later age. Accuracy increases at an early age can be mostly attributed to improved estimates of parental EBV for shell quality and egg production, while for other egg quality traits it is mostly due to improved estimates of Mendelian sampling effects. A relatively small number of markers was sufficient to explain most of the genetic variation for egg weight and body weight.</p

Rational Redesign of Glucose Oxidase for Improved Catalytic Function and Stability

Glucose oxidase (GOx) is an enzymatic workhorse used in the food and wine industries to combat microbial contamination, to produce wines with lowered alcohol content, as the recognition element in amperometric glucose sensors, and as an anodic catalyst in biofuel cells. It is naturally produced by several species of fungi, and genetic variants are known to differ considerably in both stability and activity. Two of the more widely studied glucose oxidases come from the species Aspergillus niger (A. niger) and Penicillium amagasakiense (P. amag.), which have both had their respective genes isolated and sequenced. GOx from A. niger is known to be more stable than GOx from P. amag., while GOx from P. amag. has a six-fold superior substrate affinity (KM) and nearly four-fold greater catalytic rate (kcat). Here we sought to combine genetic elements from these two varieties to produce an enzyme displaying both superior catalytic capacity and stability. A comparison of the genes from the two organisms revealed 17 residues that differ between their active sites and cofactor binding regions. Fifteen of these residues in a parental A. niger GOx were altered to either mirror the corresponding residues in P. amag. GOx, or mutated into all possible amino acids via saturation mutagenesis. Ultimately, four mutants were identified with significantly improved catalytic activity. A single point mutation from threonine to serine at amino acid 132 (mutant T132S, numbering includes leader peptide) led to a three-fold improvement in kcat at the expense of a 3% loss of substrate affinity (increase in apparent KM for glucose) resulting in a specify constant (kcat/KM) of 23.8 (mM−1 · s−1) compared to 8.39 for the parental (A. niger) GOx and 170 for the P. amag. GOx. Three other mutant enzymes were also identified that had improvements in overall catalysis: V42Y, and the double mutants T132S/T56V and T132S/V42Y, with specificity constants of 31.5, 32.2, and 31.8 mM−1 · s−1, respectively. The thermal stability of these mutants was also measured and showed moderate improvement over the parental strain

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

Symptom Remission and Brain Cortical Networks at First Clinical Presentation of Psychosis: The OPTiMiSE Study

Individuals with psychoses have brain alterations, particularly in frontal and temporal cortices, that may be particularly prominent, already at illness onset, in those more likely to have poorer symptom remission following treatment with the first antipsychotic. The identification of strong neuroanatomical markers of symptom remission could thus facilitate stratification and individualized treatment of patients with schizophrenia. We used magnetic resonance imaging at baseline to examine brain regional and network correlates of subsequent symptomatic remission in 167 medication-naïve or minimally treated patients with first-episode schizophrenia, schizophreniform disorder, or schizoaffective disorder entering a three-phase trial, at seven sites. Patients in remission at the end of each phase were randomized to treatment as usual, with or without an adjunctive psycho-social intervention for medication adherence. The final follow-up visit was at 74 weeks. A total of 108 patients (70%) were in remission at Week 4, 85 (55%) at Week 22, and 97 (63%) at Week 74. We found no baseline regional differences in volumes, cortical thickness, surface area, or local gyrification between patients who did or did not achieved remission at any time point. However, patients not in remission at Week 74, at baseline showed reduced structural connectivity across frontal, anterior cingulate, and insular cortices. A similar pattern was evident in patients not in remission at Week 4 and Week 22, although not significantly. Lack of symptom remission in first-episode psychosis is not associated with regional brain alterations at illness onset. Instead, when the illness becomes a stable entity, its association with the altered organization of cortical gyrification becomes more defined

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