Integrating genetic, neuropsychological and neuroimaging data to model early-onset obsessive compulsive disorder severity

We propose an integrative approach that combines structural magnetic resonance imaging data (MRI), diffusion tensor imaging data (DTI), neuropsychological data, and genetic data to predict early-onset obsessive compulsive disorder (OCD) severity. From a cohort of 87 patients, 56 with complete information were used in the present analysis. First, we performed a multivariate genetic association analysis of OCD severity with 266 genetic polymorphisms. This association analysis was used to select and prioritize the SNPs that would be included in the model. Second, we split the sample into a training set (N = 38) and a validation set (N = 18). Third, entropy-based measures of information gain were used for feature selection with the training subset. Fourth, the selected features were fed into two supervised methods of class prediction based on machine learning, using the leave-one-out procedure with the train- ing set. Finally, the resulting model was validated with the validation set. Nine variables were used for the creation of the OCD severity predictor, including six genetic polymorphisms and three variables from the neuropsychological data. The developed model classified child and adolescent patients with OCD by disease severity with an accuracy of 0.90 in the testing set and 0.70 in the validation sample. Above its clinical applicability, the combination of particular neuropsychological, neuroimaging, and genetic characteristics could enhance our under- standing of the neurobiological basis of the disorder

Five-year diagnostic stability among adolescents in an inpatient psychiatric unit

Introduction: In childhood, diagnoses made at the first admission to a psychiatric unit are frequently unstable and temporary. In this study, we examined the stability of DSM-IV-TR disorders and groups of disorders among adolescents followed-up for 5 years after hospitalization. Method: All inpatients admitted for the first time between 2007 and 2008 were included and contacted after 5 years for re-evaluation. The final sample comprised 72 patients. At admission, diagnoses were based on the DSM-IV-TR criteria, Fourth Edition. At five years, diagnoses were made using structured clinical interviews for DSM-IV axis I Disorders and for axis II (SCID-I and SCID-II) as well as the Personality Diagnostic Questionnaire, Fourth Edition (PDQ-4). We also evaluated and collected information on the global assessment of functioning using the World Health Organization Quality of Life-BREF (WHOQOL-BREF) instrument. Depending on the distribution of variables, we used the chi-squared and Fisher exact tests or the Student t and McNemar tests for statistical analyses. Results: The most stable diagnoses were schizophrenia spectrum disorders, bipolar disorder, generalized anxiety disorder, obsessive-compulsive disorder, attention deficit hyperactivity disorder, Tourette syndrome, and pervasive developmental disorder. The most unstable diagnoses were disruptive disorders. Participants were satisfied with their quality of life and the global outcomes of the sample were positive. Conclusion: Major psychiatric disorders, including mood and schizophrenia spectrum disorders, were significantly more stable than other diagnoses and tended to continue into adulthood. In the case of study participants, suffering a mental disorder during adolescence did not appear to affect global functioning outcomes

An Empirical Comparison of Meta- and Mega-Analysis With Data From the ENIGMA Obsessive-Compulsive Disorder Working Group

Objective: Brain imaging communities focusing on different diseases have increasingly started to collaborate and to pool data to perform well-powered meta- and mega-analyses. Some methodologists claim that a one-stage individual-participant data (IPD) mega-analysis can be superior to a two-stage aggregated data meta-analysis, since more detailed computations can be performed in a mega-analysis. Before definitive conclusions regarding the performance of either method can be drawn, it is necessary to critically evaluate the methodology of, and results obtained by, meta- and mega-analyses. Methods: Here, we compare the inverse variance weighted random-effect meta-analysis model with a multiple linear regression mega-analysis model, as well as with a linear mixed-effects random-intercept mega-analysis model, using data from 38 cohorts including 3,665 participants of the ENIGMA-OCD consortium. We assessed the effect sizes and standard errors, and the fit of the models, to evaluate the performance of the different methods. Results: The mega-analytical models showed lower standard errors and narrower confidence intervals than the meta-analysis. Similar standard errors and confidence intervals were found for the linear regression and linear mixed-effects random-intercept models. Moreover, the linear mixed-effects random-intercept models showed better fit indices compared to linear regression mega-analytical models. Conclusions: Our findings indicate that results obtained by meta- and mega-analysis differ, in favor of the latter. In multi-center studies with a moderate amount of variation between cohorts, a linear mixed-effects random-intercept mega-analytical framework appears to be the better approach to investigate structural neuroimaging dat

Structural neuroimaging biomarkers for obsessive-compulsive disorder in the ENIGMA-OCD consortium: medication matters

No diagnostic biomarkers are available for obsessive-compulsive disorder (OCD). Here, we aimed to identify magnetic resonance imaging (MRI) biomarkers for OCD, using 46 data sets with 2304 OCD patients and 2068 healthy controls from the ENIGMA consortium. We performed machine learning analysis of regional measures of cortical thickness, surface area and subcortical volume and tested classification performance using cross-validation. Classification performance for OCD vs. controls using the complete sample with different classifiers and cross-validation strategies was poor. When models were validated on data from other sites, model performance did not exceed chance-level. In contrast, fair classification performance was achieved when patients were grouped according to their medication status. These results indicate that medication use is associated with substantial differences in brain anatomy that are widely distributed, and indicate that clinical heterogeneity contributes to the poor performance of structural MRI as a disease marker

Inflammatory dysregulation of monocytes in pediatric patients with obsessive-compulsive disorder

BACKGROUND: Although the exact etiology of obsessive-compulsive disorder (OCD) is unknown, there is growing evidence of a role for immune dysregulation in the pathophysiology of the disease, especially in the innate immune system including the microglia. To test this hypothesis, we studied inflammatory markers in monocytes from pediatric patients with OCD and from healthy controls. METHODS: We determined the percentages of total monocytes, CD16+ monocytes, and classical (CD14highCD16-), intermediate (CD14highCD16low), and non-classical (CD14lowCD16high) monocyte subsets in 102 patients with early-onset OCD and in 47 healthy controls. Moreover, proinflammatory cytokine production (GM-CSF, IL-1β, IL-6, IL-8, and TNF-α) was measured by multiplex Luminex analysis in isolated monocyte cultures, in basal conditions, after exposure to lipopolysaccharide (LPS) to stimulate immune response or after exposure to LPS and the immunosuppressant dexamethasone. RESULTS: OCD patients had significantly higher percentages of total monocytes and CD16+ monocytes than healthy controls, mainly due to an increase in the intermediate subset but also in the non-classical monocytes. Monocytes from OCD patients released higher amounts of GM-CSF, IL-1β, IL-6, IL-8, and TNF-α than healthy controls after exposure to LPS. However, there were no significant differences in basal cytokine production or the sensitivity of monocytes to dexamethasone treatment between both groups. Based on monocyte subset distribution and cytokine production after LPS stimulation, patients receiving psychoactive medications seem to have an intermediate inflammatory profile, that is, lower than non-medicated OCD individuals and higher than healthy controls. CONCLUSIONS: These results strongly support the involvement of an enhanced proinflammatory innate immune response in the etiopathogenesis of early-onset OCD

Effects of climate trends and drought events on urban tree growth in Santiago de Chile

Urban trees and the services they provide (e.g., evapotranspirational cooling, shading, recreation, carbon storage, air pollution filtering) can have major effects on the microclimate of a city, although the growth conditions are often inadequate to ensure tree vitality and growth, negatively affecting their beneficial effects. In a worldwide dendrochronological study on ten urban tree species in four climatic zones, the growth and impacts of common urban tree species were assessed. This paper focuses on the results for Robinia pseudoacacia L. in the Mediterranean climate city of Santiago de Chile, highlighting the faster growth of the studied black locust trees since 1960 than its growth in the years before 1960. Furthermore, black locust displayed the best growth when situated closer to the city center than the city periphery and when in the northern and western parts of Santiago de Chile. The species characteristics of black locust also revealed an immediate negative growth reaction to drought events, followed by a rapid recovery, which was similarly influenced by the direction from and distance to the city center of the growing site. The results underline the overall worldwide findings on urban tree growth that indicate that a city climate with an extended growing season and increased temperatures can lead to improved growth of urban trees in the Mediterranean climatic zone. However, with increased growth, more rapid ageing and tree death might follow, leading to increased costs for new plantings and tree management.Los árboles urbanos y los servicios que proporcionan (ej.: enfriamiento por evapotranspiración, sombra, recreación, acumulación de carbono y purificación del aire) pueden tener impactos significativos en el microclima de una ciudad. Ello, a pesar que las condiciones en las urbes, suelen ser inadecuadas para asegurar la vitalidad y el crecimiento de los árboles, disminuyendo sus efectos benéficos. En un estudio dendrocronológico mundial, se evaluó el impacto de las tendencias climáticas en el crecimiento de diez especies urbanas, en cuatro condiciones climáticas. Los resultados obtenidos al estudiar ejemplares de Robinia pseudoacacia L. plantados en Santiago de Chile muestran un mayor crecimiento de los árboles desde el año 1960, comparado con años anteriores, con mayores incrementos desde la periferia hacia el centro de la ciudad, así como en las zonas norte y oeste de ésta. En repuesta a sequías, la especie presenta disminuciones inmediatas en el crecimiento de los árboles, seguidas de una rápida recuperación, dependiendo de su ubicación geográfica y del distanciamiento al centro de la ciudad. Los resultados evidencian la tendencia global de que el clima urbano, con una estación de crecimiento más larga y temperaturas más altas, puede causar que los árboles urbanos, en la zona climática mediterránea, crezcan más rápido. Este crecimiento mayor podría ser seguido por un envejecimiento más rápido y la muerte de los árboles, provocando aumentos en los costos de reforestación y manejo de los árboles

Yale Global Tic Severity Scale (YGTSS): Psychometric Quality of the Gold Standard for Tic Assessment Based on the Large- Scale EMTICS Study.

The Yale Global Tic Severity Scale (YGTSS) is a clinician-rated instrument considered as the gold standard for assessing tics in patients with Tourette's Syndrome and other tic disorders. Previous psychometric investigations of the YGTSS exhibit different limitations such as small sample sizes and insufficient methods. To overcome these shortcomings, we used a subsample of the large-scale "European Multicentre Tics in Children Study" (EMTICS) including 706 children and adolescents with a chronic tic disorder and investigated convergent, discriminant and factorial validity, as well as internal consistency of the YGTSS. Our results confirm acceptable convergent and good to very good discriminant validity, respectively, indicated by a sufficiently high correlation of the YGTSS total tic score with the Clinical Global Impression Scale for tics (rs = 0.65) and only low to medium correlations with clinical severity ratings of attention deficit/hyperactivity symptoms (rs = 0.24), obsessive-compulsive symptoms (rs = 27) as well as internalizing symptoms (rs = 0.27). Internal consistency was found to be acceptable ( = 0.58 for YGTSS total tic score). A confirmatory factor analysis supports the concept of the two factors "motor tics" and "phonic tics," but still demonstrated just a marginal model fit (root mean square error of approximation = 0.09 [0.08; 0.10], comparative fit index = 0.90, and Tucker Lewis index = 0.87). A subsequent analysis of local misspecifications revealed correlated measurement errors, suggesting opportunities for improvement regarding the item wording. In conclusion, our results indicate acceptable psychometric quality of the YGTSS. However, taking the wide use and importance of the YGTSS into account, our results suggest the need for further investigations and improvements of the YGTSS. In addition, our results show limitations of the global severity score as a sum score indicating that the separate use of the total tic score and the impairment rating is more beneficial