18 research outputs found

    Failure to mobilize cognitive control for challenging tasks correlates with symptom severity in schizophrenia

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    Deficits in the adaptive, flexible control of behavior contribute to the clinical manifestations of schizophrenia. We used functional MRI and an antisaccade paradigm to examine the neural correlates of cognitive control deficits and their relations to symptom severity. Thirty-three chronic medicated outpatients with schizophrenia and 31 healthy controls performed an antisaccade paradigm. We examined differences in recruitment of the cognitive control network and task performance for Hard (high control) versus Easy (low control) antisaccade trials within and between groups. We focused on the key regions involved in ‘top-down’ control of ocular motor structures – dorsal anterior cingulate cortex, dorsolateral and ventrolateral prefrontal cortex. In patients, we examined whether difficulty implementing cognitive control correlated with symptom severity. Patients made more errors overall, and had shorter saccadic latencies than controls on correct Hard vs. Easy trials. Unlike controls, patients failed to increase activation in the cognitive control network for Hard vs. Easy trials. Reduced activation for Hard vs. Easy trials predicted higher error rates in both groups and increased symptom severity in schizophrenia. These findings suggest that patients with schizophrenia are impaired in mobilizing cognitive control when presented with challenges and that this contributes to deficits suppressing prepotent but contextually inappropriate responses, to behavior that is stimulus-bound and error-prone rather than flexibly guided by context, and to symptom expression. Therapies aimed at increasing cognitive control may improve both cognitive flexibility and reduce the impact of symptoms

    Diminished social motivation in early psychosis is associated with polygenic liability for low vitamin D

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    Insufficiency of vitamin D levels often occur in individuals with schizophrenia and first-episode psychosis (FEP). However, it is unknown whether this represents a biological predisposition, or it is essentially driven by illness-related alterations in lifestyle habits. Lower vitamin D has also been associated with adverse neurodevelopmental outcomes and predominant negative psychotic symptoms. This study aimed to investigate the contribution of polygenic risk score for circulating 25-hydroxyvitamin D concentration (PRS-vitD) to symptom presentation among individuals with FEP enrolled in the Athens First-Episode Psychosis Research Study (AthensFEP n = 205) and the Psychosis Incident Cohort Outcome Study (PICOS n = 123). The severity of psychopathology was evaluated using the Positive and Negative Syndrome Scale at baseline and follow-up assessments (AthensFEP: 4-weeks follow-up, PICOS: 1-year follow-up). Premorbid intelligence and adjustment domains were also examined as proxy measures of neurodevelopmental deviations. An inverse association between PRS-vitD and severity of negative symptoms, in particular lack of social motivation, was detected in the AthensFEP at baseline (adjusted R2 = 0.04, p < 0.001) and follow-up (adjusted R2 = 0.03, p < 0.01). The above observation was independently validated in PICOS at follow-up (adjusted R2 = 0.06, p < 0.01). No evidence emerged for a relationship between PRS-vitD and premorbid measures of intelligence and adjustment, likely not supporting an impact of lower PRS-vitD on developmental trajectories related to psychotic illness. These findings suggest that polygenic vulnerability to reduced vitamin D impairs motivation and social interaction in individuals with FEP, thereby interventions that encourage outdoor activities and social engagement in this patient group might attenuate enduring negative symptoms

    Association between exposome score for schizophrenia and functioning in first-episode psychosis: results from the Athens first-episode psychosis research study

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    BACKGROUND: Evidence suggests that environmental factors not only increase psychosis liability but also influence the prognosis and outcomes of psychotic disorders. We investigated temporal and cross-sectional associations of a weighted score of cumulative environmental liability for schizophrenia - the exposome score for schizophrenia (ES-SCZ) - with functioning in first-episode psychosis (FEP). METHODS: Data were derived from the baseline and 1-month assessments of the Athens FEP Research Study that enrolled 225 individuals with FEP. The Global Assessment of Functioning (GAF) and the Personal and Social Performance Scale (PSP) were used to measure social, occupational, and psychological functioning. The ES-SCZ was calculated based on the previously validated method. RESULTS: ES-SCZ was associated with the total scores of GAF and PSP at baseline and 1-month assessments. These findings remained significant when accounting for several associated alternative explanatory variables, including other environmental factors (obstetric complications, migration, ethnic minority), clinical characteristics (duration of untreated psychosis, symptom severity, previous antipsychotic use), and family history of psychosis, demonstrating that the association between ES-SCZ and functioning is over and above other risk factors and cannot be explained by symptom severity alone. Functioning improved from baseline to 1-month assessment, but no significant ES-SCZ-by-time interaction was found on functioning, indicating that functioning changes were not contingent on ES-SCZ. CONCLUSIONS: Our findings suggest that rather than a predictor of functional improvement, ES-SCZ represents a stable severity indicator that captures poor functioning in early psychosis. Environmental risk loading for schizophrenia (ES-SCZ) can be beneficial for clinical characterization and incorporated into transdiagnostic staging models

    Staging of Schizophrenia with the Use of PANSS: An International Multi-Center Study

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    Introduction: A specific clinically relevant staging model for schizophrenia has not yet been developed. The aim of the current study was to evaluate the factor structure of the PANSS and develop such a staging method.Methods: Twenty-nine centers from 25 countries contributed 2358 patients aged 37.21 ± 11.87 years with schizophrenia. Analysis of covariance, Exploratory Factor Analysis, Discriminant Function Analysis, and inspection of resultant plots were performed.Results: Exploratory Factor Analysis returned 5 factors explaining 59% of the variance (positive, negative, excitement/hostility, depression/anxiety, and neurocognition). The staging model included 4 main stages with substages that were predominantly characterized by a single domain of symptoms (stage 1: positive; stages 2a and 2b: excitement/hostility; stage 3a and 3b: depression/anxiety; stage 4a and 4b: neurocognition). There were no differences between sexes. The Discriminant Function Analysis developed an algorithm that correctly classified >85% of patients.Discussion: This study elaborates a 5-factor solution and a clinical staging method for patients with schizophrenia. It is the largest study to address these issues among patients who are more likely to remain affiliated with mental health services for prolonged periods of time.<br /

    Study of mental functions in major mental disorders using neuroimaging techniques, functional and anatomical, magnetic resonance

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    The deficit in functional connectivity (functional dysconnectivity) of the brain, as found in rsfMRI data, has been linked to cognitive deficits in schizophrenia. IPT). IPT is a therapeutic intervention program based on a cognitive and be- havioral approach. Toward this end, we constructed embedded FCNs to model the plasticity of brain connections In the present study, 31 patients with schizophrenia participated. Patients were initially divided into two groups, one group underwent IPT and the other a non-specialized psychological control treatment of equivalent intensity in a non-randomized clinical trial. Study re- sults showed improvement in executive and social functions, psychopatholo- gy, and overall level of functioning for the IPT treatment group only. Further- more, for some indicators, the improvement remained detectable during the follow-up of the patients one year after the end of the treatment program. To construct functional connectivity networks from rsfMRI data, ICA and ISO- MAP, a nonlinear manifold learning algorithm, were used. Functional dysfunc- tion at a global and local level was identified in the patients through compari- son with a control group of 17 healthy individuals. Specifically, differences were found in the resting state network (DMN) and frontoparietal network (FPN), where functional connectivity was reversed in the direction of healthy only for the group that received the IPT treatment program. These recovery effects were maintained at one-year post-treatment follow-up for the DMN, but not for the FPN. This study presents evidence suggesting the use of rsfMRI as a biomarker for the supervision and monitoring of cognitive rehabilitation interventions for schizophrenia.Το έλλειμμα στη λειτουργική συνδεσιμότητα (functional dysconnectivity) του εγκεφάλου, όπως εντοπίζεται σε δεδομένα rsfMRI, έχει συνδεθεί με γνωστικά ελλείματα στη σχιζοφρένεια.. Σκοπός της παρούσας διατριβής είναι η ανί- χνευση επιδράσεων στη λειτουργική συνδεσιμότητα του εγκεφάλου ασθενών με σχιζοφρένεια που υποβλήθηκαν στην Ολοκληρωμένη Ψυχολογική Θερα- πεία (IPT). Η IPT αποτελεί ένα πρόγραμμα θεραπευτικής παρέμβασης βασι- σμένο στη γνωσιακή και τη συμπεριφοριστική προσέγγιση. Προς το σκοπό αυτό, κατασκευάσαμε ενσωματωμένα FCN για τη μοντελοποίηση της πλαστι- κότητας των εγκεφαλικών συνδέσεων Στην παρούσα μελέτη, συμμετείχαν 31 ασθενείς με σχιζοφρένεια. Οι ασθενείς χωρίστηκαν αρχικά σε δύο ομάδες, η μια ομάδα υποβλήθηκε στην IPT, ενώ η άλλη σε μία μη εξειδικευμένη ισοδύ- ναμης έντασης ψυχολογική θεραπεία ελέγχου σε μία μη τυχαιοποιημένη κλινι- κή δοκιμή (non randomized clinical trial). Τα αποτελέσματα της μελέτης έδει- ξαν βελτίωση των εκτελεστικών και κοινωνικών λειτουργιών, της ψυχοπαθο- λογίας και του συνολικού επιπέδου λειτουργικότητας μόνο για την ομάδα θε- ραπείας IPT. Ακόμη, για κάποιους δείκτες, η βελτίωση παρέμεινε ανιχνεύσιμη κατά την παρακολούθηση των ασθενών ένα έτος μετά το πέρας του θεραπευ- τικού προγράμματος. Για την κατασκευή λειτουργικών δικτύων συνδεσιμότη- τας από δεδομένα rsfMRI, χρησιμοποιήθηκαν η ICA και η ISOMAP, ένας μη γραμμικός αλγόριθμος εκμάθησης πολλαπλοτήτων. Λειτουργική δυσλειτουρ- γία σε καθολικό (global) και τοπικό επίπεδο εντοπίστηκε στους ασθενείς μέσω σύγκρισης με μια ομάδα ελέγχου 17 υγιών. Συγκεκριμένα, οι διαφορές εντο- πίστηκαν στο δίκτυο κατάστασης ηρεμίας (DMN) και στο μετωπιαίο βρεγματι- κό δίκτυο (FPN), όπου η λειτουργική συνδεσιμότητα αντιστράφηκε προς την κατεύθυνση των υγιών μόνο για την ομάδα που έλαβε το θεραπευτικό πρό- γραμμα IPT. Αυτά τα αποτελέσματα αποκατάστασης διατηρήθηκαν κατά την παρακολούθηση ενός έτους μετά το πέρας της θεραπείας για το DMN, αλλά όχι και για το FPN. Η μελέτη αυτή παρουσιάζει ενδείξεις που προτείνουν τη χρήση rsfMRI ως βιοδείκτη (biomarker) για την εποπτεία και παρακολούθηση παρεμβάσεων γνωστικής αποκατάστασης για τη σχιζοφρένεια

    Cognitive Inflexibility Predicts Negative Symptoms Severity in Patients with First-Episode Psychosis: A 1-Year Follow-Up Study

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    Negative symptoms and cognitive deficits play a major role in psychosis and significantly influence the functional outcomes of patients, particularly those with a first episode of psychosis (FEP). However, limited research has explored the predictive capacity of cognitive deficits during FEP for subsequent negative symptomatology. Drawing from the Athens FEP research study, we conducted a retrospective longitudinal study in 80 individuals with FEP. All patients were drug naive at admission. Cognitive tests were administered at 1-month and 1-year post-admission, while negative symptomatology was assessed at the same time points using PANSS by trained raters. We considered confounding factors such as age, gender, duration of untreated psychosis (DUP), treatment received, premorbid social adjustment, and premorbid IQ. Univariate regression analysis identified cognitive domains that correlated with negative symptomatology. These, along with the confounders, were incorporated into a multiple regression, with the 1-year PANSS negative scale serving as the dependent variable. Employing the backward elimination technique, we found a statistically significant inverse relationship between the categories completed in the Wisconsin card sorting test (WCST) and the 1-year PANNS negative scale (p = 0.01), beyond the associations with DUP and the 1-month PANSS negative scale. Our results suggest that cognitive flexibility, a key component of executive functions, predicts negative symptom severity one year after FEP

    E-Prevention: Advanced Support System for Monitoring and Relapse Prevention in Patients with Psychotic Disorders Analyzing Long-Term Multimodal Data from Wearables and Video Captures

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    Wearable technologies and digital phenotyping foster unique opportunities for designing novel intelligent electronic services that can address various well-being issues in patients with mental disorders (i.e., schizophrenia and bipolar disorder), thus having the potential to revolutionize psychiatry and its clinical practice. In this paper, we present e-Prevention, an innovative integrated system for medical support that facilitates effective monitoring and relapse prevention in patients with mental disorders. The technologies offered through e-Prevention include: (i) long-term continuous recording of biometric and behavioral indices through a smartwatch; (ii) video recordings of patients while being interviewed by a clinician, using a tablet; (iii) automatic and systematic storage of these data in a dedicated Cloud server and; (iv) the ability of relapse detection and prediction. This paper focuses on the description of the e-Prevention system and the methodologies developed for the identification of feature representations that correlate with and can predict psychopathology and relapses in patients with mental disorders. Specifically, we tackle the problem of relapse detection and prediction using Machine and Deep Learning techniques on all collected data. The results are promising, indicating that such predictions could be made and leading eventually to the prediction of psychopathology and the prevention of relapses

    Association between exposome score for schizophrenia and functioning in first-episode psychosis: results from the Athens first-episode psychosis research study

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    BACKGROUND: Evidence suggests that environmental factors not only increase psychosis liability but also influence the prognosis and outcomes of psychotic disorders. We investigated temporal and cross-sectional associations of a weighted score of cumulative environmental liability for schizophrenia - the exposome score for schizophrenia (ES-SCZ) - with functioning in first-episode psychosis (FEP). METHODS: Data were derived from the baseline and 1-month assessments of the Athens FEP Research Study that enrolled 225 individuals with FEP. The Global Assessment of Functioning (GAF) and the Personal and Social Performance Scale (PSP) were used to measure social, occupational, and psychological functioning. The ES-SCZ was calculated based on the previously validated method. RESULTS: ES-SCZ was associated with the total scores of GAF and PSP at baseline and 1-month assessments. These findings remained significant when accounting for several associated alternative explanatory variables, including other environmental factors (obstetric complications, migration, ethnic minority), clinical characteristics (duration of untreated psychosis, symptom severity, previous antipsychotic use), and family history of psychosis, demonstrating that the association between ES-SCZ and functioning is over and above other risk factors and cannot be explained by symptom severity alone. Functioning improved from baseline to 1-month assessment, but no significant ES-SCZ-by-time interaction was found on functioning, indicating that functioning changes were not contingent on ES-SCZ. CONCLUSIONS: Our findings suggest that rather than a predictor of functional improvement, ES-SCZ represents a stable severity indicator that captures poor functioning in early psychosis. Environmental risk loading for schizophrenia (ES-SCZ) can be beneficial for clinical characterization and incorporated into transdiagnostic staging models

    Organization framework and preliminary findings from the Athens First-Episode Psychosis Research Study

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    Aims: Athens First-Episode Psychosis (FEP) Research study, aims to explore the potential associations between multiple genetic, environmental and neurometabolic risk factors of psychotic disorders, through the clinical management of FEP patients with minimal exposure (<2 weeks) to antipsychotic treatment at entry. The goal of this paper is to introduce the background, rationale and design of the study and present its preliminary findings. Methods: We developed a longitudinal cohort study of FEP patients 16-45 years old, presenting at the emergency units of five psychiatric hospitals across Athens, Greece. Research timeline includes baseline, 1-month and 1-year follow-up. Clinical, genetic, environmental, cognitive and biochemical parameters are measured, using psychometric tools, clinical interviews and laboratory tests. A descriptive analysis of baseline and 1-month assessments was performed including demographic characteristics, family history, medication, clinical picture, traumatic experiences, drug use and cognitive functioning. Results: During the last 3 years, 130 subjects have been enrolled in the study. Data so far reveal that, despite the severity of baseline presentation, at 1-month the majority (57.4%) met the Andreasen symptom severity criteria for remission, without the time criterion and showed mild functional improvement. Several environmental adversities and poor cognitive performance were identified, which need to be further elaborated. Conclusions: Athens FEP Research study is the first gene-environment interaction study in Greece. In this article we introduce the organization and methodological framework of the project, along with its basic initial findings. Future analysis will allow the validation of tractable predictors and risk factors implicated in the development and outcome of psychosis

    Prediction of Early Symptom Remission in Two Independent Samples of First-Episode Psychosis Patients Using Machine Learning

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    BACKGROUND: Validated clinical prediction models of short-term remission in psychosis are lacking. Our aim was to develop a clinical prediction model aimed at predicting 4−6-week remission following a first episode of psychosis. METHOD: Baseline clinical data from the Athens First Episode Research Study was used to develop a Support Vector Machine prediction model of 4-week symptom remission in first-episode psychosis patients using repeated nested cross-validation. This model was further tested to predict 6-week remission in a sample of two independent, consecutive Danish first-episode cohorts. RESULTS: Of the 179 participants in Athens, 120 were male with an average age of 25.8 years and average duration of untreated psychosis of 32.8 weeks. 62.9% were antipsychotic-naïve. Fifty-seven percent attained remission after 4 weeks. In the Danish cohort, 31% attained remission. Eleven clinical scale items were selected in the Athens 4-week remission cohort. These included the Duration of Untreated Psychosis, Personal and Social Performance Scale, Global Assessment of Functioning and eight items from the Positive and Negative Syndrome Scale. This model significantly predicted 4-week remission status (area under the receiver operator characteristic curve (ROC-AUC) = 71.45, P < .0001). It also predicted 6-week remission status in the Danish cohort (ROC-AUC = 67.74, P < .0001), demonstrating reliability. CONCLUSIONS: Using items from common and validated clinical scales, our model significantly predicted early remission in patients with first-episode psychosis. Although replicated in an independent cohort, forward testing between machine learning models and clinicians’ assessment should be undertaken to evaluate the possible utility as a routine clinical tool
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