In Support of Neuroimaging Biomarkers of Treatment Response in First-Episode Schizophrenia.
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ABSTRACT:
SUBMITTER: Sarpal DK
PROVIDER: S-EPMC6071671 | biostudies-literature | 2016 Jul
REPOSITORIES: biostudies-literature
Publications
In Support of Neuroimaging Biomarkers of Treatment Response in First-Episode Schizophrenia.
Sarpal Deepak K DK Lencz Todd T Malhotra Anil K AK
The American journal of psychiatry 20160701 7
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Project description:Preclinical studies have shown that the gut microbiota can play a role in schizophrenia (SCH) pathogenesis via the gut-brain axis. However, its role in the antipsychotic treatment response is unclear. Here, we present a 24-week follow-up study to identify gut microbial biomarkers for SCH diagnosis and treatment response, using a sample of 107 first-episode, drug-naïve SCH patients, and 107 healthy controls (HCs). We collected biological samples at baseline (all participants) and follow-up time points after risperidone treatment (SCH patients). Treatment response was assessed using the Positive and Negative Symptoms Scale total (PANSS-T) score. False discovery rate was used to correct for multiple testing. We found that SCH patients showed lower α-diversity (the Shannon and Simpson's indices) compared to HCs at baseline (p = 1.21 × 10-9, 1.23 × 10-8, respectively). We also found a significant difference in β-diversity between SCH patients and HCs (p = 0.001). At baseline, using microbes that showed different abundance between patients and controls as predictors, a prediction model can distinguish patients from HCs with an area under the curve (AUC) of 0.867. In SCH patients, after 24 weeks of risperidone treatment, we observed an increase of α-diversity toward the basal level of HCs. At the genus level, we observed decreased abundance of Lachnoclostridium (p = 0.019) and increased abundance Romboutsia (p = 0.067). Moreover, the treatment response in SCH patients was significantly associated with the basal levels of Lachnoclostridium and Romboutsia (p = 0.005 and 0.006, respectively). Our results suggest that SCH patients may present characteristic microbiota, and certain microbiota biomarkers may predict treatment response in this patient population.
| S-EPMC8355081 | biostudies-literature
Project description:Although schizophrenia patients exhibit structural abnormalities in the striatum, it remains largely unknown for the role of the striatum subregions in the treatment response of antipsychotic drugs. The purpose of this study was to investigate the associations between the striatal subregions and improved clinical symptoms in first-episode drug-naïve (FEDN) schizophrenia. Forty-two FEDN schizophrenia patients and 29 healthy controls (HCs) were recruited. At baseline, the Positive and Negative Syndrome Scale (PANSS) was used to assess the clinical symptoms of patients, MRI scanner was used to obtain anatomical images of patients and HCs. After 12-week stable doses of risperidone treatment, clinical symptoms were obtained in 38 patients and anatomical images in 26 patients. After 12 weeks of treatment, the left nucleus accumbens volume decreased, whereas the left pallidum volume increased in schizophrenia patients. The decreased left nucleus accumbens volume was positively correlated with cognitive factor improvement measured by PANSS. Intriguingly, greater left nucleus accumbens volume at baseline predicted greater cognitive improvements. Furthermore, the responders who had >50 % improvement in cognitive symptoms exhibited significantly greater baseline left nucleus accumbens volume compared to non-responders. The left striatum volume at baseline and after treatment predicted the cognitive improvements in FEDN schizophrenia, which could be a potential biomarker for the development of precision medicine approaches targeting cognitive function.
| S-EPMC10950692 | biostudies-literature
Project description:Response patterns may differ between patients with first-episode and multiepisode schizophrenia. This analysis explored trial duration with first-episode patients and asked whether early limited improvement predicts ultimate lack of treatment response with first-episode patients as it does with multiepisode patients.One hundred twelve subjects (mean age = 23.3 years, SD = 5.1 years) who presented between November 1998 and October 2004 with a first episode of psychosis and had a DSM-IV diagnosis of schizophrenia or schizophreniform or schizoaffective disorder were randomly assigned to treatment with olanzapine or risperidone for 16 weeks. Treatment response, the primary outcome measure, was defined as a rating of mild or better on all of the positive symptom items on the Schedule for Affective Disorders and Schizophrenia Change Version With Psychosis and Disorganization Items. Response rates were calculated for each study week. A logistic regression analysis examined the association between percentage reduction in symptom severity scores from baseline values at weeks 2, 4, or 8 and response by week 16. The study was conducted at The Zucker Hillside Hospital, Glen Oaks, New York and the Bronx-Lebanon Hospital Center, Bronx, New York.The estimated cumulative response rate was 39.59% (95% CI, 29.77%-49.41%) by week 8 and 65.19% (95% CI, 55.11%-75.27%) by week 16. The confidence intervals for estimated response at weeks 10, 12, 14, and 16 were not distinct. Response rates increased approximately 5 to 6 percentage points each 2-week interval between week 10 and 16. Percentage reduction in symptom severity score at week 4 (but not 2 or 8) was associated (?²? = 3.96; P < .05) with responder status at week 16 (odds ratio = 1.03; 95% CI, 1.00-1.05). However, receiver operating characteristic curves did not suggest any level of percentage symptom reduction that would be clinically useful as a predictor of response by week 16.Many first-episode patients respond between weeks 8 and 16 of treatment with a single antipsychotic medication. Limited early symptom improvement does not identify those first-episode patients who will not improve with a full 16-week trial with enough accuracy to be clinically useful.clinicaltrials.gov Identifier: NCT00000374.
| S-EPMC3246541 | biostudies-literature
Project description:Blood methylomes of the first-episode schizophrenia patients differing in their response to amisulpride treatment (OPTiMiSE cohort)
2024-12-30 | E-MTAB-13006 | biostudies-arrayexpress
Project description:BackgroundCognitive development after schizophrenia onset can be shaped by interventions such as cognitive remediation, yet no study to date has investigated whether patterns of early behavioral development may predict later cognitive changes following intervention. We therefore investigated the extent to which premorbid adjustment trajectories predict cognitive remediation gains in schizophrenia.MethodsIn a total sample of 215 participants (170 first-episode schizophrenia participants and 45 controls), we classified premorbid functioning trajectories from childhood through late adolescence using the Cannon-Spoor Premorbid Adjustment Scale. For the 62 schizophrenia participants who underwent 6 months of computer-assisted, bottom-up cognitive remediation interventions, we identified MATRICS Consensus Cognitive Battery scores for which participants demonstrated mean changes after intervention, then evaluated whether developmental trajectories predicted these changes.ResultsGrowth mixture models supported three premorbid functioning trajectories: stable-good, deteriorating, and stable-poor adjustment. Schizophrenia participants demonstrated significant cognitive remediation gains in processing speed, verbal learning, and overall cognition. Notably, participants with stable-poor trajectories demonstrated significantly greater improvements in processing speed compared to participants with deteriorating trajectories.ConclusionsThis is the first study to our knowledge to characterize the associations between premorbid functioning trajectories and cognitive remediation gains after schizophrenia onset, indicating that 6 months of bottom-up cognitive remediation appears to be sufficient to yield a full standard deviation gain in processing speed for individuals with early, enduring functioning difficulties. Our findings highlight the connection between trajectories of premorbid and postmorbid functioning in schizophrenia and emphasize the utility of considering the lifespan developmental course in personalizing therapeutic interventions.
| S-EPMC10166766 | biostudies-literature
Project description:Although some studies have suggested that relapse may be associated with antipsychotic treatment resistance in schizophrenia, the number and quality of studies is limited. The current analysis included patients with a diagnosis of first-episode schizophrenia or schizoaffective disorder who met the following criteria: (1) referral to the First-Episode Psychosis Program between 2003 and 2013; (2) treatment with an oral second-generation antipsychotic according to a standardized treatment algorithm; (3) positive symptom remission; (4) subsequent relapse (i.e., second episode) in association with non-adherence; and (5) reintroduction of antipsychotic treatment with the same agent used to achieve response in the first episode. The following outcomes were used as an index of antipsychotic treatment response: changes in the brief psychiatric rating scale (BPRS) total and positive symptom scores and number of patients who achieved positive symptom remission and 20 and 50% response. A total of 130 patients were included in the analyses. Although all patients took the same antipsychotic in both episodes, there were significant episode-by-time interactions for all outcomes of antipsychotic treatment response over 1 year in favor of the first episode compared to the second episode (50% response rate: 48.7 vs. 10.4% at week 7; 88.2 vs. 27.8% at week 27, respectively). Although antipsychotic doses in the second episode were significantly higher than those in the first episode, results remained unchanged after adjusting for antipsychotic dose. The present findings suggest that antipsychotic treatment response is reduced or delayed in the face of relapse following effective treatment of the first episode of schizophrenia.
| S-EPMC6462044 | biostudies-literature
Project description:BackgroundBrain age is a popular brain-based biomarker that offers a powerful strategy for using neuroscience in clinical practice. We investigated the brain-predicted age difference (PAD) in patients with schizophrenia (SCZ), first-episode schizophrenia spectrum disorders (FE-SSDs), and treatment-resistant schizophrenia (TRS) using structural magnetic resonance imaging data. The association between brain-PAD and clinical parameters was also assessed.MethodsWe developed brain age prediction models for the association between 77 average structural brain measures and age in a training sample of controls (HCs) using ridge regression, support vector regression, and relevance vector regression. The trained models in the controls were applied to the test samples of the controls and 3 patient groups to obtain brain-based age estimates. The correlations were tested between the brain PAD and clinical measures in the patient groups.ResultsModel performance indicated that, regardless of the type of regression metric, the best model was support vector regression and the worst model was relevance vector regression for the training HCs. Accelerated brain aging was identified in patients with SCZ, FE-SSDs, and TRS compared with the HCs. A significant difference in brain PAD was observed between FE-SSDs and TRS using the ridge regression algorithm. Symptom severity, the Social and Occupational Functioning Assessment Scale, chlorpromazine equivalents, and cognitive function were correlated with the brain PAD in the patient groups.ConclusionsThese findings suggest additional progressive neuronal changes in the brain after SCZ onset. Therefore, pharmacological or psychosocial interventions targeting brain health should be developed and provided during the early course of SCZ.
| S-EPMC10032294 | biostudies-literature
Project description:ObjectivesThis prospective cohort study tested for associations between baseline cognitive performance in individuals early within their first episode and antipsychotic treatment of psychosis. We hypothesised that poorer cognitive functioning at the initial assessment would be associated with poorer antipsychotic response following the subsequent 6 weeks.DesignProspective cohort .SettingNational Health Service users with a first-episode schizophrenia diagnosis, recently starting antipsychotic medication, recruited from two UK sites (King's College London, UK and University of Manchester, UK). Participants attended three study visits following screening.ParticipantsEighty-nine participants were recruited, with 46 included in the main analysis. Participants required to be within the first 2 years of illness onset, had received minimal antipsychotic treatment, have the capacity to provide consent, and be able to read and write in English. Participants were excluded if they met remission criteria or showed mild to no symptoms.Primary and secondary outcome measuresAntipsychotic response was determined at 6 weeks using the Positive and Negative Syndrome Scale (PANSS), with cognitive performance assessed at each visit using the Brief Assessment of Cognition in Schizophrenia (BACS). The groups identified (responders and non-responders) from trajectory analyses, as well as from >20% PANSS criteria, were compared on baseline BACS performance.ResultsTrajectory analyses identified 84.78% of the sample as treatment responsive, and the remaining 15.22% as treatment non-responsive. Unadjusted and adjusted logistic regressions observed no significant relationship between baseline BACS on subscale and total performance (BACS t-score: OR=0.98, p=0.620, Cohen's d=0.218) and antipsychotic response at 6 weeks.ConclusionsThis investigation identified two clear trajectories of treatment response in the first 6 weeks of antipsychotic treatment. Responder and non-responder groups did not significantly differ on performance on the BACS, suggesting that larger samples may be required or that an association between cognitive performance and antipsychotic response is not observable in the first 2 years of illness onset.Trial registration numberREC: 17/NI/0209.
| S-EPMC9680154 | biostudies-literature
Project description:Neuropsychiatric disorders are diagnosed based on behavioral criteria, which makes the diagnosis challenging. Objective biomarkers such as neuroimaging are needed, and when coupled with machine learning, can assist the diagnostic decision and increase its reliability. Sixty-four schizophrenia, 36 autism spectrum disorder (ASD), and 106 typically developing individuals were analyzed. FreeSurfer was used to obtain the data from the participant's brain scans. Six classifiers were utilized to classify the subjects. Subsequently, 26 ultra-high risk for psychosis (UHR) and 17 first-episode psychosis (FEP) subjects were run through the trained classifiers. Lastly, the classifiers' output of the patient groups was correlated with their clinical severity. All six classifiers performed relatively well to distinguish the subject groups, especially support vector machine (SVM) and Logistic regression (LR). Cortical thickness and subcortical volume feature groups were most useful for the classification. LR and SVM were highly consistent with clinical indices of ASD. When UHR and FEP groups were run with the trained classifiers, majority of the cases were classified as schizophrenia, none as ASD. Overall, SVM and LR were the best performing classifiers. Cortical thickness and subcortical volume were most useful for the classification, compared to surface area. LR, SVM, and DT's output were clinically informative. The trained classifiers were able to help predict the diagnostic category of both UHR and FEP Individuals.
| S-EPMC7429957 | biostudies-literature
Project description:ObjectiveFunctional impairment continues to represent a major challenge in schizophrenia. Surprisingly, patients with schizophrenia report a level of happiness comparable with control subjects, even in the face of the prominent functional deficits, a finding at odds with evidence indicating a positive relation between happiness and level of functioning. In attempting to reconcile these findings, we chose to examine the issue of values, defined as affectively infused criteria or motivational goals used to select and justify actions, people, and the self, as values are related to both happiness and functioning.MethodsFifty-six first-episode patients in remission and 56 healthy control subjects completed happiness and values measures. Statistical analyses included correlations, analysis of variance, structural equation modelling, and smallest space analysis.ResultsResults indicated that patients with schizophrenia placed significantly greater priority on the value dimensions of Tradition (P = 0.02) and Power (P = 0.03), and significantly less priority on Self-direction (P = 0.007) and Stimulation, (P = 0.008).ConclusionsEssentially, people with schizophrenia place more emphasis on the customs and ideas that traditional culture or religion provide in conjunction with a decreased interest in change, which is at odds with the expectations of early adulthood. This value difference could be related to functional deficits. To this point, we have assumed that people hold to the same values that guided them before the illness' onset, but this may not be the case. Our study indicates that values differ in people with schizophrenia, compared with control subjects, even early in the illness and in the face of symptomatic remission.
| S-EPMC4679131 | biostudies-literature