Influence of psychopathology and metabolic parameters on quality of life in patients with first-episode psychosis before and after initial antipsychotic treatment.

The impact of psychological and physical health on quality of life (QoL) in patients with early psychosis remain relatively unexplored. We evaluated the predictive value of psychopathological and metabolic parameters on QoL in antipsychotic-naïve patients with first-episode psychosis before and after initial antipsychotic treatment. At baseline, 125 patients underwent assessments of psychopathology, prevalence of metabolic syndrome (MetS), and QoL. After 6 weeks of antipsychotic monotherapy, 89 patients were re-investigated. At baseline, the prevalence of MetS was 19.3% (n = 22). After 6 weeks, body weight (1.3 kg, p < 0.001) and body mass index (0.4 kg/m2, p < 0.001) increased, and four additional patients developed MetS. Multivariate linear regression revealed that positive and negative symptoms, and to some degree waist circumference, were predictors of QoL at both time points. Our findings suggest that in the earliest stages of antipsychotic treatment, metabolic side-effects may be less influential on QoL than psychopathological severity.

Reward disturbances in antipsychotic-naïve patients with first-episode psychosis and their association to glutamate levels.

BACKGROUND: Aberrant anticipation of motivational salient events and processing of outcome evaluation in striatal and prefrontal regions have been suggested to underlie psychosis. Altered glutamate levels have likewise been linked to schizophrenia. Glutamatergic abnormalities may affect the processing of motivational salience and outcome evaluation. It remains unresolved, whether glutamatergic dysfunction is associated with the coding of motivational salience and outcome evaluation in antipsychotic-naïve patients with first-episode psychosis. METHODS: Fifty-one antipsychotic-naïve patients with first-episode psychosis (22 ± 5.2 years, female/male: 31/20) and 52 healthy controls (HC) matched on age, sex, and parental education underwent functional magnetic resonance imaging and magnetic resonance spectroscopy (3T) in one session. Brain responses to motivational salience and negative outcome evaluation (NOE) were examined using a monetary incentive delay task. Glutamate levels were estimated in the left thalamus and anterior cingulate cortex using LCModel. RESULTS: Patients displayed a positive signal change to NOE in the caudate (p = 0.001) and dorsolateral prefrontal cortex (DLPFC; p = 0.003) compared to HC. No group difference was observed in motivational salience or in levels of glutamate. There was a different association between NOE signal in the caudate and DLPFC and thalamic glutamate levels in patients and HC due to a negative correlation in patients (caudate: p = 0.004, DLPFC: p = 0.005) that was not seen in HC. CONCLUSIONS: Our findings confirm prior findings of abnormal outcome evaluation as a part of the pathophysiology of schizophrenia. The results also suggest a possible link between thalamic glutamate and NOE signaling in patients with first-episode psychosis.

Fibre density and fibre-bundle cross-section of the corticospinal tract are distinctly linked to psychosis-specific symptoms in antipsychotic-naïve patients with first-episode schizophrenia.

Multiple lines of research support the dysconnectivity hypothesis of schizophrenia. However, findings on white matter (WM) alterations in patients with schizophrenia are widespread and non-specific. Confounding factors from magnetic resonance image (MRI) processing, clinical diversity, antipsychotic exposure, and substance use may underlie some of the variability. By application of refined methodology and careful sampling, we rectified common confounders investigating WM and symptom correlates in a sample of strictly antipsychotic-naïve first-episode patients with schizophrenia. Eighty-six patients and 112 matched controls underwent diffusion MRI. Using fixel-based analysis (FBA), we extracted fibre-specific measures such as fibre density and fibre-bundle cross-section. Group differences on fixel-wise measures were examined with multivariate general linear modelling. Psychopathology was assessed with the Positive and Negative Syndrome Scale. We separately tested multivariate correlations between fixel-wise measures and predefined psychosis-specific versus anxio-depressive symptoms. Results were corrected for multiple comparisons. Patients displayed reduced fibre density in the body of corpus callosum and in the middle cerebellar peduncle. Fibre density and fibre-bundle cross-section of the corticospinal tract were positively correlated with suspiciousness/persecution, and negatively correlated with delusions. Fibre-bundle cross-section of isthmus of corpus callosum and hallucinatory behaviour were negatively correlated. Fibre density and fibre-bundle cross-section of genu and splenium of corpus callosum were negative correlated with anxio-depressive symptoms. FBA revealed fibre-specific properties of WM abnormalities in patients and differentiated associations between WM and psychosis-specific versus anxio-depressive symptoms. Our findings encourage an itemised approach to investigate the relationship between WM microstructure and clinical symptoms in patients with schizophrenia.

Clustering of antipsychotic-naïve patients with schizophrenia based on functional connectivity from resting-state electroencephalography.

Schizophrenia is associated with aberrations in the Default Mode Network (DMN), but the clinical implications remain unclear. We applied data-driven, unsupervised machine learning based on resting-state electroencephalography (rsEEG) functional connectivity within the DMN to cluster antipsychotic-naïve patients with first-episode schizophrenia. The identified clusters were investigated with respect to psychopathological profile and cognitive deficits. Thirty-seven antipsychotic-naïve, first-episode patients with schizophrenia (mean age 24.4 (5.4); 59.5% males) and 97 matched healthy controls (mean age 24.0 (5.1); 52.6% males) underwent assessments of rsEEG, psychopathology, and cognition. Source-localized, frequency-dependent functional connectivity was estimated using Phase Lag Index (PLI). The DMN-PLI was factorized for each frequency band using principal component analysis. Clusters of patients were identified using a Gaussian mixture model and neurocognitive and psychopathological profiles of identified clusters were explored. We identified two clusters of patients based on the theta band (4-8 Hz), and two clusters based on the beta band (12-30 Hz). Baseline psychopathology could predict theta clusters with an accuracy of 69.4% (p = 0.003), primarily driven by negative symptoms. Five a priori selected cognitive functions conjointly predicted the beta clusters with an accuracy of 63.6% (p = 0.034). The two beta clusters displayed higher and lower DMN connectivity, respectively, compared to healthy controls. In conclusion, the functional connectivity within the DMN provides a novel, data-driven means to stratify patients into clinically relevant clusters. The results support the notion of biological subgroups in schizophrenia and endorse the application of data-driven methods to recognize pathophysiological patterns at earliest stage of this syndrome.

Add-On MEmaNtine to Dopamine Antagonism to Improve Negative Symptoms at First Psychosis- the AMEND Trial Protocol.

Background: Antipsychotic drugs are primarily efficacious in treating positive symptoms by blocking the dopamine D2 receptor, but they fail to substantially improve negative symptoms and cognitive deficits. The limited efficacy may be attributed to the fact that the pathophysiology of psychosis involves multiple neurotransmitter systems. In patients with chronic schizophrenia, memantine, a non-competitive glutamatergic NMDA receptor antagonist, shows promise for ameliorating negative symptoms and improving cognition. Yet, it is unknown how memantine modulates glutamate levels, and memantine has not been investigated in patients with first-episode psychosis. Aims: This investigator-initiated double-blinded randomized controlled trial is designed to (1) test the clinical effects on negative symptoms of add-on memantine to antipsychotic medication, and (2) neurobiologically characterize the responders to add-on memantine. Materials and Equipment: Antipsychotic-naïve patients with first-episode psychosis will be randomized to 12 weeks treatment with [amisulpride + memantine] or [amisulpride + placebo]. We aim for a minimum of 18 patients in each treatment arm to complete the trial. Brain mapping will be performed before and after 12 weeks focusing on glutamate and neuromelanin in predefined regions. Regional glutamate levels will be probed with proton magnetic resonance spectroscopy (MRS), while neuromelanin signal will be mapped with neuromelanin-sensitive magnetic resonance imaging (MRI). We will also perform structural and diffusion weighted, whole-brain MRI. MRS and MRI will be performed at an ultra-high field strength (7 Tesla). Alongside, participants undergo clinical and neuropsychological assessments. Twenty matched healthy controls will undergo similar baseline- and 12-week examinations, but without receiving treatment. Outcome Measures: The primary endpoint is negative symptom severity. Secondary outcomes comprise: (i) clinical endpoints related to cognition, psychotic symptoms, side effects, and (ii) neurobiological endpoints related to regional glutamate- and neuromelanin levels, and structural brain changes. Anticipated Results: We hypothesize that add-on memantine to amisulpride will be superior to amisulpride monotherapy in reducing negative symptoms, and that this effect will correlate with thalamic glutamate levels. Moreover, we anticipate that add-on memantine will restore regional white matter integrity and improve cognitive functioning. Perspectives: By combining two licensed, off-patent drugs, AMEND aims to optimize treatment of psychosis while investigating the memantine response. Alongside, AMEND will provide neurobiological insights to effects of dual receptor modulation, which may enable future stratification of patients with first-episode psychosis before initial antipsychotic treatment. Clinical Trial Registration: [ClinicalTrials.gov], identifier [NCT04789915].

Scalability of the Positive and Negative Syndrome Scale in first-episode schizophrenia assessed by Rasch models.

OBJECTIVE: Historically, assessment of the psychometric properties of the Positive and Negative Syndrome Scale (PANSS) has had several foci: (1) calculation of reliability indexes, (2) extraction of subdimensions from the scale, and (3) assessment of the validity of the total score. In this study, we aimed to examine the scalability and to assess the clinical performance of the 30-item PANSS total score as well as the scalability of a shorter version (PANSS-6) of the scale. METHODS: A composite data set of 1073 patients with first-episode schizophrenia or schizophrenia spectrum disorder was subjected to Rasch analysis of PANSS data from baseline and 4-6 weeks follow-up. RESULTS: The central tests of fit of the Rasch model failed to satisfy the statistical requirements behind item homogeneity for the PANSS-30 as well as the PANSS-6 total score. For the PANSS-30, Differential Item Functioning was pronounced both for the 7-point Likert scale rating categories and when dichotomizing the rating categories. Subsequently, the Rasch structure analysis in the context of dichotomized items was used to isolate and estimate a systematic error because of item inhomogeneity, as well as a random error. The size of the combined sources of error for the PANSS-30 total score approximated 20% which is often regarded as clinical cut-off between response versus no-response. CONCLUSION: The results demonstrate the operational consequences of a lack of statistical fit of the Rasch model and suggest that the calculated measure of uncertainty needs to be considered when using the PANSS-30 total score.

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

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.

Treatment response after 6 and 26 weeks is related to baseline glutamate and GABA levels in antipsychotic-naïve patients with psychosis.

BACKGROUND: Poor response to dopaminergic antipsychotics constitutes a major challenge in the treatment of psychotic disorders and markers for non-response during first-episode are warranted. Previous studies have found increased levels of glutamate and γ-aminobutyric acid (GABA) in non-responding first-episode patients compared to responders, but it is unknown if non-responders can be identified using reference levels from healthy controls (HCs). METHODS: Thirty-nine antipsychotic-naïve patients with first-episode psychosis and 36 matched HCs underwent repeated assessments with the Positive and Negative Syndrome Scale and 3T magnetic resonance spectroscopy. Glutamate scaled to total creatine (/Cr) was measured in the anterior cingulate cortex (ACC) and left thalamus, and levels of GABA/Cr were measured in ACC. After 6 weeks, we re-examined 32 patients on aripiprazole monotherapy and 35 HCs, and after 26 weeks we re-examined 30 patients on naturalistic antipsychotic treatment and 32 HCs. The Andreasen criteria defined non-response. RESULTS: Before treatment, thalamic glutamate/Cr was higher in the whole group of patients but levels normalized after treatment. ACC levels of glutamate/Cr and GABA/Cr were lower at all assessments and unaffected by treatment. When compared with HCs, non-responders at week 6 (19 patients) and week 26 (16 patients) had higher baseline glutamate/Cr in the thalamus. Moreover, non-responders at 26 weeks had lower baseline GABA/Cr in ACC. Baseline levels in responders and HCs did not differ. CONCLUSION: Glutamatergic and GABAergic abnormalities in antipsychotic-naïve patients appear driven by non-responders to antipsychotic treatment. If replicated, normative reference levels for glutamate and GABA may aid estimation of clinical prognosis in first-episode psychosis patients.

Patterns of Cortical Structures and Cognition in Antipsychotic-Naïve Patients With First-Episode Schizophrenia: A Partial Least Squares Correlation Analysis.

BACKGROUND: Schizophrenia is associated with alterations in cortical structures and cognitive impairments, but antipsychotic medication may affect these measures. We investigated patterns of relationships between cortical structures and cognitive domains in antipsychotic-naïve patients with first-episode schizophrenia. METHODS: T1-weighted 3T magnetic resonance imaging was performed in 105 patients and 136 healthy control subjects. Using FreeSurfer, we obtained measurements of cortical thickness, surface area, and mean curvature. Using an extensive neurocognitive battery including the Danish Adult Reading Test and subtests from the Cambridge Neuropsychological Test Automated Battery, we obtained estimates of premorbid intelligence, spatial working memory, spatial planning, intra-extradimensional set shifting, and reaction and movement times. With univariate analyses, we tested group differences between cortical structures and cognition. With partial least squares correlation analyses, we investigated patterns of associations between cortical structures and cognition. RESULTS: Patients had significantly higher mean curvature and were impaired on 7 of 11 cognitive parameters. The between-group partial least squares correlation analysis revealed two cortical thickness/cognition patterns that differentiated patients and healthy control subjects (omnibus test, p = .011). Most cortical regions contributed reliably to these patterns. In patients, spatial working memory, spatial planning, reaction and movement times, and premorbid intelligence contributed reliably to the pattern; in healthy control subjects, spatial planning and intra-extradimensional set shifting contributed reliably. CONCLUSIONS: Antipsychotic-naïve patients with first-episode schizophrenia displayed a higher mean curvature, but no significant difference in other gray matter indices was found. Nevertheless, the pattern of associations between global cortical thickness and cognitive functions was markedly different between groups. These multivariate analyses reveal a novel linkage between regional cortical brain structure and cognitive deficits at the earliest, never-medicated illness stage.

Nectin-1 binds and signals through the fibroblast growth factor receptor.

Nectins belong to a family of immunoglobulin (Ig)-like cell-adhesion molecules comprising four members, nectin-1 through nectin-4. Nectins are involved in formation of the mechanical adhesive puncta adherentia junctions of synapses. Nectins share the same overall structural topology with an extracellular region containing three Ig modules, a transmembrane region, and a cytoplasmic region. In nectin-1, the first and second Ig module in the extracellular region are necessary for the trans-interaction with nectin-3 and formation of cis-dimers, respectively. The function of the third Ig module of nectin-1 remains unknown. We here report the structure in solution of the third, membrane-proximal Ig module of mouse nectin-1 (nectin-1 Ig3) solved by means of nuclear magnetic resonance (NMR) spectroscopy. It belongs to the C1 set of the Ig superfamily. Nectin-1 Ig3 was produced as a recombinant protein and induced neurite outgrowth in primary cultures of hippocampal and cerebellar granule neurons, an effect abolished by treatment with the fibroblast growth factor receptor (FGFR) inhibitor SU5402, or by transfection with a dominant-negative FGFR1 construct. We showed by surface plasmon resonance (SPR) analysis that nectin-1 Ig3 directly interacted with various isoforms of FGFR. Nectin-1 Ig3 induced phosphorylation of FGFR1c in the same manner as the whole nectin-1 ectodomain, and promoted survival of cerebellar granule neurons induced to undergo apoptosis. Finally, we constructed a peptide, nectide, by employing in silico modeling of various FGFR ligand-binding sites. Nectide mimicked all the effects of nectin-1 Ig3. We suggest that FGFR is a downstream signaling partner of nectin-1.