Compensatory Cognitive Training for Latino Youth at Clinical High Risk for Psychosis: Study Protocol for a Randomized Controlled Trial.

Background: Early psychosocial interventions targeting cognitive and functional outcomes in individuals at clinical high risk for psychosis are a research priority. An even greater need is the identification of effective interventions in underserved populations. Compensatory Cognitive Training (CCT) is a psychosocial intervention with demonstrated efficacy in chronic schizophrenia and first episode psychosis, but remains to be evaluated in pre-illness phases. The aim of this study was to describe the development and implementation of an ongoing pilot randomized controlled trial investigating the efficacy of group-based, manualized CCT, as compared to recreational therapy (RT), for Latino participants at clinical high risk for psychosis (CHR) in both the United States and Mexico. It is hypothesized that, in comparison to those receiving RT, participants receiving CCT will show significant improvements in neurocognitive performance and functional capacity (co-primary outcomes) and self-rated functioning and clinical symptoms (secondary outcomes). Methods: Latino CHR participants aged 12-30 years will be included in the study. Both CCT and RT will be delivered in either Spanish or English, depending on group preference. Additionally, all assessments will be administered in participants' preferred language. A comprehensive assessment of neurocognitive and functional performance and clinical symptomatology will be performed at baseline, mid-intervention (4 weeks, 8 weeks), post-intervention (12 weeks) and 3-month follow-up. The primary outcome measures are neurocognition and functional capacity, as assessed by the MATRICS (Measurement and Treatment Research in Cognition in Schizophrenia) Consensus Cognitive Battery and the University of California, San Diego Performance-Based Skills Assessment-Brief, respectively. Furthermore, secondary outcomes measures will be used to examine change in clinical symptoms and self-reported functioning in response to CCT versus RT. Discussion: The evaluation of a novel treatment such as CCT in CHR youth will provide empirical support for a low risk, comprehensive cognitive intervention that could have important implications for public health if it improves neurocognition and functioning

Can we accurately classify schizophrenia patients from healthy controls using magnetic resonance imaging and machine learning?:A multi-method and multi-dataset study

Machine learning is a powerful tool that has previously been used to classify schizophrenia (SZ) patients from healthy controls (HC) using magnetic resonance images. Each study, however, uses different datasets, classification algorithms, and validation techniques. Here, we perform a critical appraisal of the accuracy of machine learning methodologies used in SZ/HC classifications studies by comparing three machine learning algorithms (logistic regression [LR], support vector machines [SVMs], and linear discriminant analysis [LDA]) on three independent datasets (435 subjects total) using two tissue density estimates and cortical thickness (CT). Performance is assessed using 10-fold cross-validation, as well as a held-out validation set. Classification using CT outperformed tissue densities, but there was no clear effect of dataset. LR, SVMs, and LDA each yielded the highest accuracies for a different feature set and validation paradigm, but most accuracies were between 55 and 70%, well below previously reported values. The highest accuracy achieved was 73.5% using CT data and an SVM. Taken together, these results illustrate some of the obstacles to constructing effective disease classifiers, and suggest that tissue densities and CT may not be sufficiently sensitive for SZ/HC classification given current available methodologies and sample sizes

Glutamate Concentration in the Serum of Patients with Schizophrenia

Glutamate is the major neurotransmitter with multiple functions in the central nervous system. Glutamate-mediated excitotoxicity is involved in the pathophysiological processes in schizophrenia. The purpose of this study was to determine the concentration of glutamate in the serum of patients with paranoid schizophrenia compared with healthy individuals, and depending on the duration of the schizophrenic process and leading clinical symptoms. We investigated the level of glutamate in the serum of 158 patients with paranoid schizophrenia and 94 healthy persons. Higher concentrations of glutamate in schizophrenic patients compared with healthy persons have been found. The maximum concentrations of glutamate were detected in patients with disease duration of more than ten years. Glutamate level in the serum does not depend on the prevailing negative or positive clinical symptoms. The increased concentration of glutamate can hypothetically contribute to dopaminergic and glutamatergic imbalance, leading to the development of psychotic symptoms and cognitive dysfunction

Variability and magnitude of brain glutamate levels in schizophrenia:a meta and mega-analysis

Glutamatergic dysfunction is implicated in schizophrenia pathoaetiology, but this may vary in extent between patients. It is unclear whether inter-individual variability in glutamate is greater in schizophrenia than the general population. We conducted meta-analyses to assess (1) variability of glutamate measures in patients relative to controls (log coefficient of variation ratio: CVR); (2) standardised mean differences (SMD) using Hedges g; (3) modal distribution of individual-level glutamate data (Hartigan’s unimodality dip test). MEDLINE and EMBASE databases were searched from inception to September 2022 for proton magnetic resonance spectroscopy (1H-MRS) studies reporting glutamate, glutamine or Glx in schizophrenia. 123 studies reporting on 8256 patients and 7532 controls were included. Compared with controls, patients demonstrated greater variability in glutamatergic metabolites in the medial frontal cortex (MFC, glutamate: CVR = 0.15, p &lt; 0.001; glutamine: CVR = 0.15, p = 0.003; Glx: CVR = 0.11, p = 0.002), dorsolateral prefrontal cortex (glutamine: CVR = 0.14, p = 0.05; Glx: CVR = 0.25, p &lt; 0.001) and thalamus (glutamate: CVR = 0.16, p = 0.008; Glx: CVR = 0.19, p = 0.008). Studies in younger, more symptomatic patients were associated with greater variability in the basal ganglia (BG glutamate with age: z = −0.03, p = 0.003, symptoms: z = 0.007, p = 0.02) and temporal lobe (glutamate with age: z = −0.03, p = 0.02), while studies with older, more symptomatic patients associated with greater variability in MFC (glutamate with age: z = 0.01, p = 0.02, glutamine with symptoms: z = 0.01, p = 0.02). For individual patient data, most studies showed a unimodal distribution of glutamatergic metabolites. Meta-analysis of mean differences found lower MFC glutamate (g = −0.15, p = 0.03), higher thalamic glutamine (g = 0.53, p &lt; 0.001) and higher BG Glx in patients relative to controls (g = 0.28, p &lt; 0.001). Proportion of males was negatively associated with MFC glutamate (z = −0.02, p &lt; 0.001) and frontal white matter Glx (z = −0.03, p = 0.02) in patients relative to controls. Patient PANSS total score was positively associated with glutamate SMD in BG (z = 0.01, p = 0.01) and temporal lobe (z = 0.05, p = 0.008). Further research into the mechanisms underlying greater glutamatergic metabolite variability in schizophrenia and their clinical consequences may inform the identification of patient subgroups for future treatment strategies.</p

Country-level gender inequality is associated with structural differences in the brains of women and men

Gender inequality across the world has been associated with a higher risk to mental health problems and lower academic achievement in women compared to men. We also know that the brain is shaped by nurturing and adverse socio-environmental experiences. Therefore, unequal exposure to harsher conditions for women compared to men in gender-unequal countries might be reflected in differences in their brain structure, and this could be the neural mechanism partly explaining women´s worse outcomes in gender-unequal countries. We examined this through a random-effects meta-analysis on cortical thickness and surface area differences between adult healthy men and women, including a meta-regression in which country-level gender inequality acted as an explanatory variable for the observed differences. A total of 139 samples from 29 different countries, totaling 7,876 MRI scans, were included. Thickness of the right hemisphere, and particularly the right caudal anterior cingulate, right medial orbitofrontal, and left lateral occipital cortex, presented no differences or even thicker regional cortices in women compared to men in gender-equal countries, reversing to thinner cortices in countries with greater gender inequality. These results point to the potentially hazardous effect of gender inequality on women´s brains and provide initial evidence for neuroscience-informed policies for gender equality.Fil: Zugman, André. National Institutes of Health; Estados UnidosFil: Alliende, Luz María. Pontificia Universidad Católica de Chile; Chile. Universidad Católica de Chile; Chile. Northwestern University; Estados UnidosFil: Medel, Vicente. Universidad Adolfo Ibañez; ChileFil: Bethlehem, Richard A.I.. University of Cambridge; Estados UnidosFil: Seidlitz, Jakob. University of Pennsylvania; Estados UnidosFil: Ringlein, Grace. National Institutes of Health; Estados UnidosFil: Arango, Celso. Universidad Complutense de Madrid; EspañaFil: Arnatkevičiūtė, Aurina. Monash University; AustraliaFil: Asmal, Laila. Stellenbosch University; SudáfricaFil: Bellgrove, Mark. Monash University; AustraliaFil: Benegal, Vivek. National Institute Of Mental Health And Neuro Sciences; IndiaFil: Bernardo, Miquel. Universidad de Barcelona; EspañaFil: Billeke, Pablo. Universidad del Desarrollo; ChileFil: Bosch Bayard, Jorge. McGill University. Montreal Neurological Institute and Hospital; Canadá. Université Mcgill; CanadáFil: Bressan, Rodrigo. Universidade Federal de Sao Paulo; BrasilFil: Busatto, Geraldo F.. Universidade de Sao Paulo; BrasilFil: Castro, Mariana Nair. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires; Argentina. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Chaim Avancini, Tiffany. Universidade de Sao Paulo; BrasilFil: Compte, Albert. Institut d’Investigacions Biomèdiques August Pi i Sunyer; EspañaFil: Costanzi, Monise. Hospital de Clinicas de Porto Alegre; BrasilFil: Czepielewski, Leticia. Hospital de Clinicas de Porto Alegre; Brasil. Universidade Federal do Rio Grande do Sul; BrasilFil: Dazzan, Paola. Kings College London (kcl);Fil: de la Fuente-Sandoval, Camilo. Instituto Nacional de Neurología y Neurocirugía; MéxicoFil: Gonzalez Campo, Cecilia. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Zamorano, Francisco. Universidad del Desarrollo; Chile. Universidad San Sebastián; ChileFil: Zanetti, Marcus V.. Universidade de Sao Paulo; BrasilFil: Winkler, Anderson M.. University of Texas; Estados UnidosFil: Pine, Daniel S.. National Institutes of Health; Estados UnidosFil: Evans Lacko, Sara. School of Economics and Political Science; Reino UnidoFil: Crossley, Nicolas A.. Pontificia Universidad Católica de Chile; Chile. Universidad Católica de Chile; Chile. University of Oxford; Reino Unid

Normative modeling of brain morphometry in Clinical High-Risk for Psychosis

Importance: The lack of robust neuroanatomical markers of psychosis risk has been traditionally attributed to heterogeneity. A complementary hypothesis is that variation in neuroanatomical measures in the majority of individuals at psychosis risk may be nested within the range observed in healthy individuals. Objective: To quantify deviations from the normative range of neuroanatomical variation in individuals at clinical high-risk for psychosis (CHR-P) and evaluate their overlap with healthy variation and their association with positive symptoms, cognition, and conversion to a psychotic disorder. Design setting and participants: Clinical, IQ and FreeSurfer-derived regional measures of cortical thickness (CT), cortical surface area (SA), and subcortical volume (SV) from 1,340 CHR-P individuals [47.09% female; mean age: 20.75 (4.74) years] and 1,237 healthy individuals [44.70% female; mean age: 22.32 (4.95) years] from 29 international sites participating in the ENIGMA Clinical High Risk for Psychosis Working Group. Main outcomes and measures: For each regional morphometric measure, z-scores were computed that index the degree of deviation from the normative means of that measure in a healthy reference population (N=37,407). Average deviation scores (ADS) for CT, SA, SV, and globally across all measures (G) were generated by averaging the respective regional z-scores. Regression analyses were used to quantify the association of deviation scores with clinical severity and cognition and two-proportion z-tests to identify case-control differences in the proportion of individuals with infranormal (z1.96) scores. Results: CHR-P and healthy individuals overlapped in the distributions of the observed values, regional z-scores, and all ADS vales. The proportion of CHR-P individuals with infranormal or supranormal values in any metric was low (<12%) and similar to that of healthy individuals. CHR-P individuals who converted to psychosis compared to those who did not convert had a higher percentage of infranormal values in temporal regions (5-7% vs 0.9-1.4%). In the CHR-P group, only the ADS SA showed significant but weak associations (|β|<0.09; P FDR <0.05) with positive symptoms and IQ. Conclusions and relevance: The study findings challenge the usefulness of macroscale neuromorphometric measures as diagnostic biomarkers of psychosis risk and suggest that such measures do not provide an adequate explanation for psychosis risk. Key points: Question: Is the risk of psychosis associated with brain morphometric changes that deviate significantly from healthy variation?Findings: In this study of 1340 individuals high-risk for psychosis (CHR-P) and 1237 healthy participants, individual-level variation in macroscale neuromorphometric measures of the CHR-P group was largely nested within healthy variation and was not associated with the severity of positive psychotic symptoms or conversion to a psychotic disorder.Meaning: The findings suggest the macroscale neuromorphometric measures have limited utility as diagnostic biomarkers of psychosis risk