Global and regional cortical thinning in first-episode psychosis patients: relationships with clinical and cognitive features

BackgroundThe thickness of the cortical mantle is a sensitive measure for identifying alterations in cortical structure. We aimed to explore whether first episode schizophrenia patients already show a significant cortical thinning and whether cortical thickness anomalies may significantly influence clinical and cognitive features.MethodWe investigated regional changes in cortical thickness in a large and heterogeneous sample of schizophrenia spectrum patients (n=142) at their first break of the illness and healthy controls (n=83). Magnetic resonance imaging brain scans (1.5 T) were obtained and images were analyzed by using BRAINS2. The contribution of sociodemographic, cognitive and clinical characterictics was investigated.ResultsPatients showed a significant total cortical thinning (F=17.55, d=−0.62, p0.53). No significant group × gender interactions were observed (all p’s>0.15). There were no significant associations between the clinical and pre-morbid variables and cortical thickness measurements (all r’s<0.12). A weak significant negative correlation between attention and total (r=−0.24, p=0.021) and parietal cortical thickness (r=−0.27, p=0.009) was found in patients (thicker cortex was associated with lower attention). Our data revealed a similar pattern of cortical thickness changes related to age in patients and controls.ConclusionsCortical thinning is independent of gender, age, age of onset and duration of the illness and does not seem to significantly influence clinical and functional symptomatology. These findings support a primary neuro-development disorder affecting the normal cerebral cortex development in schizophrenia

Childhood abuse in the etiological continuum underlying psychosis from first-episode psychosis to psychotic experiences

Goal The present study aimed to examine the prevalence of child abuse across the continuum of psychosis. Patients and methods The sample consisted of 198 individuals divided in three groups: (1) 48 FEP patients, (2) 77 individuals scoring high in Community Assessment of Psychic Experiences (CAPE), classified as “High CAPE” group and (3) 73 individuals scoring low, classified as “Low CAPE” group. Childhood abuse was assessed using self-report instruments. Chi2 tests and logistic regression models controlling by sex, age and cannabis were used to perform three comparisons: (i) FEP vs. Low CAPE; (ii) FEP vs. High CAPE and (iii) High CAPE vs. Low CAPE. Results The frequency of individuals exposed to childhood abuse for FEP, High CAPE and Low CAPE groups were 52.1%, 41.6% and 11%, respectively. FEP and High CAPE group presented significantly higher rates of childhood abuse compared to Low CAPE group, however, no significant differences were found between FEP and High CAPE groups regarding the frequency of childhood abuse. Conclusion There is an increasing frequency of childhood abuse from low subclinical psychosis to FEP patients. However, childhood abuse is equally common in FEP and at risk individuals

Transcriptomic and connectomic correlates of differential spatial patterning among gliomas.

Unravelling the complex events driving grade-specific spatial distribution of brain tumour occurrence requires rich datasets from both healthy individuals and patients. Here, we combined open-access data from The Cancer Genome Atlas, the UKBiobank and the Allen Brain Human Atlas to disentangle how the different spatial occurrences of Glioblastoma Multiforme (GBM) and Low-Grade Gliomas (LGG) are linked to brain network features and the normative transcriptional profiles of brain regions. From MRI of brain tumour patients we first constructed a grade-related frequency map of the regional occurrence of LGG and the more aggressive GBM. Using associated mRNA transcription data, we derived a set of differential gene expressions from GBM and LGG tissues of the same patients. By combining the resulting values with normative gene expressions from postmortem brain tissue, we constructed a grade-related expression map indicating which brain regions express genes dysregulated in aggressive gliomas. Additionally, we derived an expression map of genes previously associated with tumour subtypes in a GWAS study (tumour-related genes). There were significant associations between grade-related frequency, grade-related expression, and tumour-related expression maps, as well as functional brain network features (specifically, nodal strength and participation coefficient) that are implicated in neurological and psychiatric disorders. These findings identify brain network dynamics and transcriptomic signatures as key factors in regional vulnerability for GBM and LGG occurrence, placing primary brain tumours within a well-established framework of neurological and psychiatric cortical alterations

Trajectories of Symptom Dimensions in Short-Term Response to Antipsychotic Treatment in Patients with a First Episode of Non-Affective Psychosis

Background Trajectory patterns of positive, disorganized and negative dimension symptoms during antipsychotic treatment in drug-naive patients with first-episode psychosis have yet to be examined by using naturalistic data. Method This pragmatic clinical trial randomized 161 drug-naive patients with a first episode of psychosis to olanzapine, risperidone or haloperidol. Patients were assessed with the Scale for the Assessment of Negative Symptoms (SANS) and Positive Symptoms (SAPS) at baseline and at the end of weeks 1, 2, 3, 4 and 6 of antipsychotic treatment. Censored normal models of response trajectories were developed with three dimensions of the SAPS-SANS scores (positive, disorganized and negative) in order to identify the different response trajectories. Diagnosis, cannabis use, duration of untreated psychosis (DUP), smoking and antipsychotic class were examined as possible predictive variables. Results Patients were classified in five groups according to the positive dimension, three groups according to the disorganized dimension and five groups according to the negative dimension. Longer DUPs and cannabis use were associated with higher scores and poorer responses in the positive dimension. Cannabis use was associated with higher scores and poorer responses in the disorganized dimension. Only schizophrenia diagnosis was associated with higher scores and poorer responses in the negative dimension. Conclusions Our results illustrate the heterogeneity of short-term response to antipsychotics in patients with a first episode of psychosis and highlight markedly different patterns of response in the positive, disorganized and negative dimensions. DUP, cannabis use and diagnosis appeared to have a prognostic value in predicting treatment response with different implications for each dimension

Lifestyle in undergraduate students and demographically matched controls during the COVID-19 pandemic in Spain

Few studies have used a multidimensional approach to describe lifestyle changes among undergraduate students during the COVID-19 pandemic or have included controls. This study aimed to evaluate lifestyle behaviors and mental health of undergraduate students and compare them with an age and sex-matched control group. A cross-sectional web survey using snowball sampling was conducted several months after the beginning of COVID-19 pandemic in Spain. A sample of 221 students was recruited. The main outcome was the total SMILE-C score. Students showed a better SMILE-C score than controls (79.8 + 8.1 vs. 77.2 + 8.3; p < 0.001), although these differences disappeared after controlling for covariates. While groups did not differ in the screenings of depression and alcohol abuse, students reported lower rates of anxiety (28.5% vs. 37.1%; p = 0.042). A lower number of cohabitants, poorer self-perceived health and positive screening for depression and anxiety, or for depression only were independently associated (p < 0.05) with unhealthier lifestyles in both groups. History of mental illness and financial difficulties were predictors of unhealthier lifestyles for students, whereas totally/moderate changes in substance abuse and stress management (p < 0.05) were predictors for the members of the control group. Several months after the pandemic, undergraduate students and other young adults had similar lifestyles

Homocysteine and cognition: A systematic review of 111 studies

Background Elevated plasma homocysteine ​​(Hcy) levels have been associated with cognitive dysfunction in a wide range of conditions. The aim of this review is to establish which cognitive domains and populations are the most affected. Methods We systematically review the literature and consider all articles that showed any relationship between plasma Hcy levels and scores achieved on cognitive performance tests in both, the general population and patients suffering from central nervous system disorders and other diseases. When effect sizes were available and combinable, several meta-analyses were performed. Results We found 111 pertinent articles. There were 24 cohort studies, 18 randomized trials, 21 case-control studies, and 48 cross-sectional studies. This review reveals a positive trend between cognitive decline and increased plasma Hcy concentrations in general population and in patients with cognitive impairments. Results from the meta-analyses also confirm this trend. Treatment with vitamin supplementation fails to show a reduction in cognitive decline. Discussion Further investigations are warranted to clarify this relationship. Earlier detection of the elevated Hcy levels may be an effective intervention to prevent cognitive impairment and dementia

Stability of schizophrenia diagnosis in a ten-year longitudinal study on first episode of non-affective psychosis: conclusions from the PAFIP cohort

OBJECTIVE: To evaluate the ten-year stability of schizophrenia diagnosis in a cohort of first-episode psychosis (FEP) patients and the factors associated with it. METHODS: Changes in diagnosis of 209 FEP patients were described during ten years of follow-up. Related factors with maintenance or change of schizophrenia diagnosis were evaluated in prospective and retrospective approaches through Binary Logistic Regressions, ROC and survival curves. RESULTS: Out of the 209 patients, 126 were diagnosed of schizophrenia six months after their inclusion in the clinical program. Prospective analyses showed that eight of those 126 schizophrenia patients had changed to a different diagnosis after ten years, and predictors of change were better childhood premorbid adjustment, less severity of clinical global impression at baseline, and diagnosis of comorbid personality disorder during follow-up. Retrospectively, out of the 154 patients with schizophrenia in the ten-year assessment, 36 had a different diagnosis at baseline, and those factors related with a different prior diagnosis than schizophrenia were better socioeconomic status and shorter duration of untreated psychosis (DUP). A survival analysis on the timing of schizophrenia diagnosis showed that male gender and longer DUP were predictors of earlier definite diagnosis. CONCLUSIONS: Diagnostic stability of schizophrenia in our FEP sample is high, especially prospective stability, and the group of patients with diagnostic change corresponded to a milder psychopathological profile before and at the onset of disease. Moreover, we observed a cautious attitude in the diagnosis of schizophrenia in patients with shorter DUP who had schizophrenia diagnosis after ten years

The effect of excess weight on circulating inflammatory cytokines in drug-naïve first-episode psychosis individuals

Background: Low-grade inflammation has been repeatedly associated with both excess weight and psychosis. However, no previous studies have addressed the direct effect of body mass index (BMI) on basal serum cytokines in individuals with first-episode psychosis (FEP). Objectives: The aim of this study is to analyze the effect of BMI on basal serum cytokine levels in FEP patients and control subjects, separating the total sample into two groups: normal-weight and overweight individuals. Methods: This is a prospective and open-label study. We selected 75 FEP patients and 75 healthy controls with similar characteristics to patients according to the following variables: sex, age, and cannabis and tobacco consumption. Both controls and patients were separated into two groups according to their BMI: subjects with a BMI under 25 were considered as normal weight and those with a BMI equal to or more than 25 were considered as overweight. Serum levels of 21 cytokines/chemokines were measured at baseline using the Human High Sensitivity T Cell Magnetic Bead Panel protocol from the Milliplex® Map Kit. We compared the basal serum levels of the 21 cytokines between control and patient groups according to their BMI. Results: In the normal-weight group, IL-8 was the only cytokine that was higher in patients than in the control group (p = 0.001), whereas in the overweight group, serum levels of two pro-inflammatory cytokines (IL-6, p = 0.000; IL-1?, p = 0.003), two chemokines (IL-8, p = 0.001; MIP-1?, p = 0.001), four Th-1 and Th-2 cytokines (IL-13, p = 0.009; IL-2, p = 0.001; IL-7, p = 0.001; IL-12p70, p = 0.010), and one Type-3 cytokine (IL-23, p = 0.010) were higher in patients than in controls. Conclusions: Most differences in the basal serum cytokine levels between patients and healthy volunteers were found in the overweight group. These findings suggest that excess weight can alter the homeostasis of the immune system and therefore may have an additive pro-inflammatory effect on the one produced by psychosis in the central nervous system.Funding: The present study was carried out at the Hospital Marqués de Valdecilla, University of Cantabria, Santander, Spain, under the following grant support from MINECO SAF2013-46292-R, Instituto de Salud Carlos III, and Fundación Marqués de Valdecilla. No pharmaceutical company has participated in the study concept and design, data collection, analysis and interpretation of the results, and drafting of the manuscript. We thank the Valdecilla Biobank for blood sampling handling and storage. We also wish to thank the participants and their families for enrolling in this study. The study, designed and directed by B C-F, conformed to international standards for research ethics and was approved by the local institutional review board

Sexual regional dimorphism of post-adolescent and middle age brain maturation. A multi-center 3T MRI study

Sex-related differences are tied into neurodevelopmental and lifespan processes, beginning early in the perinatal and developmental phases and continue into adulthood. The present study was designed to investigate sexual dimorphism of changes in gray matter (GM) volume in post-adolescence, with a focus on early and middle-adulthood using a structural magnetic resonance imaging (MRI) dataset of healthy controls from the European Network on Psychosis, Affective disorders and Cognitive Trajectory (ENPACT). Three hundred and seventy three subjects underwent a 3.0 T MRI session across four European Centers. Age by sex effects on GM volumes were investigated using voxel-based morphometry (VBM) and the Automated Anatomical Labeling atlas regions (ROI). Females and males showed overlapping and non-overlapping patterns of GM volume changes during aging. Overlapping age-related changes emerged in bilateral frontal and temporal cortices, insula and thalamus. Both VBM and ROI analyses revealed non-overlapping changes in multiple regions, including cerebellum and vermis, bilateral mid frontal, mid occipital cortices, left inferior temporal and precentral gyri. These findings highlight the importance of accounting for sex differences in cross-sectional analyses, not only in the study of normative changes, but particularly in the context of psychiatric and neurologic disorders, wherein sex effects may be confounded with disease-related changes

Multi-center MRI prediction models: Predicting sex and illness course in first episode psychosis patients.

Structural Magnetic Resonance Imaging (MRI) studies have attempted to use brain measures obtained at the first-episode of psychosis to predict subsequent outcome, with inconsistent results. Thus, there is a real need to validate the utility of brain measures in the prediction of outcome using large datasets, from independent samples, obtained with different protocols and from different MRI scanners. This study had three main aims: 1) to investigate whether structural MRI data from multiple centers can be combined to create a machine-learning model able to predict a strong biological variable like sex; 2) to replicate our previous finding that an MRI scan obtained at first episode significantly predicts subsequent illness course in other independent datasets; and finally, 3) to test whether these datasets can be combined to generate multicenter models with better accuracy in the prediction of illness course. The multi-center sample included brain structural MRI scans from 256 males and 133 females patients with first episode psychosis, acquired in five centers: University Medical Center Utrecht (The Netherlands) (n=67); Institute of Psychiatry, Psychology and Neuroscience, London (United Kingdom) (n=97); University of São Paulo (Brazil) (n=64); University of Cantabria, Santander (Spain) (n=107); and University of Melbourne (Australia) (n=54). All images were acquired on 1.5-Tesla scanners and all centers provided information on illness course during a follow-up period ranging 3 to 7years. We only included in the analyses of outcome prediction patients for whom illness course was categorized as either "continuous" (n=94) or "remitting" (n=118). Using structural brain scans from all centers, sex was predicted with significant accuracy (89%; p<0.001). In the single- or multi-center models, illness course could not be predicted with significant accuracy. However, when reducing heterogeneity by restricting the analyses to male patients only, classification accuracy improved in some samples. This study provides proof of concept that combining multi-center MRI data to create a well performing classification model is possible. However, to create complex multi-center models that perform accurately, each center should contribute a sample either large or homogeneous enough to first allow accurate classification within the single-center