European Archives of Psychiatry and Clinical Neuroscience最新文献

Patients with treatment-resistant schizophrenia (TRS), particularly those resistant to clozapine (CTRS), pose a clinical challenge due to limited response to standard antipsychotic treatments. Inflammatory factors like tumor necrosis factor-alpha (TNF-α), interleukin 2 (IL-2), and interleukin 6 (IL-6) are implicated in schizophrenia's pathophysiology. Our study examines cognitive function, psychopathological symptoms and inflammatory factors in TRS patients, focusing on differences between CTRS and non-CTRS individuals, as well as healthy controls. A cohort of 115 TRS patients and 84 healthy controls were recruited, assessing IL-2, IL-6 and TNF-α. The Positive and Negative Syndrome Scale (PANSS) was applied to assess psychopathological symptoms, while the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) was applied to assess cognitive functioning. CTRS patients showed lower visuospatial constructional score (p = 0.015), higher PANSS scores, higher levels of IL-2 and reduced TNF-α than non-CTRS patients (p < 0.05). Notably, IL-2 was independently associated with psychopathology symptoms in CTRS patients (Beta = 0.268, t = 2.075, p = 0.042), while IL-6 was associated with psychopathology symptoms in non-CTRS patients (Beta = - 0.327, t = - 2.109, p = 0.042). Sex-specific analysis in CTRS patients revealed IL-2 associations with PANSS total and positive symptoms in females, and TNF-α associations with PANSS positive symptoms in males. Furthermore, IL-2, IL-6, and TNF-α displayed potential diagnostic value in TRS patients and CTRS patients (p < 0.05). Clozapine‑resistant symptoms represent an independent endophenotype in schizophrenia with distinctive immunoinflammatory characteristics, potentially influenced by sex.

Treatment response and resistance in major depressive disorder (MDD) show a significant genetic component, but previous studies had limited power also due to MDD heterogeneity. This literature review focuses on the genetic factors associated with treatment outcomes in MDD, exploring their overlap with those associated with clinically relevant symptom dimensions. We searched PubMed for: (1) genome-wide association studies (GWASs) or whole exome sequencing studies (WESs) that investigated efficacy outcomes in MDD; (2) studies examining the association between MDD treatment outcomes and specific depressive symptom dimensions; and (3) GWASs of the identified symptom dimensions. We identified 13 GWASs and one WES of treatment outcomes in MDD, reporting several significant loci, genes, and gene sets involved in gene expression, immune system regulation, synaptic transmission and plasticity, neurogenesis and differentiation. Nine symptom dimensions were associated with poor treatment outcomes and studied by previous GWASs (anxiety, neuroticism, anhedonia, cognitive functioning, melancholia, suicide attempt, psychosis, sleep, sociability). Four genes were associated with both treatment outcomes and these symptom dimensions: CGREF1 (anxiety); MCHR1 (neuroticism); FTO and NRXN3 (sleep). Other overlapping signals were found when considering genes suggestively associated with treatment outcomes. Genetic studies of treatment outcomes showed convergence at the level of biological processes, despite no replication at gene or variant level. The genetic signals overlapping with symptom dimensions of interest may point to shared biological mechanisms and potential targets for new treatments tailored to the individual patient's clinical profile.

Background: It remains unclear whether subjective and objective measures of cognitive function in Post COVID-19 Condition (PCC) are correlated. The extent of correlation has mechanistic and clinical implications.

Methods: This post-hoc analysis of a randomized, double-blind, placebo-controlled clinical trial contains baseline data of subjective and objective measures of cognition in a rigorously characterized cohort living with PCC. Herein, we evaluated the association between subjective and objective condition function, as measured by the Perceived Deficits Questionnaire, 20-item (PDQ-20) and the Digit Symbol Substitution Test (DSST) and Trails Making Test (TMT)-A/B, respectively.

Results: A total of 152 participants comprised the baseline sample. Due to missing data, our statistical analyses included 150 for self-reported PDQ-20, 147 individuals for combined DSST-measured cognitive function (composite z-score of the Pen/Paper plus Online CogState Version, N_combinedDSST), 71 for in-person DSST-measured cognitive function (Pen/Paper Version), 70 for TMT-A-measured cognitive function, and 70 for TMT-B-measured cognitive function. After adjusting for age, sex, and education, PDQ-20 was significantly correlated with pen-and-paper DSST (β = -0.003, p = 0.002) and TMT-B (β = 0.003, p = 0.008) scores, but not with TMT-A scores (β = -0.001, p = 0.751).

Conclusions: Overall, a statistically significant correlation was observed between subjective and objective cognitive functions. Clinicians providing care for individuals with PCC who have subjective cognitive function complaints may consider taking a measurement-based approach to cognition at the point of care that focuses exclusively on patient-reported measures.

Research on anxiety faces challenges due to the wide range of symptoms, making it difficult to determine if different aspects of anxiety are linked to distinct neurobiological processes. Both alterations in functional brain connectivity (FC) and monoaminergic neurotransmitter systems are implicated as potential neural bases of anxiety. We aimed to investigate whole-brain FC involving monoaminergic nuclei and its association with anxiety dimensions in 178 non-clinical participants. Nine anxiety-related scales were used, encompassing trait and state anxiety scores, along with measures of cost-probability, hypervigilance, reward-punishment sensitivity, uncertainty, and trait worry. Resting-state functional magnetic resonance imaging data were acquired, focusing on seven brainstem regions representing serotonergic, dopaminergic, and noradrenergic nuclei, with their FC patterns voxel-wise correlated with the scales. All models underwent family-wise-error correction for multiple comparisons. We observed intriguing relationships: trait and state anxiety scores exhibited opposing correlations in FC between the dorsal raphe nucleus and the paracingulate gyrus. Additionally, we identified shared neural correlates, such as a negative correlation between the locus coeruleus and the frontal pole. This connection was significantly associated with scores on measures of probability, hypervigilance, reward sensitivity, and trait worry. These findings underscore the intricate interplay between anxiety dimensions and subcortico-cortical FC patterns, shedding light on the underlying neural mechanisms governing anxiety.

One of the main goals for supporting people with a psychotic disorder is early detection and intervention, and the detection of Clinical High Risk (CHR) is a major challenge in this respect. This study sought to compare core symptoms of CHR for psychosis networks based on two CHR self-assessment tools, across different risk thresholds and age groups. This cross-sectional online investigation analyzed 936 individuals for CHR, in France and the UK, with the Prodromal Questionnaire-16 (PQ-16) and the Perceptual and Cognitive Aberrations (PCA). Twelve different symptom networks were constructed, assessing relationships, compactness, centrality, predictability, and comparisons between them, based on different thresholds and age groups. In the above-threshold PQ-16 network, the most central symptom was "Voices or whispers"; in the PCA network, the most central symptom was "Non-relevant thoughts distract or bother". They presented low overall predictability. No significant difference was found between them. This study makes three key contributions. First, this cross-network analyses highlight the relative importance of some central symptoms. Secondly, comparisons between networks demonstrate the unity of the CHR construct across scales, thresholds, and ages, affirming its phenotypic homogeneity, an essential issue for patient care pathways. Thirdly, the low average network predictability suggests the existence of unconsidered symptoms within these CHR networks. These results shed light on the organization of CHR symptoms using routine clinical questionnaires, offering insights for preventive targets in a logic of precision semiology.

Schizophrenia is a neurodevelopmental disorder that affects brain structure and function. The retina, as well as the brain, consists of neuronal and glial cells packed in layers. Cortical volume and brain thickness are associated with inflammatory biomarkers, however, no study has been performed associating inflammatory biomarkers and retina in schizophrenia. our study aims to compare the retinal macular thickness and volume and peripapillary thickness in patients with schizophrenia and controls, and associate it to symptoms of schizophrenia, to interleukin-6 (IL-6) and C Reactive Protein (CRP) levels. Optical coherence tomography was performed to assess retinal layer thickness and volume, and CRP and IL-6 levels were measured in patients with schizophrenia and controls. Positive, negative, and general symptoms of schizophrenia were measured with the Positive and Negative Syndrome Scale (PANSS). A linear regression controlling for confounding factors was performed. 70 subjects were included, 35 patients, and 35 controls matched for sex and age. Patients with schizophrenia presented a significantly lower macular volume (p < 0.05) and thickness (< 0.05) than controls. PANSS positive, general and total scores were associated with retinal nerve fiber layer (RNFL) thickness (p < 0.05). There was no association between inflammatory markers (CRP and IL-6) levels and the retinal layer. A reduction in macular volume and thickness was found in patients with schizophrenia. The severity of schizophrenia symptoms was associated with RNFL thickness. CRP and IL-6 are not associated with retinal thickness/volume in schizophrenia or controls.

Individuals with schizophrenia and bipolar disorder are at an increased risk of cardiovascular disease (CVD), and a range of biomarkers related to CVD risk have been found to be abnormal in these patients. Common genetic factors are a putative underlying mechanism, alongside lifestyle factors and antipsychotic medication. However, the extent to which the altered CVD biomarkers are related to genetic factors involved in schizophrenia and bipolar disorder is unknown. In a sample including 699 patients with schizophrenia, 391 with bipolar disorder, and 822 healthy controls, we evaluated 8 CVD risk biomarkers, including BMI, and fasting plasma levels of CVD biomarkers from a subsample. Polygenic risk scores (PGRS) were obtained from genome-wide associations studies (GWAS) of schizophrenia and bipolar disorder from the Psychiatric Genomics Consortium. The CVD biomarkers were used as outcome variables in linear regression models including schizophrenia and bipolar disorder PGRS as predictors, age, sex, diagnostic category, batch and 10 principal components as covariates, controlling for multiple testing by Bonferroni correction for the number of independent tests. Bipolar disorder PGRS was significantly (p = 0.03) negatively associated with BMI after multiple testing correction, and schizophrenia PGRS was nominally negatively associated with BMI. There were no other significant associations between bipolar or schizophrenia PGRS, and other investigated CVD biomarkers. Despite a range of abnormal CVD risk biomarkers in psychotic disorders, we only found a significant negative association between bipolar disorder PGRS and BMI. This has previously been shown for schizophrenia PGRS and BMI, and warrants further exploration.

The role of gut-brain axis functioning gains growing attention in research on the pathophysiology of major depressive disorders. Here, especially consequences of altered microbiota composition on tryptophan metabolism resulting in altered serotonergic neurotransmission in the central nervous system (CNS) have reached a central position. Previous research, however, mainly focused on either microbiota and peripheral serotonin levels or central serotonergic neurotransmission. The present study aimed to combine the analysis of microbiota composition and central serotonergic activity using a valid neurophysiological indicator. We recruited 19 adult patients with type 1 diabetes and depression (D + D; 7 males), 19 patients with type 1 diabetes (D-; 7 male), and 20 healthy participants (HC; 7 males). Next to the analysis of fecal microbiota regarding α- and β-diversity, the loudness dependence of auditory evoked potential (LDAEP) was investigated, a non-invasive measurement of central serotonergic activity. High α-diversity was associated with high LDAEP, i.e., low serotonergic activity, in patients with diabetes and additional depression. Furthermore, relative abundances of bacterial families belonging to Bacteroidetes, Proteobacteria and Firmicutes were shown to have an impact on central serotonergic activity. This finding was supported by a tendency indicating an association of central serotonergic activity with the Bacteroidetes-Firmicutes ratio in both patients' groups. Together, this data suggests that the guts' microbiota composition might play an important role in regulating the central serotonergic activity in the brain.

This study starts from the metabolic related indexes and cellular inflammatory factors in patients with chronic schizophrenia to find out that it can be used as an effective screening index of metabolic syndrome. 320 patients with chronic schizophrenia (course of disease > 5 years) and 165 healthy subjects were selected. The mental symptoms of the patients were measured by positive and negative syndrome scale. Blood samples from patients and healthy controls were collected to detect blood glucose, triglyceride, HDL and fasting insulin. The serum levels of IL-1β, IL-2, IL-6, IL-17, IFN-γ and TNF-α were determined repeatedly by sandwich enzyme-linked immunosorbent assay. The levels of HOMA-IR, plasma inflammatory factors IL-2, IL-6, IL-17 and TNF-α in patient group were higher than those in healthy group. It was found that there were differences in age and related metabolic indexes between patients with chronic schizophrenia with and without metabolic syndrome. In addition, HOMA-IR, plasma cytokines IL-2 and IL-6 still showed differences between groups. In the Spearmen correlation analysis of insulin resistance index, cytokines and metabolic indexes, it was found that there was a significant correlation between HOMA-IR, IL-6 and related metabolic indexes and metabolic syndrome. ROC curve analysis showed that HOMAIR and IL-6 could be used as screening indexes for MS in male and female patients with schizophrenia.Metabolic syndrome is an important risk factor for cardiovascular disease in patients with chronic schizophrenia. HOMA-IR and IL-6 can be used as effective biological indicators to screen MS in patients with chronic schizophrenia.