The interaction of lipids and inflammatory markers predict negative symptom severity in patients with schizophrenia

Predictors of successful anti-inflammatory drug trials in patients with schizophrenia: A meta-regression and critical commentary

Given evidence pointing toward a role for immune dysregulation in the pathogenesis of schizophrenia, anti-inflammatory agents are promising adjunctive treatments that have potential to support a causal relationship for inflammation and psychopathology and lead to novel treatments for individuals. Indeed, previous meta-analyses have demonstrated small-to-medium effect sizes (ES) in favor of various anti-inflammatory agents, though there is significant heterogeneity and challenges in the interpretation of this literature. Identifying predictors, including sociodemographic variables, trial duration, and/or symptoms themselves, of successful anti-inflammatory trials may help identify which patients who might benefit from these compounds. We performed a meta-regression analysis of 63 adjunctive anti-inflammatory trial arms (2232 patients randomized to adjunctive anti-inflammatory agents and 2207 patients randomized to placebo).Potential predictors of effect size estimates for changes in psychopathology scores from baseline to endpoint included geography, trial duration, sample size, age, sex, race, smoking, body mass index, illness duration, age of onset of psychosis, study quality score and psychopathology scores (total and subscale) at baseline. Geography (β = 0.31, p = 0.011), smaller sample size (β = 0.33, p = 0.009), and higher study quality score (β = 0.44, p < 0.001) were significant predictors of larger ES estimates for change in total psychopathology in favor of anti-inflammatory agents. Smaller sample size (β = 0.37, p = 0.034) and higher study quality score (β = 0.55, p = 0.003) were significant predictors of larger ES estimates for change in negative psychopathology in favor of anti-inflammatory agents. Higher study quality score (β = 0.46, p = 0.019) was a significant predictor of larger ES estimates for change in general psychopathology in favor of anti-inflammatory agents. These findings should be interpreted with caution given concerns of publication bias regarding the geographic differences and small study effects. The lack of an association with other demographic variables should be seen as a primary limitation of the literature that needs to be considered in future studies. The association with study quality score suggests that future anti-inflammatory trials must consider demographic variables known to be associated with inflammation (e.g., BMI and smoking) and evidence of increased baseline inflammation should be incorporated in study design. Moreover, evidence of target engagement and endpoints thoughts to be associated with increased inflammation should be considered as well.

Diet and physical activity and metabolic disorders in patients with schizophrenia and bipolar affective disorder in the Polish population

Introduction

There are numerous reports of a higher prevalence of metabolic disorders in patients with schizophrenia and bipolar disorder (BD), yet its connections to diet and physical activity remain not fully explained. This article aimed to evaluate diet, physical activity and selected biochemical and anthropometric parameters associated with metabolism in patients with schizophrenia and BD and to analyse the relationships between these variables in the subjects.

Materials and Methods

A total of 126 adults participated in the study: 47 patients with schizophrenia, 54 patients with BD and 25 patients in mental illness remission (reference group). Data were collected on the underlying illness and concomitant illnesses, and the severity of symptoms of the current episode was assessed using the following scales: PANSS, MADRS and YMRS. An assessment of the subjects' diet (KomPAN questionnaire) and their physical activity (International Physical Activity Questionnaire) was carried out. Anthropometric and blood pressure measurements were taken and BMI and WHR were calculated. Serum concentrations of fasting glucose, TSH, total cholesterol, LDL and HDL fractions, triglycerides and leptin, ghrelin and resistin were determined. For statistical analysis, the significance level was set at 0.05. For multiple comparisons one way ANOVA or Kruskal Wallis were used with post hoc Tukey and Dunn tests, respectively. To determine correlation of variables, Pearson's linear correlation coefficient or Spearman's rank correlation coefficient were used.

Results

A total of 50.8% of the subjects had at least one metabolic disorder-most commonly excessive body weight (66.7%) and abdominal obesity (64.3%). Patients did not differ significantly in terms of physical activity, but they did differ in mean time spent sitting-with this being significantly longer for all groups than in the general population. The subjects differed in diet: patients with BD consumed less unhealthy foods than patients with schizophrenia. The highest correlations between physical activity, diet and variables defining metabolic disorders were found in patients with BD. Only in patients with schizophrenia were there significant correlations between the course of the disease and physical activity.

Discussion

The results suggest the existence of associations between diet, physical activity, and metabolic disorders in both BD and schizophrenia patients. They also suggest a tendency among those patients to spend long periods of time sitting.

Using support vector machine to explore the difference of function connection between deficit and non-deficit schizophrenia based on gray matter volume

Objective

Schizophrenia can be divided into deficient schizophrenia (DS) and non-deficient schizophrenia (NDS) according to the presence of primary and persistent negative symptoms. So far, there are few studies that have explored the differences in functional connectivity (FC) between the different subtypes based on the region of interest (ROI) from GMV (Gray matter volume), especially since the characteristics of brain networks are still unknown. This study aimed to investigate the alterations of functional connectivity between DS and NDS based on the ROI obtained by machine learning algorithms and differential GMV. Then, the relationships between the alterations and the clinical symptoms were analyzed. In addition, the thalamic functional connection imbalance in the two groups was further explored.

Methods

A total of 16 DS, 31 NDS, and 38 health controls (HC) underwent resting-state fMRI scans, patient group will further be evaluated by clinical scales including the Brief Psychiatric Rating Scale (BPRS), the Scale for the Assessment of Negative Symptoms (SANS), and the Scale for the Assessment of Positive Symptoms (SAPS). Based on GMV image data, a support vector machine (SVM) is used to classify DS and NDS. Brain regions with high weight in the classification were used as seed points in whole-brain FC analysis and thalamic FC imbalance analysis. Finally, partial correlation analysis explored the relationships between altered FC and clinical scale in the two subtypes.

Results

The relatively high classification accuracy is obtained based on the SVM. Compared to HC, the FC increased between the right inferior parietal lobule (IPL.R) bilateral thalamus, and lingual gyrus, and between the right inferior temporal gyrus (ITG.R) and the Salience Network (SN) in NDS. The FC between the right thalamus (THA.R) and Visual network (VN), between ITG.R and right superior occipital gyrus in the DS group was higher than that in HC. Furthermore, compared with NDS, the FC between the ITG.R and the left superior and middle frontal gyrus decreased in the DS group. The thalamic FC imbalance, which is characterized by frontotemporal-THA.R hypoconnectivity and sensory motor network (SMN)-THA.R hyperconnectivity was found in both subtypes. The FC value of THA.R and SMN was negatively correlated with the SANS score in the DS group but positively correlated with the SAPS score in the NDS group.

Conclusion

Using an SVM classification method and based on an ROI from GMV, we highlighted the difference in functional connectivity between DS and NDS from the local to the brain network, which provides new information for exploring the neural physiopathology of the two subtypes of schizophrenic.

Gene co-expression architecture in peripheral blood in a cohort of remitted first-episode schizophrenia patients

A better understanding of schizophrenia subtypes is necessary to stratify the patients according to clinical attributes. To explore the genomic architecture of schizophrenia symptomatology, we analyzed blood co-expression modules and their association with clinical data from patients in remission after a first episode of schizophrenia. In total, 91 participants of the 2EPS project were included. Gene expression was assessed using the Clariom S Human Array. Weighted-gene co-expression network analysis (WGCNA) was applied to identify modules of co-expressed genes and to test its correlation with global functioning, clinical symptomatology, and premorbid adjustment. Among the 25 modules identified, six modules were significantly correlated with clinical data. These modules could be clustered in two groups according to their correlation with clinical data. Hub genes in each group showing overlap with risk genes for schizophrenia were enriched in biological processes related to metabolic processes, regulation of gene expression, cellular localization and protein transport, immune processes, and neurotrophin pathways. Our results indicate that modules with significant associations with clinical data showed overlap with gene sets previously identified in differential gene-expression analysis in brain, indicating that peripheral tissues could reveal pathogenic mechanisms. Hub genes involved in these modules revealed multiple signaling pathways previously related to schizophrenia, which may represent the complex interplay in the pathological mechanisms behind the disease. These genes could represent potential targets for the development of peripheral biomarkers underlying illness traits in clinical remission stages after a first episode of schizophrenia.

Cellular and immunometabolic mechanisms of inflammation in depression: Preliminary findings from single cell RNA sequencing and a tribute to Bruce McEwen

Inflammation is associated with symptoms of anhedonia, a core feature of major depression (MD). We have shown that MD patients with high inflammation as measured by plasma C-reactive protein (CRP) and anhedonia display gene signatures of metabolic reprograming (e.g., shift to glycolysis) necessary to sustain cellular immune activation. To gain preliminary insight into the immune cell subsets and transcriptomic signatures that underlie increased inflammation and its relationship with behavior in MD at the single-cell (sc) level, herein we conducted scRNA-Seq on peripheral blood mononuclear cells from a subset of medically-stable, unmedicated MD outpatients. Three MD patients with high CRP (>3 mg/L) before and two weeks after anti-inflammatory challenge with the tumor necrosis factor antagonist infliximab and three patients with low CRP (≤3 mg/L) were studied. Cell clusters were identified using a Single Cell Wizard pipeline, followed by pathway analysis. CD14⁺ and CD16⁺ monocytes were more abundant in MD patients with high CRP and were reduced by 29% and 55% respectively after infliximab treatment. Within CD14⁺ and CD16⁺ monocytes, genes upregulated in high CRP patients were enriched for inflammatory (phagocytosis, complement, leukocyte migration) and immunometabolic (hypoxia-inducible factor [HIF]-1, aerobic glycolysis) pathways. Shifts in CD4⁺ T cell subsets included ∼30% and ∼10% lower abundance of CD4⁺ central memory (T_CM) and naïve cells and ∼50% increase in effector memory-like (T_EM-like) cells in high versus low CRP patients. T_CM cells of high CRP patients displayed downregulation of the oxidative phosphorylation (OXPHOS) pathway, a main energy source in this cell type. Following infliximab, changes in the number of CD14⁺ monocytes and CD4⁺ T_EM-like cells predicted improvements in anhedonia scores (r = 1.0, p < 0.001). In sum, monocytes and CD4⁺ T cells from MD patients with increased inflammation exhibited immunometabolic reprograming in association with symptoms of anhedonia. These findings are the first step toward determining the cellular and molecular immune pathways associated with inflammatory phenotypes in MD, which may lead to novel immunomodulatory treatments of psychiatric illnesses with increased inflammation.

Brick by Brick: Building a Transdiagnostic Understanding of Inflammation in Psychiatry

ABSTRACT

Inflammatory phenomena are found in many psychiatric disorders-notably, depression, schizophrenia, and posttraumatic stress disorder. Inflammation has been linked to severity and treatment resistance, and may both contribute to, and result from, the pathophysiology of some psychiatric illnesses. Emerging research suggests that inflammation may contribute to symptom domains of reward, motor processing, and threat reactivity across different psychiatric diagnoses. Reward-processing deficits contribute to motivational impairments in depression and schizophrenia, and motor-processing deficits contribute to psychomotor slowing in both depression and schizophrenia. A number of experimental models and clinical trials suggest that inflammation produces deficits in reward and motor processing through common pathways connecting the cortex and the striatum, which includes the nucleus accumbens, caudate nucleus, and putamen.The observed effects of inflammation on psychiatric disorders may cut across traditional conceptualizations of psychiatric diagnoses. Further study may lead to targeted immunomodulating treatments that address difficult-to-treat symptoms in a number of psychiatric disorders. In this review, we use a Research Domain Criteria framework to discuss proposed mechanisms for inflammation and its effects on the domains of reward processing, psychomotor slowing, and threat reactivity. We also discuss data that support contributing roles of metabolic dysregulation and sex differences on the behavioral outcomes of inflammation. Finally, we discuss ways that future studies can help disentangle this complex topic to yield fruitful results that will help advance the field of psychoneuroimmunology.