Identify Potential Causal Relationships Between Cortical Thickness, Mismatch Negativity, Neurocognition, and Psychosocial Functioning in Drug-Naïve First-Episode Psychosis Patients.

BACKGROUND: Cortical thickness (CT) alterations, mismatch negativity (MMN) reductions, and cognitive deficits are robust findings in first-episode psychosis (FEP). However, most studies focused on medicated patients, leaving gaps in our understanding of the interrelationships between CT, MMN, neurocognition, and psychosocial functioning in unmedicated FEP. This study aimed to employ multiple mediation analysis to investigate potential pathways among these variables in unmedicated drug-naïve FEP. METHODS: We enrolled 28 drug-naïve FEP and 34 age and sex-matched healthy controls. Clinical symptoms, neurocognition, psychosocial functioning, auditory duration MMN, and T1 structural magnetic resonance imaging data were collected. We measured CT in the superior temporal gyrus (STG), a primary MMN-generating region. RESULTS: We found a significant negative correlation between MMN amplitude and bilateral CT of STG (CT_STG) in FEP (left: r = -.709, P < .001; right: r = -.612, P = .008). Multiple mediation models revealed that a thinner left STG cortex affected functioning through both direct (24.66%) and indirect effects (75.34%). In contrast, the effects of the right CT_STG on functioning were mainly mediated through MMN and neurocognitive pathways. CONCLUSIONS: Bilateral CT_STG showed significant association with MMN, and MMN plays a mediating role between CT and cognition. Both MMN alone and its interaction with cognition mediated the effects of structural alterations on psychosocial function. The decline in overall function in FEP may stem from decreased CT_STG, leading to subsequent MMN deficits and neurocognitive dysfunction. These findings underline the crucial role of MMN in elucidating how subtle structural alterations can impact neurocognition and psychosocial function in FEP.

Novel α-amino-3-hydroxy-5-methyl-4-isoxazole-propionic acid receptor (AMPAR) potentiator LT-102: A promising therapeutic agent for treating cognitive impairment associated with schizophrenia.

AIMS: We aimed to evaluate the potential of a novel selective α-amino-3-hydroxy-5-methyl-4-isoxazole-propionic acid receptor (AMPAR) potentiator, LT-102, in treating cognitive impairments associated with schizophrenia (CIAS) and elucidating its mechanism of action. METHODS: The activity of LT-102 was examined by Ca2+ influx assays and patch-clamp in rat primary hippocampal neurons. The structure of the complex was determined by X-ray crystallography. The selectivity of LT-102 was evaluated by hERG tail current recording and kinase-inhibition assays. The electrophysiological characterization of LT-102 was characterized by patch-clamp recording in mouse hippocampal slices. The expression and phosphorylation levels of proteins were examined by Western blotting. Cognitive function was assessed using the Morris water maze and novel object recognition tests. RESULTS: LT-102 is a novel and selective AMPAR potentiator with little agonistic effect, which binds to the allosteric site formed by the intradimer interface of AMPAR's GluA2 subunit. Treatment with LT-102 facilitated long-term potentiation in mouse hippocampal slices and reversed cognitive deficits in a phencyclidine-induced mouse model. Additionally, LT-102 treatment increased the protein level of brain-derived neurotrophic factor and the phosphorylation of GluA1 in primary neurons and hippocampal tissues. CONCLUSION: We conclude that LT-102 ameliorates cognitive impairments in a phencyclidine-induced model of schizophrenia by enhancing synaptic function, which could make it a potential therapeutic candidate for CIAS.

New role of platelets in schizophrenia: predicting drug response.

Background: Elevated platelet count (PLTc) is associated with first-episode schizophrenia and adverse outcomes in individuals with precursory psychosis. However, the impact of antipsychotic medications on PLTc and its association with symptom improvement remain unclear. Aims: We aimed to investigate changes in PLTc levels following antipsychotic treatment and assess whether PLTc can predict antipsychotic responses and metabolic changes after accounting for other related variables. Methods: A total of 2985 patients with schizophrenia were randomised into seven groups. Each group received one of seven antipsychotic treatments and was assessed at 2, 4 and 6 weeks. Clinical symptoms were evaluated using the positive and negative syndrome scale (PANSS). Additionally, we measured blood cell counts and metabolic parameters, such as blood lipids. Repeated measures analysis of variance was used to examine the effect of antipsychotics on PLTc changes, while structural equation modelling was used to assess the predictive value of PLTc on PANSS changes. Results: PLTc significantly increased in patients treated with aripiprazole (F=6.00, p=0.003), ziprasidone (F=7.10, p<0.001) and haloperidol (F=3.59, p=0.029). It exhibited a positive association with white blood cell count and metabolic indicators. Higher baseline PLTc was observed in non-responders, particularly in those defined by the PANSS-negative subscale. In the structural equation model, PLTc, white blood cell count and a latent metabolic variable predicted the rate of change in the PANSS-negative subscale scores. Moreover, higher baseline PLTc was observed in individuals with less metabolic change, although this association was no longer significant after accounting for baseline metabolic values. Conclusions: Platelet parameters, specifically PLTc, are influenced by antipsychotic treatment and could potentially elevate the risk of venous thromboembolism in patients with schizophrenia. Elevated PLTc levels and associated factors may impede symptom improvement by promoting inflammation. Given PLTc's easy measurement and clinical relevance, it warrants increased attention from psychiatrists. Trial registration number: ChiCTR-TRC-10000934.

The Influence of Genetic and Environmental Factors on Anxiety among Chinese Adolescents: A Twin Study.

This study explored the influence of genetic and environmental factors on adolescent anxiety. Ninety-eight monozygotic and dizygotic twins from Chongqing, China (aged 15-18 years) were assessed for anxiety with the Self-Rating Anxiety Scale (SAS). The Parenting Styles and Dimensions Questionnaire (PSDQ) and Strengths and Difficulties Questionnaire (SDQ) were applied to assess environmental factors. Venous blood was drawn from the twins for zygosity determination. Structural equation modeling was performed to evaluate the effects of additive genetic factors (A), common environmental factors (C), and individual-specific environmental factors (E) on adolescent anxiety. The estimates of A and E on adolescent anxiety were 0.34 (95% CI = 0.12-0.53) and 0.66 (95% CI:0.47-0.89), respectively. The environment played an important role in adolescent anxiety. Adolescent anxiety was significantly positively correlated with peer relations (r = 0.606, p < 0.05) and negatively correlated with prosocial behavior (r = 0.207, p < 0. 05). No sex differences were observed. Adolescent anxiety was influenced by both genetic and environmental factors. The individual-specific environmental factors played an important role. Consideration of these variables will facilitate the targeted and individualized implementation of specific interventions for adolescent anxiety.

Dynamic aberrances of substantia nigra-relevant coactivation patterns in first-episode treatment-naïve patients with schizophrenia.

BACKGROUND: Although dopaminergic disturbances are well-known in schizophrenia, the understanding of dopamine-related brain dynamics remains limited. This study investigates the dynamic coactivation patterns (CAPs) associated with the substantia nigra (SN), a key dopaminergic nucleus, in first-episode treatment-naïve patients with schizophrenia (FES). METHODS: Resting-state fMRI data were collected from 84 FES and 94 healthy controls (HCs). Frame-wise clustering was implemented to generate CAPs related to SN activation or deactivation. Connectome features of each CAP were derived using an edge-centric method. The occurrence for each CAP and the balance ratio for antagonistic CAPs were calculated and compared between two groups, and correlations between temporal dynamic metrics and symptom burdens were explored. RESULTS: Functional reconfigurations in CAPs exhibited significant differences between the activation and deactivation states of SN. During SN activation, FES more frequently recruited a CAP characterized by activated default network, language network, control network, and the caudate, compared to HCs (F = 8.54, FDR-p = 0.030). Moreover, FES displayed a tilted balance towards a CAP featuring SN-coactivation with the control network, caudate, and thalamus, as opposed to its antagonistic CAP (F = 7.48, FDR-p = 0.030). During SN deactivation, FES exhibited increased recruitment of a CAP with activated visual and dorsal attention networks but decreased recruitment of its opposing CAP (F = 6.58, FDR-p = 0.034). CONCLUSION: Our results suggest that neuroregulatory dysfunction in dopaminergic pathways involving SN potentially mediates aberrant time-varying functional reorganizations in schizophrenia. This finding enriches the dopamine hypothesis of schizophrenia from the perspective of brain dynamics.

Temporal changes in brain morphology related to inflammation and schizophrenia: an omnigenic Mendelian randomization study.

BACKGROUND: Over the past several decades, more research focuses have been made on the inflammation/immune hypothesis of schizophrenia. Building upon synaptic plasticity hypothesis, inflammation may contribute the underlying pathophysiology of schizophrenia. Yet, pinpointing the specific inflammatory agents responsible for schizophrenia remains a complex challenge, mainly due to medication and metabolic status. Multiple lines of evidence point to a wide-spread genetic association across genome underlying the phenotypic variations of schizophrenia. METHOD: We collected the latest genome-wide association analysis (GWAS) summary data of schizophrenia, cytokines, and longitudinal change of brain. We utilized the omnigenic model which takes into account all genomic SNPs included in the GWAS of trait, instead of traditional Mendelian randomization (MR) methods. We conducted two round MR to investigate the inflammatory triggers of schizophrenia and the resulting longitudinal changes in the brain. RESULTS: We identified seven inflammation markers linked to schizophrenia onset, which all passed the Bonferroni correction for multiple comparisons (bNGF, GROA(CXCL1), IL-8, M-CSF, MCP-3 (CCL7), TNF-ß, CRP). Moreover, CRP were found to significantly influence the linear rate of brain morphology changes, predominantly in the white matter of the cerebrum and cerebellum. CONCLUSION: With an omnigenic approach, our study sheds light on the immune pathology of schizophrenia. Although these findings need confirmation from future studies employing different methodologies, our work provides substantial evidence that pervasive, low-level neuroinflammation may play a pivotal role in schizophrenia, potentially leading to notable longitudinal changes in brain morphology.

Dysconnectivity of the brain functional network and abnormally expressed peripheral transcriptional profiles in patients with anxious depression.

BACKGROUND: Major depressive disorder (MDD) is a heterogeneous mental disorder, and accompanying anxiety symptoms, known as anxious depression (AD), are the most common subtype. However, the pathophysiology of AD may be distinct in depressed patients without anxiety (NAD) and remains unknown. This study aimed to investigate the relationship between functional connectivity and peripheral transcriptional profiles in patients with AD and NAD. METHODS: Functional imaging data were collected to identify differences in functional networks among patients with AD (n = 66), patients with NAD (n = 115), and healthy controls (HC, n = 200). The peripheral transcriptional data were clustered as co-expression modules, and their associations with AD, AND, and HC were analyzed. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses of the genes in the significant module were performed. Correlation analysis was performed to identify functional network-associated gene co-expression modules. RESULTS: A network was identified which consisted of 23 nodes and 28 edges that were significantly different among three sample groups. The regions of the network were located in temporal and occipital lobe. Two gene co-expression modules were shown to be associated with NAD, and one of which was correlated with the disrupted network in the AD group. The biological function of this module was enriched in immune regulation pathways. CONCLUSION: The results suggested that immune-related mechanisms were associated with functional networks in AD.

Abnormal functional connectivity within the prefrontal cortex is associated with multiple plasma lipid species in major depressive disorder.

BACKGROUND: Abnormalities in functional connectivity (FC) in major depressive disorder (MDD) have been widely reported. Analysis of the relationship between FC and plasma lipid profiles would be meaningful in the exploration of pathophysiological mechanisms and helpful for the identification of biomarkers for MDD. METHODS: Patients with MDD (n = 49) and healthy controls (HC, n = 87) were recruited. Resting-state functional magnetic resonance imaging (rs-fMRI) data were collected for FC construction. The plasma lipid profiles were acquired using ultra-performance liquid chromatography (UPLC) and mass spectrometry (MS) analysis and clustered as co-expression modules. The differential FC and lipid modules between HCs and patients with MDD were identified, and then the association between FC and lipid co-expression modules was analyzed using correlation analysis. The modules associated molecular function was explored using metabolite set enrichment analysis (MSEA). RESULTS: MDD-associated FC and lipid co-expression modules were identified. One module was associated with FC values between the right orbital part of the middle frontal gyrus and the opercular part of the left inferior frontal gyrus, which was enriched in lipid sets of diacylglycerols and fatty alcohols; another module was associated with FC values between the right middle frontal gyrus and the right anterior cingulate and paracingulate gyri, which was enriched in lipid sets of glycerophosphocholines and glycerophosphoethanolamines. CONCLUSION: Our results indicated that abnormal FC in the prefrontal cortex is associated with multiple plasma lipid species, which may provide novel clues for exploring the pathophysiology of MDD.

Frontostriatal circuitry and the tryptophan kynurenine pathway in major psychiatric disorders.

RATIONALE: An imbalance of the tryptophan kynurenine pathway (KP) commonly occurs in psychiatric disorders, though the neurocognitive and network-level effects of this aberration are unclear. OBJECTIVES: In this study, we examined the connection between dysfunction in the frontostriatal brain circuits, imbalances in the tryptophan kynurenine pathway (KP), and neurocognition in major psychiatric disorders. METHODS: Forty first-episode medication-naive patients with schizophrenia (SCZ), fifty patients with bipolar disorder (BD), fifty patients with major depressive disorder (MDD), and forty-two healthy controls underwent resting-state functional magnetic resonance imaging. Plasma levels of KP metabolites were measured, and neurocognitive function was evaluated. Frontostriatal connectivity and KP metabolites were compared between groups while controlling for demographic and clinical characteristics. Canonical correlation analyses were conducted to explore multidimensional relationships between frontostriatal circuits-KP and KP-cognitive features. RESULTS: Patient groups shared hypoconnectivity between bilateral ventrolateral prefrontal cortex (vlPFC) and left insula, with disorder-specific dysconnectivity in SCZ related to PFC, left dorsal striatum hypoconnectivity. The BD group had higher anthranilic acid and lower xanthurenic acid levels than the other groups. KP metabolites and ratios related to disrupted frontostriatal dysconnectivity in a transdiagnostic manner. The SCZ group and MDD group separately had high-dimensional associations between KP metabolites and cognitive measures. CONCLUSIONS: The findings suggest that KP may influence cognitive performance across psychiatric conditions via frontostriatal dysfunction.

The Role of Total White Blood Cell Count in Antipsychotic Treatment for Patients with Schizophrenia.

BACKGROUND: Total white blood cell count (TWBCc), an index of chronic and low-grade inflammation, is associated with clinical symptoms and metabolic alterations in patients with schizophrenia. The effect of antipsychotics on TWBCc, predictive values of TWBCc for drug response, and role of metabolic alterations require further study. METHODS: Patients with schizophrenia were randomized to monotherapy with risperidone, olanzapine, quetiapine, aripiprazole, ziprasidone, perphenazine or haloperidol in a 6-week pharmacological trial. We repeatedly measured clinical symptoms, TWBCc, and metabolic measures (body mass index, blood pressure, waist circumference, fasting blood lipids and glucose). We used mixed-effect linear regression models to test whether TWBCc can predict drug response. Mediation analysis to investigate metabolic alteration effects on drug response. RESULTS: At baseline, TWBCc was higher among patients previously medicated. After treatment with risperidone, olanzapine, quetiapine, perphenazine, and haloperidol, TWBCc decreased significantly (p < 0.05). Lower baseline TWBCc predicted greater reductions in Positive and Negative Syndrome Scale (PANSS) total and negative scores over time (p < 0.05). We found significant mediation of TWBCc for effects of waist circumference, fasting low-density lipoprotein cholesterol, and glucose on reductions in PANSS total scores and PANSS negative subscale scores (p < 0.05). CONCLUSION: TWBCc is affected by certain antipsychotics among patients with schizophrenia, with decreases observed following short-term, but increases following long-term treatment. TWBCc is predictive of drug response, with lower TWBCc predicting better responses to antipsychotics. It also mediates the effects of certain metabolic measures on improvement of negative symptoms. This indicates that the metabolic state may affect clinical manifestations through inflammation.

Differential effects of sleep deprivation on behavior and microglia in a brain-region-specific manner in young and aged male mice.

Microglia, resident immune cells in the central nervous system, constantly monitor the state of the surrounding brain activity. The animal model induced by sleep deprivation (SD) is widely used to study the pathophysiological mechanisms of insomnia and bipolar disorder. However, it remains unclear whether SD affects behaviors in young and aged male mice and microglia in various brain regions. In this study, we confirmed brain region-specific changes in microglial density and morphology in the accumbens nucleus (Acb), amygdala (AMY), cerebellum (Cb), corpus callosum (cc), caudate putamen, hippocampus (HIP), hypothalamus (HYP), medial prefrontal cortex (mPFC), and thalamus (TH) of young mice. In addition, the density of microglia in old mice was higher than that in young mice. Compared with young mice, old mice showed a markedly increased microglial size, decreased total length of microglial processes, and decreased maximum length. Importantly, we found that 48-h SD decreased microglial density and morphology in old mice, whereas SD increased microglial density and morphology in most observed brain regions in young mice. SD-induced hyperactivity was observed only in young mice but not in old mice. Moreover, microglial density (HIP, AMY, mPFC, CPu) was significantly positively correlated with behaviors in SD- and vehicle-treated young mice. Contrarily, negative correlations were shown between the microglial density (cc, Cb, TH, HYP, Acb, AMY) and behaviors in vehicle-treated young and old mice. These results suggest that SD dysregulates the homeostatic state of microglia in a region- and age-dependent manner. Microglia may be involved in regulating age-related behavioral responses to SD.

Dynamic structure-function coupling across three major psychiatric disorders.

BACKGROUND: Convergent evidence has suggested atypical relationships between brain structure and function in major psychiatric disorders, yet how the abnormal patterns coincide and/or differ across different disorders remains largely unknown. Here, we aim to investigate the common and/or unique dynamic structure-function coupling patterns across major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SZ). METHODS: We quantified the dynamic structure-function coupling in 452 patients with psychiatric disorders (MDD/BD/SZ = 166/168/118) and 205 unaffected controls at three distinct brain network levels, such as global, meso-, and local levels. We also correlated dynamic structure-function coupling with the topological features of functional networks to examine how the structure-function relationship facilitates brain information communication over time. RESULTS: The dynamic structure-function coupling is preserved for the three disorders at the global network level. Similar abnormalities in the rich-club organization are found in two distinct functional configuration states at the meso-level and are associated with the disease severity of MDD, BD, and SZ. At the local level, shared and unique alterations are observed in the brain regions involving the visual, cognitive control, and default mode networks. In addition, the relationships between structure-function coupling and the topological features of functional networks are altered in a manner indicative of state specificity. CONCLUSIONS: These findings suggest both transdiagnostic and illness-specific alterations in the dynamic structure-function relationship of large-scale brain networks across MDD, BD, and SZ, providing new insights and potential biomarkers into the neurodevelopmental basis underlying the behavioral and cognitive deficits observed in these disorders.

Association of elevated levels of peripheral complement components with cortical thinning and impaired logical memory in drug-naïve patients with first-episode schizophrenia.

Schizophrenia has been linked to polymorphism in genes encoding components of the complement system, and hyperactive complement activity has been linked to immune dysfunction in schizophrenia patients. Whether and how specific complement components influence brain structure and cognition in the disease is unclear. Here we compared 52 drug-naïve patients with first-episode schizophrenia and 52 healthy controls in terms of levels of peripheral complement factors, cortical thickness (CT), logical memory and psychotic symptoms. We also explored the relationship between complement factors with CT, cognition and psychotic symptoms. Patients showed significantly higher levels of C1q, C4, factor B, factor H, and properdin in plasma. Among patients, higher levels of C3 in plasma were associated with worse memory recall, while higher levels of C4, factor B and factor H were associated with thinner sensory cortex. These findings link dysregulation of specific complement components to abnormal brain structure and cognition in schizophrenia.

Multivariate classification based on large-scale brain networks during early abstinence predicted lapse among male detoxified alcohol-dependent patients.

Identifying biomarkers to predict lapse of alcohol-dependence (AD) is essential for treatment and prevention strategies, but remains remarkably challenging. With an aim to identify neuroimaging features for predicting AD lapse, 66 male AD patients during early-abstinence (baseline) after hospitalized detoxification underwent resting-state functional magnetic resonance imaging and were then followed-up for 6 months. The relevance-vector-machine (RVM) analysis on baseline large-scale brain networks yielded an elegant model for differentiating relapsing patients (n = 38) from abstainers, with the area under the curve of 0.912 and the accuracy by leave-one-out cross-validation of 0.833. This model captured key information about neuro-connectome biomarkers for predicting AD lapse.

Neural variability in three major psychiatric disorders.

Across the major psychiatric disorders (MPDs), a shared disruption in brain physiology is suspected. Here we investigate the neural variability at rest, a well-established behavior-relevant marker of brain function, and probe its basis in gene expression and neurotransmitter receptor profiles across the MPDs. We recruited 219 healthy controls and 279 patients with schizophrenia, major depressive disorder, or bipolar disorders (manic or depressive state). The standard deviation of blood oxygenation level-dependent signal (SDBOLD) obtained from resting-state fMRI was used to characterize neural variability. Transdiagnostic disruptions in SDBOLD patterns and their relationships with clinical symptoms and cognitive functions were tested by partial least-squares correlation. Moving beyond the clinical sample, spatial correlations between the observed patterns of SDBOLD disruption and postmortem gene expressions, Neurosynth meta-analytic cognitive functions, and neurotransmitter receptor profiles were estimated. Two transdiagnostic patterns of disrupted SDBOLD were discovered. Pattern 1 is exhibited in all diagnostic groups and is most pronounced in schizophrenia, characterized by higher SDBOLD in the language/auditory networks but lower SDBOLD in the default mode/sensorimotor networks. In comparison, pattern 2 is only exhibited in unipolar and bipolar depression, characterized by higher SDBOLD in the default mode/salience networks but lower SDBOLD in the sensorimotor network. The expression of pattern 1 related to the severity of clinical symptoms and cognitive deficits across MPDs. The two disrupted patterns had distinct spatial correlations with gene expressions (e.g., neuronal projections/cellular processes), meta-analytic cognitive functions (e.g., language/memory), and neurotransmitter receptor expression profiles (e.g., D2/serotonin/opioid receptors). In conclusion, neural variability is a potential transdiagnostic biomarker of MPDs with a substantial amount of its spatial distribution explained by gene expressions and neurotransmitter receptor profiles. The pathophysiology of MPDs can be traced through the measures of neural variability at rest, with varying clinical-cognitive profiles arising from differential spatial patterns of aberrant variability.

Assisting schizophrenia diagnosis using clinical electroencephalography and interpretable graph neural networks: a real-world and cross-site study.

Schizophrenia (SCZ) is a chronic and serious mental disorder with a high mortality rate. At present, there is a lack of objective, cost-effective and widely disseminated diagnosis tools to address this mental health crisis globally. Clinical electroencephalogram (EEG) is a noninvasive technique to measure brain activity with high temporal resolution, and accumulating evidence demonstrates that clinical EEG is capable of capturing abnormal SCZ neuropathology. Although EEG-based automated diagnostic tools have obtained impressive performance on individual datasets, the transportability of potential EEG biomarkers in cross-site real-world application is still an open question. To address the challenges of small sample sizes and population heterogeneity, we develop an advanced interpretable deep learning model using multimodal clinical EEG features and demographic information as inputs to graph neural networks, and further propose different transfer learning strategies to adapt to different clinical scenarios. Taking the disease discrimination of health control (HC) and SCZ with 1030 participants as a use case, our model is trained on a small clinical dataset (N = 188, Chinese) and enhanced using a large-scale public dataset (N = 508, American) of adult participants. Cross-site validation from an independent dataset of adult participants (N = 157, Chinese) produced stable performance, with AUCs of 0.793-0.852 and accuracies of 0.786-0.858 for different SCZ prevalence, respectively. In addition, cross-site validation from another dataset of adolescent boys (N = 84, Russian) yielded an AUC of 0.702 and an accuracy of 0.690. Moreover, feature visualization further revealed that the ranking of feature importance varied significantly among different datasets, and that EEG theta and alpha band power appeared to be the most significant and translational biomarkers of SCZ pathology. Overall, our promising results demonstrate the feasibility of SCZ discrimination using EEG biomarkers in multiple clinical settings.

Decreased plasma neuropeptides in first-episode schizophrenia, bipolar disorder, major depressive disorder: associations with clinical symptoms and cognitive function.

Background: There is an urgent need to identify differentiating and disease-monitoring biomarkers of schizophrenia, bipolar disorders (BD), and major depressive disorders (MDD) to improve treatment and management. Methods: We recruited 54 first-episode schizophrenia (FES) patients, 52 BD patients, 35 MDD patients, and 54 healthy controls from inpatient and outpatient clinics. α-Melanocyte Stimulating Hormone (α-MSH), ß-endorphin, neurotensin, orexin-A, oxytocin, and substance P were investigated using quantitative multiplex assay method. Psychotic symptoms were measured using the Brief Psychiatric Rating Scale (BPRS) and Positive and Negative Syndrome Scale (PANSS), manic symptoms using the Young Mania Rating Scale (YMRS), and depressive symptoms using 17 item-Hamilton Depression Rating Scale (HAMD). We additionally measured cognitive function by using a battery of tests given to all participants. Results: α-MSH, neurotensin, orexin-A, oxytocin, and substance P were decreased in the three patient groups compared with controls. Neurotensin outperformed all biomarkers in differentiating patient groups from controls. There were no significant differences for 6 neuropeptides in their ability to differentiate between the three patient groups. Higher neurotensin was associated with better executive function across the entire sample. Lower oxytocin and higher substance p were associated with more psychotic symptoms in FES and BD groups. ß-endorphin was associated with early morning wakening symptom in all three patient groups. Conclusion: Our research shows decreased circulating neuropeptides have the potential to differentiate severe mental illnesses from controls. These neuropeptides are promising treatment targets for improving clinical symptoms and cognitive function in FES, BD, and MDD.

Depletion of microglia with PLX3397 attenuates MK-801-induced hyperactivity associated with regulating inflammation-related genes in the brain.

Acute administration of MK-801 (dizocilpine), an N-methyl-D-aspartate receptor (NMDAR) antagonist, can establish animal models of psychiatric disorders. However, the roles of microglia and inflammation-related genes in these animal models of psychiatric disorders remain unknown. Here, we found rapid elimination of microglia in the prefrontal cortex (PFC) and hippocampus (HPC) of mice following administration of the dual colony-stimulating factor 1 receptor (CSF1R)/c-Kit kinase inhibitor PLX3397 (pexidartinib) in drinking water. Single administration of MK-801 induced hyperactivity in the open-field test (OFT). Importantly, PLX3397-induced depletion of microglia prevented the hyperactivity and schizophrenia-like behaviors induced by MK-801. However, neither repopulation of microglia nor inhibition of microglial activation by minocycline affected MK-801-induced hyperactivity. Importantly, microglial density in the PFC and HPC was significantly correlated with behavioral changes. In addition, common and distinct glutamate-, GABA-, and inflammation-related gene (116 genes) expression patterns were observed in the brains of PLX3397- and/or MK-801-treated mice. Moreover, 10 common inflammation-related genes ( CD68, CD163, CD206, TMEM119, CSF3R, CX3CR1, TREM2, CD11b, CSF1R, and F4/80) with very strong correlations were identified in the brain using hierarchical clustering analysis. Further correlation analysis demonstrated that the behavioral changes in the OFT were most significantly associated with the expression of inflammation-related genes ( NLRP3, CD163, CD206, F4/80, TMEM119, and TMEM176a), but not glutamate- or GABA-related genes in PLX3397- and MK-801-treated mice. Thus, our results suggest that microglial depletion via a CSF1R/c-Kit kinase inhibitor can ameliorate the hyperactivity induced by an NMDAR antagonist, which is associated with modulation of immune-related genes in the brain.

Down-regulated miR-16-2 in peripheral blood is positively correlated with decreased bilateral insula volume in patients with major depressive disorder.

BACKGROUND: The downregulated microRNA-16-2-3p (miR-16-2) had been believed to be associated with major depressive disorder (MDD). This study aimed to investigate the potential of miR-16-2 as a biomarker for MDD by analysing its expression levels, furthermore, to explore the relationship between miR-16-2, clinical symptoms and alterations in grey matter volume (GMV) in MDD patients. METHODS: Real-time quantitative polymerase chain reaction (RT-qPCR) was used to detect the expression level of miR-16-2 in 48 drug-naïve patients with MDD and 50 healthy controls (HCs). We conducted ROC curve analysis to assess the diagnostic value of miR-16-2 in MDD, and evaluated its ability to predict antidepressant response by reassessing depressive and anxiety symptoms after treatment. Voxel-based morphometry was carried out to explore alterations in regional GMV that may be associated with MDD. Pearson analysis was used to explore the relationship between miR-16-2 expression, clinical symptoms, and altered GMV in the brains of MDD patients. RESULTS: We found that MDD patients had significantly downregulated miR-16-2 expression, which was negatively correlated with HAMD-17 and HAMA-14 scores, and had great diagnostic value for MDD (AUC = 0.806, 95 % CI: 0.721-0.891). In addition, MDD patients had significantly lower GMV in the bilateral insula and left superior temporal gyrus (STG_L) than HCs. GMV reduction in the bilateral insula was found to be correlated with miR-16-2 expression. CONCLUSIONS: Our findings support the potential value of miRNA-16-2 as a biomarker for MDD. It also suggests that miRNA-16-2 may be associated with abnormal insula and involved in pathophysiological mechanisms of MDD.