Unraveling multi-scale neuroimaging biomarkers and molecular foundations for schizophrenia: A combined multivariate pattern analysis and transcriptome-neuroimaging association study.

AIMS: Schizophrenia is characterized by alterations in resting-state spontaneous brain activity; however, it remains uncertain whether variations at diverse spatial scales are capable of effectively distinguishing patients from healthy controls. Additionally, the genetic underpinnings of these alterations remain poorly elucidated. We aimed to address these questions in this study to gain better understanding of brain alterations and their underlying genetic factors in schizophrenia. METHODS: A cohort of 103 individuals with diagnosed schizophrenia and 110 healthy controls underwent resting-state functional MRI scans. Spontaneous brain activity was assessed using the regional homogeneity (ReHo) metric at four spatial scales: voxel-level (Scale 1) and regional-level (Scales 2-4: 272, 53, 17 regions, respectively). For each spatial scale, multivariate pattern analysis was performed to classify schizophrenia patients from healthy controls, and a transcriptome-neuroimaging association analysis was performed to establish connections between gene expression data and ReHo alterations in schizophrenia. RESULTS: The ReHo metrics at all spatial scales effectively discriminated schizophrenia from healthy controls. Scale 2 showed the highest classification accuracy at 84.6%, followed by Scale 1 (83.1%) and Scale 3 (78.5%), while Scale 4 exhibited the lowest accuracy (74.2%). Furthermore, the transcriptome-neuroimaging association analysis showed that there were not only shared but also unique enriched biological processes across the four spatial scales. These related biological processes were mainly linked to immune responses, inflammation, synaptic signaling, ion channels, cellular development, myelination, and transporter activity. CONCLUSIONS: This study highlights the potential of multi-scale ReHo as a valuable neuroimaging biomarker in the diagnosis of schizophrenia. By elucidating the complex molecular basis underlying the ReHo alterations of this disorder, this study not only enhances our understanding of its pathophysiology, but also pave the way for future advancements in genetic diagnosis and treatment of schizophrenia.

Genetic overlap between schizophrenia and cognitive performance.

Schizophrenia (SCZ), a highly heritable mental disorder, is characterized by cognitive impairment, yet the extent of the shared genetic basis between schizophrenia and cognitive performance (CP) remains poorly understood. Therefore, we aimed to explore the polygenic overlap between SCZ and CP. Specifically, the bivariate causal mixture model (MiXeR) was employed to estimate the extent of genetic overlap between SCZ (n = 130,644) and CP (n = 257,841), and conjunctional false discovery rate (conjFDR) approach was used to identify shared genetic loci. Subsequently, functional annotation and enrichment analysis were carried out on the identified genomic loci. The MiXeR analyses revealed that 9.6 K genetic variants are associated with SCZ and 10.9 K genetic variants for CP, of which 9.5 K variants are shared between these two traits (Dice coefficient = 92.8%). By employing conjFDR, 236 loci were identified jointly associated with SCZ and CP, of which 139 were novel for the two traits. Within these shared loci, 60 exhibited consistent effect directions, while 176 had opposite effect directions. Functional annotation analysis indicated that the shared genetic loci were mainly located in intronic and intergenic regions, and were found to be involved in relevant biological processes such as nervous system development, multicellular organism development, and generation of neurons. Together, our findings provide insights into the shared genetic architecture between SCZ and CP, suggesting common pathways and mechanisms contributing to both traits.

Anxiolytic effect of antidiabetic metformin is mediated by AMPK activation in mPFC inhibitory neurons.

Diabetic patients receiving the antidiabetic drug metformin have been observed to exhibit a lower prevalence of anxiety disorders, yet the precise mechanism behind this phenomenon is unclear. In our study, we found that anxiety induces a region-specific reduction in AMPK activity in the medial prefrontal cortex (mPFC). Concurrently, transgenic mice with brain-specific AMPK knockout displayed abnormal anxiety-like behaviors. Treatment with metformin or the overexpression of AMPK restored normal AMPK activity in the mPFC and mitigated social stress-induced anxiety-like behaviors. Furthermore, the specific genetic deletion of AMPK in the mPFC not only instigated anxiety in mice but also nullified the anxiolytic effects of metformin. Brain slice recordings revealed that GABAergic excitation and the resulting inhibitory inputs to mPFC pyramidal neurons were selectively diminished in stressed mice. This reduction led to an excitation-inhibition imbalance, which was effectively reversed by metformin treatment or AMPK overexpression. Moreover, the genetic deletion of AMPK in the mPFC resulted in a similar defect in GABAergic inhibitory transmission and a consequent hypo-inhibition of mPFC pyramidal neurons. We also generated a mouse model with AMPK knockout specific to GABAergic neurons. The anxiety-like behaviors in this transgenic mouse demonstrated the unique role of AMPK in the GABAergic system in relation to anxiety. Therefore, our findings suggest that the activation of AMPK in mPFC inhibitory neurons underlies the anxiolytic effects of metformin, highlighting the potential of this primary antidiabetic drug as a therapeutic option for treating anxiety disorders.

Cortical structural changes after subcortical stroke: Patterns and correlates.

Subcortical ischemic stroke can lead to persistent structural changes in the cerebral cortex. The evolution of cortical structural changes after subcortical stroke is largely unknown, as are their relations with motor recovery, lesion location, and early impairment of specific subsets of fibers in the corticospinal tract (CST). In this observational study, cortical structural changes were compared between 181 chronic patients with subcortical stroke involving the motor pathway and 113 healthy controls. The impacts of acute lesion location and early impairments of specific CSTs on cortical structural changes were investigated in the patients by combining voxel-based correlation analysis with an association study that compared CST damage and cortical structural changes. Longitudinal patterns of cortical structural change were explored in a group of 81 patients with subcortical stroke using a linear mixed-effects model. In the cross-sectional analyses, patients with partial recovery showed more significant reductions in cortical thickness, surface area, or gray matter volume in the sensorimotor cortex, cingulate gyrus, and gyrus rectus than did patients with complete recovery; however, patients with complete recovery demonstrated more significant increases in the cortical structural measures in frontal, temporal, and occipital regions than did patients with partial recovery. Voxel-based correlation analysis in these patients showed that acute stroke lesions involving the CST fibers originating from the primary motor cortex were associated with cortical thickness reductions in the ipsilesional motor cortex in the chronic stage. Acute stroke lesions in the putamen were correlated with increased surface area in the temporal pole in the chronic stage. The early impairment of the CST fibers originating from the primary sensory area was associated with increased cortical thickness in the occipital cortex. In the longitudinal analyses, patients with partial recovery showed gradually reduced cortical thickness, surface area, and gray matter volume in brain regions with significant structural damage in the chronic stage. Patients with complete recovery demonstrated gradually increasing cortical thickness, surface area, and gray-matter volume in the frontal, temporal, and occipital regions. The directions of slow structural changes in the frontal, occipital, and cingulate cortices were completely different between patients with partial and complete recovery. Complex cortical structural changes and their dynamic evolution patterns were different, even contrasting, in patients with partial and complete recovery, and were associated with lesion location and with impairment of specific CST fiber subsets.

Histone deacetylase 4 inhibition ameliorates the social deficits induced by Ephrin-B2 mutation.

Deterioration of inhibitory synapse may be an essential neurological basis underlying abnormal social behaviours. Manipulations that regulate GABAergic transmission are associated with improved behavioural phenotypes in sociability. The synaptic protein, Ephrin-B2 (EB2), plays an important role in the maintenance and reconfiguration of inhibitory synapses in the medial prefrontal cortex (mPFC). However, the inhibitory cell-type specific role of EB2 in the pathophysiology and treatment of social deficits remains unknown. As expected, we revealed that tdTomato-expressing cells were only found in GABAergic neurons instead of excitatory neurons in transgenic EB2-vGATCre mice. This result indicated that depletion of EB2 would occur in those neurons, which further contribute to social deficits. In addition, specific over-expression of mPFC EB2 restored the defective social behaviour abnormalities. These results suggest that the effect of EB2 on social deficits is anatomically and cell-type specific. More importantly, the global upregulation of HDAC4 expression was found in EB2-vGATCre mice. Significant subcellular nuclear shuttling of HDAC4 in vGAT+ neurons was examined and quantified, suggesting a role of nuclear HDAC4 in mediating the mechanism underlying EB2 impairment in vGAT+ neurons. Treatment with LMK235 led to a remarkable rescue of social deficits, thus our data revealed a new domain for the potential utility of HDAC targeting agents to treat social deficits. In conclusion, these results not only revealed a novel molecular mechanism underlying the pathophysiology of social deficits, but also suggested a potential intervention avenue for the treatment of social deficits.

Chronic restraint stress-induced depression-like behavior is mediated by upregulation of melanopsin expression in C57BL/6 mice retina.

BACKGROUND: Depression is associated with circadian disturbances in which melanopsin was a key mechanism. Further studies have demonstrated that melanopsin gene variations are associated with some depressive disorders and aberrant light can impair mood through melanopsin-expressing retinal ganglion cells (mRGCs). The goal of this study was to explore the direct relationship between depression and melanopsin. METHODS: Adult C57BL/6 male mice were physically restrained for 16 h in a 50-ml polypropylene centrifuge tube and all behavioral tests were performed after CRS treatment. Western blot analysis and immunofluorescence were used to detect melanopsin expression in the retina of C57BL/6 mice. And we observed the change of the electrophysiological function and release of glutamate of mRGCs. RESULTS: The melanopsin expression upregulate in mRGCs of chronic restraint stress (CRS)-treating mice which exhibit depression-like behavior. The frequency of blue light-induced action potentials and light-induced glutamate release mediated by melanopsin also increase significantly. This change of melanopsin is mediated by the CRS-induced glucocorticoid. CONCLUSIONS: CRS may induce the depression-like behavior in mice via glucocorticoid-melanopsin pathway. Our findings provide a novel mechanistic link between CRS-induced depression and melanopsin in mice.

Exploring neurometabolic alterations in bipolar disorder with suicidal ideation based on proton magnetic resonance spectroscopy and machine learning technology.

Bipolar disorder (BD) is associated with a high risk of suicide. We used proton magnetic resonance spectroscopy (1H-MRS) to detect biochemical metabolite ratios in the bilateral prefrontal white matter (PWM) and hippocampus in 32 BD patients with suicidal ideation (SI) and 18 BD patients without SI, identified potential brain biochemical differences and used abnormal metabolite ratios to predict the severity of suicide risk based on the support vector machine (SVM) algorithm. Furthermore, we analyzed the correlations between biochemical metabolites and clinical variables in BD patients with SI. There were three main findings: (1) the highest classification accuracy of 88% and an area under the curve of 0.9 were achieved in distinguishing BD patients with and without SI, with N-acetyl aspartate (NAA)/creatine (Cr), myo-inositol (mI)/Cr values in the bilateral PWM, NAA/Cr and choline (Cho)/Cr values in the left hippocampus, and Cho/Cr values in the right hippocampus being the features contributing the most; (2) the above seven features could be used to predict Self-rating Idea of Suicide Scale scores (r = 0.4261, p = 0.0302); and (3) the level of neuronal function in the left hippocampus may be related to the duration of illness, the level of membrane phospholipid catabolism in the left hippocampus may be related to the severity of depression, and the level of inositol metabolism in the left PWM may be related to the age of onset in BD patients with SI. Our results showed that the combination of multiple brain biochemical metabolites could better predict the risk and severity of suicide in patients with BD and that there was a significant correlation between biochemical metabolic values and clinical variables in BD patients with SI.

Widespread aberrant functional connectivity throughout the whole brain in obstructive sleep apnea.

Objective: Obstructive sleep apnea (OSA) is a sleep-related breathing disorder with high prevalence and is associated with cognitive impairment. Previous neuroimaging studies have reported abnormal brain functional connectivity (FC) in patients with OSA that might contribute to their neurocognitive impairments. However, it is unclear whether patients with OSA have a characteristic pattern of FC changes that can serve as a neuroimaging biomarker for identifying OSA. Methods: A total of 21 patients with OSA and 21 healthy controls (HCs) were included in this study and scanned using resting-state functional magnetic resonance imaging (fMRI). The automated anatomical labeling (AAL) atlas was used to divide the cerebrum into 90 regions, and FC between each pair of regions was calculated. Univariate analyses were then performed to detect abnormal FCs in patients with OSA compared with controls, and multivariate pattern analyses (MVPAs) were applied to classify between patients with OSA and controls. Results: The univariate comparisons did not detect any significantly altered FC. However, the MVPA showed a successful classification between patients with OSA and controls with an accuracy of 83.33% (p = 0.0001). Furthermore, the selected FCs were associated with nearly all brain regions and widely distributed in the whole brain, both within and between, many resting-state functional networks. Among these selected FCs, 3 were significantly correlated with the apnea-hypopnea index (AHI) and 2 were significantly correlated with the percentage of time with the saturation of oxygen (SaO2) below 90% of the total sleep time (%TST < 90%). Conclusion: There existed widespread abnormal FCs in the whole brain in patients with OSA. This aberrant FC pattern has the potential to serve as a neurological biomarker of OSA, highlighting its importance for understanding the complex neural mechanism underlying OSA and its cognitive impairment.

A distinct parabrachial-to-lateral hypothalamus circuit for motivational suppression of feeding by nociception.

The motivation to eat is not only shaped by nutrition but also competed by external stimuli including pain. How the mouse hypothalamus, the feeding regulation center, integrates nociceptive inputs to modulate feeding is unclear. Within the key nociception relay center parabrachial nucleus (PBN), we demonstrated that neurons projecting to the lateral hypothalamus (LHPBN) are nociceptive yet distinct from danger-encoding central amygdala-projecting (CeAPBN) neurons. Activation of LHPBN strongly suppressed feeding by limiting eating frequency and also reduced motivation to work for food reward. Refined approach-avoidance paradigm revealed that suppression of LHPBN, but not CeAPBN, sustained motivation to obtain food. The effect of LHPBN neurons on feeding was reversed by suppressing downstream LHVGluT2 neurons. Thus, distinct from a circuit for fear and escape responses, LHPBN neurons channel nociceptive signals to LHVGluT2 neurons to suppress motivational drive for feeding. Our study provides a new perspective in understanding feeding regulation by external competing stimuli.

TPN672: A Novel Serotonin-Dopamine Receptor Modulator for the Treatment of Schizophrenia.

TPN672 [7-(2-(4-(benzothiophen-4-yl) piperazin-1-yl)ethyl)quinolin-2(1H)-one maleate] is a novel antipsychotic candidate with high affinity for serotonin and dopamine receptors that is currently in clinical trial for the treatment of psychiatric disorders. In vitro binding study showed that TPN672 exhibited extremely high affinity for serotonin 1A receptor (5-HT1AR) (K i = 0.23 nM) and 5-HT2AR (K i = 2.58 nM) as well as moderate affinity for D3R (K i = 11.55 nM) and D2R (K i = 17.91 nM). In vitro functional assays demonstrated that TPN672 acted as a potent 5-HT1AR agonist, D2R/D3R partial agonist, and 5-HT2AR antagonist. TPN672 displayed robust antipsychotic efficacy in rodent models (e.g., blocking phencyclidine-induced hyperactivity), significantly better than aripiprazole, and ameliorated negative symptoms and cognitive deficits in the sociability test, dark avoidance response, Morris water maze test, and novel object recognition test. The results of electrophysiological experiments showed that TPN672 might inhibit the excitability of the glutamate system through activating 5-HT1AR in medial prefrontal cortex, thereby improving cognitive and negative symptoms. Moreover, the safety margin (the ratio of minimum catalepsy-inducing dose to minimum effective dose) of TPN672 was about 10-fold, which was superior to aripiprazole. In conclusion, TPN672 is a promising new drug candidate for the treatment of schizophrenia and has been shown to be more effective in attenuating negative symptoms and cognitive deficits while having lower risk of extrapyramidal symptoms and hyperprolactinemia. SIGNIFICANCE STATEMENT: TPN672 is a promising new drug candidate for the treatment of schizophrenia and has been shown to be more effective in attenuating negative symptoms and cognitive deficits while having a lower risk of extrapyramidal symptoms and hyperprolactinemia. A phase I clinical trial is now under way to test its tolerance, pharmacokinetics, and pharmacodynamic effects in human volunteers. Accordingly, the present results will have significant impact on the development of new antischizophrenia drugs.

Lack of Association Between PLA2G6 Genetic Variation and Parkinson's Disease: A Systematic Review.

BACKGROUND: The phospholipase A2 Group 6 (PLA2G6, also known as PLA2, PARK14, and iPLA2) gene encodes a group VIA calcium-independent phospholipase A2. Genetic polymorphism of PLA2G6 has been indicated to be involved in conferring susceptibility for Parkinson's disease (PD), whereas conclusive results have not been obtained. Thus, we intended to conduct a systematic review to determine if PLA2G6 genetic variation confers a greater susceptibility to PD. METHODS: All case-control studies that investigated the association of the PLA2G6 polymorphisms with the risk of PD published before 15 July 2018 were included. The literature was comprehensively searched and identified in five English databases (EBSCO, Pubmed, OVID, EMBASE and ISI Web of Knowledge) and four Chinese databases (Wanfang database, Chinese Biomedical Literature Database, China Academic Journals Database and VIP database). We performed analyses of study characteristics, heterogeneity, and forest plot in analyses analogous to dominant, codominant and additive models with the pooled odds ratio (OR) in fixed- or random-effects models as the measure of association. RESULTS: A total of 664 potentially relevant studies were retrieved with the initial search, of which eight studies fulfilled the inclusion criteria, and included 2,779 PD patients and 3,291 control participants,. Among all the reported 27 genetic variants, 15 single nucleotide polymorphisms (SNPs) were present only in patients, and only five available SNPs (rs2267369, rs140758033, c.1959T>A (Gly653Gly), rs76718524, rs199935023) were pooled in the meta-analysis. However, there was no evidence for a significant association between the five SNPs and PD risk in dominant, codominant and allele models, suggesting a lack of association between PLA2G6 genetic variation and PD susceptibility. CONCLUSION: The present study assessed the association of PLA2G6 genetic polymorphism with the risk PD, and the result strongly demonstrates that PLA2G6 polymorphism is not associated with PD susceptibility.

MVPANI: A Toolkit With Friendly Graphical User Interface for Multivariate Pattern Analysis of Neuroimaging Data.

With the rapid development of machine learning techniques, multivariate pattern analysis (MVPA) is becoming increasingly popular in the field of neuroimaging data analysis. Several software packages have been developed to facilitate its application in neuroimaging studies. As most of these software packages are based on command lines, researchers are required to learn how to program, which has greatly limited the use of MVPA for researchers without programming skills. Moreover, lacking a graphical user interface (GUI) also hinders the standardization of the application of MVPA in neuroimaging studies and, consequently, the replication of previous studies or comparisons of results between different studies. Therefore, we developed a GUI-based toolkit for MVPA of neuroimaging data: MVPANI (MVPA for Neuroimaging). Compared with other existing software packages, MVPANI has several advantages. First, MVPANI has a GUI and is, thus, more friendly for non-programmers. Second, MVPANI offers a variety of machine learning algorithms with the flexibility of parameter modification so that researchers can test different algorithms and tune parameters to identify the most suitable algorithms and parameters for their own data. Third, MVPANI also offers the function of data fusion at two levels (feature level or decision level) to utilize complementary information contained in different measures obtained from multimodal neuroimaging techniques. In this paper, we introduce this toolkit and provide four examples to demonstrate its usage, including (1) classification between patients and controls, (2) identification of brain areas containing discriminating information, (3) prediction of clinical scores, and (4) multimodal data fusion.

A Systematic Characterization of Structural Brain Changes in Schizophrenia.

A systematic characterization of the similarities and differences among different methods for detecting structural brain abnormalities in schizophrenia, such as voxel-based morphometry (VBM), tensor-based morphometry (TBM), and projection-based thickness (PBT), is important for understanding the brain pathology in schizophrenia and for developing effective biomarkers for a diagnosis of schizophrenia. However, such studies are still lacking. Here, we performed VBM, TBM, and PBT analyses on T1-weighted brain MR images acquired from 116 patients with schizophrenia and 116 healthy controls. We found that, although all methods detected wide-spread structural changes, different methods captured different information - only 10.35% of the grey matter changes in cortex were detected by all three methods, and VBM only detected 11.36% of the white matter changes detected by TBM. Further, pattern classification between patients and controls revealed that combining different measures improved the classification accuracy (81.9%), indicating that fusion of different structural measures serves as a better neuroimaging marker for the objective diagnosis of schizophrenia.

Disrupted pathways from limbic areas to thalamus in schizophrenia highlighted by whole-brain resting-state effective connectivity analysis.

BACKGROUND: Numerous neuroimaging studies have revealed that schizophrenia was characterized by wide-spread dysconnection among brain regions during rest measured by functional connectivity (FC). In contrast with FC, effective connectivity (EC) provides information about directionality of brain connections and is thus valuable in mechanistic investigation of schizophrenic brain. However, a systematic characterization of whole-brain resting-state EC (rsEC) and how it captures different information compared with resting-state FC (rsFC) in schizophrenia are still lacking. AIMS: To systematically characterize the abnormalities of rsEC, compared with rsFC, in schizophrenia, and to test its discriminative power as a neuroimaging marker for schizophrenia diagnosis. METHOD: Whole-brain rsEC and rsFC networks were constructed using resting-state fMRI data and compared between 103 patients with schizophrenia and 110 healthy participants. Pattern classifications between patients and controls based on whole-brain rsEC and rsFC were further performed using multivariate pattern analysis. RESULTS: We identified 17 rsEC significantly disrupted (mostly decreased) in patients, among which all were associated with the thalamus and 15 were from limbic areas (including hippocampus, parahippocampus and cingulate cortex) to the thalamus. In contrast, abnormal rsFC were widely distributed in the whole brain. The classification accuracies for distinguishing patients and controls using whole-brain rsEC and rsFC patterns were 78.6% and 82.7%, respectively, and was further improved to 84.5% when combining rsEC and rsFC. CONCLUSIONS: Schizophrenia is featured by disrupted 'limbic areas-to-thalamus' rsEC, in contrast with diffusively altered rsFC. Moreover, both rsEC and rsFC contain valuable and complementary information which may be used as diagnostic markers for schizophrenia.

Enhanced Effective Connectivity From Ipsilesional to Contralesional M1 in Well-Recovered Subcortical Stroke Patients.

Background and Purpose: Interhemispheric imbalance may provide a framework for developing new strategies to facilitate post-stroke motor recovery especially for patients in chronic stage. Using effective connectivity analysis, we aimed to investigate interactions between the bilateral primary motor cortices (M1) and their correlations with motor function and M1-related structural and functional changes in well-recovered patients with chronic subcortical ischemic stroke. Methods: Twenty subcortical stroke patients and 20 normal controls underwent multimodal magnetic resonance imaging (MRI) examinations. During the movement of the affected hand, functional MRI was used to calculate the M1 activation and M1-M1 effective connectivity. Diffusion tensor imaging was used to compute the fractional anisotropy (FA) of the affected corticospinal tract (CST) and M1-M1 anatomical connection. After intergroup comparisons, we tested whether the altered M1-M1 effective connectivity was correlated with the motor function, M1 activation and FA of the affected CST and M1-M1 anatomical connection in patients. Results: Compared to normal controls, stroke patients exhibited increased excitatory effective connectivity from ipsilesional to contralesional M1 and increased ipsilesional M1 activation; however, they showed reduced FA values in the affected CST and M1-M1 anatomical connection. The increased effective connectivity was positively correlated with motor score and the FA of the M1-M1 anatomical connection, but not with the M1 activation or the FA of the affected CST in these patients. Conclusions: These findings suggest that the enhancement of M1-M1 effective connectivity from ipsilesional to contralesional hemisphere depends on the integrity of the underlying M1-M1 anatomical connection (i.e., less deficits of the M1-M1 anatomical connection, greater enhancement of the corresponding effective connectivity), and such M1-M1 effective connectivity enhancement plays a supportive role in motor function in chronic subcortical stroke.

Macrophage migration inhibitory factor mediates metabolic dysfunction induced by atypical antipsychotic therapy.

Atypical antipsychotics are highly effective antischizophrenic medications but their clinical utility is limited by adverse metabolic sequelae. We investigated whether upregulation of macrophage migration inhibitory factor (MIF) underlies the insulin resistance that develops during treatment with the most commonly prescribed atypical antipsychotic, olanzapine. Olanzapine monotherapy increased BMI and circulating insulin, triglyceride, and MIF concentrations in drug-naive schizophrenic patients with normal MIF expression, but not in genotypic low MIF expressers. Olanzapine administration to mice increased their food intake and hypothalamic MIF expression, which led to activation of the appetite-related AMP-activated protein kinase and Agouti-related protein pathway. Olanzapine also upregulated MIF expression in adipose tissue, which reduced lipolysis and increased lipogenic pathways. Increased plasma lipid concentrations were associated with abnormal fat deposition in liver and skeletal muscle, which are important determinants of insulin resistance. Global MIF-gene deletion protected mice from olanzapine-induced insulin resistance, as did intracerebroventricular injection of neutralizing anti-MIF antibody, supporting the role of increased hypothalamic MIF expression in metabolic dysfunction. These findings uphold the potential pharmacogenomic value of MIF genotype determination and suggest that MIF may be a tractable target for reducing the metabolic side effects of atypical antipsychotic therapy.

Serum IL-1ra, a novel biomarker predicting olanzapine-induced hypercholesterolemia and hyperleptinemia in schizophrenia.

Olanzapine (OLZ) is efficacious whereas leads to adverse metabolic effects thus lead to higher risk of cardiovascular diseases (CVD) on schizophrenia. Cytokines have been found associated with metabolic disorders. Therefore, pretreatment prediction of OLZ-induced adverse metabolic effects is urgently needed. To investigate if baseline cytokine levels could become biomarkers for pathogenesis of schizophrenia or prediction for OLZ-induced adverse metabolic effects, we recruited 75 participants, including 23 schizophrenia inpatients, who were antipsychotic-free over the past 6 months or first episode and drug-naive and 52 matched health controls, in our prospective cohort study and cross-sectional study. We simultaneously examined 7 serum cytokine levels (IFN-γ, IL-1ra, IL-1ß, IL-8, TNF-α, MCP-1, VEGF) before OLZ treatment by using liquid suspension array technique and obtained clinical correlates at 4-week intervals in total 8 weeks. The psychopathology was assessed with the Positive and Negative Symptom Scale (PANSS). The metabolic parameters were BMI, TG, total cholesterol, LDL, HDL, ApoA1, ApoB, lipoprotein a, fasting glucose, HbA1c, insulin, and leptin. At baseline, IL-1ra and MCP-1 levels in schizophrenia were significantly higher than health controls (t = 4.55, P = 0.0001, t = 3.08 P = 0.003). BMI, fasting insulin, cholesterol, triglyceride, LDL, ApoB and leptin were significantly increased in patients with schizophrenia after 8 weeks of olanzapine treatment. Correlation analysis showed that the baseline IL-1ra level were significantly correlated with the increased levels of cholesterol (P = 0.004), LDL (P = 0.005), ApoB (P = 0.018) and leptin (P = 0.010), but not with the increased BMI, insulin or triglycerides. Further stepwise multiple linear regression analysis indicated that IL-1ra levels prior to treatment remained significantly associated with increased levels of cholesterol, LDL, ApoB and leptin. Above all, higher IL-1ra and MCP-1 levels may be biomarkers indicating pathogenesis of schizophrenia. Higher serum levels of IL-1ra may predict subsequent higher possibility of hypercholesterolemia and hyperleptinemia following OLZ treatment in schizophrenia patients.

Increased plasma leptin as a novel predictor for psychopathological depressive symptoms in chronic schizophrenia.

BACKGROUND: Depressive symptoms are often seen in schizophrenia. The overlap in presentation makes it difficult to distinguish depressive symptoms from the negative symptoms of schizophrenia. The adipokine leptin was found to be altered in both depression and schizophrenia. There are few studies focusing on the prediction of leptin in diagnosis and evaluation of depressive symptoms in schizophrenia. OBJECTIVEAIMS: To assess the plasma leptin level in patients with schizophrenia and its relationships with depressive symptoms. METHODS: Cross-sectional studies were applied to (1) compare the levels of plasma leptin between schizophrenia (n=74) and healthy controls (n=50); and (2) investigate the relationship between plasma leptin levels and depressive subscores. RESULTS: (1) Plasma leptin levels were significantly higher in patients with schizophrenia than in healthy controls. (2) Correlation analysis revealed a significant negative association between leptin levels and the depressed factor scores on the Positive and Negative Syndrome Scale (PANSS). (3) Stepwise multiple regression analyses identified leptin as an influencing factor for depressed factor score on PANSS. CONCLUSION: Leptin may serve as a predictor for the depressive symptoms of chronic schizophrenia.

Pretreatment Serum MCP-1 Level Predicts Response to Risperidone in Schizophrenia.

BACKGROUND: Schizophrenia is a chronic debilitating disease. The pathogenesis and treatment may be associated with inflammatory cytokines. There are few studies focusing on the prediction of cytokines in response to antipsychotics. AIM: To investigate whether cytokines would predict response to antipsychotics. METHODS: Cross-sectional and natural observational cohort studies were applied to:(1) compare the baseline levels of serum IL-1ß, TNF-α and MCP-1 between schizophrenia (n=64) and healthy controls (n=53); (2) To investigate the impact of baseline cytokines to psychopathology following olanzapine and risperidone monotherapy. RESULTS: (1) Baseline MCP-1 level of patients with schizophrenia was significantly higher than healthy controls (t=2.62, p=0.010), while no significance was found in IL-1ß (t=1.43, p=0.154) and TNF-α (t=0.79, p=0.434); (2) Pretreatment level of MCP-1 significantly correlated with PANSS-G reduction following 4 weeks' of risperidone monotherapy (r =-0.658; p<0.001) but not olanzapine monotherapy (r =-0.031; p=0.855); (3) Further stepwise multiple linear regression analysis indicated that higher MCP-1 level prior to treatment was a significant predictor of less PANSS-G reduction in schizophrenia patients following risperidone monotherapy (adjusted R2= 0.409, ß = -0.658, p <0.001), but not in the olanzapine group. CONCLUSION: MCP-1 may play a role in the pathogenesis of schizophrenia. Pretreatment level of MCP-1 may serve as a biomarker indicating response to risperidone treatment.

Novel CHOP activator LGH00168 induces necroptosis in A549 human lung cancer cells via ROS-mediated ER stress and NF-κB inhibition.

AIM: C/EBP homologous protein (CHOP) is a transcription factor that is activated at multiple levels during ER stress and plays an important role in ER stress-induced apoptosis. In this study we identified a novel CHOP activator, and further investigated its potential to be a therapeutic agent for human lung cancer. METHODS: HEK293-CHOP-luc reporter cells were used in high-throughput screening (HTS) to identify CHOP activators. The cytotoxicity against cancer cells in vitro was measured with MTT assay. The anticancer effects were further examined in A549 human non-small cell lung cancer xenograft mice. The mechanisms underlying CHOP activation were analyzed using luciferase assays, and the anticancer mechanisms were elucidated in A549 cells. RESULTS: From chemical libraries of 50 000 compounds, LGH00168 was identified as a CHOP activator, which showed cytotoxic activities against a panel of 9 cancer cell lines with an average IC50 value of 3.26 µmol/L. Moreover, administration of LGH00168 significantly suppressed tumor growth in A549 xenograft bearing mice. LGH00168 activated CHOP promoter via AARE1 and AP1 elements, increased DR5 expression, decreased Bcl-2 expression, and inhibited the NF-κB pathway. Treatment of A549 cells with LGH00168 (10 µmol/L) did not induce apoptosis, but lead to RIP1-dependent necroptosis, accompanied by cell swelling, plasma membrane rupture, lysosomal membrane permeabilization, MMP collapse and caspase 8 inhibition. Furthermore, LGH00168 (10 and 20 µmol/L) dose-dependently induced mito-ROS production in A549 cells, which was reversed by the ROS scavenger N-acetyl-L-cysteine (NAC, 10 mmol/L). Moreover, NAC significantly diminished LGH00168-induced CHOP activation, NF-κB inhibition and necroptosis in A549 cells. CONCLUSION: LGH00168 is a CHOP activator that inhibits A549 cell growth in vitro and lung tumor growth in vivo.