AimThe aim of this study was to assess whether tumor necrosis factor alpha (TNF-α) levels are correlated with the behavioral syndrome of schizophrenia and/or metabolic abnormalities.MethodsSixty patients with first-onset schizophrenia were recruited. The concentrations of TNF-α in the cerebrospinal fluid (CSF) were determined in 22 schizophrenia patients and ten patients with nonsuppurative appendicitis using a radioimmunoassay. Physiological characteristics such as fasting blood glucose, fasting insulin, triglycerides, corrected QT interval, waist circumference, and body mass index were measured prior to CSF collection. Subjects were screened for insulin resistance using the homeostasis model assessment. The extent of positive and negative behavioral symptoms was scored using the Positive and Negative Syndrome Scale.ResultsThe CSF TNF-α levels in schizophrenic patients were significantly lower than those in the control group. The age of disease onset was positively correlated with the CSF TNF-α level using Pearson correlation analysis (r=0.37, P<0.05). There were no significant differences in CSF TNF-α levels in terms of age, duration of schizophrenia, or systolic and diastolic blood pressure. Furthermore, the CSF TNF-α levels were not significantly correlated with fasting blood glucose, fasting insulin, insulin resistance index, triglycerides, corrected QT interval, waist circumference, or body mass index. No significant correlation was found between CSF TNF-α levels and the Positive and Negative Syndrome Scale total scores or other factors scores. There were also no significant differences in CSF TNF-α levels between patients with schizophrenia types I and II.ConclusionCSF TNF-α levels are decreased in schizophrenia, although this reduction does not correlate with the psychopathology or coincident metabolic characteristics of this disease.

The etiology of major depressive disorder (MDD) involves many factors such as heredity and environment. There are very few MDD-related studies in Chinese population using twin or sib-pairs for depression-control samples. Here we used the microarray approach and compared gene expression profiling of peripheral blood lymphocytes from 6 sib-pairs discordant on lifetime history of MDD. Within sib-pair differentially expressed genes are obvious fewer in the 1st, 2nd, and 5th compared with those in the 3rd, 4th, and 6th sib-pairs. Gene expression pattern of these DEGs distinguished MDD individuals from the normal one in 3rd, 4th, and 6th sib-pair but not in the 1st, 2nd, and 5th pair, suggesting heterogeneity of different sib-pairs and somewhat commonalities among the 3rd, 4th, and 6th sib-pairs. Comprehensive protein interaction network analysis revealed two key genes PTH and FGF2 in a dominant network where the majority of the genes were significantly down-regulated. PTH was significantly down-regulated in all the sib-pairs while FGF2 was in the 3rd, 4th, and 6th sib-pairs. KEGG enrichment analysis of all the DEGs in networks showed that PTH and related genes were significantly enriched in the pathway of parathyroid hormone secretion, synthesis, and action while FGF2 and related genes were significantly enriched in the pathways of cancer and specifically breast cancer. Generally reduced expression of these genes in peripheral blood lymphocytes of MDD individuals implied their functional repression associated with MDD. Pending validation in more samples, the findings in this study provided valuable cues for understanding the potential mechanism of MDD, as well as potential markers for the diagnosis and treatment of depression in the Chinese population.

Objective: To investigate the relationship between attentional bias and the severity of depression as assessed by the TORAWARE state and physical symptoms. Methods: We enrolled 55 patients with depression and 60 healthy people. The Hamilton Depression Scale (HAMD-24), Somatic Self-Rating Scale (SSS), and the Chinese version of the Self-Rating Scale for the TORAWARE State of Neurosis (SSTN) were selected to assess the severity of psychological symptoms. Dot-probe tasks were used to detect attentional bias. We then analyzed the correlation of attentional bias with the total scores on the symptom scales. Results: The negative attentional bias and negative disengaging index scores were both greater than 0 (t = 3.15 and 2.78, respectively; all P < 0.01). The negative attention bias score was positively correlated with the SSTN and negative disengaging index scores (r = 0.29 and 0.53, respectively; all P < 0.05). SSTN score was positively correlated with the total HAMD and SSS scores (r = 0.34 and 0.38, respectively; all P < 0.05). Conclusion: There is no direct correlation between negative attentional bias and depression. It may be through the intermediate mechanism of TORAWARE state to influence symptoms.

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