NONO regulates multiple cytokine production in sepsis via the ERK1/2 signaling pathway.

The massive release of pro-inflammatory cytokines is a crucial step in triggering the inflammatory cascade in sepsis. Exploring the key molecules regulating the expression and release of multiple cytokines has important value for revealing the mechanism of the cytokine storm in sepsis. This study aimed to investigate the role of multifunctional nuclear protein non-POU domain containing octamer-binding protein (NONO) in the sepsis cytokine storm and to elucidate the underlying mechanism. We found that NONO expression in tissues and cells of sepsis mice was significantly upregulated. Downregulation of NONO expression inhibited the mRNA expression of multiple cytokines, including IL-6, IL-1ß, MCP-1, MIP-1α, and MIP-1ß in inflammatory cells from mice and human leukemic monocyte-THP1 cells challenged with lipopolysaccharide (LPS), and significantly decreased the level of these cytokines and TNF-α in the supernatant of THP1 cells challenged by LPS. Nono knockout also reduced the levels of TNF-α, IL-6, MIP-1α, and MIP-1ß in serum, alleviated hepatocyte edema, and improved the survival rate of sepsis mice. Reduced NONO expression decreased the phospho-ERK1/2 level in inflammatory cells from sepsis mice or THP1 cells challenged by LPS. Phospho-ERK1/2 inhibitor decreased the mRNA expression and concentration of cytokines in the culture supernatant of LPS-induced THP1 cells, similar to the effect of NONO knockdown. After LPS challenge, the levels of phospho-ERK1/2 and NONO were increased, with obvious colocalization in the nucleus and vesicular-like organelles in macrophages. NONO knockdown decreased nuclear translocation of phospho-ERK1/2 in LPS-challenged THP1 cells. These results suggest that NONO is a potentially critical molecule involved in multiple cytokine production in sepsis. Upregulated NONO in sepsis may promote the expression and release of multiple cytokines to participate in a sepsis cytokine storm by promoting ERK1/2 phosphorylation.

The influence of TNIK gene polymorphisms on risperidone response in a Chinese Han population.

Aim: To investigate whether the TNIK gene affects risperidone treatment outcomes in the Chinese population. Methods: A total of 148 unrelated inpatients who received risperidone for six weeks were enrolled. The selected single nucleotide polymorphisms (SNPs; rs2088885, rs7627954 and rs13065441) were genotyped using the MassARRAY® SNP IPLEX platform. Results: The analysis showed that one novel SNP of TNIK, rs7627954, had a significant association with the response to risperidone (χ2 = 4.472; p = 0.034). This work also identified rs2088885 as significantly associated with risperidone response (χ2 = 5.257; p = 0.022). The result revealed that the rs2088885-rs7627954 C-T haplotype was more prevalent in good responders than in poor responders (p = 0.0278). Conclusion: This study revealed that the rs2088885 and rs7627954 SNPs of TNIK are associated with risperidone treatment response.

TNIK influence the effects of antipsychotics on Wnt/ß-catenin signaling pathway.

RationaleTraf2- and Nck-interacting kinase (TNIK), a member of germinal center kinase (GCK) family, has been implicated as a risk factor in schizophrenia and bipolar disorder as well as the action of antipsychotics. TNIK is an essential activator of Wnt/ß-catenin signaling pathway which has been identified involved in the mechanism underlying the effects of antipsychotics. Thus, the effects of TNIK on antipsychotics may be achieved by influencing Wnt/ß-catenin signaling pathway proteins.Objectives and methodsIn the current study, the effects of up- or downregulated TNIK on ß-catenin, T-cell factor 4 (TCF-4), glycogen synthase kinase-3ß (GSK3ß), and phosphorylated GSK3ß (p-GSK3ß) were examined in the human glioma U251 cells. Then, we observed the effects of antipsychotics (clozapine and risperidone) on the above proteins and evaluated the role of differentially expressed TNIK on antipsychotic-treated cell groups.ResultsThe result showed that clozapine treatment decreased ß-catenin and TCF-4 levels in U251 cells, and risperidone had the similar effects on ß-catenin and p-GSK3ß. The downregulated TNIK using siRNA impeded the regulation of antipsychotics on Wnt pathway proteins via increasing the expression levels of TCF-4, ß-catenin, or p-GSK3ß, whereas the upregulated TNIK made no significant change.ConclusionsThe influence of TNIK on the effects of antipsychotics may be partly through Wnt/ß-catenin signaling pathway.

Two Novel Loci of RELN Associated With Antipsychotics Response in Chinese Han Population.

BACKGROUND: There are great individual differences in the drug responses; however, there are few prognostic drug response biomarkers available. RELN is one of the more extensively examined schizophrenia candidate genes. The purpose of this study was to determine whether RELN can affect antipsychotics response in the Chinese population. This may lead to the discovery of relevant novel drug response markers. METHODS: The unrelated 260 Chinese Han inpatients with schizophrenia were enrolled in the present study. The enrolled subjects have been prescribed antipsychotic medication during the study. A total of 15 SNPs of RELN were genotyped by MassARRAY® platform. The association of the RELN gene with therapeutic response to antipsychotics was analyzed based on sex and age at onset. RESULTS: Two novel SNPs of RELN were found to be associated with antipsychotic treatment response (rs155333, p = 0.010 and rs6465938, p = 0.049) at nominal significance threshold, but not after multiple correction. Our study also revealed highly significant association of a haplotype consisting of three SNPs (rs362814-rs362626-rs2237628) with antipsychotic treatment response. Even after permutation, the p-value indicated significant association (rs362814-rs362626-rs2237628: ACT, χ2 = 6.353, p = 0.0117, permuted p = 0.04). Furthermore, a novel SNP, rs2535764, was found to be associated with antipsychotic response under overdominant genetic model at a marginal significant level of 0.046 (C/T vs. C/C + T/T: p = 0.046, AIC = 314.7, BIC = 321.6). CONCLUSION: Our data indicated that RELN can affect antipsychotic treatment outcomes in the Chinese population. SNPs of RELN could be used as predictive biomarkers for future personalized medicine of antipsychotic drug treatment. However, none of the three novel SNPs (rs155333, rs6465938, and rs2535764) remained significant after Bonferroni correction. Therefore, validation is needed in larger pharmacogenetic studies.