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Previous studies have explored associations between Tumour Necrosis factor-Alpha (TNF-a) polymorphisms and Schizophrenia. Their results were controversial. We conducted a meta-analysis to clarify the association between TNF-a − 308 G/A(rs1800629), −1031T/C(rs1799964), −863C/A(rs1800630) and −857 C/T (rs1799724) polymorphisms and Schizophrenia. All the studies that investigated the association between TNF-a polymorphisms and Schizophrenia published before 15 October 2020 were included in. The literature were comprehensively searched and identified in 2 English databases and 2 Chinese databases. The odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated. For −1031 T/C polymorphism, at the overall analysis, significantly decreased Schizophrenia risk was found in T allele in the allele model (p = 0.006, OR = 0.88) and increased Schizophrenia risk was found in TC + CC genotype in the dominant model (p = 0.005, OR = 1.17). Similarly, the same results were obtained when pooled analyses were included in high-quality studies (allele model: p = 0.005, OR = 0.86; dominant model: p = 0.007, OR = 1.20). In addition, when stratified by ethnicity, the results showed that in allele model, the T allele decreased Schizophrenia risk in East Asian (p = 0.031, OR = 0.90). The association may most likely result from less-credible, rather than from true associations or biological factors on the TNF-a − 1031 T/C polymorphism with Schizophrenia risk. For −1031T/C polymorphism, at the overall analysis, significantly decreased schizophrenia risk was found in T allele in the allele model, and increased schizophrenia risk was found in TC + CC genotype in the dominant model. In allele model, the T allele decreased schizophrenia risk in East Asian when stratified by ethnicity, and in the dominant model, TC + CC genotype increased schizophrenia risk in East Asian. [ABSTRACT FROM AUTHOR]

Objectives: The identification of the potential molecule targets for subsyndromal symptomatic depression (SSD) is critical for improving the effective clinical treatment on the mental illness. In the current study, we mined the genome-wide expression profiling and investigated the novel biological pathways associated with SSD. Methods: Expression of differentially expressed genes (DEGs) were analysed with microarrays of blood tissue cohort of eight SSD patients and eight healthy subjects. The gene co-expression is calculated by WGCNA, an R package software. The function of the genes was annotated by gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Results: We identified 11 modules from the 9,427 DEGs. Three co-expression modules (blue, cyan and red) showed striking correlation with the phenotypic trait between SSD and healthy controls. Gene ontology and KEGG pathway analysis demonstrated that the function of these three modules was enriched with the pathway of inflammatory response and type II diabetes mellitus. Finally, three hub genes, NT5DC1, SGSM2 and MYCBP, were identified from the blue module as significant genes. Conclusions: This first blood gene expression study in SSD observed distinct patterns between cases and controls which may provide novel insight into understanding the molecular mechanisms of SSD. [ABSTRACT FROM AUTHOR]