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Primary Sjögren's syndrome (pSS) is a systematic autoimmune disease with evidence of genetic predisposition. The IKZF1 (IKAROS family zinc finger 1 (Ikaros)) gene is located at 7p12.2, encodes a transcription factor related to chromatin remodeling, regulates lymphocyte differentiation, and has been reported to be associated with some autoimmune diseases. However, there have been no reports of an association between IKZF1 and pSS. To investigate the possibility of an association between the IKZF1 locus and pSS, we selected two single nucleotide polymorphisms (SNPs) in the IKZF1 locus, rs4917129 and rs4917014, based on a detailed analysis of genome-wide association study (GWAS) data and performed genotyping in 665 Han Chinese pSS patients and 863 healthy controls. The results of an association test showed significant association signals (rs4917129: P-value = 5.5e-4, OR (odds ratio) = 0.72, 95% CI (confidence interval) = 0.60–0.87; rs4917014: P-value = 1.2e-3, OR = 0.76, 95% CI = 0.64–0.89). A meta-analysis that combined the above results with data from previous GWAS, further confirmed these associations (rs4917129: Pmeta = 4.24e-8, ORmeta = 0.70, 95% CI = 0.61–0.79; rs4917014: Pmeta = 6.0e-8, ORmeta = 0.72, 95% CI = 0.64–0.81). A bioinformatics analysis indicated that both SNPs were located in a putative enhancer area in immune-related cell lines and tissues. A protein-protein interaction analysis found that IKZF1, together with GTF2I (an SS susceptibility gene newly identified through GWAS), could interact with histone deacetylase family proteins. In summary, this is the first study to report an association between IKZF1 and SS in Han Chinese. [ABSTRACT FROM AUTHOR]

Schizophrenia is a common psychiatric disorder with high heritability and complex genetic architecture. Genome-wide association studies (GWAS) have identified several significant loci associated with schizophrenia. However, the explained heritability is still low. Growing evidence has shown schizophrenia is attributable to multiple genes with moderate effects. In-depth mining and integration of GWAS data is urgently expected to uncover disease-related gene combination patterns. Network-based analysis is a promising strategy to better interpret GWAS to identify disease-related network modules. We performed a network-based analysis on three independent schizophrenia GWASs by using a refined analysis framework, which included a more accurate gene P-value calculation, dynamic network module searching algorithm and detailed functional analysis for the obtained modules genes. The result generated 79 modules including 238 genes, which form a highly connected subnetwork with more statistical significance than expected by chance. The result validated several reported disease genes, such as MAD1L1, MCC, SDCCAG8, VAT1L, MAPK14, MYH9 and FXYD6, and also obtained several novel candidate genes and gene-gene interactions. Pathway enrichment analysis of the module genes suggested they were enriched in several neural and immune system related pathways/GO terms, such as neurotrophin signaling pathway, synaptosome, regulation of protein ubiquitination, and antigen processing and presentation. Further crosstalk analysis revealed these pathways/GO terms were cooperated with each other, and identified several important genes, which might play vital roles to connect these functions. Our network-based analysis of schizophrenia GWASs will facilitate the understanding of genetic mechanisms of schizophrenia. [ABSTRACT FROM AUTHOR]

Background: The involvement of cytokines in schizophrenia (SZ) has been proposed in recent years and various studies have accumulated convergent lines of evidence. Among which, the role of interleukin-10 (IL-10) in SZ has been explored in a number of studies by investigating association of single nucleotide polymorphisms (SNPs) and susceptibility of SZ. However, the results are inconsistent since its power is limited by the individual sample size. To evaluate the overall effect between them, we conducted a meta-analysis by combining all available studies. Methods: Studies were searched from the database of PubMed, PsycINFO and ISI web of Knowledge up to Nov 2013. The meta-analysis was conducted based on statement of preferred reporting items for systematic reviews and meta-analyses (PRISMA). Results: Eleven studies including 6399 subjects (3129 cases and 3270 controls) were available for the meta-analysis. Among three investigated SNPs, rs1800872 was observed to be significantly associated with risk of SZ (AA vs. AC+CC, Pooled OR = 1.351, P-value  = 2.06E-04). Meanwhile, among six haplotypes of rs1800896 - rs1800871 - rs1800872, significant associations were observed in haplotype A-C-A (Pooled OR = 1.762, P-value  = 2.00E-03) and G-C-C (Pooled OR = 0.649, P-value  = 2.00E-03) for Asians. These results were still significant after adjusting for multiple comparisons. Conclusions: This meta-analysis demonstrated an SNP and two haplotypes of IL-10 significantly associated with SZ, suggesting that IL-10 might be a risk factor of SZ. [ABSTRACT FROM AUTHOR]

Background: Major depressive disorder (MDD) is a complex neuropsychiatric syndrome with high heterogeneity. There are different levels of biological components that underlie MDD and interact with each other. To uncover the disease mechanism, large numbers of studies at different levels have been conducted. There is a growing need to integrate data from multiple levels of research into a database to provide a systematic review of current research results. The cross level integration will also help bridge gaps of different research levels for further understanding on MDD. So far, there has been no such effort for MDD., Descriptions: We offer researchers a Multi-level Knowledge base for MDD (MK4MDD) to study the interesting interplay of components in the pathophysiological cascade of MDD from genetic variations to diagnostic syndrome. MK4MDD contains 2,341 components and 5,206 relationships between components based on reported experimental results obtained by diligent literature reading with manual curation. All components were well classified with careful curation and supplementary annotation. The powerful search and visualization tools make all data in MK4MDD form a cross-linked network to be applied to a broad range of both basic and applied research., Conclusions: MK4MDD aims to provide researchers with a central knowledge base and analysis platform for MDD etiological and pathophysiological mechanisms research. MK4MDD is freely available at http://mdd.psych.ac.cn.