The rs2910164 single nucleotide polymorphism (SNP) in miR-146a has been implicated in the etiology of psoriasis in different relevant studies with contradictory conclusions and limited sample size. Therefore, the aim of this study was to undertake a systematic review and meta-analysis to estimate the association between rs2910164 SNP and psoriasis. We searched the databases of PubMed, EMBASE, Web of Science, WanFang, and Chinese National Knowledge Infrastructure (CNKI) to identify relevant literatures published before July 15, 2018. Four case–control studies including 2212 cases and 2274 healthy controls from 4 different countries met the predetermined criteria. The effect size was pooled by odds ratios (ORs) and 95% confidence intervals (95%CIs). Recessive model (CC vs CG+GG) was confirmed to be the optimal model. The results indicated that rs2910164 SNP was significantly associated with psoriasis (OR = 0.74, 95%CI 0.60–0.91, P = .004), and individuals with CC-genotype were predisposed to have decreased risk of psoriasis.
Background: To date, the fundamental pathophysiology underlying the occurrence and progression of psoriasis are still unanswered questions. Genome-wide association surveys have revealed that TNFAIP3 and TNIP1 were key biomarkers for psoriasis. Here, we intended to conduct a survey on the association between TNFAIP3 and TNIP1 gene polymorphisms and psoriasis risk. Methods: A comprehensive search of four online databases-China National Knowledge Infrastructure (CNKI), PubMed, Embase, and Cochrane Library was undertaken up to August 25, 2019. We chose allele genetic model to deal with the original data. Newcastle-Ottawa scale (NOS) was used to evaluate the risk bias of each study. The RevMan 5.3 software was used to calculate the combined odds ratio and 95% confidence interval. Results: In total, we included 13 case-control studies consist of 13,908 psoriasis patients and 20,051 controls in this work. Our results demonstrated that rs610604 in TNFAIP3 polymorphism was significantly associated with psoriasis risk using random-effect model (G vs. T, OR = 1.19, 95% CI: 1.09-1.31, P = 0.0002), and a significant association between rs17728338 in TNIP1 polymorphism and psoriasis vulnerability using fixed-effect model (A vs. G, OR = 1.69, 95% CI:1.58-1.80, P < 0.00001). Conclusions: Our findings indicated that rs610604 in TNFAIP3 and rs17728338 in TNIP1 gene polymorphisms were associated with psoriasis susceptibility.
Kaposi sarcoma (KS) is an endothelial tumor etiologically related to Kaposi sarcoma herpesvirus (KSHV) infection. The aim of our study was to screen out candidate genes of KSHV infected endothelial cells and to elucidate the underlying molecular mechanisms by bioinformatics methods. Microarray datasets GSE16354 and GSE22522 were downloaded from Gene Expression Omnibus (GEO) database. the differentially expressed genes (DEGs) between endothelial cells and KSHV infected endothelial cells were identified. And then, functional enrichment analyses of gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis were performed. After that, Search Tool for the Retrieval of Interacting Genes (STRING) was used to investigate the potential protein–protein interaction (PPI) network between DEGs, Cytoscape software was used to visualize the interaction network of DEGs and to screen out the hub genes. A total of 113 DEGs and 11 hub genes were identified from the 2 datasets. GO enrichment analysis revealed that most of the DEGs were enrichen in regulation of cell proliferation, extracellular region part and sequence-specific DNA binding; KEGG pathway enrichments analysis displayed that DEGs were mostly enrichen in cell cycle, Jak-STAT signaling pathway, pathways in cancer, and Insulin signaling pathway. In conclusion, the present study identified a host of DEGs and hub genes in KSHV infected endothelial cells which may serve as potential key biomarkers and therapeutic targets, helping us to have a better understanding of the molecular mechanism of KS.
Background: To date, The pathological mechanisms underlying the occurrence and development of psoriasis are still unanswered questions. Genome-wide association surveys have revealed that TNFAIP3 and TNIP1 were key biomarkers for psoriasis. This study aimed to investigate the association between TNFAIP3 and TNIP1 gene polymorphisms with psoriasis susceptibility.Methods Comprehensive literature search was undertook across four online databases—PubMed, Embase, Cochrane Library, and China National Knowledge Infrastructure (CNKI) up to August 25, 2019. Allele model of inheritance was used to analyze the original data. Newcastle–Ottawa scale (NOS) was used to evaluate the risk bias of each study. Pooled odds ratios and 95% confidence intervals were calculated using the RevMan 5.3 software.Results In all, 13 case-control studies comprising 13,908 psoriasis patients and 20,051 controls were identified and included in this meta-analysis. The results demonstrated that rs610604 in TNFAIP3 polymorphism was significantly associated with psoriasis risk using random effect model (G vs. T, OR = 1.19, 95% CI: 1.09–1.31, P = 0.0002), and a significant association between rs17728338 in TNIP1 polymorphism and psoriasis vulnerability using fixed effect model (A vs. G, OR = 1.69, 95% CI:1.58–1.80, P < 0.00001).Conclusions This meta-analysis indicated that rs610604 in TNFAIP3 and rs17728338 in TNIP1 gene polymorphisms were associated with psoriasis susceptibility.
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