Wos İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/11727/4807

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    Single-Nucleotide Polymorphisms on the RYD5 Gene in Nasal Polyposis
    (2015) Ozdas, Sibel; Izbirak, Afife; Ozdas, Talih; Ozcan, Kursat Murat; Erbek, Selim S.; Koseoglu, Sabri; Dere, Huseyin; 26204469
    Nasal polyposis (NP) is a chronic inflammatory disease. Several genes play major roles in the pathophysiology of the disease. We analyzed RYD5 gene polymorphisms to determine the effect of these variants or their genetic combinations on NP. We genotyped the RYD5 gene in 434 participants (196 patients with NP and 238 controls). Data were analyzed with SPSS, SNPStats, and multifactor dimensionality reduction (MDR) software. We genotyped 10 single-nucleotide polymorphisms (SNPs) in the RYD5 gene. RYD5 (+152G>T) (p.Gly51Va) has not been reported previously. The PolyPhen and PROVEAN predicted the missense mutation as deleterious, but sorting intolerant from tolerant (SIFT) did not. In the genotype analysis, we found that four SNPs (RYD5 [-264A>G], [-103G>A], [+57-14C>T], and [+66A>G]) were significantly associated with NP. The individuals with combined genotypes of six risk alleles (RYD5-264G, -103A, +13C, +57-14T, +66G, and +279T) had significantly higher risks for NP compared with the ones with one or four risk alleles. Haplotype analysis revealed that the two haplotypes were associated with risk of NP. As indicated by MDR analysis, RYD5 (-264A>G and -103G>A) and RYD5 (-264A>G, -177C>A, and -103G>A) were the best predictive combinations and they had the highest synergistic interaction on NP. In addition, RYD5 (+13C>T) was significantly associated with increased risk of both NP with asthma and NP with allergy and asthma. Some SNPs and their combinations in the RYD5 gene are associated with increased probability for developing NP. We emphasize the importance of genetic factors on NP and NP-related clinical phenotypes.
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    Behcet's: A Disease or a Syndrome? Answer from an Expression Profiling Study
    (2016) Oguz, Ali Kemal; Yilmaz, Seda Tasir; Oygur, Cagdas Sahap; Candar, Tuba; Sayin, Irmak; Kilicoglu, Sibel Serin; Ergun, Ihsan; Ates, Askin; Ozdag, Hilal; Akar, Nejat; 26890122
    Behcet's disease (BD) is a chronic, relapsing, multisystemic inflammatory disorder with unanswered questions regarding its etiology/pathogenesis and classification. Distinct manifestation based subsets, pronounced geographical variations in expression, and discrepant immunological abnormalities raised the question whether Behcet's is "a disease or a syndrome". To answer the preceding question we aimed to display and compare the molecular mechanisms underlying distinct subsets of BD. For this purpose, the expression data of the gene expression profiling and association study on BD by Xavier et al (2013) was retrieved from GEO database and reanalysed by gene expression data analysis/visualization and bioinformatics enrichment tools. There were 15 BD patients (B) and 14 controls (C). Three subsets of BD patients were generated: MB (isolated mucocutaneous manifestations, n = 7), OB (ocular involvement, n = 4), and VB (large vein thrombosis, n = 4). Class comparison analyses yielded the following numbers of differentially expressed genes (DEGs); B vs C: 4, MB vs C: 5, OB vs C: 151, VB vs C: 274, MB vs OB: 215, MB vs VB: 760, OB vs VB: 984. Venn diagram analysis showed that there were no common DEGs in the intersection "MB vs C" boolean AND "OB vs C" boolean AND "VB vs C". Cluster analyses successfully clustered distinct expressions of BD. During gene ontology term enrichment analyses, categories with relevance to IL-8 production (MB vs C) and immune response to microorganisms (OB vs C) were differentially enriched. Distinct subsets of BD display distinct expression profiles and different disease associated pathways. Based on these clear discrepancies, the designation as "Behcet's syndrome" (BS) should be encouraged and future research should take into consideration the immunogenetic heterogeneity of BS subsets. Four gene groups, namely, negative regulators of inflammation (CD69, CLEC12A, CLEC12B, TNFAIP3), neutrophil granule proteins (LTF, OLFM4, AZU1, MMP8, DEFA4, CAMP), antigen processing and presentation proteins (CTSS, ERAP1), and regulators of immune response (LGALS2, BCL10, ITCH, CEACAM8, CD36, IL8, CCL4, EREG, NFKBIZ, CCR2, CD180, KLRC4, NFAT5) appear to be instrumental in BS immunopathogenesis.