Comparative expression profiling of Portuguese and Turkish Behçet syndrome patients: Are we looking at the same Behçet?

Background: Behçet syndrome (BS) is a multisystemic inflammatory disorder with an obscure pathogenesis. Inconsistent, sometimes contrasting immunological findings observed in BS studies and considerable geographic variation in BS’s disease expression need explanation. This study compared the gene expression profiles of Portuguese and Turkish BS patients. Methods: Publicly available transcriptome datasets from Portuguese (GSE17114) and Turkish (GSE209567) BS cohorts were retrieved and analyzed. Behçet syndrome patients were grouped as mucocutaneous, ocular, and vascular. Differentially expressed genes (DEGs) were identified using p ≤ 0.05 and fold-changes (FC) ≥1.5 and ≥2. BRB-ArrayTools for class comparisons, Venny 2.1.0 for Venn diagram analyses, Cluster 3.0 and Java Treeview for clustering, and WebGestalt for functional enrichment analyses were used. Results: During the class comparison PB versus TB (PB: Portuguese and TB: Turkish BS patients), 8024 DEGs were documented with an FC ≥2. Venn diagram analysis showed no shared genes at the intersection PB versus PC ∩ TB versus TC (PC: Portuguese and TC: Turkish controls). Both populations demonstrated decreased anti-inflammatory gene expressions, albeit with distinct gene identities. A set of 20 genes including IFI27 successfully clustered PB & TB. No enriched gene ontology terms were shared during functional enrichment analyses. Conclusion: Significant molecular differences exist between Portuguese and Turkish BS patients. Decreased expression of anti-inflammatory genes (e.g., CD69 , CLEC12A , CLC ) is common in BS. The identities of these genes are different across populations. Pro-inflammatory genes (e.g., IFI27 ) may further enhance disease severity in BS. A forthcoming era of personalized therapeutics based on molecular profiles may be approaching for BS. Specifically, CD69 for Portuguese and CLEC12A , CLC , and IFI27 genes for Turkish BS patients, may prove to be promising drug targets for BS

The Hidden Footprints of Platelets in IgG4-Related Disease Pathogenesis

AbstractPlatelets have grabbed great attention as immune cells and principal modulators of tissue remodeling besides their well-known hemostatic and vascular wall safeguarding functions. In line with this knowledge, findings indicating an excessive platelet activation have been reported in systemic sclerosis, which is an autoimmune, multisystem, fibrotic disorder. By borrowing the transcriptomic data of Nakajima et al. (GEO data repository, GSE66465) we sought a platelet contribution in immunoglobulin G4-related disease (IgG4-RD) pathogenesis, another immune-mediated, fibroinflammatory, multiorgan disease. GEO2R for class comparisons and WebGestalt for functional enrichment analyses were used. When treatment naïve IgG4-RD patients were compared with healthy controls, 268 differentially expressed genes (204 with increased and 64 with decreased expression) were detected. Enrichment analyses performed using gene ontology (Biological Process), pathway (Panther), and disease (GLAD4U) functional databases documented many significantly enriched terms relating to platelets, coagulation, and thrombosis, including “ Thrombasthenia”, “ Low on-treatment platelet reactivity”, “ High on-treatment platelet reactivity”, “ Platelet reactivity”, “ Platelet aggregation inhibition”, “ Blood platelet disorders”, “ Platelet degranulation”, “ Platelet aggregation”, and “ Platelet activation”. The enrichment ratios of these terms were found to be between 6.4 and 83.2. Together with the limited data in the relevant literature, it seems imperative to plan meticulously designed research specifically focusing on platelets’ contribution to IgG4-RD pathogenesis.</jats:p

Behcet's: A Disease or a Syndrome? Answer from an Expression Profiling Study

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

The Platelet-Specific Gene Signature in the Immunoglobulin G4-Related Disease Transcriptome

Background and Objectives: Immunoglobulin G4-related disease (IgG4-RD) is an immune-mediated, fibroinflammatory, multiorgan disease with an obscure pathogenesis. Findings indicating excessive platelet activation have been reported in systemic sclerosis, which is another autoimmune, multisystemic fibrotic disorder. The immune-mediated, inflammatory, and fibrosing intersections of IgG4-RD and systemic sclerosis raised a question about platelets’ role in IgG4-RD. Materials and Methods: By borrowing transcriptomic data from Nakajima et al. (GEO repository, GSE66465) we sought a platelet contribution to the pathogenesis of IgG4-RD. GEO2R and BRB-ArrayTools were used for class comparisons, and WebGestalt for functional enrichment analysis. During the selection of differentially expressed genes (DEGs), the translationally active but significantly low amount of platelet mRNA was specifically considered. The platelet-specific gene signature derived was used for cluster analysis of patient and control groups. Results: When IgG4-RD patients were compared with controls, 268 DEGs (204 with increased and 64 with decreased expression) were detected. Among these, a molecular signature of 22 platelet-specific genes harbored genes important for leukocyte–platelet aggregate formation (i.e., CLEC1B, GP1BA, ITGA2B, ITGB3, SELP, and TREML1) and extracellular matrix synthesis (i.e., CLU, PF4, PPBP, SPARC, and THBS1). Functional enrichment analysis documented significantly enriched terms related to platelets, including but not limited to “platelet reactivity”, “platelet degranulation”, “platelet aggregation”, and “platelet activation”. During clustering, the 22 gene signatures successfully discriminated IgG4-RD and the control and the IgG4-RD before and after treatment groups. Conclusions: Patients with IgG4-RD apparently display an activated platelet phenotype with a potential contribution to disease immunopathogenesis. If the platelets’ role is validated through further carefully designed research, the therapeutic potentials of selected conventional and/or novel antiplatelet agents remain to be evaluated in patients with IgG4-RD. Transcriptomics and/or proteomics research with platelets should take into account the relatively low amounts of platelet mRNA, miRNA, and protein. Secondary analysis of omics data sets has great potential to reveal new and valuable information

Behcet's: A Disease or a Syndrome? Answer from an Expression Profiling Study

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