Multiple Processes May Involve in the IgG4-RD Pathogenesis: An Integrative Study via Proteomic and Transcriptomic Analysis

Cai, Shaozhe; Chen, Yu; Lin, Shaochong; Ye, Cong; Zheng, Fang; Dong, Lingli

doi:10.3389/fimmu.2020.01795

Cited by 12 publications

(20 citation statements)

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“…Notably, IGLV2-11 and IGLV7-43 were involved in the Fc-gamma receptor-signaling pathway and were increased in Mikulicz group compared with Head and neck group in saliva ( Figure 3C ). Interestingly, “Fc-gamma receptor signaling pathway” was also detected in IgG4-RD tissue in our previous paper ( 11 ), which may suggest a potential role in the pathogenesis of IgG4-RD Mikulicz group.…”

Section: Resultsmentioning

confidence: 54%

“…In this paper, we compared the DEPs identified in our previously published proteomic plasma data (11) with the screened DEPs between IgG4-RD patients and HCs in this study, we found a number of DEPs were overlapped (Table S5). Thus, we will examine the potential of these proteins in the differential diagnosis of IgG4-RD using a larger number of IgG4-RD samples in future studies.…”

Section: Discussionmentioning

confidence: 99%

“…For example, mass spectrometry (MS) based quantitative proteomics techniques were applied to obtain accurate and comprehensive protein profile of small samples in rare disease ( 10 ). In our previous work, we detected both serologic and tissue proteasome between IgG4-RD patients and healthy controls and identified multiple processes/factors and several signaling pathways involved in IgG4-RD ( 11 ). However, those studies did not elucidate the differences between four distinct IgG4-RD phenotypes and the key molecules are unclear.…”

Section: Introductionmentioning

confidence: 99%

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Proteomic characteristics of saliva in patients with different subgroups of IgG4-RD

et al. 2022

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BackgroundImmunoglobulin G4-related disease (IgG4-RD) is a newly defined disease entity, with great heterogeneity among IgG4-RD subgroups with different organ involvement patterns. Identification of the proteomic characteristics of IgG4-RD subgroups will be critical for the understanding of the pathogenic mechanisms of IgG4-RD.MethodIn this study, we performed proteomic analysis using Tandem Mass Tags (TMT) technology with “high field” mass analyzer with improved resolution and sequencing speed to investigate the proteomic profile of saliva and plasma samples from ten untreated IgG4-RD patients and five healthy controls (HCs). Differentially expressed proteins (DEPs) were identified by “t test” function in R package. Functional enrichment analysis was used to investigate pathways enriched in IgG4-RD samples.ResultsMost salivary DEPs identified in IgG4-RD patients compared with HCs were mainly enriched in neutrophil mediated GO bioprocess. Within the comparisons between four IgG4-RD subgroups, more DEPs were identified in the comparison of Mikulicz group and Head and neck group. Among four subgroups of IgG4-RD, Head and neck group showed the most distinctive proteomic expression pattern when compared with HCs. Moreover, “Neutrophil mediated process” related GO bioprocess was commonly identified between comparisons of Mikulicz group and Head and neck group, Head and neck group and Retroperitoneal aorta group, Head and neck group and HCs, IgG4-RD patients with saliva gland involvement and those without saliva gland involvement. Key DEPs that involved in this GO bioprocess were identified. Besides, we performed proteomic analysis for plasma samples between ten IgG4-RD and five HCs and there were several DEPs identified overlapped in saliva and plasma.ConclusionWe identified multiple processes/factors and several signaling pathways in saliva that may be involved in the IgG4-RD pathogenesis.

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Section: Resultsmentioning

confidence: 54%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Proteomic characteristics of saliva in patients with different subgroups of IgG4-RD

et al. 2022

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“…[39][40][41] Four recent articles reviewing the pathogenesis of IgG4-RD were not mentioning platelets in any context. 9,35,36,38 Another significant research was performed by Cai et al 13 by Tsuboi et al) from GEO data repository for validation of their findings. 13 In both serum and tissue samples of IgG4-RD patients, Cai et al documented several platelet related terms (i.e., "Platelet activation", "Platelet degranulation", "Platelet aggregation", "Blood coagulation", "Hemostasis", and "Coagulation") to be enriched among many other titles.…”

Section: Discussionmentioning

confidence: 97%

The Hidden Footprints of Platelets in IgG4-Related Disease Pathogenesis

Oguz

Oygür

Dedeoğlu

et al. 2023

Preprint

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Platelets 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 naive 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.

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“…The Gene Expression Omnibus (GEO) database is a large repository, integrated with a series of high-throughput microarray and next-generation sequence functional genomic datasets, and is free for global researchers [12]. Up to now, GEO database have helped numerous researchers to identify key mechanisms and hub targets of cardiovascular diseases, tumors, and other diseases [13][14][15]. The regulation of a pathway often involves several genes, and there are coexpression relationships among these genes.…”

Section: Introductionmentioning

confidence: 99%

Identification of the Potential Molecular Mechanism of TGFBI Gene in Persistent Atrial Fibrillation

Guan

Liu

Huang

et al. 2022

Computational and Mathematical Methods in Medicine

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Background. Transforming growth factor beta-induced protein (TGFBI, encoded by TGFBI gene), is an extracellular matrix protein, widely expressed in variety of tissues. It binds to collagens type I, II, and IV and plays important roles in the interactions of cell with cell, collagen, and matrix. It has been reported to be associated with myocardial fibrosis, and the latter is an important pathophysiologyical basis of atrial fibrillation (AF). However, the mechanism of TGFBI in AF remains unclear. We aimed to detect the potential mechanism of TGFBI in AF via bioinformatics analysis. Methods. The microarray dataset of GSE115574 was examined to detect the genes coexpressed with TGFBI from 14 left atrial tissue samples of AF patients. TGFBI coexpression genes were then screened using the R package. Using online analytical tools, we determined the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, Gene Ontology (GO) annotation, and protein-protein interaction (PPI) network of TGFBI and its coexpression genes. The modules and hub genes of the PPI-network were then identified. Another dataset, GSE79768 was examined to verify the hub genes. DrugBank was used to detect the potential target drugs. Results. In GSE115574 dataset, a total of 1818 coexpression genes (769 positive and 1049 negative) were identified, enriched in 120 biological processes (BP), 38 cellular components (CC), 36 molecular functions (MF), and 39 KEGG pathways. A PPI-network with average 12.2-degree nodes was constructed. The genes clustered in the top module constructed from this network mainly play a role in PI3K-Akt signaling pathway, viral myocarditis, inflammatory bowel disease, and platelet activation. CXCL12, C3, FN1, COL1A2, ACTB, VCAM1, and MMP2 were identified and finally verified as the hub genes, mainly enriched in pathways like leukocyte transendothelial migration, PI3K-Akt signaling pathway, viral myocarditis, rheumatoid arthritis, and platelet activation. Pegcetacoplan, ocriplasmin, and carvedilol were the potential target drugs. Conclusions. We used microdataset to identify the potential functions and mechanisms of the TGFBI and its coexpression genes in AF patients. Our findings suggest that CXCL12, C3, FN1, COL1A2, ACTB, VCAM1, and MMP2 may be the hub genes.

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Multiple Processes May Involve in the IgG4-RD Pathogenesis: An Integrative Study via Proteomic and Transcriptomic Analysis

Cited by 12 publications

References 50 publications

Proteomic characteristics of saliva in patients with different subgroups of IgG4-RD

Proteomic characteristics of saliva in patients with different subgroups of IgG4-RD

The Hidden Footprints of Platelets in IgG4-Related Disease Pathogenesis

Identification of the Potential Molecular Mechanism of TGFBI Gene in Persistent Atrial Fibrillation

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