FcγRIIA expression accelerates nephritis and increases platelet activation in systemic lupus erythematosus

Melki, Imène; Allaeys, Isabelle; Tessandier, Nicolas; Mailhot, Benoit; Cloutier, Nathalie; Campbell, Robert A.; Rowley, Jesse W.; Salem, David; Zufferey, Anne; Laroche, Audrée; Lévesque, Tania; Patey, Natalie; Rauch, Joyce; Lood, Christian; Droit, Arnaud; McKenzie, Steven E.; Machlus, Kellie R.; Rondina, Matthew T.; Lacroix, Steve; Fortin, Paul R.; Boilard, Éric

doi:10.1182/blood.2020004974

Cited by 34 publications

(33 citation statements)

References 76 publications

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“…FCGR2A , formerly known as CD32, plays an important role in the clearance of immune complexes by phagocytic cells such as macrophages and neutrophils. Prior studies have demonstrated strong evidence that FCGR2A is not only involved in immune system activities but also with autoimmunity ( 17 , 18 ). Based on the above findings, we can infer subtype 1 may be related to an autoimmune response targeting bile ducts which result into BA.…”

Section: Discussionmentioning

confidence: 99%

Unsupervised Clustering Reveals Distinct Subtypes of Biliary Atresia Based on Immune Cell Types and Gene Expression

et al. 2021

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BackgroundBiliary atresia (BA) is a severe cholangiopathy of early infancy that destroys cholangiocytes, obstructs ductular pathways and if left untreated, culminates to liver cirrhosis. Mechanisms underlying the etiological heterogeneity remain elusive and few studies have attempted phenotyping BA. We applied machine learning to identify distinct subtypes of BA which correlate with the underlying pathogenesis.MethodsThe BA microarray dataset GSE46995 was downloaded from the Gene Expression Omnibus (GEO) database. Unsupervised hierarchical cluster analysis was performed to identify BA subtypes. Then, functional enrichment analysis was applied and hub genes identified to explore molecular mechanisms associated with each subtype. An independent dataset GSE15235 was used for validation process.ResultsBased on unsupervised cluster analysis, BA patients can be classified into three distinct subtypes: Autoimmune, Viral and Embryonic subtypes. Functional analysis of Subtype 1 correlated with Fc Gamma Receptor (FCGR) activation and hub gene FCGR2A, suggesting an autoimmune response targeting bile ducts. Subtype 2 was associated with immune receptor activity, cytokine receptor, signaling by interleukins, viral protein interaction, suggesting BA is associated with viral infection. Subtype 3 was associated with signaling and regulation of expression of Robo receptors and hub gene ITGB2, corresponding to embryonic BA. Moreover, Reactome pathway analysis showed Neutrophil degranulation pathway enrichment in all subtypes, suggesting it may result from an early insult that leads to biliary stasis.ConclusionsThe classification of BA into different subtypes improves our current understanding of the underlying pathogenesis of BA and provides new insights for future studies.

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Section: Discussionmentioning

confidence: 99%

Unsupervised Clustering Reveals Distinct Subtypes of Biliary Atresia Based on Immune Cell Types and Gene Expression

et al. 2021

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“…SLE is an autoimmune disease that is characterized by the production of autoantibodies and multiorgan damage, especially nephritis 30‐32 . Previous studies have shown that Dex is able to reduce ANA and anti‐dsDNA antibody levels in MRL/lpr mice 29 .…”

Section: Discusionmentioning

confidence: 99%

Dexamethasone reduces autoantibody levels in MRL/lpr mice by inhibiting Tfh cell responses

Shen

Xue

Zhang

et al. 2021

J Cellular Molecular Medi

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Previous studies have shown that dexamethasone (Dex) reduces the levels of anti‐nuclear (ANA) and anti‐dsDNA antibodies in MRL/lpr mice (a mouse model of SLE). However, the effect of Dex on T follicular helper (Tfh) cells is less documented. Here, using the MRL/lpr mouse model, we investigated the influence of Dex on Tfh cells and potential underlying mechanisms. The data showed that the proportion of Tfh cells, identified as CD4+CXCR5+ICOS+, CD4+CXCR5+PD‐1+ or CD4+BCL‐6+ cells, markedly decreased after treatment with the Dex, in both Balb/c mice and MRL/lpr mice. Dex significantly inhibited IL‐21 expression at both the mRNA and the protein levels. Dex also significantly reduced the proportion of germinal centre B cells and decreased serum IgG, IgG2a/b and IgA levels. Moreover, a positive correlation between the proportion of Tfh cells (CD4+CXCR5+ICOS+, CD4+CXCR5+PD‐1+ or CD4+BCL‐6+) and autoantibodies was observed. Dex significantly increased the Prdm1 and Stat5b mRNA expression and decreased the Bcl‐6 and c‐Maf mRNA expression of CD4+T cells. In brief, Dex inhibited the Tfh development, which relies on many other transcription factors in addition to Bcl‐6. Our data indicate that Dex can be used as a Tfh cell inhibitor in SLE.

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“…The seed node of this cluster is FCGR2A (also known as FcγRIIA), which is expressed in human platelets. The expression of FcγRIIA by transgenic technology in lupus mice can trigger major changes in the platelet transcriptome and cause lung and kidney thrombosis 39 . Cluster 4 contains 26 nodes and 104 edges, with a score of 8.16.…”

Section: Resultsmentioning

confidence: 99%

Reveals of candidate active ingredients in Justicia and its anti-thrombotic action of mechanism based on network pharmacology approach and experimental validation

Hong

Zhang

et al. 2021

Sci Rep

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Thrombotic diseases seriously threaten human life. Justicia, as a common Chinese medicine, is usually used for anti-inflammatory treatment, and further studies have found that it has an inhibitory effect on platelet aggregation. Therefore, it can be inferred that Justicia can be used as a therapeutic drug for thrombosis. This work aims to reveal the pharmacological mechanism of the anti-thrombotic effect of Justicia through network pharmacology combined with wet experimental verification. During the analysis, 461 compound targets were predicted from various databases and 881 thrombus-related targets were collected. Then, herb-compound-target network and protein–protein interaction network of disease and prediction targets were constructed and cluster analysis was applied to further explore the connection between the targets. In addition, Gene Ontology (GO) and pathway (KEGG) enrichment were used to further determine the association between target proteins and diseases. Finally, the expression of hub target proteins of the core component and the anti-thrombotic effect of Justicia’s core compounds were verified by experiments. In conclusion, the core bioactive components, especially justicidin D, can reduce thrombosis by regulating F2, MMP9, CXCL12, MET, RAC1, PDE5A, and ABCB1. The combination of network pharmacology and the experimental research strategies proposed in this paper provides a comprehensive method for systematically exploring the therapeutic mechanism of multi-component medicine.

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FcγRIIA expression accelerates nephritis and increases platelet activation in systemic lupus erythematosus

Cited by 34 publications

References 76 publications

Unsupervised Clustering Reveals Distinct Subtypes of Biliary Atresia Based on Immune Cell Types and Gene Expression

Unsupervised Clustering Reveals Distinct Subtypes of Biliary Atresia Based on Immune Cell Types and Gene Expression

Dexamethasone reduces autoantibody levels in MRL/lpr mice by inhibiting Tfh cell responses

Reveals of candidate active ingredients in Justicia and its anti-thrombotic action of mechanism based on network pharmacology approach and experimental validation

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