Bulk Gene Expression Deconvolution Reveals Infiltration of M2 Macrophages in Retinal Neovascularization

大量基因表达反卷积揭示 M2 巨噬细胞在视网膜新生血管中的浸润

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作者:Jiang-Hui Wang, Satheesh Kumar, Guei-Sheung Liu

Conclusions

This study highlights application of the gene expression deconvolution tool to identify immune cell types in inflammatory ocular diseases with transcriptomes, providing a new approach to assess changes in immune cell types in diseased ocular tissues.

Methods

Bulk RNA sequencing was performed with retinal RNA isolated from control and OIR rats. Gene set enrichment analysis (GSEA) was undertaken to identify gene sets associated with immune responses in retinal neovascularization. Bulk gene expression deconvolution analysis by CIBERSORTx was performed to identify immune cell types involved in retinal neovascularization, followed by functional enrichment analysis of differentially expressed genes (DEGs). Protein-protein interaction analysis was performed to predict the hub genes relevant to identified immune cell types. CIBERSORTx was applied to profile immune cell types in the macula of patients with both proliferative diabetic retinopathy (PDR) and diabetic macular edema using a public RNA-seq dataset.

Purpose

This study interrogated the transcriptional features and immune cellular landscape of the retinae of rats subjected to oxygen-induced retinopathy (OIR).

Results

Transcriptome analysis by GSEA revealed that the retina of OIR rats and patients with PDR is characterized by increased immunoregulatory interactions and complement cascade. Deconvolution analysis demonstrated that M2 macrophages infiltrate the retinae of OIR rats and patients with PDR. Functional enrichment analysis of DEGs in OIR rats showed that the dysregulated genes are related to leukocyte-mediated immunity and myeloid leukocyte activation. Downstream protein-protein interaction analysis revealed that several potential hub genes, including Ccl2, Itgam, and Tlr2, contribute to M2 macrophage infiltration in the ischemic retina. Conclusions: This study highlights application of the gene expression deconvolution tool to identify immune cell types in inflammatory ocular diseases with transcriptomes, providing a new approach to assess changes in immune cell types in diseased ocular tissues.

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