Differential expression and alternative splicing of transcripts in orbital adipose/connective tissue of thyroid-associated ophthalmopathy

Differentially expressed genes in orbital adipose/connective tissue of thyroid-associated orbitopathy

Background

Thyroid-associated orbitopathy (TAO) is a disease associated with autoimmune thyroid disorders and it can lead to proptosis, diplopia, and vision-threatening compressive optic neuropathy. To comprehensively understand the molecular mechanisms underlying orbital adipogenesis in TAO, we characterize the intrinsic molecular properties of orbital adipose/connective tissue from patients with TAO and control individuals.

Methods

RNA sequencing analysis (RNA-seq) was performed to measure the gene expression of orbital adipose/connective tissues of TAO patients. Differentially expressed genes (DEGs) were detected and analyzed through Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and Gene Set Enrichment Analysis (GSEA). The protein-protein interaction (PPI) network was constructed using the STRING database, and hub genes were identified by the Cytoscape plug-in, cytoHubba. We validated several top DEGs through quantitative real-time polymerase chain reaction (qRT-PCR).

Results

We identified 183 DEGs in adipose tissue between TAO patients (n = 3) and control patients (n = 3) through RNA sequencing, including 114 upregulated genes and 69 downregulated genes. The PPI network of these DEGs had 202 nodes and 743 edges. PCR-based validation results of orbital adipose tissue showed multiple top-ranked genes in TAO patients (n = 4) are immune and inflammatory response genes compared with the control individual (n = 4). They include ceruloplasmin isoform x3 (CP), alkaline tissue-nonspecific isozyme isoform x1 (ALPL), and angiotensinogen (AGT), which were overrepresented by 2.27- to 6.40-fold. Meanwhile, protein mab-21-like 1 (MAB21L1), phosphoinositide 3-kinase gamma-subunit (PIK3C2G), and clavesin-2 (CLVS2) decreased by 2.6% to 32.8%. R-spondin 1 (RSPO1), which is related to oogonia differentiation and developmental angiogenesis, was significantly downregulated in the orbital muscle tissues of patients with TAO compared with the control groups (P = 0.024).

Conclusions

Our results suggest that there are genetic differences in orbital adipose-connective tissues derived from TAO patients. The upregulation of the inflammatory response in orbital fat of TAO may be consistent with the clinical phenotype like eyelid edema, exophthalmos, and excess tearing. Downregulation of MAB21L1, PIK3C2G, and CLVS2 in TAO tissue demonstrates dysregulation of differentiation, oxidative stress, and developmental pathways.

The Role of PRRC2B in Cerebral Vascular Remodeling Under Acute Hypoxia in Mice

High altitude exposure leads to various cognitive impairments. The cerebral vasculature system plays an integral role in hypoxia-induced cognitive defects by reducing oxygen and nutrition supply to the brain. RNA N6-methyladenosine (m6A) is susceptible to modification and regulates gene expression in response to environmental changes, including hypoxia. However, the biological significance of m6A in endothelial cell performance under hypoxic conditions is unknown. Using m6A-seq, RNA immunoprcipitation-seq, and transcriptomic co-analysis, the molecular mechanism of vascular system remodeling under acute hypoxia is investigated. A novel m6A reader protein, proline-rich coiled-coil 2B (PRRC2B), exists in endothelial cells. PRRC2B knockdown promoted hypoxia-induced endothelial cell migration by regulating alternative splicing of the alpha 1 chain of collagen type XII in an m6A-dependent manner and the decay of matrix metallopeptidase domain 14 and ADAM metallopeptidase domain 19 mRNA in an m6A-independent manner. In addition, conditional knockout of PRRC2B in endothelial cells promotes hypoxia-induced vascular remodeling and cerebral blood flow redistribution, thus alleviating hypoxia-induced cognitive decline. Therefore, PRRC2B is integral in the hypoxia-induced vascular remodeling process as a novel RNA-binding protein. These findings provide a new potential therapeutic target for hypoxia-induced cognitive decline.

Mechanisms of immune-related differentially expressed genes in thyroid-associated ophthalmopathy based on the GEO database

Background

We performed a differential analysis, enrichment analysis, and immune-infiltration analysis of the thyroid-associated ophthalmopathy (TAO) gene using data from the Gene Expression Omnibus (GEO) database to provide a theoretical basis for understanding the immune-related mechanisms of TAO.

Methods

We searched the GEO database for “Graves disease” and selected the genes expressed in the lacrimal gland of thyroid-related eye disease patients as the test group and the genes expressed in the lacrimal gland of normal subjects as the control group. Immune-related differentially expressed genes (irDEGs), gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, protein-protein interaction, gene-gene interaction (GGI) network, pivotal gene identification, and immune-infiltration analyses were carried out, and finally, risk-prediction models were constructed.

Results

The GSE105149 and GSE58331 data sets contained 200 DEGs, of which 15 were immune-related. In relation to the GO biological processes (BPs), the main pathways included the interleukin (IL)-27-mediated signaling pathway, the IL-35-mediated signaling pathway, cytokine activity, T helper 17 cell differentiation, the phosphatidylinositol-3-kinase and protein kinase B signaling pathway, cytokine-cytokine receptor interaction, the Janus kinase and signal transducer and activator of transcription signaling pathway, and other KEGG pathways. Cluster of differentiation (CD)4⁺ T cells, monocytes, M0 macrophages, and Mast cells were significantly elevated in TAO, while M2 macrophages were significantly reduced. In the immune cell correlation analysis, CD4⁺ T cells and naïve B cells were significantly positively correlated with activated natural killer (NK) cells, and Mast cells were positively correlated with plasma cells and negatively correlated with M2 macrophages. Risk models for a total of 6 genes (i.e., Janus kinase 1, heat shock protein 90-α, phospholipase A 2 group IIA, fibroblast growth factor 3, glucose-6-phosphate isomerase, and protein disulfide isomerase family A, member 2), were constructed, and over 100 potential targeted therapeutic agents were obtained.

Conclusions

In TAO, various types of immune cells infiltrate to different degrees, and the immune response and inflammatory response are throughout the disease. Our constructed risk-prediction models provide a reference for predicting TAO.