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Erschienen in: BMC Ophthalmology 1/2023

Open Access 01.12.2023 | Research

Identification of immune associated potential molecular targets in proliferative diabetic retinopathy

verfasst von: Ying Gao, Min Xue, Bing Dai, Yun Tang, Jingyu Liu, Changlin Zhao, Hu Meng, Feng Yan, Xiaomin Zhu, Yan Lu, Yirui Ge

Erschienen in: BMC Ophthalmology | Ausgabe 1/2023

Abstract

Background

Diabetic retinopathy (DR) is one of the most common microvascular complications of diabetes and causes of blindness in developed countries. Our study was designed to identify immune-related genes involved in the progression of proliferative diabetic retinopathy (PDR).

Methods

The “GSE102485” dataset of neovascular membrane samples (NVMs) from type 1 and 2 diabetes mellitus patients was downloaded from the Gene Expression Omnibus database. Functional enrichment analyses, protein–protein interaction network (PPI) construction, and module analysis of immune pathways in NVMs and controls were conducted via Gene Set Enrichment Analysis and Metascape.

Results

The significantly upregulated hallmark gene sets in DR2 and DR1 groups were involved in five immune pathways. Only CCR4, CXCR6, C3AR1, LPAR1, C5AR1, and P2RY14 were not previously reported in the context of PDR molecular pathophysiology. Except for P2RY14, all of the above were upregulated in retinal samples from experimental diabetes mouse models and human retina microvascular endothelial cells (HRMECs) treated with high glucose (HG) by quantitative Real Time Polymerase Chain Reaction (qRT-PCR).

Conclusion

The genes identified herein provide insight into immune-related differential gene expression during DR progression.
Hinweise
Ying Gao, Min Xue, Bing Dai and Yun Tang are co-first authors.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Abkürzungen
DR
Diabetic retinopathy
PDR
Proliferative diabetic retinopathy
NVMs
Neovascular membrane samples
HRMECs
Human retina microvascular endothelial cells
qRT-PCR
Quantitative Real Time Polymerase Chain Reaction
PPI
Protein-protein interaction
NV
Neovascularization
DEGs
Differentially expressed genes
FVMs
Fibrovascular membranes
PGF
Placental Growth Factor
GSEA
the Gene Set Enrichment Analysis
MSigDB
the Molecular Signatures Database
NES
Normalized enrichment scores
FDR
False discovery rate
GPCRs
G protein-coupled receptors
CCR
C-C cchemokine motif receptor
CXCR
C-X-C cchemokine motif receptor
FPR
Formyl peptide receptor
PAFR
Platelet-activating factor receptor
C5aR
Component 5 receptor
BLT
Leukotriene B4 receptor
PRP-Exos
Platelet-rich plasma exosomes
ONH
Optic nerve head
LPAR1–6
Six G-coupled protein receptors
LPA
Lysophosphatidic acid
ICS
Insertion cells

Background

Diabetic retinopathy (DR), resulting from chronic hyperglycemia, is one of the most common microvascular complications of diabetes and causes of blindness among adults aged between 20 and 74 in developed countries [1, 2]. Depending on the degree of related ischemic injury and microvascular lesions, DR can be divided into two phases, non-PDR (proliferative diabetic retinopathy) and PDR [3]. DR is recognized as a microvascular, inflammatory, and neurodegenerative complication of diabetes [4], which can be triggered by mitochondrial damage, endoplasmic reticulum stress, and oxidative stress, among others [5]. However, the pathogenesis of DR has not been fully elucidated. Inflammation and angiogenesis play key roles during DR pathogenesis [6]. Thus, the morphological and molecular alterations in DR caused by these two processes are receiving great attention, becoming the focus of extensive research [7, 8].
Chronic low-grade inflammation is present during both the early and advanced stages of DR, eventually resulting in retinal vasculopathy, which is characterized by increased retinal vascular permeability and neovascularization [9, 10]. Inflammation is undoubtedly implicated in the dysregulated pathological angiogenesis during early and advanced stages of DR [11]. Neovascularization and inflammation share several common mediators and signaling pathways [11, 12]. Inflammatory responses drive angiogenic processes through the production of pro-angiogenic cytokines and growth factors [1113].
Shao et al. identified a subset of differentially expressed genes (DEGs) from both active and inactive fibrovascular membranes (FVMs) with normal retinas, which were enriched for angiogenic factors [hypoxia inducible factor-1 subunit alpha (HIF-1α) and placental growth factor (PGF)] [14]. Pathological secretion of vascular endothelial growth factor A was shown to promote the expression of pro-angiogenic transcription factors and growth factors, which in turn induced retinal neovascularization [15]. In the present study, we first analyzed an RNA-seq dataset of NVMs from PDR patients from the GEO database. We identified genes associated with the immune system in order to elucidate the role of inflammatory processes during DR pathogenesis and identify novel diagnostic and therapeutic markers for DR.

Methods

Dataset

The clinical sample dataset “GSE102485” was downloaded from GEO (http://​www.​ncbi.​nlm.​nih.​gov/​geo/​). Twenty-five samples from “GSE102485” were analyzed, including 19 samples of type 2 DR, three from type 1 DR, and three normal retina samples.

Data grouping

The 25 samples were of NVMs from PDR and were divided into three paired groups: DR2 group (type 2 PDR and normal retina), DR1 group (type 1 PDR and normal retina), and DR2 VS DR1 group (type 2 PDR and type 1 PDR).

Gene set enrichment analysis (GSEA)

The DR2 and the DR1 groups were respectively subjected to GSEA. GSEA was implemented to detect the enriched gene sets for the two paired groups respectively, so as to identify the potential hallmarks of DR. The annotated gene sets of “h.all.v7.2.symbols.gmt” in the Molecular Signatures Database (MSigDB) were selected in GSEA version 4.0.3, and 1000 times of permutations were conducted. Collapse dataset of gene symbols was termed as “no-Collapse”, and the permutation type was “phenotype”. The cut-off criteria for GSEA were as follows: normalized enrichment scores (NES) > 1.0; false discovery rate (FDR) q< 0.25; nominal p < 0.05. The minimum number of 15 genes and maximum 500 genes were set by default. All significantly enriched immune-related hallmark gene sets were collected and displayed via enrichment plots. Immune-related hub genes in the DR2 and DR1 groups were then identified using Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses.

Metascape hub gene analysis

Metascape (http://​metascape.​org) is a free website analysis tool for gene function annotation and pathway enrichment analysis [16]. We used it for process enrichment as well as pathway and protein–protein interaction (PPI) enrichment analysis of immune-related hub gene sets. The highest-scoring genes in both groups were presented in Venn diagrams (http://​bioinformatics.​psb.​ugent.​be/​webtools/​Venn/​).

Animal model and HRMECs culture

Adult C57Bl/6 J mice (male, 8 weeks old, 10–22 g), provided by the Laboratory Animal Center, Nanjing Medical University, were used in this study. Animal experiments were performed in accordance with the criteria of the National Institutes of Health guide for the care and use of laboratory animals as well as the ARRIVE guidelines. The Ethics Committee of the Affiliated Jinling Hospital of Nanjing University approved the study protocol (2021JLHDWLS-007). After housing for 24–36 h, mice were intraperitoneally administered streptozotocin (Sigma, 0.1 mg per 10 g of bodyweight) in citrate saline. Mice with blood glucose levels over 16.7 mmol/L for two consecutive weeks were considered diabetic. After 4 months, diabetic and age-matched non-diabetic mice were sacrificed via excessive intraperitoneal injection of the mixture of ketamine and xylazine, both eyes of each mouse were enucleated, and retinas were detached. Retinal samples were then moved and subjected to cryopreservation. HRMECs were purchased from American Type Culture Collection (ATCC, U.S.A.). HRMECs were cultured in endothelial cell medium (ECM, Gibco) supplemented with 10% fetal bovine serum (FBS, Gibco, U.S.A.), penicillin and streptomycin (100 U/ml) at 37 °C under 5% CO2. To detect the effect of glucose on HRMECs, the medium was further supplemented with high concentration of glucose (35.5 mM; HG) and normal concentration of glucose (5.5 mM; NG) for 24 h,respectively.

RNA isolation and qRT-PCR

Total RNA was extracted from the retinal tissue of diabetic retinopathy mouse models using TRIzol reagent (Invitrogen). Total RNA was then reverse-transcribed using a PrimeScript RT reagent Kit (Takara). Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was detected as an internal control.
Total RNA of HRMECs was extracted using TRIzol reagent (Invitrogen), and was then reverse-transcribed using a PrimeScript RT reagent Kit (Takara). The cDNA was used as the template for qRT-PCR. respectively. Actin beta (ACTB) was detected as an internal control.
The reaction mixture (20 μL) contained 1 μL cDNA template, 2 μL (10 μM) each of sense and antisense primers (designed by Primer6, Table 1), 0.1% DEPC 7 μL, and 10 μL Real-time PCR Master Mix (SYBR Green). qRT-PCR was performed on an ABI Step one plus qRT-PCR system (Applied Biosystems). qRT-PCR was performed in duplo for each sample, and dissociation curves were used to estimate the specificity of qRT-PCR products.
Table 1
Gene primer information of diabetic retinopathy mouse models and HRMECs
Gene
Forward Primer
Reverse Primer
Gene primer information of diabetic retinopathy mouse models
 C5ar1
CATACCTGCGGATGGCATTCA
GGAACACCACCGAGTAGATGAT
 CXCR6
GAGTCAGCTCTGTACGATGGG
TCCTTGAACTTTAGGAAGCGTTT
 C3AR1
TCGATGCTGACACCAATTCAA
TCCCAATAGACAAGTGAGACCAA
 LPAR1
AGCCATGAACGAACAACAGTG
CATGATGAACACGCAAACAGTG
 P2RY14
AGCAGATCATTCCCGTGTTGT
AGCCACCACTATGTTCTTGAGA
 CCR4
GGAAGGTATCAAGGCATTTGGG
GTACACGTCCGTCATGGACTT
Gene primer information of HRMECs
 C5ar1
CCATCCATCCATCCATCCATCCATC
GAGGCAGGAGAATCGCTTGAACC
 CXCR6
TGCCACTGCTCACCATGATTGTC
GGAACACAGCCATCACCAGGAAG
 C3AR1
TGAAGATGCAGCGGACAGTGAAC
GCCAAGTGAGCCAGCGAGAAG
 LPAR1
TTCAAGCGATTCTCCTGCCTAAGC
TTCAAGACCAGCCTGACCAACATG
 P2RY14
TCCCTCTACACACTGCTTTGAATGC
ACTGAACAACCTGCTCCTGAATGAC
 CCR4
GGCTCAAGTGATCCTCCCTCCTC
CCACCACCACACACCCAATGC

Statistical analysis

Data were analyzed using the unpaired Student’s t-test and one-way ANOVA for multiple comparisons in Graphpad Prism 8. Data were presented as an average of 6 SEM, unless indicated otherwise. Statistical significance was set at p < 0.05.

Results

In the DR2 phenotype, 46 out of 50 gene sets were upregulated, and 13 were significantly enriched, with a nominal p < 0.05, NES > 1.0, and FDR q<0.25. In the DR1 phenotype, 39 out of 50 gene sets were upregulated, and 11 were significantly enriched. All gene sets of the two groups are shown in Table 2 (DR2) and Table 3 (DR1). In the DR2 VS DR1 group, 28 out of 50 gene sets were upregulated in type 2 PDR, while 0 were significantly enriched, with a nominal p < 0.05, NES > 1.0, and FDR q<0.25. Twenty-two out of 50 gene sets were upregulated in type 1 PDR, and 0 were significantly enriched, with a nominal p < 0.05, NES > 1.0, and FDR q<0.25. There were no significantly enriched gene sets between the type 2 and type 1 PDR groups. Significantly upregulated immune-related hallmark gene sets in the DR2 and DR1 groups are shown in Fig. 1 (DR2) and Fig. 2 (DR1): INTERFERON_GAMMA_RESPONSE, INTERFERON_ALPHA_RESPONSE, IL6_JAK_STAT3_SIGNALING, INFLAMMATORY_RESPONSE, IL2_STAT5_SIGNALING.
Table 2
GSEA pathways up-regulated and down-regulated due to DR2 group
Gene sets
SIZE
NES
NOM p-val
FDR
q-val
Up-regulated gene sets in DR2 group
 HALLMARK_INTERFERON_GAMMA_RESPONSE
194
1.78
0.000
0.000
 HALLMARK_COAGULATION
133
1.69
0.000
0.000
 HALLMARK_INTERFERON_ALPHA_RESPONSE
95
1.69
0.000
0.000
 HALLMARK_EPITHELIAL_MESENCHYMAL_TRANSITION
198
1.68
0.000
0.000
 HALLMARK_ANGIOGENESIS
36
1.67
0.000
0.000
 HALLMARK_IL6_JAK_STAT3_SIGNALING
83
1.62
0.000
0.000
 HALLMARK_INFLAMMATORY_RESPONSE
198
1.56
0.000
0.000
 HALLMARK_ALLOGRAFT_REJECTION
195
1.53
0.000
0.000
 HALLMARK_COMPLEMENT
198
1.38
0.000
0.042
 HALLMARK_TNFA_SIGNALING_VIA_NFKB
199
1.37
0.000
0.075
 HALLMARK_IL2_STAT5_SIGNALING
197
1.35
0.000
0.085
 HALLMARK_XENOBIOTIC_METABOLISM
198
1.26
0.000
0.234
 HALLMARK_APOPTOSIS
158
1.25
0.000
0.244
Down-regulated gene sets in the DR2 group
 HALLMARK_PANCREAS_BETA_CELLS
40
−1.91
0.000
0.000
Table 3
GSEA pathways up-regulated and down-regulated due to DR1 group
Gene sets
SIZE
NES
NOM p-val
FDR q-val
Up-regulated gene sets in DR1 group
 HALLMARK_COAGULATION
133
2.17
0.000
0.000
 HALLMARK_IL2_STAT5_SIGNALING
197
1.81
0.000
0.122
 HALLMARK_ANGIOGENESIS
36
1.69
0.000
0.135
 HALLMARK_IL6_JAK_STAT3_SIGNALING
83
1.68
0.000
0.116
 HALLMARK_INFLAMMATORY_RESPONSE
198
1.68
0.000
0.102
 HALLMARK_EPITHELIAL_MESENCHYMAL_TRANSITION
198
1.68
0.000
0.090
 HALLMARK_KRAS_SIGNALING_UP
194
1.58
0.000
0.130
 HALLMARK_ALLOGRAFT_REJECTION
195
1.54
0.000
0.118
 HALLMARK_INTERFERON_GAMMA_RESPONSE
194
1.47
0.000
0.135
 HALLMARK_APICAL_SURFACE
44
1.44
0.000
0.150
 HALLMARK_INTERFERON_ALPHA_RESPONSE
95
1.37
0.000
0.173
Down-regulated gene sets in the DR1 group
 HALLMARK_PANCREAS_BETA_CELLS
40
−1.67
0.000
0.187
 HALLMARK_SPERMATOGENESIS
131
− 1.46
0.000
0.211
GO and KEGG enrichment analyses of all immune-related hub genes.
GO functional and KEGG pathway enrichment analyses of all immune-related hub genes for the DR2 and DR1 groups were carried out in Metascape.
The overlaps in these gene lists were significantly improved by considering overlaps between genes sharing the same enriched ontology terms. Circus plots for DR2 and DR1 are shown in Fig. 3 (A, B) and Table 4.
Table 4
Statistics of input gene lists
Name
Description
Total
Unique
The DR2 group
 list1
HALLMARK_IL2_STAT5_SIGNALING
115
115
 list2
HALLMARK_IL6_JAK_STAT3_SIGNALING
62
62
 list3
HALLMARK_INFLAMMATORY_RESPONSE
133
133
 list4
HALLMARK_INTERFERON_ALPHA_RESPONSE
69
69
 list5
HALLMARK_INTERFERON_GAMMA_RESPONSE
149
149
The DR1 group
 list1
HALLMARK_IL2_STAT5_SIGNALING
115
115
 list2
HALLMARK_IL6_JAK_STAT3_SIGNALING
58
58
 list3
HALLMARK_INFLAMMATORY_RESPONSE
125
125
 list4
HALLMARK_INTERFERON_ALPHA_RESPONSE
72
72
 list5
HALLMARK_INTERFERON_GAMMA_RESPONSE
141
141
The top 20 GO enriched terms for the DR2 group are shown in Fig. 4, separated into biological process (17 items), molecular function (2 items), and cellular component (1 item) categories. For biological process, the enriched GO terms included 0002237 (response to molecule of bacterial origin), 0032103 (positive regulation of response to external stimulus), 0046649 (lymphocyte activation), 0002274 (myeloid leukocyte activation), 0002521 (leukocyte differentiation), 0001819 (positive regulation of cytokine production), 0002697 (regulation of immune effector process), 0098542 (defense response to other organism), 0034341 (response to interferon-gamma), 0002253 (activation of immune response), 0060759 (regulation of response to cytokine stimulus), 0034612 (response to tumor necrosis factor), 0050730 (regulation of peptidyl-tyrosine phosphorylation), 0043068 (positive regulation of programmed cell death), 0008285 (negative regulation of cell proliferation), 0050900 (leukocyte migration), and 0006875 (cellular metal ion homeostasis). For molecular function, there were two GO terms, namely 0005126 (cytokine receptor binding) and 0004896 (cytokine receptor activity). 0098552 (side of membrane) was the only enriched GO item in the cellular component category in DR2.
The top 20 KEGG pathways identified for the DR2 group are shown in Fig. 4 (C, D), including hsa04080 (Neuroactive ligand-receptor interaction), ko05150 (Staphylococcus aureus infection), ko05323 (Rheumatoid arthritis), ko04064 (NF-kappa B signaling pathway), ko05144 (Malaria), ko04640 (Hematopoietic cell lineage), ko04650 (Natural killer cell mediated cytotoxicity), ko04672 (Intestinal immune network for IgA production), ko05145 (Toxoplasmosis), ko04060 (Cytokine–cytokine receptor interaction), hsa05202 (Transcriptional misregulation in cancer), hsa04668 (TNF signaling pathway), hsa04630 (JAK-STAT signaling pathway), hsa05162 (Measles), hsa05169 (Epstein-Barr virus infection), hsa05163 (human cytomegalovirus infection), ko04380 (Osteoclast differentiation), hsa04062 (Chemokine signaling pathway), ko05132 (Salmonella infection), and hsa05205 (Proteoglycans in cancer).
The 20 most enriched GO items for the DR1 group are shown in Fig. 5 (A, B). For biological process (17 items), these included 0002697 (regulation of immune effector process), 0009617 (response to bacterium), 0001819 (positive regulation of cytokine production), 0007159 (leukocyte cell-cell adhesion), 0032103 (positive regulation of response to external stimulus), 0002274 (myeloid leukocyte activation), 0008285 (negative regulation of cell proliferation), 0031349 (positive regulation of defense response), 0060759 (regulation of response to cytokine stimulus), 0034341 (response to interferon-gamma), 0060337 (type I interferon signaling pathway), 0050730 (regulation of peptidyl-tyrosine phosphorylation), 0043410 (positive regulation of MAPK cascade), 0009611 (response to wounding), 0050900 (leukocyte migration), 0043068 (positive regulation of programmed cell death), and 0006875 (cellular metal ion homeostasis). For molecular function, there was only one item, GO: 0004896 (cytokine receptor activity). For cellular component, there were two enriched GO items, 0098552 (side of membrane) and 0043235 (receptor complex).
The top 20 KEGG pathways in the DR1 group are shown in Fig. 5 (C, D), including hsa05166 (Human T-cell leukemia virus 1 infection), ko04672 (Intestinal immune network for lgA production), ko04064 (NF-kappa B signaling pathway), ko05144 (Malaria), ko05321 (Inflammatory bowel disease), ko04151 (PI3K-Akt signaling pathway), hsa05205 (Proteoglycans in cancer), ko05202 (Transcriptional misregulation in cancer), ko04060 (Cytokine–cytokine receptor interaction), hsa04630 (JAK-STAT signaling pathway), ko04640 (Hematopoietic cell lineage), hsa04668 (TNF signaling pathway), hsa05169 (Epstein-Barr virus infection), ko05164 (Influenza A), hsa04062 (Chemokine signaling pathway), ko05132 (Salmonella infection), ko04920 (Adipocytokine signaling pathway), hsa04217 (necroptosis), hsa05170 (human immunodeficiency virus 1 infection), and hsa04080 (Neuroactive ligand-receptor interaction).
PPI analysis was performed using Metascape. The PPI network and the top three MCODE components were identified for DR2 (Fig. 6A, B) and DR1 (Fig. 6C, D) gene sets. The significant MCODE components were involved in the chemokine signaling pathway and cytokine–cytokine receptor interaction in the PPI network. The 17 genes with highest scores in both groups were CCR1, CCR7, CCL5, CCL20, CXCL1, CXCL3, CXCL8, CXCL9, CXCL10, FPR1, GNAI3, CCR4, CXCR6, C3AR1, LPAR1, C5AR1, and P2RY14.

qRT-PCR analysis of diabetic mouse retinal tissue and HRMECs treated with HG

qRT-PCR results indicated that the expression of CCR4, C5ar1, CXCR6, C3AR1, and LPAR1 was upregulated in both diabetic retina (DR) and HRMECs treated with HG, when compared to expression in the naive retina (NR) and NG. Notably, P2RY14 was significantly downregulated (Fig. 7. A, and B, p < 0.05).

Discussion

In this study, we first separately analyzed immune-related gene expression in NVMs from PDR of both types in order to narrow down and identify potential genes implicated in PDR pathogenesis. The most significantly enriched pathways were mainly implicated in chemokine signaling and cytokine-cytokine receptor interactions. The current study provides better insight into the immune mechanisms underlying DR progression, with potential implications for diagnosis and treatment.
Chemokines are critical mediators of immune cell migration, with essential roles in immune surveillance, development, and inflammation. Chemokines exert their effects via transmembrane G protein-coupled receptors (GPCRs) present on a wide variety of cell types. Upon binding, conformational changes in trimeric G proteins trigger intracellular signaling pathways, promoting cellular movement and activation [17]. Based on the locations of conserved cysteine residues near the amino terminus, chemokines are divided into four subfamilies: C-C chemokine motif receptor (CCR), C-X-C chemokine motif receptor (CXCR), CX3CR, and XCR [18]. GPCRs regulate leukocyte trafficking and promote immune responses, mediating cell chemotaxis. GPCRs can be categorized into classical and chemokine subfamilies according to the ligand source. Classical GPCRs include formyl peptide receptors (FPR1, FPR2, and FPR3), platelet-activating factor receptor (PAFR), activated complement component 5 receptor (C5aR), and leukotriene B4 receptors (BLT1 and BLT2) [19].
In our study, 11 chemokines and their cognate receptors were identified as related to the pathogenesis of DR, including CCR1, CCR7, CCL5, CCL20, CXCL1, CXCL3, CXCL8, CXCL9, CXCL10, FPR1, and GNAI3.
CSF3, COL18A1, CXCR2, CCR1, FGF23, CXCL11, and IL13 were previously reported as related to PDR pathogenesis based on a Laplacian heat diffusion algorithm [20]. Therapeutic strategies targeting MIP1γ to inhibit CCR1-related signaling in retinal endothelial cells might have potential against DR progression [21]. CCR7 significantly enhanced neovascularization and the non-perfusion area in oxygen-induced retinopathy [22]. CCL5 could be measured in the blood, vitreous body, retina, aqueous humor, and tears of patients with DR [23]. C-C-chemokine receptor 6 is the only receptor interacting with CCL20. Treatment with CCL20-neutralizing antibodies or PG inhibits CCL20 expression, alleviating retinal degeneration and inflammation [24]. CCL20, CXCL2, and other core genes have been described as playing key roles in DR pathogenesis [25]. Activation of the P2X7R-NLRP3 pathway significantly increased the production of TNF-α, CXCL-1, CSF-1, IL-6, IL-1β, IL-18, and other pro-inflammatory cytokines in retinal microglia [26]. CXCL3, VEGF, CXCL5, and other inflammatory mediators were increased in DR and retinopathy of prematurity [27]. CXCL8 (also known as IL-8) is known to be elevated in the vitreous humor of patients with DR [28, 29]. Autocrine CXCL9 and CXCL10 signaling in retinal endothelial cells were enhanced in DR [30]. Recent research suggests that the level of CXCL10/IP-10 in normal vitreous humor was significantly higher than that in serum. Further, CXCL10/IP-10 levels in the vitreous humor of proliferative vitroretinopathy and PDR patients were much higher than that in patients with rhegmatogenous retinal detachment. CXCL10/IP-10 was also significantly upregulated in patients with active PDR compared to those with inactive disease [31]. CXCL10 derived from platelet-rich plasma exosomes can cause retinal endothelial injury, which was considerably alleviated by antagonizing CXCL10 with a neutralizing antibody [32]. UPARAR is a peptide inhibitor of the uPAR system, which could reverse the upregulation of uPAR, FPR1, and FPR2, thus slowing DR development [33]. The GαI1/3 protein plays a key role in vascular endothelial growth factor-induced endocytosis, signal transduction, and angiogenesis. High GαI1/3 protein expression was previously reported in the proliferative retinal tissue of PDR patients [34].
CCR4, CXCR6, C3AR1, LPAR1, C5AR1, and P2RY14 have been implicated in a number of eye diseases, but not in PDR. Upregulated CCR4 expression was previously observed in keratoconjunctivitis, glaucoma, and uveitis [3537], in addition to its downregulation in dry eyes [38]. The IFN-γ and IL-17 expression of CD4+ T cells was significantly increased in patients with age-related macular degeneration. IFN-γ-expressing Th1 cells and IL-17-expressing Th17 cells could be selectively enriched based on the expression of surface CCR3+, CCR4+, CCR6+ [39]. CXCR6 was upregulated in the primary culture of orbital fibroblasts from patients with Graves’ orbitopathy, following treatment with pro-inflammatory cytokines IL-1β and TNF-α [40]. Furthermore, CXCR6 expression was highly confined to memory Th1 cells, which can be categorized into activated memory Th1 and Tc1 cells secreting IFN-γ [41]. A previous study reported that CD4+ and CXCR6+ cells were decreased in T1D patients [42]. A possible reason for the reduction in CD4+ cells expressing CXCR6, CXCR3, and CCR5 could be the selective recruitment of Th1 cells into the pancreas [43]. In human T cells, intracellular C5AR1 signaling induces ROS production through the mitochondria. ROS in turn trigger assembly of the NLRP3 (NACHT, leucine-rich repeat and pyrin domain-containing protein 3) inflammasome. Inflammasome formation initiates caspase-1-dependent IL-1β secretion, which promotes IFN-γ production and Th1 differentiation in an autocrine manner. Secreted C5a/C5a-Desarg interacts with surface-expressed C5AR2, which negatively controls NLRP3 activation through a currently undetermined mechanism [44]. Further, there is growing evidence that microglia-mediated inflammatory responses are associated with deleterious effects implicated in DR [7]. In fact, increased hypertrophic amoeba-like microglia were observed in the outer retina and subretinal space of human DR patients [45]. Overactivated amoeba-like microglia lead to a dysregulation of the complement system by upregulating the expression of activators C3, CFB, C1q, and C5AR1, while downregulating that of complement inhibitors CFH, CFI, CD46, and CD93 [46]. Subsequently, microglial overactivation establishes a pro-inflammatory environment conducive to further invasion of retinal microglia and exogenous monocyte infiltration [47]. The accumulation of subretinal microglia derived paracrine factors can trigger NLRP3 inflammasome activation in the retinal pigment epithelium [48]. Studies previously showed that complement may modulate the production of inflammatory factors and angiogenic factors via C5AR on Müller cells, which are implicated in DR pathogenesis [49]. C3AR1 is considered an injury-induced neuroinflammatory factor, whose interaction with IL-10 signaling and other immune-related pathways might be a major regulator of microglial activity and neuroinflammatory function [50]. In DBA/2 J mice, significant damage occurred with in the optic nerve head (ONH) prior to in other regions of the optic nerve [51]. At the same time point, the expression of C3AR1 in the ONH increased, with no increase observed in the retina [52]. In healthy brains, cell types other than the microglia exhibited low or no expression of C3AR1 [53]. The involvement of C3AR1/C5AR1 signaling in angiogenesis was reported on day 5 in ocular and retinal angiogenesis neonatal mouse models [54]. In our study, the sampled area included the area around the optic nipple. Previous works have shown that six G-coupled protein receptors (LPAR1–6) can be activated by lysophosphatidic acid (LPA). LPA and its receptors play vital roles in the central nervous system, cancer, and macular edema [55]. A link between LPA and retinopathy was previously demonstrated, as LPA1 and LPA2 expression were significantly increased in retinal ganglion cells after retinal ischemia in adult rats, leading to LPA1-mediated retinal ganglion cell death in preterm infants. In contrast, LPAR1–3 expression of retinal pigment epithelial cells promoted retinal healing. It was suggested that LPA exerts either a neuroprotective or neurodegenerative effect on the retina by binding to different LPA receptors on different cell types [56]. ATX, AGK, and LPA1 receptors are expressed in vascular endothelial cells and stromal cells within PDR epiretinal membranes. LPA-producing enzymes or LPA were shown to play a key role in the development of PDR and PVR [57]. The expression of P2Ry14 (purinergic receptor P2Y, G-protein coupled, 14) in the trabecular meshwork is higher than that of other purine receptors, suggesting that the protein product reduces IOP in monkeys, an observation that has not been further confirmed [58]. P2Ry14 was down regulated during both oxygen-induced pathologic neovascularization and physiological angiogenesis of the retina [59]. Purine receptor P2Y14 is highly expressed in collecting tube insertion cells and mediates renal aseptic inflammation [60].
He et al. previously suggested that differential ALDH2/SIRT1 expression might be responsible for the differences in DR severity between chronic inflammation-related T1 diabetes mellitus and T2 diabetes mellitus. Retinal IL-1 and IL-6 production in the T1 diabetes mellitus group was significantly increased compared to that in the T2 diabetes mellitus group [61]. In our study, we found no significantly enriched gene sets between type 1 and type 2 PDR groups. Li et al. previously reported that the prevalence of DR in diabetes patients was affected by diabetes duration, diabetic nephropathy occurrence, and regular DR screening. Diabetes type indirectly affected DR occurrence through its influence on diabetes duration and diabetic nephropathy occurrence [62].
In the present study, we found that six immune-related genes, namely, CCR4, CXCR6, C3AR1, LPAR1, C5AR1, and P2RY14, were upregulated based on bioinformatics analysis. CCR4, C5AR1, CXCR6, C3AR1, and LPAR1 expression was further confirmed via qRT-PCR, which was not the case for P2RY14, necessitating further study. Moreover, the upregulation of LPAR1 was found to have both neuroprotective and PDR promoting properties. Therefore, whether LPAR1 acts as a protective or pathogenic factor in PDR remains unclear.

Conclusion

In summary, our findings provide insight into the molecular pathogenesis of DR, which may be of value for disease diagnosis and treatment. The roles of P2RY14 and LPAR1 in the pathogenesis of DR require further study. Our data provide a new idea for the diagnosis and treatment of DR in the future.
In our study, Nevertheless, the current study had some limitations, one being the limited number of neovascularization samples from patients with type 1 DR and the normal retina samples. We analyzed hub gene expression only via qRT-PCR, and it should be further validated via western blotting. Meanwhile, the alterations of immune-elated pathways might be explored in the future.

Acknowledgements

Not applicable.

Declarations

Animal experiments were performed in accordance with the criteria of the National Institutes of Health guide for the care and use of laboratory animals as well as the ARRIVE guidelines.
Not applicable.

Competing interests

The authors declare that they have no competing interests.
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Literatur
1.
Zurück zum Zitat Ogurtsova K, da Rocha Fernandes JD, Huang Y, Linnenkamp U, Guariguata L, Cho NH, et al. IDF diabetes atlas: global estimates for the prevalence of diabetes for 2015 and 2040. Diabetes Res Clin Pract. 2017;128:40–50.CrossRef Ogurtsova K, da Rocha Fernandes JD, Huang Y, Linnenkamp U, Guariguata L, Cho NH, et al. IDF diabetes atlas: global estimates for the prevalence of diabetes for 2015 and 2040. Diabetes Res Clin Pract. 2017;128:40–50.CrossRef
2.
Zurück zum Zitat Solomon SD, Chew E, Duh EJ, Sobrin L, Sun JK, VanderBeek BL, et al. Diabetic retinopathy: a position statement by the American Diabetes Association. Diabetes Care. 2017;40(3):412–8.CrossRef Solomon SD, Chew E, Duh EJ, Sobrin L, Sun JK, VanderBeek BL, et al. Diabetic retinopathy: a position statement by the American Diabetes Association. Diabetes Care. 2017;40(3):412–8.CrossRef
3.
Zurück zum Zitat Stitt AW, Curtis TM, Chen M, Medina RJ, McKay GJ, Jenkins A, et al. The progress in understanding and treatment of diabetic retinopathy. Prog Retin Eye Res. 2016;51:156–86.CrossRef Stitt AW, Curtis TM, Chen M, Medina RJ, McKay GJ, Jenkins A, et al. The progress in understanding and treatment of diabetic retinopathy. Prog Retin Eye Res. 2016;51:156–86.CrossRef
4.
Zurück zum Zitat Semeraro F, Cancarini A, dell'Omo R, Rezzola S, Romano MR, Costagliola C. Diabetic retinopathy: vascular and inflammatory disease. J Diabetes Res. 2015;2015:582060.CrossRef Semeraro F, Cancarini A, dell'Omo R, Rezzola S, Romano MR, Costagliola C. Diabetic retinopathy: vascular and inflammatory disease. J Diabetes Res. 2015;2015:582060.CrossRef
5.
Zurück zum Zitat Petrovski G, Kaarniranta K, Petrovic D. Oxidative stress, epigenetics, environment, and epidemiology of diabetic retinopathy. J Diabetes Res. 2017;2017:6419357.CrossRef Petrovski G, Kaarniranta K, Petrovic D. Oxidative stress, epigenetics, environment, and epidemiology of diabetic retinopathy. J Diabetes Res. 2017;2017:6419357.CrossRef
6.
Zurück zum Zitat Simo-Servat O, Hernandez C, Simo R. Usefulness of the vitreous fluid analysis in the translational research of diabetic retinopathy. Mediat Inflamm. 2012;2012:872978.CrossRef Simo-Servat O, Hernandez C, Simo R. Usefulness of the vitreous fluid analysis in the translational research of diabetic retinopathy. Mediat Inflamm. 2012;2012:872978.CrossRef
7.
Zurück zum Zitat Altmann C, Schmidt MHH. The role of microglia in diabetic retinopathy: inflammation, microvasculature defects and Neurodegeneration. Int J Mol Sci. 2018;19(1):110. Altmann C, Schmidt MHH. The role of microglia in diabetic retinopathy: inflammation, microvasculature defects and Neurodegeneration. Int J Mol Sci. 2018;19(1):110.
8.
Zurück zum Zitat Rubsam A, Parikh S, Fort PE. Role of inflammation in diabetic retinopathy. Int J Mol Sci. 2018;19(4):942. Rubsam A, Parikh S, Fort PE. Role of inflammation in diabetic retinopathy. Int J Mol Sci. 2018;19(4):942.
9.
Zurück zum Zitat Zhang W, Liu H, Rojas M, Caldwell RW, Caldwell RB. Anti-inflammatory therapy for diabetic retinopathy. Immunotherapy. 2011;3(5):609–28.CrossRef Zhang W, Liu H, Rojas M, Caldwell RW, Caldwell RB. Anti-inflammatory therapy for diabetic retinopathy. Immunotherapy. 2011;3(5):609–28.CrossRef
10.
Zurück zum Zitat Rangasamy S, McGuire PG, Das A. Diabetic retinopathy and inflammation: novel therapeutic targets. Middle East Afr J Ophthalmol. 2012;19(1):52–9.CrossRef Rangasamy S, McGuire PG, Das A. Diabetic retinopathy and inflammation: novel therapeutic targets. Middle East Afr J Ophthalmol. 2012;19(1):52–9.CrossRef
11.
Zurück zum Zitat Capitao M, Soares R. Angiogenesis and inflammation crosstalk in diabetic retinopathy. J Cell Biochem. 2016;117(11):2443–53.CrossRef Capitao M, Soares R. Angiogenesis and inflammation crosstalk in diabetic retinopathy. J Cell Biochem. 2016;117(11):2443–53.CrossRef
12.
Zurück zum Zitat Qazi Y, Maddula S, Ambati BK. Mediators of ocular angiogenesis. J Genet. 2009;88(4):495–515.CrossRef Qazi Y, Maddula S, Ambati BK. Mediators of ocular angiogenesis. J Genet. 2009;88(4):495–515.CrossRef
13.
Zurück zum Zitat Joussen AM, Poulaki V, Qin W, Kirchhof B, Mitsiades N, Wiegand SJ, et al. Retinal vascular endothelial growth factor induces intercellular adhesion molecule-1 and endothelial nitric oxide synthase expression and initiates early diabetic retinal leukocyte adhesion in vivo. Am J Pathol. 2002;160(2):501–9.CrossRef Joussen AM, Poulaki V, Qin W, Kirchhof B, Mitsiades N, Wiegand SJ, et al. Retinal vascular endothelial growth factor induces intercellular adhesion molecule-1 and endothelial nitric oxide synthase expression and initiates early diabetic retinal leukocyte adhesion in vivo. Am J Pathol. 2002;160(2):501–9.CrossRef
14.
Zurück zum Zitat Shao D, He S, Ye Z, Zhu X, Sun W, Fu W, et al. Identification of potential molecular targets associated with proliferative diabetic retinopathy. BMC Ophthalmol. 2020;20(1):143.CrossRef Shao D, He S, Ye Z, Zhu X, Sun W, Fu W, et al. Identification of potential molecular targets associated with proliferative diabetic retinopathy. BMC Ophthalmol. 2020;20(1):143.CrossRef
15.
Zurück zum Zitat Li Y, Chen D, Sun L, Wu Y, Zou Y, Liang C, et al. Induced expression of VEGFC, ANGPT, and EFNB2 and their receptors characterizes neovascularization in proliferative diabetic retinopathy. Invest Ophthalmol Vis Sci. 2019;60(13):4084–96.CrossRef Li Y, Chen D, Sun L, Wu Y, Zou Y, Liang C, et al. Induced expression of VEGFC, ANGPT, and EFNB2 and their receptors characterizes neovascularization in proliferative diabetic retinopathy. Invest Ophthalmol Vis Sci. 2019;60(13):4084–96.CrossRef
16.
Zurück zum Zitat Zhou Y, Zhou B, Pache L, Chang M, Khodabakhshi AH, Tanaseichuk O, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun. 2019;10(1):1523.CrossRef Zhou Y, Zhou B, Pache L, Chang M, Khodabakhshi AH, Tanaseichuk O, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun. 2019;10(1):1523.CrossRef
17.
Zurück zum Zitat Chen K, Bao Z, Tang P, Gong W, Yoshimura T, Wang JM. Chemokines in homeostasis and diseases. Cell Mol Immunol. 2018;15(4):324–34.CrossRef Chen K, Bao Z, Tang P, Gong W, Yoshimura T, Wang JM. Chemokines in homeostasis and diseases. Cell Mol Immunol. 2018;15(4):324–34.CrossRef
18.
Zurück zum Zitat Fox JC, Nakayama T, Tyler RC, Sander TL, Yoshie O, Volkman BF. Structural and agonist properties of XCL2, the other member of the C-chemokine subfamily. Cytokine. 2015;71(2):302–11.CrossRef Fox JC, Nakayama T, Tyler RC, Sander TL, Yoshie O, Volkman BF. Structural and agonist properties of XCL2, the other member of the C-chemokine subfamily. Cytokine. 2015;71(2):302–11.CrossRef
19.
Zurück zum Zitat Zhou J, Xiang Y, Yoshimura T, Chen K, Gong W, Huang J, et al. The role of chemoattractant receptors in shaping the tumor microenvironment. Biomed Res Int. 2014;2014:751392.CrossRef Zhou J, Xiang Y, Yoshimura T, Chen K, Gong W, Huang J, et al. The role of chemoattractant receptors in shaping the tumor microenvironment. Biomed Res Int. 2014;2014:751392.CrossRef
20.
Zurück zum Zitat Zhang J, Zhang M, Zhao H, Xu X. Identification of proliferative diabetic retinopathy-associated genes on the protein-protein interaction network by using heat diffusion algorithm. Biochim Biophys Acta Mol Basis Dis. 2020;1866(10):165794.CrossRef Zhang J, Zhang M, Zhao H, Xu X. Identification of proliferative diabetic retinopathy-associated genes on the protein-protein interaction network by using heat diffusion algorithm. Biochim Biophys Acta Mol Basis Dis. 2020;1866(10):165794.CrossRef
21.
Zurück zum Zitat Wang N, Zhang C, Xu Y, Li S, Tan HY, Xia W, et al. OMICs approaches-assisted identification of macrophages-derived MIP-1gamma as the therapeutic target of botanical products TNTL in diabetic retinopathy. Cell Commun Signal. 2019;17(1):81.CrossRef Wang N, Zhang C, Xu Y, Li S, Tan HY, Xia W, et al. OMICs approaches-assisted identification of macrophages-derived MIP-1gamma as the therapeutic target of botanical products TNTL in diabetic retinopathy. Cell Commun Signal. 2019;17(1):81.CrossRef
22.
Zurück zum Zitat Yuan LH, Chen XL, Di Y, Liu ML. CCR7/p-ERK1/2/VEGF signaling promotes retinal neovascularization in a mouse model of oxygen-induced retinopathy. Int J Ophthalmol. 2017;10(6):862–9. Yuan LH, Chen XL, Di Y, Liu ML. CCR7/p-ERK1/2/VEGF signaling promotes retinal neovascularization in a mouse model of oxygen-induced retinopathy. Int J Ophthalmol. 2017;10(6):862–9.
23.
Zurück zum Zitat Kastelan S, Oreskovic I, Biscan F, Kastelan H, Gverovic Antunica A. Inflammatory and angiogenic biomarkers in diabetic retinopathy. Biochem Med. 2020;30(3):030502.CrossRef Kastelan S, Oreskovic I, Biscan F, Kastelan H, Gverovic Antunica A. Inflammatory and angiogenic biomarkers in diabetic retinopathy. Biochem Med. 2020;30(3):030502.CrossRef
24.
Zurück zum Zitat Das M, Tang X, Han JY, Mayilsamy K, Foran E, Biswal MR, et al. CCL20-CCR6 axis modulated traumatic brain injury-induced visual pathologies. J Neuroinflammation. 2019;16(1):115.CrossRef Das M, Tang X, Han JY, Mayilsamy K, Foran E, Biswal MR, et al. CCL20-CCR6 axis modulated traumatic brain injury-induced visual pathologies. J Neuroinflammation. 2019;16(1):115.CrossRef
25.
Zurück zum Zitat Sun H, Cheng Y, Yan Z, Liu X, Zhang J. Mining the proliferative diabetic retinopathy-associated genes and pathways by integrated bioinformatic analysis. Int Ophthalmol. 2020;40(2):269–79.CrossRef Sun H, Cheng Y, Yan Z, Liu X, Zhang J. Mining the proliferative diabetic retinopathy-associated genes and pathways by integrated bioinformatic analysis. Int Ophthalmol. 2020;40(2):269–79.CrossRef
26.
Zurück zum Zitat Zhang Y, Xu Y, Sun Q, Xue S, Guan H, Ji M. Activation of P2X7R- NLRP3 pathway in retinal microglia contribute to retinal ganglion cells death in chronic ocular hypertension (COH). Exp Eye Res. 2019;188:107771.CrossRef Zhang Y, Xu Y, Sun Q, Xue S, Guan H, Ji M. Activation of P2X7R- NLRP3 pathway in retinal microglia contribute to retinal ganglion cells death in chronic ocular hypertension (COH). Exp Eye Res. 2019;188:107771.CrossRef
27.
Zurück zum Zitat Deliyanti D, Wilkinson-Berka JL. Inhibition of NOX1/4 with GKT137831: a potential novel treatment to attenuate neuroglial cell inflammation in the retina. J Neuroinflammation. 2015;12:136.CrossRef Deliyanti D, Wilkinson-Berka JL. Inhibition of NOX1/4 with GKT137831: a potential novel treatment to attenuate neuroglial cell inflammation in the retina. J Neuroinflammation. 2015;12:136.CrossRef
28.
Zurück zum Zitat Bromberg-White JL, Glazer L, Downer R, Furge K, Boguslawski E, Duesbery NS. Identification of VEGF-independent cytokines in proliferative diabetic retinopathy vitreous. Invest Ophthalmol Vis Sci. 2013;54(10):6472–80.CrossRef Bromberg-White JL, Glazer L, Downer R, Furge K, Boguslawski E, Duesbery NS. Identification of VEGF-independent cytokines in proliferative diabetic retinopathy vitreous. Invest Ophthalmol Vis Sci. 2013;54(10):6472–80.CrossRef
29.
Zurück zum Zitat Petrovic MG, Korosec P, Kosnik M, Hawlina M. Vitreous levels of interleukin-8 in patients with proliferative diabetic retinopathy. Am J Ophthalmol. 2007;143(1):175–6.CrossRef Petrovic MG, Korosec P, Kosnik M, Hawlina M. Vitreous levels of interleukin-8 in patients with proliferative diabetic retinopathy. Am J Ophthalmol. 2007;143(1):175–6.CrossRef
30.
Zurück zum Zitat Nawaz MI, Van Raemdonck K, Mohammad G, Kangave D, Van Damme J, Abu El-Asrar AM, et al. Autocrine CCL2, CXCL4, CXCL9 and CXCL10 signal in retinal endothelial cells and are enhanced in diabetic retinopathy. Exp Eye Res. 2013;109:67–76.CrossRef Nawaz MI, Van Raemdonck K, Mohammad G, Kangave D, Van Damme J, Abu El-Asrar AM, et al. Autocrine CCL2, CXCL4, CXCL9 and CXCL10 signal in retinal endothelial cells and are enhanced in diabetic retinopathy. Exp Eye Res. 2013;109:67–76.CrossRef
31.
Zurück zum Zitat Abu El-Asrar AM, Struyf S, Kangave D, Geboes K, Van Damme J. Chemokines in proliferative diabetic retinopathy and proliferative vitreoretinopathy. Eur Cytokine Netw. 2006;17(3):155–65. Abu El-Asrar AM, Struyf S, Kangave D, Geboes K, Van Damme J. Chemokines in proliferative diabetic retinopathy and proliferative vitreoretinopathy. Eur Cytokine Netw. 2006;17(3):155–65.
32.
Zurück zum Zitat Zhang W, Dong X, Wang T, Kong Y. Exosomes derived from platelet-rich plasma mediate hyperglycemia-induced retinal endothelial injury via targeting the TLR4 signaling pathway. Exp Eye Res. 2019;189:107813.CrossRef Zhang W, Dong X, Wang T, Kong Y. Exosomes derived from platelet-rich plasma mediate hyperglycemia-induced retinal endothelial injury via targeting the TLR4 signaling pathway. Exp Eye Res. 2019;189:107813.CrossRef
33.
Zurück zum Zitat Cammalleri M, Dal Monte M, Locri F, Marsili S, Lista L, De Rosa M, et al. Diabetic retinopathy in the spontaneously diabetic Torii rat: Pathogenetic mechanisms and preventive efficacy of inhibiting the Urokinase-type plasminogen activator receptor system. J Diabetes Res. 2017;2017:2904150.CrossRef Cammalleri M, Dal Monte M, Locri F, Marsili S, Lista L, De Rosa M, et al. Diabetic retinopathy in the spontaneously diabetic Torii rat: Pathogenetic mechanisms and preventive efficacy of inhibiting the Urokinase-type plasminogen activator receptor system. J Diabetes Res. 2017;2017:2904150.CrossRef
34.
Zurück zum Zitat Sun J, Huang W, Yang SF, Zhang XP, Yu Q, Zhang ZQ, et al. Galphai1 and Galphai3mediate VEGF-induced VEGFR2 endocytosis, signaling and angiogenesis. Theranostics. 2018;8(17):4695–709.CrossRef Sun J, Huang W, Yang SF, Zhang XP, Yu Q, Zhang ZQ, et al. Galphai1 and Galphai3mediate VEGF-induced VEGFR2 endocytosis, signaling and angiogenesis. Theranostics. 2018;8(17):4695–709.CrossRef
35.
Zurück zum Zitat Trinh L, Brignole-Baudouin F, Raphael M, Dupont-Monod S, Cassoux N, Lehoang P, et al. Th1 and Th2 responses on the ocular surface in uveitis identified by CCR4 and CCR5 conjunctival expression. Am J Ophthalmol. 2007;144(4):580–5.CrossRef Trinh L, Brignole-Baudouin F, Raphael M, Dupont-Monod S, Cassoux N, Lehoang P, et al. Th1 and Th2 responses on the ocular surface in uveitis identified by CCR4 and CCR5 conjunctival expression. Am J Ophthalmol. 2007;144(4):580–5.CrossRef
36.
Zurück zum Zitat Liang H, Baudouin C, Hamard P, Creuzot-Garcher C, Warnet JM, Brignole-Baudouin F. Activation of TH1/TH2 pathways detected through the expression of CCR4 and CCR5 on the ocular surface of glaucomatous patients treated over the long term. J Fr Ophtalmol. 2006;29(2):121–6.CrossRef Liang H, Baudouin C, Hamard P, Creuzot-Garcher C, Warnet JM, Brignole-Baudouin F. Activation of TH1/TH2 pathways detected through the expression of CCR4 and CCR5 on the ocular surface of glaucomatous patients treated over the long term. J Fr Ophtalmol. 2006;29(2):121–6.CrossRef
37.
Zurück zum Zitat Yamagami S, Ebihara N, Amano SY. Chemokine receptor gene expression in giant papillae of atopic keratoconjunctivitis. Mol Vis. 2005;11:192–200. Yamagami S, Ebihara N, Amano SY. Chemokine receptor gene expression in giant papillae of atopic keratoconjunctivitis. Mol Vis. 2005;11:192–200.
38.
Zurück zum Zitat Choi W, Li Z, Oh HJ, Im SK, Lee SH, Park SH, et al. Expression of CCR5 and its ligands CCL3, −4, and −5 in the tear film and ocular surface of patients with dry eye disease. Curr Eye Res. 2012;37(1):12–7.CrossRef Choi W, Li Z, Oh HJ, Im SK, Lee SH, Park SH, et al. Expression of CCR5 and its ligands CCL3, −4, and −5 in the tear film and ocular surface of patients with dry eye disease. Curr Eye Res. 2012;37(1):12–7.CrossRef
39.
Zurück zum Zitat Chen J, Wang W, Li Q. Increased Th1/Th17 responses contribute to low-grade inflammation in age-related macular degeneration. Cell Physiol Biochem. 2017;44(1):357–67.CrossRef Chen J, Wang W, Li Q. Increased Th1/Th17 responses contribute to low-grade inflammation in age-related macular degeneration. Cell Physiol Biochem. 2017;44(1):357–67.CrossRef
40.
Zurück zum Zitat Lee CE, Choi SH, Yoon JS. Chemokine expression during Adipogenesis and inflammation in orbital fibroblasts from patients with Graves' Orbitopathy. Korean J Ophthalmol. 2020;34(3):192–202.CrossRef Lee CE, Choi SH, Yoon JS. Chemokine expression during Adipogenesis and inflammation in orbital fibroblasts from patients with Graves' Orbitopathy. Korean J Ophthalmol. 2020;34(3):192–202.CrossRef
41.
Zurück zum Zitat Unutmaz D, Xiang W, Sunshine MJ, Campbell J, Butcher E, Littman DR. The primate lentiviral receptor Bonzo/STRL33 is coordinately regulated with CCR5 and its expression pattern is conserved between human and mouse. J Immunol. 2000;165(6):3284–92.CrossRef Unutmaz D, Xiang W, Sunshine MJ, Campbell J, Butcher E, Littman DR. The primate lentiviral receptor Bonzo/STRL33 is coordinately regulated with CCR5 and its expression pattern is conserved between human and mouse. J Immunol. 2000;165(6):3284–92.CrossRef
42.
Zurück zum Zitat Hedman M, Faresjo M, Axelsson S, Ludvigsson J, Casas R. Impaired CD4 and CD8 T cell phenotype and reduced chemokine secretion in recent-onset type 1 diabetic children. Clin Exp Immunol. 2008;153(3):360–8.CrossRef Hedman M, Faresjo M, Axelsson S, Ludvigsson J, Casas R. Impaired CD4 and CD8 T cell phenotype and reduced chemokine secretion in recent-onset type 1 diabetic children. Clin Exp Immunol. 2008;153(3):360–8.CrossRef
43.
Zurück zum Zitat Qin S, Rottman JB, Myers P, Kassam N, Weinblatt M, Loetscher M, et al. The chemokine receptors CXCR3 and CCR5 mark subsets of T cells associated with certain inflammatory reactions. J Clin Invest. 1998;101(4):746–54.CrossRef Qin S, Rottman JB, Myers P, Kassam N, Weinblatt M, Loetscher M, et al. The chemokine receptors CXCR3 and CCR5 mark subsets of T cells associated with certain inflammatory reactions. J Clin Invest. 1998;101(4):746–54.CrossRef
44.
Zurück zum Zitat West EE, Kolev M, Kemper C. Complement and the regulation of T cell responses. Annu Rev Immunol. 2018;36:309–38.CrossRef West EE, Kolev M, Kemper C. Complement and the regulation of T cell responses. Annu Rev Immunol. 2018;36:309–38.CrossRef
45.
Zurück zum Zitat Zeng HY, Green WR, Tso MO. Microglial activation in human diabetic retinopathy. Arch Ophthalmol. 2008;126(2):227–32.CrossRef Zeng HY, Green WR, Tso MO. Microglial activation in human diabetic retinopathy. Arch Ophthalmol. 2008;126(2):227–32.CrossRef
46.
Zurück zum Zitat Madeira MH, Rashid K, Ambrosio AF, Santiago AR, Langmann T. Blockade of microglial adenosine A2A receptor impacts inflammatory mechanisms, reduces ARPE-19 cell dysfunction and prevents photoreceptor loss in vitro. Sci Rep. 2018;8(1):2272.CrossRef Madeira MH, Rashid K, Ambrosio AF, Santiago AR, Langmann T. Blockade of microglial adenosine A2A receptor impacts inflammatory mechanisms, reduces ARPE-19 cell dysfunction and prevents photoreceptor loss in vitro. Sci Rep. 2018;8(1):2272.CrossRef
47.
Zurück zum Zitat Zhao L, Zabel MK, Wang X, Ma W, Shah P, Fariss RN, et al. Microglial phagocytosis of living photoreceptors contributes to inherited retinal degeneration. EMBO Mol Med. 2015;7(9):1179–97.CrossRef Zhao L, Zabel MK, Wang X, Ma W, Shah P, Fariss RN, et al. Microglial phagocytosis of living photoreceptors contributes to inherited retinal degeneration. EMBO Mol Med. 2015;7(9):1179–97.CrossRef
48.
Zurück zum Zitat Nebel C, Aslanidis A, Rashid K, Langmann T. Activated microglia trigger inflammasome activation and lysosomal destabilization in human RPE cells. Biochem Biophys Res Commun. 2017;484(3):681–6.CrossRef Nebel C, Aslanidis A, Rashid K, Langmann T. Activated microglia trigger inflammasome activation and lysosomal destabilization in human RPE cells. Biochem Biophys Res Commun. 2017;484(3):681–6.CrossRef
49.
Zurück zum Zitat Cheng L, Bu H, Portillo JA, Li Y, Subauste CS, Huang SS, et al. Modulation of retinal Muller cells by complement receptor C5aR. Invest Ophthalmol Vis Sci. 2013;54(13):8191–8.CrossRef Cheng L, Bu H, Portillo JA, Li Y, Subauste CS, Huang SS, et al. Modulation of retinal Muller cells by complement receptor C5aR. Invest Ophthalmol Vis Sci. 2013;54(13):8191–8.CrossRef
50.
Zurück zum Zitat Harder JM, Williams PA, Braine CE, Yang HS, Thomas JM, Foxworth NE, et al. Complement peptide C3a receptor 1 promotes optic nerve degeneration in DBA/2J mice. J Neuroinflammation. 2020;17(1):336.CrossRef Harder JM, Williams PA, Braine CE, Yang HS, Thomas JM, Foxworth NE, et al. Complement peptide C3a receptor 1 promotes optic nerve degeneration in DBA/2J mice. J Neuroinflammation. 2020;17(1):336.CrossRef
51.
Zurück zum Zitat Howell GR, Libby RT, Jakobs TC, Smith RS, Phalan FC, Barter JW, et al. Axons of retinal ganglion cells are insulted in the optic nerve early in DBA/2J glaucoma. J Cell Biol. 2007;179(7):1523–37.CrossRef Howell GR, Libby RT, Jakobs TC, Smith RS, Phalan FC, Barter JW, et al. Axons of retinal ganglion cells are insulted in the optic nerve early in DBA/2J glaucoma. J Cell Biol. 2007;179(7):1523–37.CrossRef
52.
Zurück zum Zitat Howell GR, Walton DO, King BL, Libby RT, John SW. Datgan, a reusable software system for facile interrogation and visualization of complex transcription profiling data. BMC Genomics. 2011;12:429.CrossRef Howell GR, Walton DO, King BL, Libby RT, John SW. Datgan, a reusable software system for facile interrogation and visualization of complex transcription profiling data. BMC Genomics. 2011;12:429.CrossRef
53.
Zurück zum Zitat Vanlandewijck M, He L, Mae MA, Andrae J, Ando K, Del Gaudio F, et al. A molecular atlas of cell types and zonation in the brain vasculature. Nature. 2018;554(7693):475–80.CrossRef Vanlandewijck M, He L, Mae MA, Andrae J, Ando K, Del Gaudio F, et al. A molecular atlas of cell types and zonation in the brain vasculature. Nature. 2018;554(7693):475–80.CrossRef
54.
Zurück zum Zitat Hwang MS, Strainic MG, Pohlmann E, Kim H, Pluskota E, Ramirez-Bergeron DL, et al. VEGFR2 survival and mitotic signaling depends on joint activation of associated C3ar1/C5ar1 and IL-6R-gp130. J Cell Sci. 2019;132(6):jcs219352. Hwang MS, Strainic MG, Pohlmann E, Kim H, Pluskota E, Ramirez-Bergeron DL, et al. VEGFR2 survival and mitotic signaling depends on joint activation of associated C3ar1/C5ar1 and IL-6R-gp130. J Cell Sci. 2019;132(6):jcs219352.
55.
Zurück zum Zitat Xiang H, Lu Y, Shao M, Wu T. Lysophosphatidic acid receptors: biochemical and clinical implications in different diseases. J Cancer. 2020;11(12):3519–35.CrossRef Xiang H, Lu Y, Shao M, Wu T. Lysophosphatidic acid receptors: biochemical and clinical implications in different diseases. J Cancer. 2020;11(12):3519–35.CrossRef
56.
Zurück zum Zitat Frisca F, Sabbadini RA, Goldshmit Y, Pebay A. Biological effects of lysophosphatidic acid in the nervous system. Int Rev Cell Mol Biol. 2012;296:273–322.CrossRef Frisca F, Sabbadini RA, Goldshmit Y, Pebay A. Biological effects of lysophosphatidic acid in the nervous system. Int Rev Cell Mol Biol. 2012;296:273–322.CrossRef
57.
Zurück zum Zitat Abu El-Asrar AM, Missotten L, Geboes K. Expression of autotaxin and acylglycerol kinase in proliferative vitreoretinal epiretinal membranes. Acta Ophthalmol. 2012;90(2):e84–9.CrossRef Abu El-Asrar AM, Missotten L, Geboes K. Expression of autotaxin and acylglycerol kinase in proliferative vitreoretinal epiretinal membranes. Acta Ophthalmol. 2012;90(2):e84–9.CrossRef
58.
Zurück zum Zitat Jacobson KA, Civan MM. Ocular purine receptors as drug targets in the eye. J Ocul Pharmacol Ther. 2016;32(8):534–47.CrossRef Jacobson KA, Civan MM. Ocular purine receptors as drug targets in the eye. J Ocul Pharmacol Ther. 2016;32(8):534–47.CrossRef
59.
Zurück zum Zitat Yang X, Dong X, Jia C, Wang Y. Profiling of genes associated with the murine model of oxygen-induced retinopathy. Mol Vis. 2013;19:775–88. Yang X, Dong X, Jia C, Wang Y. Profiling of genes associated with the murine model of oxygen-induced retinopathy. Mol Vis. 2013;19:775–88.
60.
Zurück zum Zitat Azroyan A, Cortez-Retamozo V, Bouley R, Liberman R, Ruan YC, Kiselev E, et al. Renal intercalated cells sense and mediate inflammation via the P2Y14 receptor. PLoS One. 2015;10(3):e0121419.CrossRef Azroyan A, Cortez-Retamozo V, Bouley R, Liberman R, Ruan YC, Kiselev E, et al. Renal intercalated cells sense and mediate inflammation via the P2Y14 receptor. PLoS One. 2015;10(3):e0121419.CrossRef
61.
Zurück zum Zitat He M, Long P, Chen T, Li K, Wei D, Zhang Y, et al. ALDH2/SIRT1 contributes to type 1 and type 2 diabetes-induced retinopathy through depressing oxidative stress. Oxidative Med Cell Longev. 2021;2021:1641717.CrossRef He M, Long P, Chen T, Li K, Wei D, Zhang Y, et al. ALDH2/SIRT1 contributes to type 1 and type 2 diabetes-induced retinopathy through depressing oxidative stress. Oxidative Med Cell Longev. 2021;2021:1641717.CrossRef
62.
Zurück zum Zitat Li W, Cheng Z, Song Y, Fang Y, Yang M, Zhang M. Is diabetic retinopathy affected by diabetes type? A retrospective study using electronic medical record data from patients with latent autoimmune diabetes in adults, type 1 diabetes, and type 2 diabetes. Acta Diabetol. 2021;58(11):1503–11.CrossRef Li W, Cheng Z, Song Y, Fang Y, Yang M, Zhang M. Is diabetic retinopathy affected by diabetes type? A retrospective study using electronic medical record data from patients with latent autoimmune diabetes in adults, type 1 diabetes, and type 2 diabetes. Acta Diabetol. 2021;58(11):1503–11.CrossRef
Metadaten
Titel
Identification of immune associated potential molecular targets in proliferative diabetic retinopathy
verfasst von
Ying Gao
Min Xue
Bing Dai
Yun Tang
Jingyu Liu
Changlin Zhao
Hu Meng
Feng Yan
Xiaomin Zhu
Yan Lu
Yirui Ge
Publikationsdatum
01.12.2023
Verlag
BioMed Central
Erschienen in
BMC Ophthalmology / Ausgabe 1/2023
Elektronische ISSN: 1471-2415
DOI
https://doi.org/10.1186/s12886-023-02774-y

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